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fill-mask | transformers |
## Malaysian DistilBERT Small
Malaysian DistilBERT Small is a masked language model based on the [DistilBERT model](https://arxiv.org/abs/1910.01108). It was trained on the [OSCAR](https://huggingface.co/datasets/oscar) dataset, specifically the `unshuffled_original_ms` subset.
The model was originally HuggingFace's ... | {"language": "ms", "license": "mit", "tags": ["malaysian-distilbert-small"], "datasets": ["oscar"], "widget": [{"text": "Hari ini adalah hari yang [MASK]!"}]} | w11wo/malaysian-distilbert-small | null | [
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"autotrain_compatible",
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] | null | 2022-03-02T23:29:05+00:00 | [
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"ms"
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| Malaysian DistilBERT Small
--------------------------
Malaysian DistilBERT Small is a masked language model based on the DistilBERT model. It was trained on the OSCAR dataset, specifically the 'unshuffled\_original\_ms' subset.
The model was originally HuggingFace's pretrained English DistilBERT model and is later ... | [
"### As Masked Language Model",
"### Feature Extraction in PyTorch\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which came from the OSCAR dataset that may be carried over into the results of this model.\n\n\nAuthor\n------\n\n\nMalaysian DistilBERT Small was trained and evaluated by Wilson Wongso. All ... | [
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"### As Masked Language Model",
"### Feature Extraction in PyTorch\n\n\nDisclaimer\n----------\n\n\nDo c... |
text-classification | transformers |
## Sundanese BERT Base Emotion Classifier
Sundanese BERT Base Emotion Classifier is an emotion-text-classification model based on the [BERT](https://arxiv.org/abs/1810.04805) model. The model was originally the pre-trained [Sundanese BERT Base Uncased](https://hf.co/luche/bert-base-sundanese-uncased) model trained by... | {"language": "su", "license": "mit", "tags": ["sundanese-bert-base-emotion-classifier"], "widget": [{"text": "Punten ini akurat ga ya sieun ihh daerah aku masuk zona merah"}]} | w11wo/sundanese-bert-base-emotion-classifier | null | [
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"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
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| Sundanese BERT Base Emotion Classifier
--------------------------------------
Sundanese BERT Base Emotion Classifier is an emotion-text-classification model based on the BERT model. The model was originally the pre-trained Sundanese BERT Base Uncased model trained by '@luche', which is then fine-tuned on the Sundanes... | [
"### As Text Classifier\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which come from both the pre-trained BERT model and the Sundanese Twitter dataset that may be carried over into the results of this model.\n\n\nAuthor\n------\n\n\nSundanese BERT Base Emotion Classifier was trained and evaluated by Wils... | [
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"### As Text Classifier\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which come from both the ... |
text-classification | transformers |
## Sundanese GPT-2 Base Emotion Classifier
Sundanese GPT-2 Base Emotion Classifier is an emotion-text-classification model based on the [OpenAI GPT-2](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) model. The model was originally the pre-trained [Sundanese GPT-2... | {"language": "su", "license": "mit", "tags": ["sundanese-gpt2-base-emotion-classifier"], "widget": [{"text": "Wah, \u00e9ta g\u00e9lo, keren pisan!"}]} | w11wo/sundanese-gpt2-base-emotion-classifier | null | [
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"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
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| Sundanese GPT-2 Base Emotion Classifier
---------------------------------------
Sundanese GPT-2 Base Emotion Classifier is an emotion-text-classification model based on the OpenAI GPT-2 model. The model was originally the pre-trained Sundanese GPT-2 Base model, which is then fine-tuned on the Sundanese Twitter datase... | [
"### As Text Classifier\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which come from both the pre-trained RoBERTa model and the Sundanese Twitter dataset that may be carried over into the results of this model.\n\n\nAuthor\n------\n\n\nSundanese GPT-2 Base Emotion Classifier was trained and evaluated by ... | [
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"### As Text Classifier\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which come from ... |
text-generation | transformers |
## Sundanese GPT-2 Base
Sundanese GPT-2 Base is a causal language model based on the [OpenAI GPT-2](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) model. It was trained on four datasets: [OSCAR](https://hf.co/datasets/oscar)'s `unshuffled_deduplicated_su` subset... | {"language": "su", "license": "mit", "tags": ["sundanese-gpt2-base"], "datasets": ["mc4", "cc100", "oscar", "wikipedia"], "widget": [{"text": "Nami abdi Budi, ti Indon\u00e9sia"}]} | w11wo/sundanese-gpt2-base | null | [
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... | null | 2022-03-02T23:29:05+00:00 | [] | [
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| Sundanese GPT-2 Base
--------------------
Sundanese GPT-2 Base is a causal language model based on the OpenAI GPT-2 model. It was trained on four datasets: OSCAR's 'unshuffled\_deduplicated\_su' subset, the Sundanese mC4 subset, the Sundanese CC100 subset, and Sundanese Wikipedia.
10% of the dataset is kept for eva... | [
"### As Causal Language Model",
"### Feature Extraction in PyTorch\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which came from all four datasets that may be carried over into the results of this model.\n\n\nAuthor\n------\n\n\nSundanese GPT-2 Base was trained and evaluated by Wilson Wongso."
] | [
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"### As Causal Language Model",
"### Feat... |
text-classification | transformers |
## Sundanese RoBERTa Base Emotion Classifier
Sundanese RoBERTa Base Emotion Classifier is an emotion-text-classification model based on the [RoBERTa](https://arxiv.org/abs/1907.11692) model. The model was originally the pre-trained [Sundanese RoBERTa Base](https://hf.co/w11wo/sundanese-roberta-base) model, which is t... | {"language": "su", "license": "mit", "tags": ["sundanese-roberta-base-emotion-classifier"], "widget": [{"text": "Wah, \u00e9ta g\u00e9lo, keren pisan!"}]} | w11wo/sundanese-roberta-base-emotion-classifier | null | [
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] | null | 2022-03-02T23:29:05+00:00 | [
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| Sundanese RoBERTa Base Emotion Classifier
-----------------------------------------
Sundanese RoBERTa Base Emotion Classifier is an emotion-text-classification model based on the RoBERTa model. The model was originally the pre-trained Sundanese RoBERTa Base model, which is then fine-tuned on the Sundanese Twitter dat... | [
"### As Text Classifier\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which come from both the pre-trained RoBERTa model and the Sundanese Twitter dataset that may be carried over into the results of this model.\n\n\nAuthor\n------\n\n\nSundanese RoBERTa Base Emotion Classifier was trained and evaluated b... | [
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"### As Text Classifier\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which come from both the pre-tra... |
fill-mask | transformers |
## Sundanese RoBERTa Base
Sundanese RoBERTa Base is a masked language model based on the [RoBERTa](https://arxiv.org/abs/1907.11692) model. It was trained on four datasets: [OSCAR](https://hf.co/datasets/oscar)'s `unshuffled_deduplicated_su` subset, the Sundanese [mC4](https://hf.co/datasets/mc4) subset, the Sundanes... | {"language": "su", "license": "mit", "tags": ["sundanese-roberta-base"], "datasets": ["mc4", "cc100", "oscar", "wikipedia"], "widget": [{"text": "Budi nuju <mask> di sakola."}]} | w11wo/sundanese-roberta-base | null | [
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"region:u... | null | 2022-03-02T23:29:05+00:00 | [
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| Sundanese RoBERTa Base
----------------------
Sundanese RoBERTa Base is a masked language model based on the RoBERTa model. It was trained on four datasets: OSCAR's 'unshuffled\_deduplicated\_su' subset, the Sundanese mC4 subset, the Sundanese CC100 subset, and Sundanese Wikipedia.
10% of the dataset is kept for ev... | [
"### As Masked Language Model",
"### Feature Extraction in PyTorch\n\n\nDisclaimer\n----------\n\n\nDo consider the biases which came from all four datasets that may be carried over into the results of this model.\n\n\nAuthor\n------\n\n\nSundanese RoBERTa Base was trained and evaluated by Wilson Wongso."
] | [
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"### As Masked Language Model",
"### Feature Extra... |
automatic-speech-recognition | transformers |
# Wav2Vec2 XLS-R 300M Korean LM
Wav2Vec2 XLS-R 300M Korean LM is an automatic speech recognition model based on the [XLS-R](https://arxiv.org/abs/2111.09296) architecture. This model is a fine-tuned version of [Wav2Vec2-XLS-R-300M](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [Zeroth Korean](https://hu... | {"language": "ko", "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "robust-speech-event"], "datasets": ["kresnik/zeroth_korean"], "base_model": "Wav2Vec2-XLS-R-300M", "model-index": [{"name": "Wav2Vec2 XLS-R 300M Korean LM", "results": [{"task": {"type":... | w11wo/wav2vec2-xls-r-300m-korean-lm | null | [
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| Wav2Vec2 XLS-R 300M Korean LM
=============================
Wav2Vec2 XLS-R 300M Korean LM is an automatic speech recognition model based on the XLS-R architecture. This model is a fine-tuned version of Wav2Vec2-XLS-R-300M on the Zeroth Korean dataset. A 5-gram Language model, trained on the Korean subset of Open Subt... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* 'learning\\_rate': 7.5e-05\n* 'train\\_batch\\_size': 8\n* 'eval\\_batch\\_size': 8\n* 'seed': 42\n* 'gradient\\_accumulation\\_steps': 4\n* 'total\\_train\\_batch\\_size': 32\n* 'optimizer': Adam with 'betas=(0.9, 0.... | [
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automatic-speech-recognition | transformers |
# Wav2Vec2 XLS-R 300M Korean
Wav2Vec2 XLS-R 300M Korean is an automatic speech recognition model based on the [XLS-R](https://arxiv.org/abs/2111.09296) architecture. This model is a fine-tuned version of [Wav2Vec2-XLS-R-300M](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [Zeroth Korean](https://huggingf... | {"language": "ko", "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "robust-speech-event"], "datasets": ["kresnik/zeroth_korean"], "base_model": "Wav2Vec2-XLS-R-300M", "model-index": [{"name": "Wav2Vec2 XLS-R 300M Korean", "results": [{"task": {"type": "a... | w11wo/wav2vec2-xls-r-300m-korean | null | [
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"... | null | 2022-03-02T23:29:05+00:00 | [
"2111.09296"
] | [
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] | TAGS
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| Wav2Vec2 XLS-R 300M Korean
==========================
Wav2Vec2 XLS-R 300M Korean is an automatic speech recognition model based on the XLS-R architecture. This model is a fine-tuned version of Wav2Vec2-XLS-R-300M on the Zeroth Korean dataset.
This model was trained using HuggingFace's PyTorch framework and is part ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* 'learning\\_rate': 7.5e-05\n* 'train\\_batch\\_size': 8\n* 'eval\\_batch\\_size': 8\n* 'seed': 42\n* 'gradient\\_accumulation\\_steps': 4\n* 'total\\_train\\_batch\\_size': 32\n* 'optimizer': Adam with 'betas=(0.9, 0.... | [
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automatic-speech-recognition | transformers |
# Wav2Vec2 XLS-R 300M Cantonese (zh-HK) LM
Wav2Vec2 XLS-R 300M Cantonese (zh-HK) LM is an automatic speech recognition model based on the [XLS-R](https://arxiv.org/abs/2111.09296) architecture. This model is a fine-tuned version of [Wav2Vec2-XLS-R-300M](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the `zh-... | {"language": "zh-HK", "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "robust-speech-event"], "datasets": ["common_voice"], "model-index": [{"name": "Wav2Vec2 XLS-R 300M Cantonese (zh-HK) LM", "results": [{"task": {"type": "automatic-speech-recognition",... | w11wo/wav2vec2-xls-r-300m-zh-HK-lm-v2 | null | [
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"zh-HK"
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| Wav2Vec2 XLS-R 300M Cantonese (zh-HK) LM
========================================
Wav2Vec2 XLS-R 300M Cantonese (zh-HK) LM is an automatic speech recognition model based on the XLS-R architecture. This model is a fine-tuned version of Wav2Vec2-XLS-R-300M on the 'zh-HK' subset of the Common Voice dataset. A 5-gram Lan... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* 'learning\\_rate': 0.0001\n* 'train\\_batch\\_size': 8\n* 'eval\\_batch\\_size': 8\n* 'seed': 42\n* 'gradient\\_accumulation\\_steps': 4\n* 'total\\_train\\_batch\\_size': 32\n* 'optimizer': Adam with 'betas=(0.9, 0.9... | [
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"### Training hyperparameters\n\n\nThe following hyperp... |
automatic-speech-recognition | transformers |
# Wav2Vec2 XLS-R 300M Cantonese (zh-HK)
Wav2Vec2 XLS-R 300M Cantonese (zh-HK) is an automatic speech recognition model based on the [XLS-R](https://arxiv.org/abs/2111.09296) architecture. This model is a fine-tuned version of [Wav2Vec2-XLS-R-300M](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the `zh-HK` su... | {"language": "zh-HK", "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "robust-speech-event"], "datasets": ["common_voice"], "model-index": [{"name": "Wav2Vec2 XLS-R 300M Cantonese (zh-HK)", "results": [{"task": {"type": "automatic-speech-recognition", "n... | w11wo/wav2vec2-xls-r-300m-zh-HK-v2 | null | [
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"pytorch",
"tensorboard",
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] | null | 2022-03-02T23:29:05+00:00 | [
"2111.09296"
] | [
"zh-HK"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #robust-speech-event #dataset-common_voice #arxiv-2111.09296 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| Wav2Vec2 XLS-R 300M Cantonese (zh-HK)
=====================================
Wav2Vec2 XLS-R 300M Cantonese (zh-HK) is an automatic speech recognition model based on the XLS-R architecture. This model is a fine-tuned version of Wav2Vec2-XLS-R-300M on the 'zh-HK' subset of the Common Voice dataset.
This model was trai... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* 'learning\\_rate': 0.0001\n* 'train\\_batch\\_size': 8\n* 'eval\\_batch\\_size': 8\n* 'seed': 42\n* 'gradient\\_accumulation\\_steps': 4\n* 'total\\_train\\_batch\\_size': 32\n* 'optimizer': Adam with 'betas=(0.9, 0.9... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #robust-speech-event #dataset-common_voice #arxiv-2111.09296 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperp... |
token-classification | transformers |
## Eval results
We obtain the following results on ```validation``` and ```test``` sets:
| Set | F1<sub>micro</sub> | F1<sub>macro</sub> |
|------------|--------------------|--------------------|
| validation | 98.2 | 93.2 |
| test | 97.7 | 87.4 | | {"language": ["fr"], "tags": ["pos-tagging"]} | waboucay/french-camembert-postag-model-finetuned-perceo | null | [
"transformers",
"pytorch",
"camembert",
"token-classification",
"pos-tagging",
"fr",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #camembert #token-classification #pos-tagging #fr #autotrain_compatible #endpoints_compatible #region-us
| Eval results
------------
We obtain the following results on and sets:
Set: validation, F1micro: 98.2, F1macro: 93.2
Set: test, F1micro: 97.7, F1macro: 87.4
| [] | [
"TAGS\n#transformers #pytorch #camembert #token-classification #pos-tagging #fr #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-generation | transformers |
#Chandler Bing DialoGPT Model | {"tags": ["conversational"]} | wadeed/DialogGPT-small-chandlerbingg | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
#Chandler Bing DialoGPT Model | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# opus-mt-en-de-finetuned-en-to-de
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-de](https://huggingface.co/Helsi... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wmt16"], "metrics": ["bleu"], "model-index": [{"name": "opus-mt-en-de-finetuned-en-to-de", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "wmt16", "type": "wmt16", "a... | wandemberg-eld/opus-mt-en-de-finetuned-en-to-de | null | [
"transformers",
"pytorch",
"marian",
"text2text-generation",
"generated_from_trainer",
"dataset:wmt16",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #marian #text2text-generation #generated_from_trainer #dataset-wmt16 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| opus-mt-en-de-finetuned-en-to-de
================================
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-de on the wmt16 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4083
* Bleu: 29.4312
* Gen Len: 24.746
Model description
-----------------
More information ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1\n* mixed\\_precis... | [
"TAGS\n#transformers #pytorch #marian #text2text-generation #generated_from_trainer #dataset-wmt16 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\... |
text-generation | transformers |
#Phoebe From Friends | {"tags": ["conversational"]} | wanderer/DialoGPT-small-Phoebe | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
#Phoebe From Friends | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
fill-mask | transformers |
在众多业务中，越来越频繁的使用预训练语言模型（Pre-trained Language Models），为了在金融场景下各任务中取得更好效果，我们发布了jdt-fin-roberta-wwm模型
## 模型
* `base模型`：12-layer, 768-hidden, 12-heads, 110M parameters
| 模型简称 | 语料 | 京盘下载 |
| - | - | - |
| fin-roberta-wwm | 金融语料 | - |
## 快速加载
### 使用Huggingface-Transformers
依托于[Huggingface-Transformers](https://github.c... | {"language": "zh", "license": "apache-2.0", "tags": ["roberta-wwm"], "datasets": ["finance"]} | wangfan/jdt-fin-roberta-wwm-large | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"roberta-wwm",
"zh",
"dataset:finance",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"zh"
] | TAGS
#transformers #pytorch #bert #fill-mask #roberta-wwm #zh #dataset-finance #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| 在众多业务中，越来越频繁的使用预训练语言模型（Pre-trained Language Models），为了在金融场景下各任务中取得更好效果，我们发布了jdt-fin-roberta-wwm模型
模型
--
* 'base模型'：12-layer, 768-hidden, 12-heads, 110M parameters
模型简称: fin-roberta-wwm, 语料: 金融语料, 京盘下载: -
快速加载
----
### 使用Huggingface-Transformers
依托于Huggingface-Transformers，可轻松调用以上模型。
注意：本目录中的所有模型均使用BertTok... | [
"### 使用Huggingface-Transformers\n\n\n依托于Huggingface-Transformers，可轻松调用以上模型。\n\n\n注意：本目录中的所有模型均使用BertTokenizer以及BertModel加载，请勿使用RobertaTokenizer/RobertaModel！\n其中'MODEL\\_NAME'对应列表如下："
] | [
"TAGS\n#transformers #pytorch #bert #fill-mask #roberta-wwm #zh #dataset-finance #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### 使用Huggingface-Transformers\n\n\n依托于Huggingface-Transformers，可轻松调用以上模型。\n\n\n注意：本目录中的所有模型均使用BertTokenizer以及BertModel加载，请勿使用RobertaTokenizer/RobertaMo... |
fill-mask | transformers |
在众多业务中，越来越频繁的使用预训练语言模型（Pre-trained Language Models），为了在金融场景下各任务中取得更好效果，我们发布了jdt-fin-roberta-wwm模型
#### 模型&下载
* `base模型`：12-layer, 768-hidden, 12-heads, 110M parameters
| 模型简称 | 京盘下载 |
| :----: | :----:|
| fin-roberta-wwm | [Tensorflow](https://3.cn/103c-hwSS)/[Pytorch](https://3.cn/103c-izpe) |
| fin-roberta-wwm-l... | {"language": "zh", "license": "apache-2.0", "tags": ["roberta-wwm"], "datasets": ["finance"]} | wangfan/jdt-fin-roberta-wwm | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"roberta-wwm",
"zh",
"dataset:finance",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"zh"
] | TAGS
#transformers #pytorch #bert #fill-mask #roberta-wwm #zh #dataset-finance #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| 在众多业务中，越来越频繁的使用预训练语言模型（Pre-trained Language Models），为了在金融场景下各任务中取得更好效果，我们发布了jdt-fin-roberta-wwm模型
#### 模型&下载
* 'base模型'：12-layer, 768-hidden, 12-heads, 110M parameters
#### 快速加载
依托于Huggingface-Transformers，可轻松调用以上模型。
注意：本目录中的所有模型均使用BertTokenizer以及BertModel加载，请勿使用RobertaTokenizer/RobertaModel！
其中'MODEL\_NAME'... | [
"#### 模型&下载\n\n\n* 'base模型'：12-layer, 768-hidden, 12-heads, 110M parameters",
"#### 快速加载\n\n\n依托于Huggingface-Transformers，可轻松调用以上模型。\n\n\n注意：本目录中的所有模型均使用BertTokenizer以及BertModel加载，请勿使用RobertaTokenizer/RobertaModel！\n其中'MODEL\\_NAME'对应列表如下：",
"#### 任务效果\n\n\n| Task | NER | 关系抽取 | 事件抽取 | 指标抽取 | 实体链接 |\n|:----:|:-... | [
"TAGS\n#transformers #pytorch #bert #fill-mask #roberta-wwm #zh #dataset-finance #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"#### 模型&下载\n\n\n* 'base模型'：12-layer, 768-hidden, 12-heads, 110M parameters",
"#### 快速加载\n\n\n依托于Huggingface-Transformers，可轻松调用以上模型。\n\n\n注意：本目录中的所有模型均... |
text-classification | transformers |
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 31237266
- CO2 Emissions (in grams): 390.39411176775826
## Validation Metrics
- Loss: 0.1643059253692627
- Accuracy: 0.9379398019660155
- Precision: 0.7467491278147795
- Recall: 0.7158710854363028
- AUC: 0.9631629384458238
- F1: 0.73098... | {"language": "unk", "tags": "autonlp", "datasets": ["wangsheng/autonlp-data-poi_train"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 390.39411176775826} | wangsheng/autonlp-poi_train-31237266 | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"autonlp",
"unk",
"dataset:wangsheng/autonlp-data-poi_train",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"unk"
] | TAGS
#transformers #pytorch #bert #text-classification #autonlp #unk #dataset-wangsheng/autonlp-data-poi_train #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 31237266
- CO2 Emissions (in grams): 390.39411176775826
## Validation Metrics
- Loss: 0.1643059253692627
- Accuracy: 0.9379398019660155
- Precision: 0.7467491278147795
- Recall: 0.7158710854363028
- AUC: 0.9631629384458238
- F1: 0.73098... | [
"# Model Trained Using AutoNLP\n\n- Problem type: Binary Classification\n- Model ID: 31237266\n- CO2 Emissions (in grams): 390.39411176775826",
"## Validation Metrics\n\n- Loss: 0.1643059253692627\n- Accuracy: 0.9379398019660155\n- Precision: 0.7467491278147795\n- Recall: 0.7158710854363028\n- AUC: 0.963162938445... | [
"TAGS\n#transformers #pytorch #bert #text-classification #autonlp #unk #dataset-wangsheng/autonlp-data-poi_train #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Trained Using AutoNLP\n\n- Problem type: Binary Classification\n- Model ID: 31237266\n- CO2 Emissions (in grams): ... |
null | null | 1111 | {} | wangweinuo/ceshi | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
| 1111 | [] | [
"TAGS\n#region-us \n"
] |
text-generation | transformers | # Thai GPT Next
It is fine-tune the GPT-Neo model for Thai language.
GitHub: https://github.com/wannaphong/thaigpt-next
**Dataset for fine-tune this model**
- prachathai67k
- thaisum
- thai_toxicity_tweet
- wongnai reviews
- wisesight_sentiment
- TLC
- scb_mt_enth_2020 (Thai only)
- Thai wikipedia (date: 2021/06/20... | {} | wannaphong/thaigpt-next-125m | null | [
"transformers",
"pytorch",
"gpt_neo",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt_neo #text-generation #autotrain_compatible #endpoints_compatible #region-us
| # Thai GPT Next
It is fine-tune the GPT-Neo model for Thai language.
GitHub: URL
Dataset for fine-tune this model
- prachathai67k
- thaisum
- thai_toxicity_tweet
- wongnai reviews
- wisesight_sentiment
- TLC
- scb_mt_enth_2020 (Thai only)
- Thai wikipedia (date: 2021/06/20)
Max Length: 280
Number of train lists: ... | [
"# Thai GPT Next\n\nIt is fine-tune the GPT-Neo model for Thai language.\n\nGitHub: URL\n\nDataset for fine-tune this model\n\n- prachathai67k\n- thaisum\n- thai_toxicity_tweet\n- wongnai reviews\n- wisesight_sentiment\n- TLC\n- scb_mt_enth_2020 (Thai only)\n- Thai wikipedia (date: 2021/06/20)\n\nMax Length: 280\n\... | [
"TAGS\n#transformers #pytorch #gpt_neo #text-generation #autotrain_compatible #endpoints_compatible #region-us \n",
"# Thai GPT Next\n\nIt is fine-tune the GPT-Neo model for Thai language.\n\nGitHub: URL\n\nDataset for fine-tune this model\n\n- prachathai67k\n- thaisum\n- thai_toxicity_tweet\n- wongnai reviews\n-... |
text-classification | transformers |
# FINPerceiver
FINPerceiver is a fine-tuned Perceiver IO language model for financial sentiment analysis.
More details on the training process of this model are available on the [GitHub repository](https://github.com/warwickai/fin-perceiver).
Weights & Biases was used to track experiments.
We achieved the following ... | {"language": "en", "license": "apache-2.0", "tags": ["financial-sentiment-analysis", "sentiment-analysis", "language-perceiver"], "datasets": ["financial_phrasebank"], "metrics": ["recall", "f1", "accuracy", "precision"], "widget": [{"text": "INDEX100 fell sharply today."}, {"text": "ImaginaryJetCo bookings hit by Omic... | warwickai/fin-perceiver | null | [
"transformers",
"pytorch",
"safetensors",
"perceiver",
"text-classification",
"financial-sentiment-analysis",
"sentiment-analysis",
"language-perceiver",
"en",
"dataset:financial_phrasebank",
"doi:10.57967/hf/0060",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_... | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #perceiver #text-classification #financial-sentiment-analysis #sentiment-analysis #language-perceiver #en #dataset-financial_phrasebank #doi-10.57967/hf/0060 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# FINPerceiver
FINPerceiver is a fine-tuned Perceiver IO language model for financial sentiment analysis.
More details on the training process of this model are available on the GitHub repository.
Weights & Biases was used to track experiments.
We achieved the following results with 10-fold cross validation.
The ... | [
"# FINPerceiver\nFINPerceiver is a fine-tuned Perceiver IO language model for financial sentiment analysis.\nMore details on the training process of this model are available on the GitHub repository.\n\nWeights & Biases was used to track experiments.\n\nWe achieved the following results with 10-fold cross validatio... | [
"TAGS\n#transformers #pytorch #safetensors #perceiver #text-classification #financial-sentiment-analysis #sentiment-analysis #language-perceiver #en #dataset-financial_phrasebank #doi-10.57967/hf/0060 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# FINPer... |
null | null | h e l l o
| {"license": "afl-3.0"} | wassimSuleiman1976/Flair_Large | null | [
"license:afl-3.0",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#license-afl-3.0 #region-us
| h e l l o
| [] | [
"TAGS\n#license-afl-3.0 #region-us \n"
] |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-fine-tune-timit
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-fine-tune-timit", "results": []}]} | webshell/wav2vec2-base-fine-tune-timit | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-fine-tune-timit
=============================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4451
* Wer: 0.3422
Model description
-----------------
More information needed
Intended uses & limita... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 3... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xlsr-53_english
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/fa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-large-xlsr-53_english", "results": []}]} | wesam266/wav2vec2-large-xlsr-53_english | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-large-xlsr-53\_english
===============================
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2620
* Wer: 0.1916
Model description
-----------------
More information needed
Intended ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 32\n* eval\\_b... |
sentence-similarity | sentence-transformers |
# whaleloops/phrase-bert
This is the official repository for the EMNLP 2021 long paper [Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration](https://arxiv.org/abs/2109.06304). We provide [code](https://github.com/sf-wa-326/phrase-bert-topic-model) for training and evaluating Ph... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | whaleloops/phrase-bert | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:2109.06304",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2109.06304"
] | [] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #arxiv-2109.06304 #endpoints_compatible #has_space #region-us
|
# whaleloops/phrase-bert
This is the official repository for the EMNLP 2021 long paper Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration. We provide code for training and evaluating Phrase-BERT in addition to the datasets used in the paper.
## Usage (Sentence-Transformers)... | [
"# whaleloops/phrase-bert\n\nThis is the official repository for the EMNLP 2021 long paper Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration. We provide code for training and evaluating Phrase-BERT in addition to the datasets used in the paper.",
"## Usage (Sentence-Trans... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #arxiv-2109.06304 #endpoints_compatible #has_space #region-us \n",
"# whaleloops/phrase-bert\n\nThis is the official repository for the EMNLP 2021 long paper Phrase-BERT: Improved Phrase Embeddings from BERT with a... |
text-generation | transformers | Model Description
------
The german-gpt2-romantik model was fine-tuned on [dbmdz's german gpt-2](https://huggingface.co/dbmdz/german-gpt2 "dbmdz's german-gpt2") for specialization in poetry generation tasks.
Training Data
------
The data for training were hand-chosen poems from the German Romanticism Era (German: *Rom... | {} | whher/german-gpt2-romantik | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| Model Description
------
The german-gpt2-romantik model was fine-tuned on dbmdz's german gpt-2 for specialization in poetry generation tasks.
Training Data
------
The data for training were hand-chosen poems from the German Romanticism Era (German: *Romantik*). In total there were 2,641 pieces of poems and 879,427 tok... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
null | null | test | {} | whitehahahah/test_bert | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
| test | [] | [
"TAGS\n#region-us \n"
] |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# thai-bert-multi-cased-finetuned-xquadv1-finetuned-squad
This model is a fine-tuned version of [mrm8488/bert-multi-cased-finetune... | {"language": "th", "license": "cc-by-4.0", "tags": ["generated_from_trainer"], "widget": [{"text": "\u0e2a\u0e23\u0e32\u0e27\u0e38\u0e18 \u0e21\u0e32\u0e15\u0e23\u0e17\u0e2d\u0e07 \u0e40\u0e02\u0e49\u0e32\u0e2a\u0e39\u0e48\u0e27\u0e07\u0e01\u0e32\u0e23\u0e1a\u0e31\u0e19\u0e40\u0e17\u0e34\u0e07\u0e40\u0e21\u0e37\u0e48\u... | wicharnkeisei/thai-bert-multi-cased-finetuned-xquadv1-finetuned-squad | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"th",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #th #license-cc-by-4.0 #endpoints_compatible #region-us
|
# thai-bert-multi-cased-finetuned-xquadv1-finetuned-squad
This model is a fine-tuned version of mrm8488/bert-multi-cased-finetuned-xquadv1 on Thai dataset from iApp Technology Co., Ltd..
## Intended uses & limitations
This model intends to use with Thai question and answering task
## Training and evaluation data... | [
"# thai-bert-multi-cased-finetuned-xquadv1-finetuned-squad\n\nThis model is a fine-tuned version of mrm8488/bert-multi-cased-finetuned-xquadv1 on Thai dataset from iApp Technology Co., Ltd..",
"## Intended uses & limitations\n\nThis model intends to use with Thai question and answering task",
"## Training and e... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #th #license-cc-by-4.0 #endpoints_compatible #region-us \n",
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question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# thai-squad
This model is a fine-tuned version of [deepset/xlm-roberta-base-squad2](https://huggingface.co/deepset/xlm-roberta-ba... | {"language": "th", "license": "cc-by-4.0", "tags": ["generated_from_trainer"], "widget": [{"text": "\u0e2a\u0e23\u0e32\u0e27\u0e38\u0e18 \u0e21\u0e32\u0e15\u0e23\u0e17\u0e2d\u0e07 \u0e40\u0e02\u0e49\u0e32\u0e2a\u0e39\u0e48\u0e27\u0e07\u0e01\u0e32\u0e23\u0e1a\u0e31\u0e19\u0e40\u0e17\u0e34\u0e07\u0e40\u0e21\u0e37\u0e48\u... | wicharnkeisei/thai-xlm-roberta-base-squad2 | null | [
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"xlm-roberta",
"question-answering",
"generated_from_trainer",
"th",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #th #license-cc-by-4.0 #endpoints_compatible #region-us
|
# thai-squad
This model is a fine-tuned version of deepset/xlm-roberta-base-squad2 on Thai dataset from iApp Technology Co., Ltd..
## Intended uses & limitations
This model intends to use with Thai question and answering task
## Training and evaluation data
Trained and evaluated by iApp Technology Co., Ltd. dat... | [
"# thai-squad\n\nThis model is a fine-tuned version of deepset/xlm-roberta-base-squad2 on Thai dataset from iApp Technology Co., Ltd..",
"## Intended uses & limitations\n\nThis model intends to use with Thai question and answering task",
"## Training and evaluation data\n\nTrained and evaluated by iApp Technolo... | [
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"# thai-squad\n\nThis model is a fine-tuned version of deepset/xlm-roberta-base-squad2 on Thai dataset from iApp Technology Co., Ltd..",
"## Intended u... |
fill-mask | transformers | # BERTje: A Dutch BERT model
BERTje is a Dutch pre-trained BERT model developed at the University of Groningen.
⚠️ **The new home of this model is the [GroNLP](https://huggingface.co/GroNLP) organization.**
BERTje now lives at: [`GroNLP/bert-base-dutch-cased`](https://huggingface.co/GroNLP/bert-base-dutch-cased)
Th... | {} | wietsedv/bert-base-dutch-cased | null | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #autotrain_compatible #endpoints_compatible #has_space #region-us
| # BERTje: A Dutch BERT model
BERTje is a Dutch pre-trained BERT model developed at the University of Groningen.
️ The new home of this model is the GroNLP organization.
BERTje now lives at: 'GroNLP/bert-base-dutch-cased'
The model weights of the versions at 'wietsedv/' and 'GroNLP/' are the same, so do not worry if... | [
"# BERTje: A Dutch BERT model\n\nBERTje is a Dutch pre-trained BERT model developed at the University of Groningen.\n\n️ The new home of this model is the GroNLP organization.\n\nBERTje now lives at: 'GroNLP/bert-base-dutch-cased'\n\nThe model weights of the versions at 'wietsedv/' and 'GroNLP/' are the same, so do... | [
"TAGS\n#transformers #pytorch #tf #jax #safetensors #bert #fill-mask #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# BERTje: A Dutch BERT model\n\nBERTje is a Dutch pre-trained BERT model developed at the University of Groningen.\n\n️ The new home of this model is the GroNLP organization... |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-Dutch
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Dutch using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model... | {"language": "nl", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "Dutch XLSR Wav2Vec2 Large 53 by Wietse de Vries", "results": [{"task": {"type": "automatic-speech-recognition", "n... | wietsedv/wav2vec2-large-xlsr-53-dutch | null | [
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"safetensors",
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"automatic-speech-recognition",
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"nl",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"nl"
] | TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #nl #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-Dutch
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Dutch using the Common Voice dataset.
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated... | [
"# Wav2Vec2-Large-XLSR-53-Dutch\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Dutch using the Common Voice dataset.\nWhen using this model, make sure that your speech input is sampled at 16kHz.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model ... | [
"TAGS\n#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #nl #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Dutch\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Dutch using the... |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-Frisian
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Frisian using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The m... | {"language": "fy-NL", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "Frisian XLSR Wav2Vec2 Large 53 by Wietse de Vries", "results": [{"task": {"type": "automatic-speech-recognition... | wietsedv/wav2vec2-large-xlsr-53-frisian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fy-NL"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-Frisian
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Frisian using the Common Voice dataset.
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evalu... | [
"# Wav2Vec2-Large-XLSR-53-Frisian\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Frisian using the Common Voice dataset.\nWhen using this model, make sure that your speech input is sampled at 16kHz.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe mo... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Frisian\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Frisian using the Common Voice... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Afrikaans
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfo... | {"language": ["af"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-af", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-af | null | [
"transformers",
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"xlm-roberta",
"token-classification",
"part-of-speech",
"af",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"af"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #af #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Afrikaans
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Afrikaans\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
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"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Afrikaans\n\nThis m... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Arabic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["ar"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ar", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ar | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ar",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ar"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ar #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Arabic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Arabic\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
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"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Arabic\n\nThis model is part of ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Belarusian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transf... | {"language": ["be"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-be", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-be | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"be",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"be"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #be #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Belarusian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Belarusian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #be #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Belarusian\n\nThis model is part... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Bulgarian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfo... | {"language": ["bg"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-bg", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-bg | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"bg",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"bg"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #bg #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Bulgarian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Bulgarian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #bg #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Bulgarian\n\nThis m... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Catalan
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["ca"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ca", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ca | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ca",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ca"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ca #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Catalan
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Catalan\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ca #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Catalan\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Czech
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["cs"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-cs", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-cs | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"cs",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"cs"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #cs #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Czech
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Czech\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #cs #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Czech\n\nThis model... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old Church Slavonic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
fr... | {"language": ["cu"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-cu", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-cu | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"cu",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"cu"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #cu #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old Church Slavonic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old Church Slavonic\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #cu #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old Church Slavonic... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Welsh
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["cy"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-cy", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-cy | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"cy",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"cy"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #cy #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Welsh
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Welsh\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #cy #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Welsh\n\nThis model is part of o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Danish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["da"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-da", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-da | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"da",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"da"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #da #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Danish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Danish\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #da #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Danish\n\nThis model is part of ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: German
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["de"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-de", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-de | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"de",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #de #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: German
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: German\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #de #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: German\n\nThis mode... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Greek
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["el"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-el", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-el | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"el",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"el"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #el #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Greek
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Greek\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #el #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Greek\n\nThis model... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: English
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-en", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-en | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"en",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #en #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: English
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: English\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #en #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: English\n\nThis mod... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Spanish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["es"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-es", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-es | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"es",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #es #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Spanish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Spanish\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #es #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Spanish\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Estonian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfor... | {"language": ["et"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-et", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-et | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"et",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"et"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #et #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Estonian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Estonian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #et #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Estonian\n\nThis model is part o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Basque
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["eu"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-eu", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-eu | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"eu",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"eu"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #eu #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Basque
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Basque\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #eu #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Basque\n\nThis mode... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Persian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["fa"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-fa", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-fa | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"fa",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #fa #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Persian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Persian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #fa #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Persian\n\nThis mod... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Finnish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["fi"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-fi", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-fi | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"fi",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fi"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #fi #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Finnish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Finnish\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #fi #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Finnish\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Faroese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["fo"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-fo", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-fo | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"fo",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fo"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #fo #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Faroese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Faroese\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #fo #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Faroese\n\nThis mod... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: French
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["fr"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-fr", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-fr | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"fr",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #fr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: French
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: French\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #fr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: French\n\nThis model is part of ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old French
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transf... | {"language": ["fro"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-fro", "results": [{"task": {"type": "token-classification", "name": "P... | wietsedv/xlm-roberta-base-ft-udpos28-fro | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"fro",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fro"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #fro #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old French
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old French\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #fro #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old French\n\nThis model is par... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Irish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["ga"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ga", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ga | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ga",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ga"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ga #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Irish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Irish\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ga #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Irish\n\nThis model is part of o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Scottish Gaelic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from t... | {"language": ["gd"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-gd", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-gd | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"gd",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"gd"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #gd #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Scottish Gaelic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Scottish Gaelic\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #gd #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Scottish Gaelic\n\nThis model is... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Galician
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfor... | {"language": ["gl"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-gl", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-gl | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"gl",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"gl"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #gl #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Galician
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Galician\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #gl #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Galician\n\nThis model is part o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Gothic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["got"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-got", "results": [{"task": {"type": "token-classification", "name": "P... | wietsedv/xlm-roberta-base-ft-udpos28-got | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"got",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"got"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #got #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Gothic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Gothic\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #got #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Gothic\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Ancient Greek
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from tra... | {"language": ["grc"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-grc", "results": [{"task": {"type": "token-classification", "name": "P... | wietsedv/xlm-roberta-base-ft-udpos28-grc | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"grc",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"grc"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #grc #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Ancient Greek
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Ancient Greek\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #grc #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Ancient Greek\n\nT... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hebrew
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["he"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-he", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-he | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"he",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"he"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #he #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hebrew
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hebrew\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #he #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hebrew\n\nThis mode... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hindi
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["hi"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-hi", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-hi | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"hi",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"hi"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #hi #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hindi
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hindi\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #hi #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hindi\n\nThis model is part of o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Croatian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfor... | {"language": ["hr"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-hr", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-hr | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"hr",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"hr"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #hr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Croatian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Croatian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #hr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Croatian\n\nThis model is part o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hungarian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfo... | {"language": ["hu"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-hu", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-hu | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"hu",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"hu"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #hu #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hungarian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hungarian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #hu #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Hungarian\n\nThis model is part ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Armenian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfor... | {"language": ["hy"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-hy", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-hy | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"hy",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"hy"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #hy #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Armenian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Armenian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #hy #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Armenian\n\nThis model is part o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Western Armenian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from ... | {"language": ["hyw"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-hyw", "results": [{"task": {"type": "token-classification", "name": "P... | wietsedv/xlm-roberta-base-ft-udpos28-hyw | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"hyw",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"hyw"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #hyw #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Western Armenian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Western Armenian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #hyw #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Western Armenian\n... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Indonesian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transf... | {"language": ["id"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-id", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-id | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"id",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"id"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #id #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Indonesian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Indonesian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #id #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Indonesian\n\nThis model is part... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Icelandic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfo... | {"language": ["is"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-is", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-is | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"is",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"is"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #is #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Icelandic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Icelandic\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #is #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Icelandic\n\nThis model is part ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Italian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["it"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-it", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-it | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"it",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"it"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #it #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Italian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Italian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #it #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Italian\n\nThis mod... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Japanese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfor... | {"language": ["ja"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ja", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ja | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ja",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ja"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #ja #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Japanese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Japanese\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #ja #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Japanese\n\nThis mo... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Korean
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["ko"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ko", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ko | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ko",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ko"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #ko #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Korean
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Korean\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #ko #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Korean\n\nThis mode... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Latin
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["la"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-la", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-la | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"la",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"la"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #la #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Latin
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Latin\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #la #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Latin\n\nThis model is part of o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Lithuanian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transf... | {"language": ["lt"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-lt", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-lt | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"lt",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"lt"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #lt #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Lithuanian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Lithuanian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #lt #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Lithuanian\n\nThis model is part... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Latvian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["lv"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-lv", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-lv | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"lv",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"lv"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #lv #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Latvian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Latvian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #lv #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Latvian\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Classical Chinese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from... | {"language": ["lzh"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-lzh", "results": [{"task": {"type": "token-classification", "name": "P... | wietsedv/xlm-roberta-base-ft-udpos28-lzh | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"lzh",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"lzh"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #lzh #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Classical Chinese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Classical Chinese\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #lzh #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Classical Chinese\... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Marathi
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["mr"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-mr", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-mr | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"mr",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"mr"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #mr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Marathi
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Marathi\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #mr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Marathi\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Maltese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["mt"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-mt", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-mt | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"mt",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"mt"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #mt #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Maltese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Maltese\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #mt #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Maltese\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Dutch
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["nl"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-nl", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-nl | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"nl",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"nl"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #nl #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Dutch
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Dutch\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #nl #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Dutch\n\nThis model... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Norwegian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfo... | {"language": [false], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-no", "results": [{"task": {"type": "token-classification", "name": "Pa... | wietsedv/xlm-roberta-base-ft-udpos28-no | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"no",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"no"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #no #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Norwegian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Norwegian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #no #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Norwegian\n\nThis model is part ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old East Slavic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from t... | {"language": ["orv"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-orv", "results": [{"task": {"type": "token-classification", "name": "P... | wietsedv/xlm-roberta-base-ft-udpos28-orv | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"orv",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"orv"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #orv #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old East Slavic
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old East Slavic\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #orv #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old East Slavic\n\nThis model i... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Naija
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["pcm"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-pcm", "results": [{"task": {"type": "token-classification", "name": "P... | wietsedv/xlm-roberta-base-ft-udpos28-pcm | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"pcm",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pcm"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #pcm #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Naija
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Naija\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #pcm #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Naija\n\nThis model is part of ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Polish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["pl"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-pl", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-pl | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"pl",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pl"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #pl #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Polish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Polish\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #pl #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Polish\n\nThis mode... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Portuguese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transf... | {"language": ["pt"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-pt", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-pt | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"pt",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #pt #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Portuguese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Portuguese\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #pt #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Portuguese\n\nThis ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Romanian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfor... | {"language": ["ro"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ro", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ro | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ro",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ro"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ro #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Romanian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Romanian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ro #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Romanian\n\nThis model is part o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Russian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["ru"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ru", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ru | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ru",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #ru #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Russian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Russian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #ru #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Russian\n\nThis mod... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Sanskrit
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfor... | {"language": ["sa"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-sa", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-sa | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"sa",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sa"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sa #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Sanskrit
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Sanskrit\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sa #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Sanskrit\n\nThis model is part o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Slovak
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["sk"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-sk", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-sk | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"sk",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sk"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sk #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Slovak
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Slovak\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sk #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Slovak\n\nThis model is part of ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Slovenian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfo... | {"language": ["sl"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-sl", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-sl | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"sl",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sl"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sl #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Slovenian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Slovenian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sl #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Slovenian\n\nThis model is part ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: North Sami
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transf... | {"language": ["sme"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-sme", "results": [{"task": {"type": "token-classification", "name": "P... | wietsedv/xlm-roberta-base-ft-udpos28-sme | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"sme",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sme"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sme #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: North Sami
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: North Sami\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sme #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: North Sami\n\nThis model is par... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Serbian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["sr"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-sr", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-sr | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"sr",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sr"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Serbian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Serbian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Serbian\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Swedish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["sv"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-sv", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-sv | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"sv",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sv"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sv #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Swedish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Swedish\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #sv #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Swedish\n\nThis model is part of... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Tamil
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["ta"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ta", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ta | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ta",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ta"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ta #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Tamil
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Tamil\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ta #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Tamil\n\nThis model is part of o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Telugu
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["te"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-te", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-te | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"te",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"te"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #te #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Telugu
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Telugu\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #te #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Telugu\n\nThis model is part of ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Turkish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["tr"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-tr", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-tr | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"tr",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"tr"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #tr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Turkish
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Turkish\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #tr #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Turkish\n\nThis mod... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Uyghur
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transforme... | {"language": ["ug"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ug", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ug | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ug",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ug"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ug #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Uyghur
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Uyghur\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #ug #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Uyghur\n\nThis model is part of ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Ukrainian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transfo... | {"language": ["uk"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-uk", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-uk | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"uk",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"uk"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #uk #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Ukrainian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Ukrainian\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #uk #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Ukrainian\n\nThis model is part ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Urdu
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformers... | {"language": ["ur"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-ur", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-ur | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"ur",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ur"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #ur #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Urdu
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Urdu\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #ur #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Urdu\n\nThis model ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Vietnamese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transf... | {"language": ["vi"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-vi", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-vi | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"vi",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"vi"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #vi #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Vietnamese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Vietnamese\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #vi #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Vietnamese\n\nThis ... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Wolof
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | {"language": ["wo"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-wo", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-wo | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"part-of-speech",
"wo",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"wo"
] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #wo #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Wolof
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Wolof\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #part-of-speech #wo #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Wolof\n\nThis model is part of o... |
token-classification | transformers |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Chinese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transform... | {"language": ["zh"], "license": "apache-2.0", "library_name": "transformers", "tags": ["part-of-speech", "token-classification"], "datasets": ["universal_dependencies"], "metrics": ["accuracy"], "model-index": [{"name": "xlm-roberta-base-ft-udpos28-zh", "results": [{"task": {"type": "token-classification", "name": "Par... | wietsedv/xlm-roberta-base-ft-udpos28-zh | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"token-classification",
"part-of-speech",
"zh",
"dataset:universal_dependencies",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"zh"
] | TAGS
#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #zh #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Chinese
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
## Usage
| [
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Chinese\n\nThis model is part of our paper called:\n\n- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages\n\nCheck the Space for more details.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #safetensors #xlm-roberta #token-classification #part-of-speech #zh #dataset-universal_dependencies #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Chinese\n\nThis mod... |
text-classification | transformers | This is the model used for knowledge clustering where we feed title-body pair and the classifier predicts if the pair is valid or not.
For further information, please refer to https://github.com/yctam/dstc10_track2_task2 for the Github repository.
Credit: Jiakai Zou, Wilson Tam
---
```python
from transformers import ... | {"language": "en", "tags": ["dstc10", "knowledge title-body validation"], "widget": [{"text": "Can you accommodate large groups? It does not offer free WiFi."}, {"text": "Is there a gym on site? It does not have an onsite fitness center."}]} | wilsontam/bert-base-uncased-dstc10-kb-title-body-validate | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"dstc10",
"knowledge title-body validation",
"en",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bert #text-classification #dstc10 #knowledge title-body validation #en #autotrain_compatible #endpoints_compatible #region-us
| This is the model used for knowledge clustering where we feed title-body pair and the classifier predicts if the pair is valid or not.
For further information, please refer to URL for the Github repository.
Credit: Jiakai Zou, Wilson Tam
---
| [] | [
"TAGS\n#transformers #pytorch #bert #text-classification #dstc10 #knowledge title-body validation #en #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-classification | transformers | This is the model used for knowledge cluster classification for the DSTC10 track2 knowledge selection task, trained with double heads, i.e., classifier head and LM head using ASR error simulator for model training.
For further information, please refer to https://github.com/yctam/dstc10_track2_task2 for the Github rep... | {"language": "en", "tags": ["dstc10", "knowledge cluster classifier"], "widget": [{"text": "oh and we'll mi thing uh is there bike clo ars or bike crac where i can park my thee"}, {"text": "oh and one more thing uhhh is there bike lockers or a bike rack where i can park my bike"}, {"text": "ni yeah that sounds great um... | wilsontam/bert-base-uncased-dstc10-knowledge-cluster-classifier | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"dstc10",
"knowledge cluster classifier",
"en",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bert #text-classification #dstc10 #knowledge cluster classifier #en #autotrain_compatible #endpoints_compatible #region-us
| This is the model used for knowledge cluster classification for the DSTC10 track2 knowledge selection task, trained with double heads, i.e., classifier head and LM head using ASR error simulator for model training.
For further information, please refer to URL for the Github repository. You can use this model and use o... | [] | [
"TAGS\n#transformers #pytorch #bert #text-classification #dstc10 #knowledge cluster classifier #en #autotrain_compatible #endpoints_compatible #region-us \n"
] |
fill-mask | transformers | # Goal
This Bert model is trained using DSTC9 training + validation data for dialogue modeling purpose.
Data link: https://github.com/alexa/alexa-with-dstc9-track1-dataset
Credit: Shuhan Yuan, Wilson Tam | {"language": "en", "tags": ["dstc10"], "widget": [{"text": "Can you accommodate large [MASK] ?"}]} | wilsontam/bert-base-uncased-dstc9 | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"dstc10",
"en",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bert #fill-mask #dstc10 #en #autotrain_compatible #endpoints_compatible #region-us
| # Goal
This Bert model is trained using DSTC9 training + validation data for dialogue modeling purpose.
Data link: URL
Credit: Shuhan Yuan, Wilson Tam | [
"# Goal\nThis Bert model is trained using DSTC9 training + validation data for dialogue modeling purpose.\nData link: URL\n\nCredit: Shuhan Yuan, Wilson Tam"
] | [
"TAGS\n#transformers #pytorch #bert #fill-mask #dstc10 #en #autotrain_compatible #endpoints_compatible #region-us \n",
"# Goal\nThis Bert model is trained using DSTC9 training + validation data for dialogue modeling purpose.\nData link: URL\n\nCredit: Shuhan Yuan, Wilson Tam"
] |
text-generation | transformers |
This GPT2 model is trained using DSTC9 data for dialogue modeling purpose.
Data link: https://github.com/alexa/alexa-with-dstc9-track1-dataset
Credit: Jia-Chen Jason Gu, Wilson Tam
| {"language": "en", "tags": ["dstc9"], "widget": [{"text": "Yes, I'm going to be in Chinatown, San Francisco and am looking"}, {"text": "Can you find me one that is in the"}]} | wilsontam/gpt2-dstc9 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"dstc9",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #dstc9 #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
This GPT2 model is trained using DSTC9 data for dialogue modeling purpose.
Data link: URL
Credit: Jia-Chen Jason Gu, Wilson Tam
| [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #dstc9 #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
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