Search is not available for this dataset
pipeline_tag stringclasses 48
values | library_name stringclasses 205
values | text stringlengths 0 18.3M | metadata stringlengths 2 1.07B | id stringlengths 5 122 | last_modified null | tags listlengths 1 1.84k | sha null | created_at stringlengths 25 25 |
|---|---|---|---|---|---|---|---|---|
null | null | {} | AhmedHassan19/model | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text2text-generation | transformers |
```
```
[](https://paperswithcode.com/sota/code-generation-on-conala?p=mariancg-a-code-generation-transformer-model)
```
```
# MarianCG: a code generation transformer... | {"widget": [{"text": "create array containing the maximum value of respective elements of array `[2, 3, 4]` and array `[1, 5, 2]"}, {"text": "check if all elements in list `mylist` are identical"}, {"text": "enable debug mode on flask application `app`"}, {"text": "getting the length of `my_tuple`"}, {"text": "find all... | AhmedSSoliman/MarianCG-CoNaLa | null | [
"transformers",
"pytorch",
"marian",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Ahmedahmed/Wewe | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-classification | transformers | {} | Ahren09/distilbert-base-uncased-finetuned-cola | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers |
# Back to the Future DialoGPT Model | {"tags": ["conversational"]} | AiPorter/DialoGPT-small-Back_to_the_future | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-generation | transformers |
# Rick DialoGPT Model | {"tags": ["conversational"]} | Aibox/DialoGPT-small-rick | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | Trained on Stephen King's top 50 books as .txt files. | {} | Aidan8756/stephenKingModel | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
fill-mask | transformers | {} | AidenGO/KDXF_Bert4MaskedLM | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AigizK/wav2vec2-large-xls-r-300m-bashkir-cv7_no_lm | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
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-xls-r-300m-bashkir-cv7_opt
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingfa... | {"language": ["ba"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-bashkir-cv7_opt",... | AigizK/wav2vec2-large-xls-r-300m-bashkir-cv7_opt | null | [
"transformers",
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"ba",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"end... | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | AimB/konlpy_berttokenizer_helsinki | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AimB/mT5-en-kr-aihub-netflix | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text2text-generation | transformers | you can use this model with simpletransfomers.
```
!pip install simpletransformers
from simpletransformers.t5 import T5Model
model = T5Model("mt5", "AimB/mT5-en-kr-natural")
print(model.predict(["I feel good today"]))
print(model.predict(["우리집 고양이는 세상에서 제일 귀엽습니다"]))
``` | {} | AimB/mT5-en-kr-natural | null | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | AimB/mT5-en-kr-opus | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Aimendo/Triage | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-classification | transformers |
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 35248482
- CO2 Emissions (in grams): 7.989144645413398
## Validation Metrics
- Loss: 0.13783401250839233
- Accuracy: 0.9728654124457308
- Macro F1: 0.949537871674076
- Micro F1: 0.9728654124457308
- Weighted F1: 0.9732422812610365
... | {"language": "en", "tags": "autonlp", "datasets": ["Aimendo/autonlp-data-triage"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 7.989144645413398} | Aimendo/autonlp-triage-35248482 | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"autonlp",
"en",
"dataset:Aimendo/autonlp-data-triage",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-classification | transformers |
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 530014983
- CO2 Emissions (in grams): 55.10196329868386
## Validation Metrics
- Loss: 0.23171618580818176
- Accuracy: 0.9298837645294338
- Precision: 0.9314414866901055
- Recall: 0.9279459594696022
- AUC: 0.979447403984557
- F1: 0.92969... | {"language": "en", "tags": "autonlp", "datasets": ["Ajay191191/autonlp-data-Test"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_emissions": 55.10196329868386} | Ajay191191/autonlp-Test-530014983 | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"autonlp",
"en",
"dataset:Ajay191191/autonlp-data-Test",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text2text-generation | transformers |
# Model Trained Using AutoNLP
- Problem type: Summarization
- Model ID: 16122692
## Validation Metrics
- Loss: 1.1877621412277222
- Rouge1: 42.0713
- Rouge2: 23.3043
- RougeL: 37.3755
- RougeLsum: 37.8961
- Gen Len: 60.7117
## Usage
You can use cURL to access this model:
```
$ curl -X POST -H "Authorization: Bea... | {"language": "unk", "tags": "autonlp", "datasets": ["Ajaykannan6/autonlp-data-manthan"], "widget": [{"text": "I love AutoNLP \ud83e\udd17"}]} | Ajaykannan6/autonlp-manthan-16122692 | null | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"autonlp",
"unk",
"dataset:Ajaykannan6/autonlp-data-manthan",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Ajteks/Chatbot | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AkaiSnow/Rick_bot | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Akame/Vi | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Akaramhuggingface/News | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
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. -->
# albert-base-v2-finetuned-squad
This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad_v2"], "model-index": [{"name": "albert-base-v2-finetuned-squad", "results": []}]} | Akari/albert-base-v2-finetuned-squad | null | [
"transformers",
"pytorch",
"tensorboard",
"albert",
"question-answering",
"generated_from_trainer",
"dataset:squad_v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
fill-mask | 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. -->
# bert-base-cased-wikitext2
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-cased-wikitext2", "results": []}]} | Akash7897/bert-base-cased-wikitext2 | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-classification | 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. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["matthews_correlation"], "model-index": [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "ar... | Akash7897/distilbert-base-uncased-finetuned-cola | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-classification | 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. -->
# distilbert-base-uncased-finetuned-sst2
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["accuracy"], "model-index": [{"name": "distilbert-base-uncased-finetuned-sst2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "args": "sst2"}... | Akash7897/distilbert-base-uncased-finetuned-sst2 | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Akash7897/fill_mask_model | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-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. -->
# gpt2-wikitext2
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the fo... | {"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-wikitext2", "results": []}]} | Akash7897/gpt2-wikitext2 | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Akash7897/my-newtokenizer | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Akash7897/test-clm | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Akashamba/distilbert-base-uncased-finetuned-ner | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
automatic-speech-recognition | transformers |
# Akashpb13/Central_kurdish_xlsr
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with inv... | {"language": ["ckb"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "ckb", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "Akashpb13/Central... | Akashpb13/Central_kurdish_xlsr | null | [
"transformers",
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"ckb",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
... | null | 2022-03-02T23:29:04+00:00 |
automatic-speech-recognition | transformers |
# Akashpb13/Galician_xlsr
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset.
It achieves the following results on the evaluation set (which is 10 percent of train data set merged with invali... | {"language": ["gl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "gl", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "Akashpb13/Galician_... | Akashpb13/Galician_xlsr | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"gl",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:04+00:00 |
automatic-speech-recognition | transformers |
# Akashpb13/Hausa_xlsr
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m)
It achieves the following results on the evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other, and dev datasets):
- Loss: 0.2... | {"language": ["ha"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "ha", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "Akashpb13/Hausa_xls... | Akashpb13/Hausa_xlsr | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"ha",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:04+00:00 |
automatic-speech-recognition | transformers |
# Akashpb13/Kabyle_xlsr
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset.
It achieves the following results on the evaluation set (which is 10 percent of train data set merged with dev data... | {"language": ["kab"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "sw", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "Akashpb13/Kabyle_x... | Akashpb13/Kabyle_xlsr | null | [
"transformers",
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"sw",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"kab",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-... | null | 2022-03-02T23:29:04+00:00 |
automatic-speech-recognition | transformers |
# Akashpb13/Swahili_xlsr
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset.
It achieves the following results on the evaluation set (which is 10 percent of train data set merged with dev dat... | {"language": ["sw"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "sw"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "Akashpb13/Swahili_x... | Akashpb13/Swahili_xlsr | null | [
"transformers",
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"sw",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"... | null | 2022-03-02T23:29:04+00:00 |
automatic-speech-recognition | transformers |
# Akashpb13/xlsr_hungarian_new
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - hu dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with inval... | {"language": ["hu"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "hu", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "Akashpb13/xlsr_hung... | Akashpb13/xlsr_hungarian_new | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"hu",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:04+00:00 |
automatic-speech-recognition | transformers |
# Akashpb13/xlsr_kurmanji_kurdish
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset.
It achieves the following results on the evaluation set (which is 10 percent of train data set merged wit... | {"language": ["kmr", "ku"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "kmr", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "Akashpb13/x... | Akashpb13/xlsr_kurmanji_kurdish | null | [
"transformers",
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"kmr",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"ku",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-... | null | 2022-03-02T23:29:04+00:00 |
automatic-speech-recognition | transformers | # Wav2Vec2-Large-XLSR-53-Maltese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Maltese using the [Common Voice](https://huggingface.co/datasets/common_voice)
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be u... | {"language": "mt", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "model-index": [{"name": "XLSR Wav2Vec2 Maltese by Akash PB", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "data... | Akashpb13/xlsr_maltese_wav2vec2 | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"mt",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Akbarariza/Anjar | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Akira-Yanagi/distilbert-base-uncased-finetuned-cola | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Akiva/Joke | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers |
# Harry Potter DialoGPT Model | {"tags": ["conversational"]} | Akjder/DialoGPT-small-harrypotter | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Aklily/Lilys | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
image-classification | transformers |
# BEiT for Face Mask Detection
BEiT model pre-trained and fine-tuned on Self Currated Custom Face-Mask18K Dataset (18k images, 2 classes) at resolution 224x224. It was introduced in the paper BEIT: BERT Pre-Training of Image Transformers by Hangbo Bao, Li Dong and Furu Wei.
## Model description
The BEiT mo... | {"license": "apache-2.0", "tags": ["image-classification"], "datasets": ["Face-Mask18K"]} | AkshatSurolia/BEiT-FaceMask-Finetuned | null | [
"transformers",
"pytorch",
"beit",
"image-classification",
"dataset:Face-Mask18K",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
image-classification | transformers |
# ConvNeXt for Face Mask Detection
ConvNeXt model pre-trained and fine-tuned on Self Currated Custom Face-Mask18K Dataset (18k images, 2 classes) at resolution 224x224. It was introduced in the paper A ConvNet for the 2020s by Zhuang Liu, Hanzi Mao et al.
## Training Metrics
epoch = ... | {"license": "apache-2.0", "tags": ["image-classification"], "datasets": ["Face-Mask18K"]} | AkshatSurolia/ConvNeXt-FaceMask-Finetuned | null | [
"transformers",
"pytorch",
"safetensors",
"convnext",
"image-classification",
"dataset:Face-Mask18K",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
image-classification | transformers |
# Distilled Data-efficient Image Transformer for Face Mask Detection
Distilled data-efficient Image Transformer (DeiT) model pre-trained and fine-tuned on Self Currated Custom Face-Mask18K Dataset (18k images, 2 classes) at resolution 224x224. It was first introduced in the paper Training data-efficient image tran... | {"license": "apache-2.0", "tags": ["image-classification"], "datasets": ["Face-Mask18K"]} | AkshatSurolia/DeiT-FaceMask-Finetuned | null | [
"transformers",
"pytorch",
"deit",
"image-classification",
"dataset:Face-Mask18K",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-classification | transformers |
# Clinical BERT for ICD-10 Prediction
The Publicly Available Clinical BERT Embeddings paper contains four unique clinicalBERT models: initialized with BERT-Base (cased_L-12_H-768_A-12) or BioBERT (BioBERT-Base v1.0 + PubMed 200K + PMC 270K) & trained on either all MIMIC notes or only discharge summaries.
---
## ... | {"license": "apache-2.0", "tags": ["text-classification"]} | AkshatSurolia/ICD-10-Code-Prediction | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
image-classification | transformers |
# Vision Transformer (ViT) for Face Mask Detection
Vision Transformer (ViT) model pre-trained and fine-tuned on Self Currated Custom Face-Mask18K Dataset (18k images, 2 classes) at resolution 224x224. It was first introduced in the paper Training data-efficient image transformers & distillation through attention b... | {"license": "apache-2.0", "tags": ["image-classification"], "datasets": ["Face-Mask18K"]} | AkshatSurolia/ViT-FaceMask-Finetuned | null | [
"transformers",
"pytorch",
"safetensors",
"vit",
"image-classification",
"dataset:Face-Mask18K",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | AkshayDev/BERT_Fine_Tuning | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AkshaySg/GrammarCorrection | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null |
# Spoken Language Identification Model
## Model description
The model can classify a speech utterance according to the language spoken.
It covers following different languages (
English,
Indonesian,
Japanese,
Korean,
Thai,
Vietnamese,
Mandarin Chinese).
| {"language": "multilingual", "license": "apache-2.0", "tags": ["LID", "spoken language recognition"], "datasets": ["VoxLingua107"], "metrics": ["ER"], "inference": false} | AkshaySg/LanguageIdentification | null | [
"LID",
"spoken language recognition",
"multilingual",
"dataset:VoxLingua107",
"license:apache-2.0",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text2text-generation | transformers | {} | AkshaySg/gramCorrection | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
audio-classification | speechbrain |
# VoxLingua107 ECAPA-TDNN Spoken Language Identification Model
## Model description
This is a spoken language recognition model trained on the VoxLingua107 dataset using SpeechBrain.
The model uses the ECAPA-TDNN architecture that has previously been used for speaker recognition.
The model can classify a speech utt... | {"language": "multilingual", "license": "apache-2.0", "tags": ["audio-classification", "speechbrain", "embeddings", "Language", "Identification", "pytorch", "ECAPA-TDNN", "TDNN", "VoxLingua107"], "datasets": ["VoxLingua107"], "metrics": ["Accuracy"], "widget": [{"example_title": "English Sample", "src": "https://cdn-me... | AkshaySg/langid | null | [
"speechbrain",
"audio-classification",
"embeddings",
"Language",
"Identification",
"pytorch",
"ECAPA-TDNN",
"TDNN",
"VoxLingua107",
"multilingual",
"dataset:VoxLingua107",
"license:apache-2.0",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Akuva2001/SocialGraph | null | [
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Al/mymodel | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AlErysvi/Erys | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
token-classification | transformers | {} | Alaeddin/convbert-base-turkish-ner-cased | null | [
"transformers",
"pytorch",
"convbert",
"token-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AlanDev/DallEMiniButBetter | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AlanDev/dall-e-better | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AlanDev/test | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | transformers | {} | AlbertHSU/BertTEST | null | [
"transformers",
"pytorch",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
feature-extraction | transformers | {} | AlbertHSU/ChineseFoodBert | null | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Alberto15Romero/GptNeo | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AlchemistDude/DialoGPT-medium-Gon | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Ale/Alen | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Aleenbo/Arcane | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
fill-mask | 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. -->
# bert-srb-base-cased-oscar
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
## Model descr... | {"tags": ["generated_from_trainer"], "model_index": [{"name": "bert-srb-base-cased-oscar", "results": [{"task": {"name": "Masked Language Modeling", "type": "fill-mask"}}]}]} | Aleksandar/bert-srb-base-cased-oscar | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Aleksandar/bert-srb-ner-setimes-lr | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
token-classification | 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. -->
# bert-srb-ner-setimes
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluatio... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model_index": [{"name": "bert-srb-ner-setimes", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "metric": {"name": "Accuracy", "type": "accuracy", "value": 0.9645112274185379}}]}]} | Aleksandar/bert-srb-ner-setimes | null | [
"transformers",
"pytorch",
"bert",
"token-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
token-classification | 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. -->
# bert-srb-ner
This model was trained from scratch on the wikiann dataset.
It achieves the following results on the evaluation set... | {"tags": ["generated_from_trainer"], "datasets": ["wikiann"], "metrics": ["precision", "recall", "f1", "accuracy"], "model_index": [{"name": "bert-srb-ner", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "wikiann", "type": "wikiann", "args": "sr"}, "metric": {... | Aleksandar/bert-srb-ner | null | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:wikiann",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
fill-mask | 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. -->
# distilbert-srb-base-cased-oscar
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
## Model... | {"tags": ["generated_from_trainer"], "model_index": [{"name": "distilbert-srb-base-cased-oscar", "results": [{"task": {"name": "Masked Language Modeling", "type": "fill-mask"}}]}]} | Aleksandar/distilbert-srb-base-cased-oscar | null | [
"transformers",
"pytorch",
"distilbert",
"fill-mask",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Aleksandar/distilbert-srb-ner-setimes-lr | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
token-classification | 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. -->
# distilbert-srb-ner-setimes
This model was trained from scratch on the None dataset.
It achieves the following results on the eva... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model_index": [{"name": "distilbert-srb-ner-setimes", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "metric": {"name": "Accuracy", "type": "accuracy", "value": 0.9665376552169005}}]}]} | Aleksandar/distilbert-srb-ner-setimes | null | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"token-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
token-classification | 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. -->
# distilbert-srb-ner
This model was trained from scratch on the wikiann dataset.
It achieves the following results on the evaluati... | {"language": ["sr"], "tags": ["generated_from_trainer"], "datasets": ["wikiann"], "metrics": ["precision", "recall", "f1", "accuracy"], "model_index": [{"name": "distilbert-srb-ner", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "wikiann", "type": "wikiann", ... | Aleksandar/distilbert-srb-ner | null | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"generated_from_trainer",
"sr",
"dataset:wikiann",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Aleksandar/electra-srb-ner-setimes-lr | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
token-classification | 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. -->
# electra-srb-ner-setimes
This model was trained from scratch on the None dataset.
It achieves the following results on the evalua... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model_index": [{"name": "electra-srb-ner-setimes", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "metric": {"name": "Accuracy", "type": "accuracy", "value": 0.9546789604788638}}]}]} | Aleksandar/electra-srb-ner-setimes | null | [
"transformers",
"pytorch",
"safetensors",
"electra",
"token-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
token-classification | 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. -->
# electra-srb-ner
This model was trained from scratch on the wikiann dataset.
It achieves the following results on the evaluation ... | {"tags": ["generated_from_trainer"], "datasets": ["wikiann"], "metrics": ["precision", "recall", "f1", "accuracy"], "model_index": [{"name": "electra-srb-ner", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "wikiann", "type": "wikiann", "args": "sr"}, "metric"... | Aleksandar/electra-srb-ner | null | [
"transformers",
"pytorch",
"safetensors",
"electra",
"token-classification",
"generated_from_trainer",
"dataset:wikiann",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
fill-mask | 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. -->
# electra-srb-oscar
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
## Model description
... | {"tags": ["generated_from_trainer"], "model_index": [{"name": "electra-srb-oscar", "results": [{"task": {"name": "Masked Language Modeling", "type": "fill-mask"}}]}]} | Aleksandar/electra-srb-oscar | null | [
"transformers",
"pytorch",
"electra",
"fill-mask",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-generation | transformers | {} | Aleksandar1932/distilgpt2-rock | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers | {} | Aleksandar1932/gpt2-country | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers | {} | Aleksandar1932/gpt2-hip-hop | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers | {} | Aleksandar1932/gpt2-pop | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers | {} | Aleksandar1932/gpt2-rock-124439808 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers | {} | Aleksandar1932/gpt2-soul | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers | {} | Aleksandar1932/gpt2-spanish-classics | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | Aleksandra/distilbert-base-uncased-finetuned-squad | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
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. -->
# herbert-base-cased-finetuned-squad
This model is a fine-tuned version of [allegro/herbert-base-cased](https://huggingface.co/all... | {"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "herbert-base-cased-finetuned-squad", "results": []}]} | Aleksandra/herbert-base-cased-finetuned-squad | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-classification | transformers |
# xlm-roberta-en-ru-emoji
- Problem type: Multi-class Classification | {"language": ["en", "ru"], "datasets": ["tweet_eval"], "model_index": [{"name": "xlm-roberta-en-ru-emoji", "results": [{"task": {"name": "Sentiment Analysis", "type": "sentiment-analysis"}, "dataset": {"name": "Tweet Eval", "type": "tweet_eval", "args": "emoji"}}]}], "widget": [{"text": "\u041e\u0442\u043b\u0438\u0447\... | adorkin/xlm-roberta-en-ru-emoji | null | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"text-classification",
"en",
"ru",
"dataset:tweet_eval",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-classification | 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. -->
# bert
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unkno... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "bert", "results": []}]} | AlekseyKorshuk/bert | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-generation | transformers | {} | AlekseyKorshuk/comedy-scripts | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text-generation | transformers | {} | AlekseyKorshuk/horror-scripts | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
text2text-generation | transformers | **Usage HuggingFace Transformers for header generation task**
```
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("AlekseyKulnevich/Pegasus-HeaderGeneration")
tokenizer = PegasusTokenizer.from_pretrained('google/pegasus-large')
input_text # your text
input_ ... | {} | AlekseyKulnevich/Pegasus-HeaderGeneration | null | [
"transformers",
"pytorch",
"pegasus",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text2text-generation | transformers | **Usage HuggingFace Transformers for question generation task**
```
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("AlekseyKulnevich/Pegasus-QuestionGeneration")
tokenizer = PegasusTokenizer.from_pretrained('google/pegasus-large')
input_text # your text
inp... | {} | AlekseyKulnevich/Pegasus-QuestionGeneration | null | [
"transformers",
"pytorch",
"pegasus",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text2text-generation | transformers | **Usage HuggingFace Transformers for summarization task**
```
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("AlekseyKulnevich/Pegasus-Summarization")
tokenizer = PegasusTokenizer.from_pretrained('google/pegasus-large')
input_text # your text
input_ = token... | {} | AlekseyKulnevich/Pegasus-Summarization | null | [
"transformers",
"pytorch",
"pegasus",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
text-generation | transformers |
This is a fine-tuned version of GPT-2, trained with the entire corpus of Plato's works. By generating text samples you should be able to generate ancient Greek philosophy on the fly!
| {"language": "en", "tags": ["text-generation"], "pipeline_tag": "text-generation", "widget": [{"text": "The Gods"}, {"text": "What is"}]} | Alerosae/SocratesGPT-2 | null | [
"transformers",
"pytorch",
"gpt2",
"feature-extraction",
"text-generation",
"en",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
null | null | {} | Alessandro/model_name | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
null | null | {} | AlexDemon/Alex | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | |
question-answering | transformers | # XLM-RoBERTa large model whole word masking finetuned on SQuAD
Pretrained model using a masked language modeling (MLM) objective.
Fine tuned on English and Russian QA datasets
## Used QA Datasets
SQuAD + SberQuAD
[SberQuAD original paper](https://arxiv.org/pdf/1912.09723.pdf) is here! Recommend to read!
## Evaluat... | {"language": ["en", "ru", "multilingual"], "license": "apache-2.0"} | AlexKay/xlm-roberta-large-qa-multilingual-finedtuned-ru | null | [
"transformers",
"pytorch",
"xlm-roberta",
"question-answering",
"en",
"ru",
"multilingual",
"arxiv:1912.09723",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
token-classification | 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. -->
# sentence-compression-roberta
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unk... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "sentence-compression-roberta", "results": []}]} | AlexMaclean/sentence-compression-roberta | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 |
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