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fill-mask | transformers |
# NOTE: This repository is now superseded by https://huggingface.co/bertin-project/bertin-roberta-base-spanish. This model corresponds to the `beta` version of the model using stepwise over sampling trained for 200k steps with 128 sequence lengths. Version 1 is now available and should be used instead.
# BERTIN
BERT... | {"language": "es", "license": "cc-by-4.0", "tags": ["spanish", "roberta"], "pipeline_tag": "fill-mask", "widget": [{"text": "Fui a la librer\u00eda a comprar un <mask>."}]} | flax-community/bertin-roberta-large-spanish | null | [
"transformers",
"pytorch",
"jax",
"safetensors",
"roberta",
"fill-mask",
"spanish",
"es",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #jax #safetensors #roberta #fill-mask #spanish #es #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# NOTE: This repository is now superseded by URL This model corresponds to the 'beta' version of the model using stepwise over sampling trained for 200k steps with 128 sequence lengths. Version 1 is now available and should be used instead.
# BERTIN
BERTIN is a series of BERT-based models for Spanish. This one is a ... | [
"# NOTE: This repository is now superseded by URL This model corresponds to the 'beta' version of the model using stepwise over sampling trained for 200k steps with 128 sequence lengths. Version 1 is now available and should be used instead.",
"# BERTIN\n\nBERTIN is a series of BERT-based models for Spanish. This... | [
"TAGS\n#transformers #pytorch #jax #safetensors #roberta #fill-mask #spanish #es #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# NOTE: This repository is now superseded by URL This model corresponds to the 'beta' version of the model using stepwise over sampling trained for 200k ... |
null | transformers |
# BigBird base model
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.
It is a pretrained model ... | {"language": "en", "license": "apache-2.0", "datasets": ["bookcorpus", "wikipedia", "cc_news"]} | flax-community/bigband | null | [
"transformers",
"big_bird",
"pretraining",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"dataset:cc_news",
"arxiv:2007.14062",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2007.14062"
] | [
"en"
] | TAGS
#transformers #big_bird #pretraining #en #dataset-bookcorpus #dataset-wikipedia #dataset-cc_news #arxiv-2007.14062 #license-apache-2.0 #endpoints_compatible #region-us
|
# BigBird base model
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.
It is a pretrained model ... | [
"# BigBird base model\n\nBigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.\n\nIt is a pretraine... | [
"TAGS\n#transformers #big_bird #pretraining #en #dataset-bookcorpus #dataset-wikipedia #dataset-cc_news #arxiv-2007.14062 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# BigBird base model\n\nBigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much... |
text2text-generation | transformers | # T5 model for sentence splitting in English
Sentence Split is the task of dividing a long sentence into multiple sentences.
E.g.:
```
Mary likes to play football in her freetime whenever she meets with her friends that are very nice people.
```
could be split into
```
Mary likes to play football in her freetime whene... | {"datasets": ["wiki_split"], "widget": [{"text": "Mary likes to play football in her freetime whenever she meets with her friends that are very nice people."}]} | flax-community/byt5-base-wikisplit | null | [
"transformers",
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"tensorboard",
"safetensors",
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"text2text-generation",
"dataset:wiki_split",
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"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1907.12461"
] | [] | TAGS
#transformers #pytorch #tf #jax #tensorboard #safetensors #t5 #text2text-generation #dataset-wiki_split #arxiv-1907.12461 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| T5 model for sentence splitting in English
==========================================
Sentence Split is the task of dividing a long sentence into multiple sentences.
E.g.:
could be split into
How to use it in your code:
---------------------------
Datasets:
---------
Wiki\_Split
Current Basline from paper
-... | [] | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #safetensors #t5 #text2text-generation #dataset-wiki_split #arxiv-1907.12461 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
null | null | # Searching Reaction GIFs with CLIP
Reaction GIFs are an integral part of today's communication. They convey complex emotions with many levels, in a short compact format.
If a picture is worth a thousand words then a GIF is worth more.
We might even say that the leve... | {} | flax-community/clip-reply | null | [
"tensorboard",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#tensorboard #has_space #region-us
| # Searching Reaction GIFs with CLIP
!header gif
Reaction GIFs are an integral part of today's communication. They convey complex emotions with many levels, in a short compact format.
If a picture is worth a thousand words then a GIF is worth more.
We might even say that the level of complexity and expressiveness in... | [
"# Searching Reaction GIFs with CLIP\n\n!header gif\n\nReaction GIFs are an integral part of today's communication. They convey complex emotions with many levels, in a short compact format.\n\nIf a picture is worth a thousand words then a GIF is worth more.\n\nWe might even say that the level of complexity and expr... | [
"TAGS\n#tensorboard #has_space #region-us \n",
"# Searching Reaction GIFs with CLIP\n\n!header gif\n\nReaction GIFs are an integral part of today's communication. They convey complex emotions with many levels, in a short compact format.\n\nIf a picture is worth a thousand words then a GIF is worth more.\n\nWe mig... |
zero-shot-image-classification | transformers |
# Model Card: clip-rsicd
## Model Details
This model is a fine-tuned [CLIP by OpenAI](https://huggingface.co/openai/clip-vit-base-patch32). It is designed with an aim to improve zero-shot image classification, text-to-image and image-to-image retrieval specifically on remote sensing images.
### Model Date
July 202... | {"tags": ["vision"]} | flax-community/clip-rsicd-v2 | null | [
"transformers",
"pytorch",
"jax",
"clip",
"zero-shot-image-classification",
"vision",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #clip #zero-shot-image-classification #vision #endpoints_compatible #has_space #region-us
| Model Card: clip-rsicd
======================
Model Details
-------------
This model is a fine-tuned CLIP by OpenAI. It is designed with an aim to improve zero-shot image classification, text-to-image and image-to-image retrieval specifically on remote sensing images.
### Model Date
July 2021
### Model Type
... | [
"### Model Date\n\n\nJuly 2021",
"### Model Type\n\n\nThe base model uses a ViT-B/32 Transformer architecture as an image encoder and uses a masked self-attention Transformer as a text encoder. These encoders are trained to maximize the similarity of (image, text) pairs via a contrastive loss.",
"### Model Vers... | [
"TAGS\n#transformers #pytorch #jax #clip #zero-shot-image-classification #vision #endpoints_compatible #has_space #region-us \n",
"### Model Date\n\n\nJuly 2021",
"### Model Type\n\n\nThe base model uses a ViT-B/32 Transformer architecture as an image encoder and uses a masked self-attention Transformer as a te... |
zero-shot-image-classification | transformers |
# Model Card: clip-rsicd
## Model Details
This model is a finetuned [CLIP by OpenAI](https://huggingface.co/openai/clip-vit-base-patch32). It is designed with an aim to improve zero-shot image classification, text-to-image and image-to-image retrieval specifically on remote sensing images.
### Model Date
July 2021... | {"tags": ["vision"]} | flax-community/clip-rsicd | null | [
"transformers",
"pytorch",
"jax",
"clip",
"zero-shot-image-classification",
"vision",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #clip #zero-shot-image-classification #vision #endpoints_compatible #has_space #region-us
| Model Card: clip-rsicd
======================
Model Details
-------------
This model is a finetuned CLIP by OpenAI. It is designed with an aim to improve zero-shot image classification, text-to-image and image-to-image retrieval specifically on remote sensing images.
### Model Date
July 2021
### Model Type
... | [
"### Model Date\n\n\nJuly 2021",
"### Model Type\n\n\nThe base model uses a ViT-B/32 Transformer architecture as an image encoder and uses a masked self-attention Transformer as a text encoder. These encoders are trained to maximize the similarity of (image, text) pairs via a contrastive loss.",
"### Model Vers... | [
"TAGS\n#transformers #pytorch #jax #clip #zero-shot-image-classification #vision #endpoints_compatible #has_space #region-us \n",
"### Model Date\n\n\nJuly 2021",
"### Model Type\n\n\nThe base model uses a ViT-B/32 Transformer architecture as an image encoder and uses a masked self-attention Transformer as a te... |
null | transformers | # CLIP-Spanish
CLIP Spanish is a CLIP-like model for Spanish language. It is composed of [BERTIN](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) as a language encoder and the ViT-B/32 image encoder from [CLIP](https://huggingface.co/openai/clip-vit-base-patch32). The model is implemented in [Flax](... | {"language": "es", "license": "cc-by-4.0", "tags": ["spanish", "roberta", "vit"]} | flax-community/clip-spanish | null | [
"transformers",
"jax",
"hybrid-clip",
"spanish",
"roberta",
"vit",
"es",
"license:cc-by-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #jax #hybrid-clip #spanish #roberta #vit #es #license-cc-by-4.0 #endpoints_compatible #has_space #region-us
| # CLIP-Spanish
CLIP Spanish is a CLIP-like model for Spanish language. It is composed of BERTIN as a language encoder and the ViT-B/32 image encoder from CLIP. The model is implemented in Flax, including training scripts (see 'URL').
This is part of the Flax/Jax Community Week, organised by HuggingFace and TPU usage s... | [
"# CLIP-Spanish\n\nCLIP Spanish is a CLIP-like model for Spanish language. It is composed of BERTIN as a language encoder and the ViT-B/32 image encoder from CLIP. The model is implemented in Flax, including training scripts (see 'URL').\nThis is part of the Flax/Jax Community Week, organised by HuggingFace and TPU... | [
"TAGS\n#transformers #jax #hybrid-clip #spanish #roberta #vit #es #license-cc-by-4.0 #endpoints_compatible #has_space #region-us \n",
"# CLIP-Spanish\n\nCLIP Spanish is a CLIP-like model for Spanish language. It is composed of BERTIN as a language encoder and the ViT-B/32 image encoder from CLIP. The model is imp... |
fill-mask | transformers | # CLIP-Vision-BERT Multilingual Pre-trained Model
Pretrained CLIP-Vision-BERT pre-trained on translated [Conceptual-12M](https://github.com/google-research-datasets/conceptual-12m) image-text pairs using a masked language modeling (MLM) objective. 10M cleaned image-text pairs are translated using [mBART-50 one-to-many... | {} | flax-community/clip-vision-bert-cc12m-60k | null | [
"transformers",
"jax",
"clip-vision-bert",
"fill-mask",
"arxiv:1908.03557",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1908.03557"
] | [] | TAGS
#transformers #jax #clip-vision-bert #fill-mask #arxiv-1908.03557 #autotrain_compatible #endpoints_compatible #region-us
| # CLIP-Vision-BERT Multilingual Pre-trained Model
Pretrained CLIP-Vision-BERT pre-trained on translated Conceptual-12M image-text pairs using a masked language modeling (MLM) objective. 10M cleaned image-text pairs are translated using mBART-50 one-to-many model to 2.5M examples each in English, French, German and Spa... | [
"# CLIP-Vision-BERT Multilingual Pre-trained Model\n\nPretrained CLIP-Vision-BERT pre-trained on translated Conceptual-12M image-text pairs using a masked language modeling (MLM) objective. 10M cleaned image-text pairs are translated using mBART-50 one-to-many model to 2.5M examples each in English, French, German ... | [
"TAGS\n#transformers #jax #clip-vision-bert #fill-mask #arxiv-1908.03557 #autotrain_compatible #endpoints_compatible #region-us \n",
"# CLIP-Vision-BERT Multilingual Pre-trained Model\n\nPretrained CLIP-Vision-BERT pre-trained on translated Conceptual-12M image-text pairs using a masked language modeling (MLM) ob... |
fill-mask | transformers | # CLIP-Vision-BERT Multilingual Pre-trained Model
Pretrained CLIP-Vision-BERT pre-trained on translated [Conceptual-12M](https://github.com/google-research-datasets/conceptual-12m) image-text pairs using a masked language modeling (MLM) objective. 10M cleaned image-text pairs are translated using [mBART-50 one-to-many... | {} | flax-community/clip-vision-bert-cc12m-70k | null | [
"transformers",
"jax",
"clip-vision-bert",
"fill-mask",
"arxiv:1908.03557",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1908.03557"
] | [] | TAGS
#transformers #jax #clip-vision-bert #fill-mask #arxiv-1908.03557 #autotrain_compatible #endpoints_compatible #has_space #region-us
| # CLIP-Vision-BERT Multilingual Pre-trained Model
Pretrained CLIP-Vision-BERT pre-trained on translated Conceptual-12M image-text pairs using a masked language modeling (MLM) objective. 10M cleaned image-text pairs are translated using mBART-50 one-to-many model to 2.5M examples each in English, French, German and Spa... | [
"# CLIP-Vision-BERT Multilingual Pre-trained Model\n\nPretrained CLIP-Vision-BERT pre-trained on translated Conceptual-12M image-text pairs using a masked language modeling (MLM) objective. 10M cleaned image-text pairs are translated using mBART-50 one-to-many model to 2.5M examples each in English, French, German ... | [
"TAGS\n#transformers #jax #clip-vision-bert #fill-mask #arxiv-1908.03557 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# CLIP-Vision-BERT Multilingual Pre-trained Model\n\nPretrained CLIP-Vision-BERT pre-trained on translated Conceptual-12M image-text pairs using a masked language modeli... |
text-classification | transformers | # CLIP-Vision-BERT Multilingual VQA Model
Fine-tuned CLIP-Vision-BERT on translated [VQAv2](https://visualqa.org/challenge.html) image-text pairs using sequence classification objective. We translate the dataset to three other languages other than English: French, German, and Spanish using the [MarianMT Models](https:... | {} | flax-community/clip-vision-bert-vqa-ft-6k | null | [
"transformers",
"jax",
"clip-vision-bert",
"text-classification",
"arxiv:1908.03557",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1908.03557"
] | [] | TAGS
#transformers #jax #clip-vision-bert #text-classification #arxiv-1908.03557 #autotrain_compatible #endpoints_compatible #has_space #region-us
| # CLIP-Vision-BERT Multilingual VQA Model
Fine-tuned CLIP-Vision-BERT on translated VQAv2 image-text pairs using sequence classification objective. We translate the dataset to three other languages other than English: French, German, and Spanish using the MarianMT Models. This model is based on the VisualBERT which wa... | [
"# CLIP-Vision-BERT Multilingual VQA Model\n\nFine-tuned CLIP-Vision-BERT on translated VQAv2 image-text pairs using sequence classification objective. We translate the dataset to three other languages other than English: French, German, and Spanish using the MarianMT Models. This model is based on the VisualBERT w... | [
"TAGS\n#transformers #jax #clip-vision-bert #text-classification #arxiv-1908.03557 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# CLIP-Vision-BERT Multilingual VQA Model\n\nFine-tuned CLIP-Vision-BERT on translated VQAv2 image-text pairs using sequence classification objective. We trans... |
null | transformers | # CLIP-Vision-Marian Seq2Seq Encoder-Decoder Model
Pretrained CLIP-Vision-Marian pre-trained on a subset of Spanish-translated Conceptual-12M image-text pairs using a seq2seq model training objective. 2.5M cleaned English image-text pairs are translated using Spanish Marian Model. We trained CLIP-Vision-Marian model d... | {} | flax-community/clip-vit-base-patch32_marian-es | null | [
"transformers",
"jax",
"tensorboard",
"clip-vision-marian",
"arxiv:2102.08981",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.08981"
] | [] | TAGS
#transformers #jax #tensorboard #clip-vision-marian #arxiv-2102.08981 #endpoints_compatible #region-us
| CLIP-Vision-Marian Seq2Seq Encoder-Decoder Model
================================================
Pretrained CLIP-Vision-Marian pre-trained on a subset of Spanish-translated Conceptual-12M image-text pairs using a seq2seq model training objective. 2.5M cleaned English image-text pairs are translated using Spanish Mar... | [
"### How to use\n\n\nYou will need to clone the model from here. An example of usage is shown below:\n\n\nTraining data ️\n----------------\n\n\nThe Spanish image captioning model was trained on a subset of Conceptual 12M dataset by Google:\n \n\n \n\nConceptual 12M, Introduced by Changpinyo et al. in Conceptual... | [
"TAGS\n#transformers #jax #tensorboard #clip-vision-marian #arxiv-2102.08981 #endpoints_compatible #region-us \n",
"### How to use\n\n\nYou will need to clone the model from here. An example of usage is shown below:\n\n\nTraining data ️\n----------------\n\n\nThe Spanish image captioning model was trained on a s... |
text2text-generation | transformers | # CLIP-Vision-mBART50 Seq2Seq Encoder-Decoder Model
Pretrained CLIP-Vision-mBART50 pre-trained on subset of translated Conceptual-12M image-text pairs using a seq2seq model training objective. 2.5M cleaned English image-text pairs are translated using Marian Model for respective languages to 2.5M examples each in Engl... | {} | flax-community/clip-vit-base-patch32_mbart-large-50 | null | [
"transformers",
"jax",
"tensorboard",
"clip-vision-mbart",
"text2text-generation",
"arxiv:2102.08981",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.08981"
] | [] | TAGS
#transformers #jax #tensorboard #clip-vision-mbart #text2text-generation #arxiv-2102.08981 #autotrain_compatible #endpoints_compatible #has_space #region-us
| CLIP-Vision-mBART50 Seq2Seq Encoder-Decoder Model
=================================================
Pretrained CLIP-Vision-mBART50 pre-trained on subset of translated Conceptual-12M image-text pairs using a seq2seq model training objective. 2.5M cleaned English image-text pairs are translated using Marian Model for r... | [
"### How to use\n\n\nYou will need to clone the model from here. An example of usage is shown below:\n\n\nTraining data ️\n----------------\n\n\nThe Multi-lingual image captioning model was trained on a subset of Conceptual 12M dataset by Google:\n \n\n \n\nConceptual 12M, Introduced by Changpinyo et al. in Conc... | [
"TAGS\n#transformers #jax #tensorboard #clip-vision-mbart #text2text-generation #arxiv-2102.08981 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### How to use\n\n\nYou will need to clone the model from here. An example of usage is shown below:\n\n\nTraining data ️\n----------------\n\n\... |
text2text-generation | transformers | # Tokenizer
We trained our tokenizer using [sentencepiece](https://github.com/google/sentencepiece)'s unigram tokenizer. Then loaded the tokenizer as MT5TokenizerFast.
## Model
We used [MT5-base](https://huggingface.co/google/mt5-base) model.
## Datasets
We used [Code Search Net](https://huggingface.co/datasets/co... | {} | flax-community/code-mt5-base | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"mt5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #mt5 #text2text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Tokenizer
We trained our tokenizer using sentencepiece's unigram tokenizer. Then loaded the tokenizer as MT5TokenizerFast.
## Model
We used MT5-base model.
## Datasets
We used Code Search Net's dataset and some scrapped data from internet to train the model. We maintained a list of datasets where each dataset ha... | [
"# Tokenizer\n\nWe trained our tokenizer using sentencepiece's unigram tokenizer. Then loaded the tokenizer as MT5TokenizerFast.",
"## Model\n\nWe used MT5-base model.",
"## Datasets\n\nWe used Code Search Net's dataset and some scrapped data from internet to train the model. We maintained a list of datasets wh... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #mt5 #text2text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Tokenizer\n\nWe trained our tokenizer using sentencepiece's unigram tokenizer. Then loaded the tokenizer as MT5TokenizerFast.",
"## Mo... |
text-to-image | transformers |
## DALL·E mini - Generate images from text
<img style="text-align:center; display:block;" src="https://raw.githubusercontent.com/borisdayma/dalle-mini/main/img/logo.png" width="200">
* [Technical Report](https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA)
* [Demo](https://huggingface.co/spac... | {"language": ["en"], "pipeline_tag": "text-to-image", "inference": false} | flax-community/dalle-mini | null | [
"transformers",
"jax",
"bart",
"text2text-generation",
"text-to-image",
"en",
"arxiv:1910.13461",
"autotrain_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1910.13461"
] | [
"en"
] | TAGS
#transformers #jax #bart #text2text-generation #text-to-image #en #arxiv-1910.13461 #autotrain_compatible #has_space #region-us
|
## DALL·E mini - Generate images from text
<img style="text-align:center; display:block;" src="URL width="200">
* Technical Report
* Demo
### Model Description
This is an attempt to replicate OpenAI's DALL·E, a model capable of generating arbitrary images from a text prompt that describes the desired result.
!DA... | [
"## DALL·E mini - Generate images from text\n\n<img style=\"text-align:center; display:block;\" src=\"URL width=\"200\">\n\n* Technical Report\n* Demo",
"### Model Description\n\nThis is an attempt to replicate OpenAI's DALL·E, a model capable of generating arbitrary images from a text prompt that describes the d... | [
"TAGS\n#transformers #jax #bart #text2text-generation #text-to-image #en #arxiv-1910.13461 #autotrain_compatible #has_space #region-us \n",
"## DALL·E mini - Generate images from text\n\n<img style=\"text-align:center; display:block;\" src=\"URL width=\"200\">\n\n* Technical Report\n* Demo",
"### Model Descript... |
text-generation | transformers |
# GPT2-svenska-wikipedia
A Danish GPT2 style model trained using Flax CLM pipeline on the Danish
part of the wiki40b dataset.
https://huggingface.co/datasets/wiki40b
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swedis... | {"language": "da", "widget": [{"text": "Jeg elsker livet"}]} | flax-community/dansk-gpt-wiki | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"da",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"da"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #gpt2 #text-generation #da #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# GPT2-svenska-wikipedia
A Danish GPT2 style model trained using Flax CLM pipeline on the Danish
part of the wiki40b dataset.
URL
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swedish Gpt
URL
## Swedish gpt wiki
URL
... | [
"# GPT2-svenska-wikipedia\nA Danish GPT2 style model trained using Flax CLM pipeline on the Danish\npart of the wiki40b dataset.\n\nURL",
"## Model series\nThis model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.",
"## Gpt models",
"## Swedish Gpt\nURL",
... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #gpt2 #text-generation #da #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# GPT2-svenska-wikipedia\nA Danish GPT2 style model trained using Flax CLM pipeline on the Danish\npart of the wiki40b dataset.... |
text2text-generation | transformers | # ft5 with re-zero
| {} | flax-community/ft5-rezero-base-openwebtext | null | [
"transformers",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #jax #tensorboard #t5 #text2text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # ft5 with re-zero
| [
"# ft5 with re-zero"
] | [
"TAGS\n#transformers #jax #tensorboard #t5 #text2text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# ft5 with re-zero"
] |
null | null |
# GPT-2 GERMAN
## Model description
See [Open AI's model card](https://github.com/openai/gpt-2/blob/master/model_card.md) and [Huggingface's model card](https://huggingface.co/gpt2) for the original model.
## Intended uses & limitations
#### How to use
```python
def foo(bar)
bar +=1
return bar
```
#### Limita... | {"language": [], "tags": [], "datasets": [], "metrics": []} | flax-community/gpt-2-german | null | [
"arxiv:1904.09751",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1904.09751"
] | [] | TAGS
#arxiv-1904.09751 #region-us
|
# GPT-2 GERMAN
## Model description
See Open AI's model card and Huggingface's model card for the original model.
## Intended uses & limitations
#### How to use
#### Limitations and bias
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? ?? URL
## Training data
URL
## Training procedur... | [
"# GPT-2 GERMAN",
"## Model description\n\nSee Open AI's model card and Huggingface's model card for the original model.",
"## Intended uses & limitations",
"#### How to use",
"#### Limitations and bias\n\nOn the Dangers of Stochastic Parrots: Can Language Models Be Too Big? ?? URL",
"## Training data\n\n... | [
"TAGS\n#arxiv-1904.09751 #region-us \n",
"# GPT-2 GERMAN",
"## Model description\n\nSee Open AI's model card and Huggingface's model card for the original model.",
"## Intended uses & limitations",
"#### How to use",
"#### Limitations and bias\n\nOn the Dangers of Stochastic Parrots: Can Language Models B... |
text-generation | transformers |
# Spanish GPT-2
GPT-2 model trained from scratch on the Spanish portion of [OSCAR](https://huggingface.co/datasets/viewer/?dataset=oscar).
The model is trained with Flax and using TPUs sponsored by Google since this is part of the
[Flax/Jax Community Week](https://discuss.huggingface.co/t/open-to-the-community-commun... | {"language": "es", "tags": ["text-generation"], "datasets": ["oscar"], "widgets": [{"text": "\u00c9rase un vez "}, {"text": "Frase: Esta pel\u00edcula es muy agradable. Sentimiento: positivo Frase: Odiaba esta pel\u00edcula, apesta. Sentimiento: negativo Frase: Esta pel\u00edcula fue bastante mala. Sentimiento: "}]} | flax-community/gpt-2-spanish | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"es",
"dataset:oscar",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #gpt2 #text-generation #es #dataset-oscar #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# Spanish GPT-2
GPT-2 model trained from scratch on the Spanish portion of OSCAR.
The model is trained with Flax and using TPUs sponsored by Google since this is part of the
Flax/Jax Community Week
organised by HuggingFace.
## Model description
The model used for training is OpenAI's GPT-2, introduced in the paper ... | [
"# Spanish GPT-2\n\nGPT-2 model trained from scratch on the Spanish portion of OSCAR.\nThe model is trained with Flax and using TPUs sponsored by Google since this is part of the\nFlax/Jax Community Week\norganised by HuggingFace.",
"## Model description\n\nThe model used for training is OpenAI's GPT-2, introduce... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #gpt2 #text-generation #es #dataset-oscar #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# Spanish GPT-2\n\nGPT-2 model trained from scratch on the Spanish portion of OSCAR.\nThe model is trained with ... |
text-generation | transformers | # GPT2-Tamil
This repository is created as part of the Flax/Jax community week by Huggingface. The aim of this project is to pretrain a language model using GPT-2 specifically for Tamil language.
## Setup:
To setup the project, run the following command,
```python
pip install -r requirements.txt
```
## Model:
Pretr... | {"language": "ta", "datasets": ["oscar", "IndicNLP"], "widget": [{"text": "\u0b92\u0bb0\u0bc1 \u0b8a\u0bb0\u0bbf\u0bb2\u0bc7 \u0b92\u0bb0\u0bc1 \u0b95\u0bbe\u0b95\u0bcd\u0b95\u0bc8\u0b95\u0bcd\u0b95\u0bc1"}]} | flax-community/gpt-2-tamil | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"ta",
"dataset:oscar",
"dataset:IndicNLP",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ta"
] | TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #ta #dataset-oscar #dataset-IndicNLP #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| # GPT2-Tamil
This repository is created as part of the Flax/Jax community week by Huggingface. The aim of this project is to pretrain a language model using GPT-2 specifically for Tamil language.
## Setup:
To setup the project, run the following command,
## Model:
Pretrained model on Tamil language using a causal ... | [
"# GPT2-Tamil\n\nThis repository is created as part of the Flax/Jax community week by Huggingface. The aim of this project is to pretrain a language model using GPT-2 specifically for Tamil language.",
"## Setup:\nTo setup the project, run the following command,",
"## Model:\nPretrained model on Tamil language ... | [
"TAGS\n#transformers #pytorch #tensorboard #gpt2 #text-generation #ta #dataset-oscar #dataset-IndicNLP #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# GPT2-Tamil\n\nThis repository is created as part of the Flax/Jax community week by Huggingface. The aim of thi... |
text-generation | transformers |
# GPT-Code-Clippy-1.3B-APPS-all
## Model Description
GPT-Neo-1.3B-APPS-all is a GPT-Neo-1.3B fine-tuned on APPS dataset. This model is specialized to solve programming tasks.
## Training data
The model is trained on the [Automated Programming Progress Standard (APPS) dataset](https://github.com/hendrycks/apps). Th... | {"language": ["en", "python"], "license": "mit", "tags": ["gpt_neo", "code_synthesis"], "datasets": ["apps"]} | flax-community/gpt-neo-1.3B-apps-all-2 | null | [
"transformers",
"pytorch",
"jax",
"gpt_neo",
"text-generation",
"code_synthesis",
"dataset:apps",
"arxiv:2107.03374",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2107.03374"
] | [
"en",
"python"
] | TAGS
#transformers #pytorch #jax #gpt_neo #text-generation #code_synthesis #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# GPT-Code-Clippy-1.3B-APPS-all
## Model Description
GPT-Neo-1.3B-APPS-all is a GPT-Neo-1.3B fine-tuned on APPS dataset. This model is specialized to solve programming tasks.
## Training data
The model is trained on the Automated Programming Progress Standard (APPS) dataset. The dataset consists of 10,000 coding p... | [
"# GPT-Code-Clippy-1.3B-APPS-all",
"## Model Description\n\nGPT-Neo-1.3B-APPS-all is a GPT-Neo-1.3B fine-tuned on APPS dataset. This model is specialized to solve programming tasks.",
"## Training data\n\nThe model is trained on the Automated Programming Progress Standard (APPS) dataset. The dataset consists of... | [
"TAGS\n#transformers #pytorch #jax #gpt_neo #text-generation #code_synthesis #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# GPT-Code-Clippy-1.3B-APPS-all",
"## Model Description\n\nGPT-Neo-1.3B-APPS-all is a GPT-Neo-1.3B fine-tuned on APPS dataset. Th... |
text-generation | transformers |
# GPT-Neo-1.3B-APPS-all
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
GPT-Neo-1.3B-APPS-all is a GPT-Neo-1.3B finetuned on APPS dataset. This model is speci... | {"language": ["en", "python"], "license": "mit", "tags": ["gpt_neo", "code_synthesis"], "datasets": ["apps"]} | flax-community/gpt-neo-1.3B-apps-all | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"code_synthesis",
"dataset:apps",
"arxiv:2107.03374",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2107.03374"
] | [
"en",
"python"
] | TAGS
#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #code_synthesis #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# GPT-Neo-1.3B-APPS-all
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
## Model Description
GPT-Neo-1.3B-APPS-all is a GPT-Neo-1.3B finetuned on APPS dataset. This model is specialized to solve programming tasks.
## Training data
T... | [
"# GPT-Neo-1.3B-APPS-all\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## Model Description\n\nGPT-Neo-1.3B-APPS-all is a GPT-Neo-1.3B finetuned on APPS dataset. This model is specialized to solve programming tasks.",
"## T... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #code_synthesis #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# GPT-Neo-1.3B-APPS-all\n> Please refer to our new GitHub Wiki which documents our efforts in detail in cre... |
text-generation | transformers |
# GPT-Neo-1.3B-APPS
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
GPT-Neo-1.3B-APPS is a GPT-Neo-125M finetuned on APPS dataset. This model is specialized ... | {"language": ["en", "python"], "license": "mit", "tags": ["gpt_neo", "code_synthesis"], "datasets": ["apps"]} | flax-community/gpt-neo-1.3B-apps | null | [
"transformers",
"pytorch",
"jax",
"gpt_neo",
"text-generation",
"code_synthesis",
"dataset:apps",
"arxiv:2107.03374",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2107.03374"
] | [
"en",
"python"
] | TAGS
#transformers #pytorch #jax #gpt_neo #text-generation #code_synthesis #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# GPT-Neo-1.3B-APPS
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
## Model Description
GPT-Neo-1.3B-APPS is a GPT-Neo-125M finetuned on APPS dataset. This model is specialized to solve programming tasks.
## Training data
The mode... | [
"# GPT-Neo-1.3B-APPS\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## Model Description\n\nGPT-Neo-1.3B-APPS is a GPT-Neo-125M finetuned on APPS dataset. This model is specialized to solve programming tasks.",
"## Training ... | [
"TAGS\n#transformers #pytorch #jax #gpt_neo #text-generation #code_synthesis #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# GPT-Neo-1.3B-APPS\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source versio... |
text-generation | transformers |
# GPT-Neo-125M-APPS-all
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
GPT-Neo-125M-APPS-all is a GPT-Neo-125M finetuned on APPS dataset. This model is spec... | {"language": ["en", "python"], "license": "mit", "tags": ["gpt_neo", "code_synthesis"], "datasets": ["apps"]} | flax-community/gpt-neo-125M-apps-all | null | [
"transformers",
"pytorch",
"jax",
"gpt_neo",
"text-generation",
"code_synthesis",
"dataset:apps",
"arxiv:2107.03374",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2107.03374"
] | [
"en",
"python"
] | TAGS
#transformers #pytorch #jax #gpt_neo #text-generation #code_synthesis #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# GPT-Neo-125M-APPS-all
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
## Model Description
GPT-Neo-125M-APPS-all is a GPT-Neo-125M finetuned on APPS dataset. This model is specialized to solve programming tasks.
## Training data
... | [
"# GPT-Neo-125M-APPS-all\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## Model Description\n\nGPT-Neo-125M-APPS-all is a GPT-Neo-125M finetuned on APPS dataset. This model is specialized to solve programming tasks.",
"## T... | [
"TAGS\n#transformers #pytorch #jax #gpt_neo #text-generation #code_synthesis #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# GPT-Neo-125M-APPS-all\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the ope... |
text-generation | transformers |
# GPT-Neo-125M-APPS
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
GPT-Neo-125M-APPS is a GPT-Neo-125M finetuned on APPS dataset. This model is specialized t... | {"language": ["en", "code"], "license": "mit", "tags": ["gpt_neo", "code_synthesis"], "datasets": ["apps"], "language_details": "python code"} | flax-community/gpt-neo-125M-apps | null | [
"transformers",
"pytorch",
"jax",
"gpt_neo",
"text-generation",
"code_synthesis",
"en",
"code",
"dataset:apps",
"arxiv:2107.03374",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2107.03374"
] | [
"en",
"code"
] | TAGS
#transformers #pytorch #jax #gpt_neo #text-generation #code_synthesis #en #code #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# GPT-Neo-125M-APPS
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
## Model Description
GPT-Neo-125M-APPS is a GPT-Neo-125M finetuned on APPS dataset. This model is specialized to solve programming tasks.
## Training data
The model... | [
"# GPT-Neo-125M-APPS\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## Model Description\n\nGPT-Neo-125M-APPS is a GPT-Neo-125M finetuned on APPS dataset. This model is specialized to solve programming tasks.",
"## Training ... | [
"TAGS\n#transformers #pytorch #jax #gpt_neo #text-generation #code_synthesis #en #code #dataset-apps #arxiv-2107.03374 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# GPT-Neo-125M-APPS\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open sou... |
text-generation | transformers | # Model Card for gpt-neo-125M-code-clippy-dedup-2048
# Model Details
## Model Description
More information needed
- **Developed by:** Flax Community
- **Shared by [Optional]:** Hugging Face
- **Model type:** Text Generation
- **Language(s) (NLP):** More information needed
- **License:** More information needed... | {"tags": ["flax"]} | flax-community/gpt-neo-125M-code-clippy-dedup-2048 | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"flax",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #flax #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
| Model Card for gpt-neo-125M-code-clippy-dedup-2048
==================================================
Model Details
=============
Model Description
-----------------
More information needed
* Developed by: Flax Community
* Shared by [Optional]: Hugging Face
* Model type: Text Generation
* Language(s) (NLP): Mor... | [
"### Preprocessing\n\n\nMore information needed",
"### Speeds, Sizes, Times\n\n\nThe model creators note in the GitHub Repo](URL\n\n\n\n> \n> For fine-tuning GPTNeo-125M on CodeClippy dataset we used AdamW optimizer (beta1=0.9, beta2=0.95) with GPT3-like learning rate schedule (4k warmup steps from 0 to 5e-5 foll... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #flax #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Preprocessing\n\n\nMore information needed",
"### Speeds, Sizes, Times\n\n\nThe model creators note in the GitHub Repo](URL\n\n\n\n> \n> For fine-tun... |
text-generation | transformers | # GPT-Code-Clippy-125M-from-Scratch
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
GPT-CC-125M-from-Scratch is a [GPT-Neo-125M model](https://huggingface.co/El... | {} | flax-community/gpt-neo-125M-code-clippy-dedup-scratch | null | [
"transformers",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"arxiv:2107.03374",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2107.03374"
] | [] | TAGS
#transformers #jax #tensorboard #gpt_neo #text-generation #arxiv-2107.03374 #autotrain_compatible #endpoints_compatible #region-us
| GPT-Code-Clippy-125M-from-Scratch
=================================
>
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
>
>
>
Model Description
-----------------
GPT-CC-125M-from-Scratch is a GPT-Neo-125M model pretrained from sc... | [
"### How to use\n\n\nYou can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:",
"### Limitations and Biases\n\n\nThe model is intended to be used for research purposes and comes with no guarantees of the quality of generated code.\n\n\nGP... | [
"TAGS\n#transformers #jax #tensorboard #gpt_neo #text-generation #arxiv-2107.03374 #autotrain_compatible #endpoints_compatible #region-us \n",
"### How to use\n\n\nYou can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:",
"### Limitati... |
text-generation | transformers | # GPT-Neo-125M-Code-Clippy-Dedup
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
PT-Neo-125M-Code-Clippy-Dedup is a [GPT-Neo-125M model](https://huggingface.co... | {} | flax-community/gpt-neo-125M-code-clippy-dedup | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"arxiv:2107.03374",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2107.03374"
] | [] | TAGS
#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #arxiv-2107.03374 #autotrain_compatible #endpoints_compatible #region-us
| # GPT-Neo-125M-Code-Clippy-Dedup
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
## Model Description
PT-Neo-125M-Code-Clippy-Dedup is a GPT-Neo-125M model finetuned using causal language modeling on our deduplicated version of the Cod... | [
"# GPT-Neo-125M-Code-Clippy-Dedup\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## Model Description\n\nPT-Neo-125M-Code-Clippy-Dedup is a GPT-Neo-125M model finetuned using causal language modeling on our deduplicated versio... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #arxiv-2107.03374 #autotrain_compatible #endpoints_compatible #region-us \n",
"# GPT-Neo-125M-Code-Clippy-Dedup\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copi... |
text-generation | transformers | # GPT-Neo-125M-Code-Clippy
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
GPT-Neo-125M-Code-Clippy is a [GPT-Neo-125M model](https://huggingface.co/EleutherAI... | {} | flax-community/gpt-neo-125M-code-clippy | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"arxiv:2107.03374",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2107.03374"
] | [] | TAGS
#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #arxiv-2107.03374 #autotrain_compatible #endpoints_compatible #has_space #region-us
| # GPT-Neo-125M-Code-Clippy
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
## Model Description
GPT-Neo-125M-Code-Clippy is a GPT-Neo-125M model finetuned using causal language modeling on our version of the Code Clippy Data dataset th... | [
"# GPT-Neo-125M-Code-Clippy\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## Model Description\n\nGPT-Neo-125M-Code-Clippy is a GPT-Neo-125M model finetuned using causal language modeling on our version of the Code Clippy Dat... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #arxiv-2107.03374 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# GPT-Neo-125M-Code-Clippy\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub ... |
text-generation | transformers | # GPT-Code-Clippy-125M-Code-Search-All
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
GPT-CC-125M-Code-Search is a [GPT-Neo-125M model](https://huggingface.c... | {} | flax-community/gpt-neo-125M-code-search-all | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #autotrain_compatible #endpoints_compatible #region-us
| # GPT-Code-Clippy-125M-Code-Search-All
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
## Model Description
GPT-CC-125M-Code-Search is a GPT-Neo-125M model finetuned using causal language modeling on all languages in the CodeSearchNet... | [
"# GPT-Code-Clippy-125M-Code-Search-All\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## Model Description\n\nGPT-CC-125M-Code-Search is a GPT-Neo-125M model finetuned using causal language modeling on all languages in the Co... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #autotrain_compatible #endpoints_compatible #region-us \n",
"# GPT-Code-Clippy-125M-Code-Search-All\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## ... |
text-generation | transformers | # GPT-Code-Clippy-125M-Code-Search-Py
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Description
GPT-CC-125M-Code-Search is a [GPT-Neo-125M model](https://huggingface.co/... | {} | flax-community/gpt-neo-125M-code-search-py | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #autotrain_compatible #endpoints_compatible #region-us
| # GPT-Code-Clippy-125M-Code-Search-Py
> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot
## Model Description
GPT-CC-125M-Code-Search is a GPT-Neo-125M model finetuned using causal language modeling on only the python language in the Code... | [
"# GPT-Code-Clippy-125M-Code-Search-Py\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## Model Description\n\nGPT-CC-125M-Code-Search is a GPT-Neo-125M model finetuned using causal language modeling on only the python language... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt_neo #text-generation #autotrain_compatible #endpoints_compatible #region-us \n",
"# GPT-Code-Clippy-125M-Code-Search-Py\n> Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot",
"## M... |
null | transformers | # Cosmos QA (gpt2)
> This is part of the
[Flax/Jax Community Week](https://discuss.huggingface.co/t/train-a-gpt2-model-for-contextual-common-sense-reasoning-using-the-cosmos-qa-dataset/7463), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.
## Team Members
-Rohan V Kashyap ([Roha... | {} | flax-community/gpt2-Cosmos | null | [
"transformers",
"jax",
"tensorboard",
"gpt2",
"arxiv:1909.00277",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1909.00277"
] | [] | TAGS
#transformers #jax #tensorboard #gpt2 #arxiv-1909.00277 #endpoints_compatible #has_space #text-generation-inference #region-us
| Cosmos QA (gpt2)
================
>
> This is part of the
> Flax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.
>
>
>
Team Members
------------
-Rohan V Kashyap (Rohan)
-Vivek V Kashyap (Vivek)
Dataset
-------
Cosmos QA: Machine Reading Comprehension with Contextual Commo... | [
"### Example\n\n\nHow to use\n----------\n\n\nPreprocessing\n-------------\n\n\nThe texts are tokenized using the GPT2 tokenizer.To feed the inputs of multiple choice we concatenated context and question as first input and all the 4 possible choices as the second input to our tokenizer.\n\n\nEvaluation\n----------\... | [
"TAGS\n#transformers #jax #tensorboard #gpt2 #arxiv-1909.00277 #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"### Example\n\n\nHow to use\n----------\n\n\nPreprocessing\n-------------\n\n\nThe texts are tokenized using the GPT2 tokenizer.To feed the inputs of multiple choice we conca... |
text-generation | transformers |
## GPT-2 Base Thai
GPT-2 Base Thai 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 the [OSCAR](https://huggingface.co/datasets/oscar) dataset, specifically the `unshuffled_deduplicate... | {"language": "th", "license": "mit", "tags": ["gpt2-base-thai"], "datasets": ["oscar"], "widget": [{"text": "\u0e2a\u0e27\u0e31\u0e2a\u0e14\u0e35\u0e15\u0e2d\u0e19\u0e40\u0e0a\u0e49\u0e32"}]} | flax-community/gpt2-base-thai | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"gpt2-base-thai",
"th",
"dataset:oscar",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #jax #tensorboard #gpt2 #text-generation #gpt2-base-thai #th #dataset-oscar #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| GPT-2 Base Thai
---------------
GPT-2 Base Thai is a causal language model based on the OpenAI GPT-2 model. It was trained on the OSCAR dataset, specifically the 'unshuffled\_deduplicated\_th' subset. The model was trained from scratch and achieved an evaluation loss of 1.708 and an evaluation perplexity of 5.516.
... | [
"### As Causal Language Model",
"### Feature Extraction in PyTorch\n\n\nTeam Members\n------------\n\n\n* Sakares Saengkaew (@sakares)\n* Wilson Wongso (@w11wo)"
] | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt2 #text-generation #gpt2-base-thai #th #dataset-oscar #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"### As Causal Language Model",
"### Feature Extraction in PyTorch\n\n\nTeam Members\n---------... |
text-generation | transformers |
# Bengali GPT-2
Bengali GPT-2 demo. Part of the [Huggingface JAX/Flax event](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/). Also features a [finetuned](https://huggingface.co/khalidsaifullaah/bengali-lyricist-gpt2?) model on bengali song lyrics.
# Model Descriptio... | {"language": "bn", "license": "mit", "datasets": ["mc4"]} | flax-community/gpt2-bengali | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
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"text-generation",
"bn",
"dataset:mc4",
"doi:10.57967/hf/0938",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"bn"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #gpt2 #text-generation #bn #dataset-mc4 #doi-10.57967/hf/0938 #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# Bengali GPT-2
Bengali GPT-2 demo. Part of the Huggingface JAX/Flax event. Also features a finetuned model on bengali song lyrics.
# Model Description
OpenAI GPT-2 model was proposed in Language Models are Unsupervised Multitask Learners paper .Original GPT2 model was a causal (unidirectional) transformer pretrai... | [
"# Bengali GPT-2\n\nBengali GPT-2 demo. Part of the Huggingface JAX/Flax event. Also features a finetuned model on bengali song lyrics.",
"# Model Description\n\nOpenAI GPT-2 model was proposed in Language Models are Unsupervised Multitask Learners paper .Original GPT2 model was a causal (unidirectional) transfor... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #gpt2 #text-generation #bn #dataset-mc4 #doi-10.57967/hf/0938 #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# Bengali GPT-2\n\nBengali GPT-2 demo. Part of the Huggingface JAX/Flax event. ... |
text-generation | transformers | # GPT2-large-indonesian
| {} | flax-community/gpt2-large-indonesian | null | [
"transformers",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # GPT2-large-indonesian
| [
"# GPT2-large-indonesian"
] | [
"TAGS\n#transformers #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# GPT2-large-indonesian"
] |
text-generation | transformers |
# GPT2-medium-indonesian
This is a pretrained model on Indonesian language using a causal language modeling (CLM) objective, which was first
introduced in [this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)
and first released at [this page]... | {"language": "id", "widget": [{"text": "Sewindu sudah kita tak berjumpa, rinduku padamu sudah tak terkira."}]} | flax-community/gpt2-medium-indonesian | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"id",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"id"
] | TAGS
#transformers #pytorch #jax #tensorboard #gpt2 #text-generation #id #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| GPT2-medium-indonesian
======================
This is a pretrained model on Indonesian language using a causal language modeling (CLM) objective, which was first
introduced in this paper
and first released at this page.
This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community ... | [
"### Gender bias\n\n\nWe generated 50 texts starting with prompts \"She/He works as\". After doing some preprocessing (lowercase and stopwords removal) we obtain texts that are used to generate word clouds of female/male professions. The most salient terms for male professions are: driver, sopir (driver), ojek, tuk... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt2 #text-generation #id #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"### Gender bias\n\n\nWe generated 50 texts starting with prompts \"She/He works as\". After doing some preprocessing (lowercase and stopword... |
text-generation | transformers |
# GPT2 Medium 4 Persian
> This is part of the
[Flax/Jax Community Week](https://discuss.huggingface.co/t/pretrain-gpt2-from-scratch-in-persian/7560), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.
## Team Members
- [Mehrdad Farahani](huggingface.co/m3hrdadfi)
- [Saied Alimorad... | {"language": "fa", "tags": ["text-generation"], "widget": [{"text": "\u062f\u0631 \u06cc\u06a9 \u0627\u062a\u0641\u0627\u0642 \u0634\u06af\u0641\u062a \u0627\u0646\u06af\u06cc\u0632\u060c \u067e\u0698\u0648\u0647\u0634\u06af\u0631\u0627\u0646"}, {"text": "\u06af\u0631\u0641\u062a\u06af\u06cc \u0628\u06cc\u0646\u06cc \u... | flax-community/gpt2-medium-persian | null | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"fa",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #tf #jax #tensorboard #gpt2 #text-generation #fa #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# GPT2 Medium 4 Persian
> This is part of the
Flax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.
## Team Members
- Mehrdad Farahani
- Saied Alimoradi
- M. Reza Zerehpoosh
- Hooman Sedghamiz
- Mazeyar Moeini Feizabadi
## Dataset
We used Oscar dataset, which is a huge multilingual c... | [
"# GPT2 Medium 4 Persian\n> This is part of the\nFlax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.",
"## Team Members\n- Mehrdad Farahani\n- Saied Alimoradi\n- M. Reza Zerehpoosh\n- Hooman Sedghamiz\n- Mazeyar Moeini Feizabadi",
"## Dataset\nWe used Oscar dataset, which is a ... | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #gpt2 #text-generation #fa #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# GPT2 Medium 4 Persian\n> This is part of the\nFlax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.",
... |
text-generation | transformers |
# Question-Answering Using GPT2 - Persian
> This is a side project of this thread
[Flax/Jax Community Week - GPT2 4 Persian](https://discuss.huggingface.co/t/pretrain-gpt2-from-scratch-in-persian/7560), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.
## Team Members
- [Mehrdad ... | {"language": "fa", "tags": ["text-generation"], "datasets": ["persian_qa"], "widget": [{"text": "\u0646\u0627\u0641 \u062c\u0627\u06cc\u06cc \u0642\u0631\u0627\u0631 \u06af\u0631\u0641\u062a\u0647 \u06a9\u0647 \u062f\u0631 \u0648\u0627\u0642\u0639 \u0628\u0646\u062f\u0646\u0627\u0641 \u062f\u0631 \u062f\u0627\u062e\u06... | flax-community/gpt2-persian-question-answering | null | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"fa",
"dataset:persian_qa",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #tf #jax #tensorboard #safetensors #gpt2 #text-generation #fa #dataset-persian_qa #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# Question-Answering Using GPT2 - Persian
> This is a side project of this thread
Flax/Jax Community Week - GPT2 4 Persian, organized by HuggingFace and TPU usage sponsored by Google.
## Team Members
- Mehrdad Farahani
## Dataset
We used PersianQA dataset which is a reading comprehension dataset on Persian Wikipedi... | [
"# Question-Answering Using GPT2 - Persian\n> This is a side project of this thread\nFlax/Jax Community Week - GPT2 4 Persian, organized by HuggingFace and TPU usage sponsored by Google.",
"## Team Members\n- Mehrdad Farahani",
"## Dataset\nWe used PersianQA dataset which is a reading comprehension dataset on P... | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #safetensors #gpt2 #text-generation #fa #dataset-persian_qa #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# Question-Answering Using GPT2 - Persian\n> This is a side project of this thread\nFlax/Jax Community ... |
text-generation | transformers | Rap Lyric Generator <br/>
GPT-2 fine tuned using FLAX/JAX on over 10000 Rap Songs from over 50 rappers, the dataset was gathered from genius.com <br/>
Checkout the deployed version on hf-spaces :- [here](https://huggingface.co/spaces/Shankhdhar/Rap-Lyric-generator) <br/>
Colab for making predictions:- [here](https://co... | {} | flax-community/gpt2-rap-lyric-generator | null | [
"transformers",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #jax #tensorboard #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| Rap Lyric Generator <br/>
GPT-2 fine tuned using FLAX/JAX on over 10000 Rap Songs from over 50 rappers, the dataset was gathered from URL <br/>
Checkout the deployed version on hf-spaces :- here <br/>
Colab for making predictions:- here<br/>
The dataset we used: dataset<br/>
Made by:-<br/>
Anant Shankhdhar<br/>
Jeronim... | [] | [
"TAGS\n#transformers #jax #tensorboard #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n"
] |
text-generation | transformers |
# GPT2-small-indonesian
This is a pretrained model on Indonesian language using a causal language modeling (CLM) objective, which was first
introduced in [this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)
and first released at [this page](... | {"language": "id", "widget": [{"text": "Sewindu sudah kita tak berjumpa, rinduku padamu sudah tak terkira."}]} | flax-community/gpt2-small-indonesian | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"id",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"id"
] | TAGS
#transformers #pytorch #jax #tensorboard #gpt2 #text-generation #id #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| GPT2-small-indonesian
=====================
This is a pretrained model on Indonesian language using a causal language modeling (CLM) objective, which was first
introduced in this paper
and first released at this page.
This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community We... | [
"### Gender bias\n\n\nWe generated 50 texts starting with prompts \"She/He works as\". After doing some preprocessing (lowercase and stopwords removal) we obtain texts that are used to generate word clouds of female/male professions. The most salient terms for male professions are: driver, sopir (driver), ojek, tuk... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #gpt2 #text-generation #id #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"### Gender bias\n\n\nWe generated 50 texts starting with prompts \"She/He works as\". After doing some preprocessing (lowercase and stopword... |
text-generation | transformers |
## GPT2 in Swahili
This model was trained using HuggingFace's Flax framework and is part of the [JAX/Flax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104) organized by [HuggingFace](https://huggingface.co). All training was done on a TPUv3-8 VM spon... | {"language": "sw", "datasets": ["flax-community/swahili-safi"], "widget": [{"text": "Ninitaka kukula"}]} | flax-community/gpt2-swahili | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"sw",
"dataset:flax-community/swahili-safi",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sw"
] | TAGS
#transformers #pytorch #jax #tensorboard #gpt2 #text-generation #sw #dataset-flax-community/swahili-safi #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
## GPT2 in Swahili
This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.
## How to use
#### Training Data:
This model was trained on Swahili Safi
#### More Details:
... | [
"## GPT2 in Swahili\n\nThis model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.",
"## How to use",
"#### Training Data:\nThis model was trained on Swahili Safi",
"###... | [
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"## GPT2 in Swahili\n\nThis model was trained using HuggingFace's Flax framework and is part of the JAX/... |
fill-mask | transformers |
## Indonesian RoBERTa Base
Indonesian RoBERTa Base is a masked language model based on the [RoBERTa](https://arxiv.org/abs/1907.11692) model. It was trained on the [OSCAR](https://huggingface.co/datasets/oscar) dataset, specifically the `unshuffled_deduplicated_id` subset. The model was trained from scratch and achie... | {"language": "id", "license": "mit", "tags": ["indonesian-roberta-base"], "datasets": ["oscar"], "widget": [{"text": "Budi telat ke sekolah karena ia <mask>."}]} | flax-community/indonesian-roberta-base | null | [
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| Indonesian RoBERTa Base
-----------------------
Indonesian RoBERTa Base is a masked language model based on the RoBERTa model. It was trained on the OSCAR dataset, specifically the 'unshuffled\_deduplicated\_id' subset. The model was trained from scratch and achieved an evaluation loss of 1.798 and an evaluation accu... | [
"### As Masked Language Model",
"### Feature Extraction in PyTorch\n\n\nTeam Members\n------------\n\n\n* Wilson Wongso (@w11wo)\n* Steven Limcorn (@stevenlimcorn)\n* Samsul Rahmadani (@munggok)\n* Chew Kok Wah (@chewkokwah)"
] | [
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"### As Masked Language Model",
"### Feature Extraction in PyTorch\n\n\nTeam Members\... |
fill-mask | transformers |
## Indonesian RoBERTa Large
Indonesian RoBERTa Large is a masked language model based on the [RoBERTa](https://arxiv.org/abs/1907.11692) model. It was trained on the [OSCAR](https://huggingface.co/datasets/oscar) dataset, specifically the `unshuffled_deduplicated_id` subset. The model was trained from scratch and ach... | {"language": "id", "license": "mit", "tags": ["indonesian-roberta-large"], "datasets": ["oscar"], "widget": [{"text": "Budi telat ke sekolah karena ia <mask>."}]} | flax-community/indonesian-roberta-large | null | [
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| Indonesian RoBERTa Large
------------------------
Indonesian RoBERTa Large is a masked language model based on the RoBERTa model. It was trained on the OSCAR dataset, specifically the 'unshuffled\_deduplicated\_id' subset. The model was trained from scratch and achieved an evaluation loss of 4.801 and an evaluation a... | [
"### As Masked Language Model",
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] | [
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"### As Masked Language Model",
"### Feature Extraction in PyTorch\n\n\nTeam Members\n---------... |
null | null | # KoCLIP
This repository includes
## Installation
Create a virtual env and install `requirements.txt`.
```
pip install -r requirements.txt
```
For Google Cloud TPU VM please follow necessary installation steps here:
[Pytorch on TPU VM](https://cloud.google.com/tpu/docs/pytorch-xla-ug-tpu-vm)
[JAX/Flax on TPU VM]... | {} | flax-community/koclip | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
| # KoCLIP
This repository includes
## Installation
Create a virtual env and install 'URL'.
For Google Cloud TPU VM please follow necessary installation steps here:
Pytorch on TPU VM
JAX/Flax on TPU VM
| [
"# KoCLIP\n\nThis repository includes",
"## Installation\n\nCreate a virtual env and install 'URL'.\n\n\n\nFor Google Cloud TPU VM please follow necessary installation steps here:\n\nPytorch on TPU VM\nJAX/Flax on TPU VM"
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] |
null | transformers | # MedCLIP: Fine-tuning a CLIP model on the ROCO medical dataset
<!--  -->
<h3 align="center">
<!-- <p>MedCLIP</p> -->
<img src="./assets/logo.png" alt="huggingface-medclip" width="250" height="250">
## Summary
This repository contains the code for fine-tuning a CLIP model on the [ROCO da... | {} | kaushalya/medclip | null | [
"transformers",
"jax",
"tensorboard",
"hybrid-clip",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #jax #tensorboard #hybrid-clip #endpoints_compatible #region-us
| # MedCLIP: Fine-tuning a CLIP model on the ROCO medical dataset
<h3 align="center">
<img src="./assets/URL" alt="huggingface-medclip" width="250" height="250">
## Summary
This repository contains the code for fine-tuning a CLIP model on the ROCO dataset, a dataset made of radiology images and a caption.
This wo... | [
"# MedCLIP: Fine-tuning a CLIP model on the ROCO medical dataset\n\n\n<h3 align=\"center\">\n \n <img src=\"./assets/URL\" alt=\"huggingface-medclip\" width=\"250\" height=\"250\">",
"## Summary\nThis repository contains the code for fine-tuning a CLIP model on the ROCO dataset, a dataset made of radiology imag... | [
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"# MedCLIP: Fine-tuning a CLIP model on the ROCO medical dataset\n\n\n<h3 align=\"center\">\n \n <img src=\"./assets/URL\" alt=\"huggingface-medclip\" width=\"250\" height=\"250\">",
"## Summary\nThis repository contains... |
null | transformers |
# MedCLIP
## Model description
## Intended uses & limitations
#### How to use
```python
# You can include sample code which will be formatted
```
#### Limitations and bias
Provide examples of latent issues and potential remediations.
## Training data
Describe the data you used to train the model.
If you initi... | {"language": ["en"], "license": "apache-2.0", "tags": ["vision"]} | flax-community/medclip | null | [
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"tensorboard",
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] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #jax #tensorboard #hybrid-clip #vision #en #license-apache-2.0 #endpoints_compatible #has_space #region-us
|
# MedCLIP
## Model description
## Intended uses & limitations
#### How to use
#### Limitations and bias
Provide examples of latent issues and potential remediations.
## Training data
Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained m... | [
"# MedCLIP",
"## Model description",
"## Intended uses & limitations",
"#### How to use",
"#### Limitations and bias\n\nProvide examples of latent issues and potential remediations.",
"## Training data\n\nDescribe the data you used to train the model.\nIf you initialized it with pre-trained weights, add a... | [
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"# MedCLIP",
"## Model description",
"## Intended uses & limitations",
"#### How to use",
"#### Limitations and bias\n\nProvide examples of latent issues and potential remed... |
text-generation | transformers |
# Mongolian GPT2
Goal is to create a strong language generation model for Mongolian
Since initial code and data is pretty much written by @patrickvonplaten and other huggingface members, it should not be so hard to get the first sense.
## Model
Randomly initialized GPT2 model
## Datasets
We can use OSCAR which is a... | {"language": "mn", "tags": ["gpt2"], "datasets": ["oscar"], "thumbnail": "https://avatars.githubusercontent.com/u/43239645?s=60&v=4"} | flax-community/mongolian-gpt2 | null | [
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"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"mn"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #mn #dataset-oscar #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mongolian GPT2
Goal is to create a strong language generation model for Mongolian
Since initial code and data is pretty much written by @patrickvonplaten and other huggingface members, it should not be so hard to get the first sense.
## Model
Randomly initialized GPT2 model
## Datasets
We can use OSCAR which is a... | [
"# Mongolian GPT2\n\nGoal is to create a strong language generation model for Mongolian\nSince initial code and data is pretty much written by @patrickvonplaten and other huggingface members, it should not be so hard to get the first sense.",
"## Model\nRandomly initialized GPT2 model",
"## Datasets\nWe can use... | [
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"# Mongolian GPT2\n\nGoal is to create a strong language generation model for Mongolian\nSince initial code and data is pretty much written by @patric... |
null | transformers | # IndicNLP Marathi News Classifier
This model was fine-tuned using [Marathi RoBERTa](https://huggingface.co/flax-community/roberta-base-mr) on [IndicNLP Marathi News Dataset](https://github.com/AI4Bharat/indicnlp_corpus#indicnlp-news-article-classification-dataset)
## Dataset
IndicNLP Marathi news dataset consists 3 c... | {} | flax-community/mr-indicnlp-classifier | null | [
"transformers",
"pytorch",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #endpoints_compatible #has_space #region-us
| IndicNLP Marathi News Classifier
================================
This model was fine-tuned using Marathi RoBERTa on IndicNLP Marathi News Dataset
Dataset
-------
IndicNLP Marathi news dataset consists 3 classes - '['lifestyle', 'entertainment', 'sports']' - with following docs distribution as per classes:
trai... | [] | [
"TAGS\n#transformers #pytorch #endpoints_compatible #has_space #region-us \n"
] |
text-generation | transformers |
# Nordic GPT2--wikipedia
A Nordic GPT2 style model trained using Flax CLM pipeline on the Nordic parts
part of the wiki40b dataset.
https://huggingface.co/datasets/wiki40b
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## ... | {"language": "sv", "widget": [{"text": "Det var en g\u00e5ng"}]} | flax-community/nordic-gpt-wiki | null | [
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] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sv"
] | TAGS
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|
# Nordic GPT2--wikipedia
A Nordic GPT2 style model trained using Flax CLM pipeline on the Nordic parts
part of the wiki40b dataset.
URL
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swedish Gpt
URL
## Swedish gpt wiki... | [
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fill-mask | transformers | # Nordic Roberta Wikipedia
## Description
Nord roberta model trainined on the swedish danish and norwegian wikipedia.
## Evaluation
Evaluation on Named Entity recognition in Danish.
I finetuned each model on 3 epochs on DaNE, repeated it 5 times for each model, and calculated 95% confidence intervals for the means. H... | {"language": "sv", "license": "cc-by-4.0", "tags": ["swedish", "roberta"], "pipeline_tag": "fill-mask", "widget": [{"text": "Meninged med livet \u00e4r <mask>."}]} | flax-community/nordic-roberta-wiki | null | [
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] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sv"
] | TAGS
#transformers #pytorch #jax #tensorboard #roberta #feature-extraction #swedish #fill-mask #sv #license-cc-by-4.0 #endpoints_compatible #region-us
| # Nordic Roberta Wikipedia
## Description
Nord roberta model trainined on the swedish danish and norwegian wikipedia.
## Evaluation
Evaluation on Named Entity recognition in Danish.
I finetuned each model on 3 epochs on DaNE, repeated it 5 times for each model, and calculated 95% confidence intervals for the means. H... | [
"# Nordic Roberta Wikipedia",
"## Description\nNord roberta model trainined on the swedish danish and norwegian wikipedia.",
"## Evaluation\nEvaluation on Named Entity recognition in Danish.\n\nI finetuned each model on 3 epochs on DaNE, repeated it 5 times for each model, and calculated 95% confidence interval... | [
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"# Nordic Roberta Wikipedia",
"## Description\nNord roberta model trainined on the swedish danish and norwegian wikipedia.",
"## Evaluation\nEvaluation ... |
text-generation | transformers |
# GPT2-svenska-wikipedia
A norwegian GPT2 style model trained using Flax CLM pipeline on the Norwegian
part of the wiki40b dataset.
https://huggingface.co/datasets/wiki40b
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## ... | {"language": false, "widget": [{"text": "Det er flott"}]} | flax-community/norsk-gpt-wiki | null | [
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] | null | 2022-03-02T23:29:05+00:00 | [] | [
"no"
] | TAGS
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|
# GPT2-svenska-wikipedia
A norwegian GPT2 style model trained using Flax CLM pipeline on the Norwegian
part of the wiki40b dataset.
URL
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swedish Gpt
URL
## Swedish gpt wiki... | [
"# GPT2-svenska-wikipedia\nA norwegian GPT2 style model trained using Flax CLM pipeline on the Norwegian\npart of the wiki40b dataset.\n\nURL",
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"## Swedish Gpt\nUR... | [
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"# GPT2-svenska-wikipedia\nA norwegian GPT2 style model trained using Flax CLM pipeline on the Norwegian\npart of the wiki40b da... |
text-generation | transformers |
# papuGaPT2 - Polish GPT2 language model
[GPT2](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) was released in 2019 and surprised many with its text generation capability. However, up until very recently, we have not had a strong text generation mode... | {"language": "pl", "tags": ["text-generation"], "widget": [{"text": "Najsmaczniejszy polski owoc to"}]} | flax-community/papuGaPT2 | null | [
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"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pl"
] | TAGS
#transformers #pytorch #jax #tensorboard #text-generation #pl #endpoints_compatible #has_space #region-us
|
# papuGaPT2 - Polish GPT2 language model
GPT2 was released in 2019 and surprised many with its text generation capability. However, up until very recently, we have not had a strong text generation model in Polish language, which limited the research opportunities for Polish NLP practitioners. With the release of this ... | [
"# papuGaPT2 - Polish GPT2 language model\nGPT2 was released in 2019 and surprised many with its text generation capability. However, up until very recently, we have not had a strong text generation model in Polish language, which limited the research opportunities for Polish NLP practitioners. With the release of ... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #text-generation #pl #endpoints_compatible #has_space #region-us \n",
"# papuGaPT2 - Polish GPT2 language model\nGPT2 was released in 2019 and surprised many with its text generation capability. However, up until very recently, we have not had a strong text generati... |
fill-mask | transformers |
# Pino (Dutch BigBird) base model
Created by [Dat Nguyen](https://www.linkedin.com/in/dat-nguyen-49a641138/) & [Yeb Havinga](https://www.linkedin.com/in/yeb-havinga-86530825/) during the [Hugging Face community week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104)... | {"language": "nl", "datasets": ["mC4", "Dutch_news"]} | flax-community/pino-bigbird-roberta-base | null | [
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"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2007.14062"
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"nl"
] | TAGS
#transformers #pytorch #jax #tensorboard #big_bird #fill-mask #nl #dataset-mC4 #dataset-Dutch_news #arxiv-2007.14062 #autotrain_compatible #endpoints_compatible #region-us
|
# Pino (Dutch BigBird) base model
Created by Dat Nguyen & Yeb Havinga during the Hugging Face community week
(Not finished yet)
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understan... | [
"# Pino (Dutch BigBird) base model\n\nCreated by Dat Nguyen & Yeb Havinga during the Hugging Face community week\n\n(Not finished yet)\n\n\n\nBigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretic... | [
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"# Pino (Dutch BigBird) base model\n\nCreated by Dat Nguyen & Yeb Havinga during the Hugging Face community week\n\n(Not finished ... |
null | null | # Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation
[](https://huggingface.co/spaces/flax-community/DietNerf-Demo) [](ht... | {} | flax-community/putting-nerf-on-a-diet | null | [
"arxiv:2104.00677",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.00677"
] | [] | TAGS
#arxiv-2104.00677 #region-us
| Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation
======================================================================================
![Open in Streamlit](URL ![Open In Colab](URL
![스크린샷 2021-07-04 오후 4 11 51](URL
<p>This project attempted to implement the paper Putti... | [
"### Rendered Rendering images by 8-shot learned Diet-NeRF\n\n\nDietNeRF has a strong capacity to generalise on novel and challenging views with EXTREMELY SMALL TRAINING SAMPLES!",
"### HOTDOG / DRUM / SHIP / CHAIR / LEGO / MIC\n\n\n<img alt=\"\" src=\"URL width=\"250\"/> <img alt=\"\" src=\"URL width=\"250\"/> <... | [
"TAGS\n#arxiv-2104.00677 #region-us \n",
"### Rendered Rendering images by 8-shot learned Diet-NeRF\n\n\nDietNeRF has a strong capacity to generalise on novel and challenging views with EXTREMELY SMALL TRAINING SAMPLES!",
"### HOTDOG / DRUM / SHIP / CHAIR / LEGO / MIC\n\n\n<img alt=\"\" src=\"URL width=\"250\"/... |
fill-mask | transformers | # roberta-base-als-demo
**roberta-base-als-demo** is a model trained by Patrick von Platen to demonstrate how to train a roberta-base model from scratch on the Alemannic language.
This is part of the
[Flax/Jax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp... | {} | flax-community/roberta-base-als-demo | null | [
"transformers",
"jax",
"roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #jax #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us
| # roberta-base-als-demo
roberta-base-als-demo is a model trained by Patrick von Platen to demonstrate how to train a roberta-base model from scratch on the Alemannic language.
This is part of the
Flax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.
## Useful links
- Community Week ti... | [
"# roberta-base-als-demo\n\nroberta-base-als-demo is a model trained by Patrick von Platen to demonstrate how to train a roberta-base model from scratch on the Alemannic language.\n\nThis is part of the\nFlax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.",
"## Useful links\n- Com... | [
"TAGS\n#transformers #jax #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us \n",
"# roberta-base-als-demo\n\nroberta-base-als-demo is a model trained by Patrick von Platen to demonstrate how to train a roberta-base model from scratch on the Alemannic language.\n\nThis is part of the\nFlax... |
fill-mask | transformers | This project pretrains a [`roberta-base`](https://huggingface.co/roberta-base) on the *Alemannic* (`als`) data subset of the [OSCAR](https://oscar-corpus.com/) corpus in JAX/Flax.
We will be using the masked-language modeling loss for pretraining. | {} | flax-community/roberta-base-als | null | [
"transformers",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #jax #tensorboard #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us
| This project pretrains a 'roberta-base' on the *Alemannic* ('als') data subset of the OSCAR corpus in JAX/Flax.
We will be using the masked-language modeling loss for pretraining. | [] | [
"TAGS\n#transformers #jax #tensorboard #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us \n"
] |
fill-mask | transformers |
# RøBÆRTa - Danish Roberta Base
## Description
RøBÆRTa is a danish pretrained Roberta base model. RøBÆRTa was pretrained on the danish mC4 dataset during the flax community week. This project was organized by Dansk Data Science Community (DDSC) 👇 <br><br>
https://www.linkedin.com/groups/9017904/
## Team RøBÆRTa:
... | {"language": "da", "license": "cc-by-4.0", "tags": ["danish", "roberta"], "pipeline_tag": "fill-mask", "widget": [{"text": "P\u00e5 biblioteket kan du l\u00e5ne en <mask>."}]} | DDSC/roberta-base-danish | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"roberta",
"fill-mask",
"danish",
"da",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"da"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #roberta #fill-mask #danish #da #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# RøBÆRTa - Danish Roberta Base
## Description
RøBÆRTa is a danish pretrained Roberta base model. RøBÆRTa was pretrained on the danish mC4 dataset during the flax community week. This project was organized by Dansk Data Science Community (DDSC) <br><br>
URL
## Team RøBÆRTa:
- Dan Saattrup Nielsen (saattrupdan)
- ... | [
"# RøBÆRTa - Danish Roberta Base",
"## Description\n\nRøBÆRTa is a danish pretrained Roberta base model. RøBÆRTa was pretrained on the danish mC4 dataset during the flax community week. This project was organized by Dansk Data Science Community (DDSC) <br><br>\nURL",
"## Team RøBÆRTa:\n- Dan Saattrup Nielsen (... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #roberta #fill-mask #danish #da #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# RøBÆRTa - Danish Roberta Base",
"## Description\n\nRøBÆRTa is a danish pretrained Roberta base model. RøBÆRTa was pretrained on the danis... |
fill-mask | transformers |
# RoBERTa base model for Marathi language (मराठी भाषा)
Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa was introduced in
[this paper](https://arxiv.org/abs/1907.11692) and first released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/roberta... | {"widget": [{"text": "\u0905\u0927\u094d\u092f\u0915\u094d\u0937 <mask> \u092a\u0935\u093e\u0930 \u0906\u0923\u093f \u0909\u092a\u092e\u0941\u0916\u094d\u092f\u092e\u0902\u0924\u094d\u0930\u0940 \u0905\u091c\u093f\u0924 \u092a\u0935\u093e\u0930 \u092f\u093e\u0902\u091a\u0940 \u092d\u0947\u091f \u0918\u0947\u0924\u0932\... | flax-community/roberta-base-mr | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"arxiv:1907.11692",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1907.11692"
] | [] | TAGS
#transformers #pytorch #jax #tensorboard #roberta #fill-mask #arxiv-1907.11692 #autotrain_compatible #endpoints_compatible #has_space #region-us
| RoBERTa base model for Marathi language (मराठी भाषा)
====================================================
Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa was introduced in
this paper and first released in
this repository. We trained RoBERTa model for Marathi Language dur... | [
"### How to use\n\n\nYou can use this model directly with a pipeline for masked language modeling:\n\n\nTraining data ️\n----------------\n\n\nThe RoBERTa Marathi model was pretrained on 'mr' dataset of C4 multilingual dataset:\n \n\n \n\nC4 (Colossal Clean Crawled Corpus), Introduced by Raffel et al. in Explori... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #roberta #fill-mask #arxiv-1907.11692 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### How to use\n\n\nYou can use this model directly with a pipeline for masked language modeling:\n\n\nTraining data ️\n----------------\n\n\nThe RoBERTa M... |
fill-mask | transformers |
# Scandinavian Roberta Base - MC4
## Description
This is a sample reference model for Flax/Jax training using only on the MC4. It is trained for roughly three day on a TPU v3-8. Training procedure...
---
## Description
My description | {"language": "da", "license": "cc-by-4.0", "tags": ["scandinavian", "roberta"], "pipeline_tag": "fill-mask", "widget": [{"text": "P\u00e5 biblioteket kan du l\u00e5ne en <mask>."}]} | DDSC/roberta-base-scandinavian | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"scandinavian",
"da",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"da"
] | TAGS
#transformers #pytorch #jax #tensorboard #roberta #fill-mask #scandinavian #da #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# Scandinavian Roberta Base - MC4
## Description
This is a sample reference model for Flax/Jax training using only on the MC4. It is trained for roughly three day on a TPU v3-8. Training procedure...
---
## Description
My description | [
"# Scandinavian Roberta Base - MC4",
"## Description\n\nThis is a sample reference model for Flax/Jax training using only on the MC4. It is trained for roughly three day on a TPU v3-8. Training procedure...\n\n---",
"## Description\nMy description"
] | [
"TAGS\n#transformers #pytorch #jax #tensorboard #roberta #fill-mask #scandinavian #da #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Scandinavian Roberta Base - MC4",
"## Description\n\nThis is a sample reference model for Flax/Jax training using only on the MC4. It is trained... |
fill-mask | transformers |
# RoBERTa base model for Hindi language
Pretrained model on Hindi language using a masked language modeling (MLM) objective. [A more interactive & comparison demo is available here](https://huggingface.co/spaces/flax-community/roberta-hindi).
> This is part of the
[Flax/Jax Community Week](https://discuss.huggingfac... | {"widget": [{"text": "\u092e\u0941\u091d\u0947 \u0909\u0928\u0938\u0947 \u092c\u093e\u0924 \u0915\u0930\u0928\u093e <mask> \u0905\u091a\u094d\u091b\u093e \u0932\u0917\u093e"}, {"text": "\u0939\u092e \u0906\u092a\u0915\u0947 \u0938\u0941\u0916\u0926 <mask> \u0915\u0940 \u0915\u093e\u092e\u0928\u093e \u0915\u0930\u0924\u... | flax-community/roberta-hindi | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #tensorboard #roberta #fill-mask #autotrain_compatible #endpoints_compatible #has_space #region-us
| RoBERTa base model for Hindi language
=====================================
Pretrained model on Hindi language using a masked language modeling (MLM) objective. A more interactive & comparison demo is available here.
>
> This is part of the
> Flax/Jax Community Week, organized by Hugging Face and TPU usage sponso... | [
"### How to use\n\n\nYou can use this model directly with a pipeline for masked language modeling:\n\n\nTraining data\n-------------\n\n\nThe RoBERTa Hindi model was pretrained on the reunion of the following datasets:\n\n\n* OSCAR is a huge multilingual corpus obtained by language classification and filtering of t... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #roberta #fill-mask #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### How to use\n\n\nYou can use this model directly with a pipeline for masked language modeling:\n\n\nTraining data\n-------------\n\n\nThe RoBERTa Hindi model was pretraine... |
fill-mask | transformers |
roberta-pretraining-hindi | {"widget": [{"text": "\u0936\u0941\u092d \u092a\u094d\u0930\u092d\u093e\u0924\u0964 \u0906\u0936\u093e \u0915\u0930\u0924\u093e \u0939\u0942\u0902 \u0915\u093f \u0906\u092a\u0915\u093e <mask> \u0936\u0941\u092d \u0939\u094b"}]} | flax-community/roberta-pretraining-hindi | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #tensorboard #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us
|
roberta-pretraining-hindi | [] | [
"TAGS\n#transformers #pytorch #jax #tensorboard #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-classification | transformers |
## Swahili News Classification with RoBERTa
This model was trained using HuggingFace's Flax framework and is part of the [JAX/Flax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104) organized by [HuggingFace](https://huggingface.co). All training was... | {"language": "sw", "datasets": ["flax-community/swahili-safi"], "widget": [{"text": "Idris ameandika kwenye ukurasa wake wa Instagram akimkumbusha Diamond kutekeleza ahadi yake kumpigia Zari magoti kumuomba msamaha kama alivyowahi kueleza awali.Idris ameandika;"}]} | flax-community/roberta-swahili-news-classification | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"sw",
"dataset:flax-community/swahili-safi",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sw"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #roberta #text-classification #sw #dataset-flax-community/swahili-safi #autotrain_compatible #endpoints_compatible #has_space #region-us
|
## Swahili News Classification with RoBERTa
This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.
This model was used as the base and fine-tuned for this task.
## How t... | [
"## Swahili News Classification with RoBERTa\n\n\nThis model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.\n\nThis model was used as the base and fine-tuned for this task."... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #roberta #text-classification #sw #dataset-flax-community/swahili-safi #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"## Swahili News Classification with RoBERTa\n\n\nThis model was trained using HuggingFace's Flax framework and... |
fill-mask | transformers |
## RoBERTa in Swahili
This model was trained using HuggingFace's Flax framework and is part of the [JAX/Flax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104) organized by [HuggingFace](https://huggingface.co). All training was done on a TPUv3-8 VM s... | {"language": "sw", "datasets": ["flax-community/swahili-safi"], "widget": [{"text": "Si kila mwenye makucha <mask> simba."}]} | flax-community/roberta-swahili | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"sw",
"dataset:flax-community/swahili-safi",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sw"
] | TAGS
#transformers #pytorch #jax #tensorboard #roberta #fill-mask #sw #dataset-flax-community/swahili-safi #autotrain_compatible #endpoints_compatible #has_space #region-us
|
## RoBERTa in Swahili
This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.
## How to use
#### Training Data:
This model was trained on Swahili Safi
#### Results:
Mas... | [
"## RoBERTa in Swahili\n\nThis model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.",
"## How to use",
"#### Training Data:\nThis model was trained on Swahili Safi",
"... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #roberta #fill-mask #sw #dataset-flax-community/swahili-safi #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"## RoBERTa in Swahili\n\nThis model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organiz... |
fill-mask | transformers | # RobIt
**RobIt** is a RoBERTa-base model for Italian. It has been trained from scratch on the Italian portion of the OSCAR dataset using [Flax](https://github.com/google/flax), including training scripts.
This is part of the
[Flax/Jax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-w... | {} | flax-community/robit-roberta-base-it | null | [
"transformers",
"jax",
"roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #jax #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us
| # RobIt
RobIt is a RoBERTa-base model for Italian. It has been trained from scratch on the Italian portion of the OSCAR dataset using Flax, including training scripts.
This is part of the
Flax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.
## Team members
- Prateek Agrawal (prateekag... | [
"# RobIt\n\nRobIt is a RoBERTa-base model for Italian. It has been trained from scratch on the Italian portion of the OSCAR dataset using Flax, including training scripts.\n\nThis is part of the\nFlax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.",
"## Team members\n- Prateek Agr... | [
"TAGS\n#transformers #jax #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us \n",
"# RobIt\n\nRobIt is a RoBERTa-base model for Italian. It has been trained from scratch on the Italian portion of the OSCAR dataset using Flax, including training scripts.\n\nThis is part of the\nFlax/Jax Com... |
text2text-generation | transformers | # Spanish T5 (small) trained on [large_spanish_corpus](https://huggingface.co/datasets/viewer/?dataset=large_spanish_corpus).
This is a Spanish **T5** (small arch) trained from scratch on the [large_spanish_corpus](https://huggingface.co/datasets/viewer/?dataset=large_spanish_corpus) aka BETO's corpus with [Flax](http... | {"language": "es", "license": "mit", "tags": ["T5", "Seq2Seq", "EconderDecoder", "Spanish"], "datasets": ["large_spanish_corpus"], "widgets": [{"text": "\u00c9rase un vez un"}]} | flax-community/spanish-t5-small | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
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"t5",
"text2text-generation",
"T5",
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"EconderDecoder",
"Spanish",
"es",
"dataset:large_spanish_corpus",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
... | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #t5 #text2text-generation #T5 #Seq2Seq #EconderDecoder #Spanish #es #dataset-large_spanish_corpus #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Spanish T5 (small) trained on large_spanish_corpus.
This is a Spanish T5 (small arch) trained from scratch on the large_spanish_corpus aka BETO's corpus with Flax
This is part of the
Flax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.
## Dataset
The dataset is about 20 GB. 95% of th... | [
"# Spanish T5 (small) trained on large_spanish_corpus.\n\nThis is a Spanish T5 (small arch) trained from scratch on the large_spanish_corpus aka BETO's corpus with Flax\n\nThis is part of the\nFlax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.",
"## Dataset\nThe dataset is about ... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #t5 #text2text-generation #T5 #Seq2Seq #EconderDecoder #Spanish #es #dataset-large_spanish_corpus #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Spanish T5 (small) trained on large_spanish_corpus.\... |
text-generation | transformers |
# GPT2-svenska-wikipedia
A swedish GPT2 style model trained using Flax CLM pipeline on the Swedish
part of the wiki40b dataset.
https://huggingface.co/datasets/wiki40b
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swed... | {"language": "sv", "widget": [{"text": "Jag \u00e4r en svensk spr\u00e5kmodell."}]} | flax-community/swe-gpt-wiki | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"sv",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sv"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #gpt2 #text-generation #sv #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# GPT2-svenska-wikipedia
A swedish GPT2 style model trained using Flax CLM pipeline on the Swedish
part of the wiki40b dataset.
URL
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swedish Gpt
URL
## Swedish gpt wiki
URL... | [
"# GPT2-svenska-wikipedia\nA swedish GPT2 style model trained using Flax CLM pipeline on the Swedish\npart of the wiki40b dataset.\n\nURL",
"## Model series\nThis model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.",
"## Gpt models",
"## Swedish Gpt\nURL",
... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #gpt2 #text-generation #sv #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# GPT2-svenska-wikipedia\nA swedish GPT2 style model trained using Flax CLM pipeline on the Swedish\npart of the wiki40b datase... |
fill-mask | transformers | # Swe Roberta Wiki Oscar
## Description
This Roberta model was trained on the Swedish Wikipedia and Oscar datasets
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swedish Gpt
https://huggingface.co/birgermoell/swedish-gpt/... | {"language": "sv", "license": "cc-by-4.0", "tags": ["swedish", "roberta"], "pipeline_tag": "fill-mask", "widget": [{"text": "Meninged med livet \u00e4r <mask>."}]} | flax-community/swe-roberta-wiki-oscar | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"roberta",
"feature-extraction",
"swedish",
"fill-mask",
"sv",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sv"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #roberta #feature-extraction #swedish #fill-mask #sv #license-cc-by-4.0 #endpoints_compatible #region-us
| # Swe Roberta Wiki Oscar
## Description
This Roberta model was trained on the Swedish Wikipedia and Oscar datasets
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swedish Gpt
URL
## Swedish gpt wiki
URL
# Nordic gpt wiki... | [
"# Swe Roberta Wiki Oscar",
"## Description\nThis Roberta model was trained on the Swedish Wikipedia and Oscar datasets",
"## Model series\nThis model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.",
"## Gpt models",
"## Swedish Gpt\nURL",
"## Swedish gp... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #roberta #feature-extraction #swedish #fill-mask #sv #license-cc-by-4.0 #endpoints_compatible #region-us \n",
"# Swe Roberta Wiki Oscar",
"## Description\nThis Roberta model was trained on the Swedish Wikipedia and Oscar datasets",
"## Model series\... |
summarization | transformers | # Model
This model is fine-tuned from https://huggingface.co/flax-community/t5-base-openwebtext, fine-tuned on cnn_dailymail.
| {"language": "en", "license": "apache-2.0", "tags": ["summarization"], "datasets": ["cnn_dailymail"], "model-index": [{"name": "flax-community/t5-base-cnn-dm", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "cnn_dailymail", "type": "cnn_dailymail", "config": "3.0.0", "split... | flax-community/t5-base-cnn-dm | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"summarization",
"en",
"dataset:cnn_dailymail",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #t5 #text2text-generation #summarization #en #dataset-cnn_dailymail #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| # Model
This model is fine-tuned from URL fine-tuned on cnn_dailymail.
| [
"# Model\nThis model is fine-tuned from URL fine-tuned on cnn_dailymail."
] | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #t5 #text2text-generation #summarization #en #dataset-cnn_dailymail #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# Model\nThis model is fine-tuned from URL fine-tuned... |
text2text-generation | transformers |
# t5-base-dutch-demo 📰
Created by [Yeb Havinga](https://www.linkedin.com/in/yeb-havinga-86530825/) & [Dat Nguyen](https://www.linkedin.com/in/dat-nguyen-49a641138/) during the [Hugging Face community week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104)
This mod... | {"language": ["dutch"], "tags": ["summarization", "seq2seq", "text-generation"], "datasets": ["cnn_dailymail", "xsum"], "pipeline_tag": "text2text-generation", "widget": [{"text": "Onderzoekers ontdekten dat vier van de vijf kinderen in Engeland die op school lunches hadden gegeten, op school voedsel hadden geprobeerd ... | flax-community/t5-base-dutch-demo | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"summarization",
"seq2seq",
"text-generation",
"dataset:cnn_dailymail",
"dataset:xsum",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
... | null | 2022-03-02T23:29:05+00:00 | [] | [
"dutch"
] | TAGS
#transformers #pytorch #jax #tensorboard #safetensors #t5 #text2text-generation #summarization #seq2seq #text-generation #dataset-cnn_dailymail #dataset-xsum #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# t5-base-dutch-demo
Created by Yeb Havinga & Dat Nguyen during the Hugging Face community week
This model is based on t5-base-dutch
and fine-tuned to create summaries of news articles.
For a demo of the model, head over to the Hugging Face Spaces for the Netherformer example application!
## Dataset
't5-base-... | [
"# t5-base-dutch-demo \n\nCreated by Yeb Havinga & Dat Nguyen during the Hugging Face community week\n\nThis model is based on t5-base-dutch \nand fine-tuned to create summaries of news articles.\n\nFor a demo of the model, head over to the Hugging Face Spaces for the Netherformer example application!",
"## Data... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #safetensors #t5 #text2text-generation #summarization #seq2seq #text-generation #dataset-cnn_dailymail #dataset-xsum #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"# t5-base-dutch-demo \n\nCreated by Yeb Havinga & ... |
text2text-generation | transformers |
# t5-base-dutch
Created by [Yeb Havinga](https://www.linkedin.com/in/yeb-havinga-86530825/)
& [Dat Nguyen](https://www.linkedin.com/in/dat-nguyen-49a641138/) during the [Hugging Face community week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104), organized by [H... | {"language": ["dutch"], "license": "apache-2.0", "tags": ["seq2seq", "lm-head"], "datasets": ["yhavinga/mc4_nl_cleaned"], "inference": false} | flax-community/t5-base-dutch | null | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"seq2seq",
"lm-head",
"dataset:yhavinga/mc4_nl_cleaned",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"dutch"
] | TAGS
#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #seq2seq #lm-head #dataset-yhavinga/mc4_nl_cleaned #license-apache-2.0 #autotrain_compatible #text-generation-inference #region-us
|
# t5-base-dutch
Created by Yeb Havinga
& Dat Nguyen during the Hugging Face community week, organized by HuggingFace and TPU usage sponsored by Google, for the project Pre-train T5 from scratch in Dutch.
See also the fine-tuned t5-base-dutch-demo model,
and the demo application Netherformer ,
that are based on this... | [
"# t5-base-dutch \n\nCreated by Yeb Havinga\n& Dat Nguyen during the Hugging Face community week, organized by HuggingFace and TPU usage sponsored by Google, for the project Pre-train T5 from scratch in Dutch.\n\nSee also the fine-tuned t5-base-dutch-demo model,\nand the demo application Netherformer ,\nthat are ba... | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #seq2seq #lm-head #dataset-yhavinga/mc4_nl_cleaned #license-apache-2.0 #autotrain_compatible #text-generation-inference #region-us \n",
"# t5-base-dutch \n\nCreated by Yeb Havinga\n& Dat Nguyen during the Hugging Face community week, or... |
null | null | # Covid19 Related Question Answering (Closed book question answering)
In 2020, COVID-19 which is caused by a coronavirus called SARS-CoV-2 took over the world. It touched the lives of many people and caused a lot of hardship for humanity. There are still many questions in regards to COVID-19 and it is often difficult ... | {} | flax-community/t5-covid-qa | null | [
"arxiv:2002.08910",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2002.08910"
] | [] | TAGS
#arxiv-2002.08910 #region-us
| # Covid19 Related Question Answering (Closed book question answering)
In 2020, COVID-19 which is caused by a coronavirus called SARS-CoV-2 took over the world. It touched the lives of many people and caused a lot of hardship for humanity. There are still many questions in regards to COVID-19 and it is often difficult ... | [
"# Covid19 Related Question Answering (Closed book question answering)\n\nIn 2020, COVID-19 which is caused by a coronavirus called SARS-CoV-2 took over the world. It touched the lives of many people and caused a lot of hardship for humanity. There are still many questions in regards to COVID-19 and it is often dif... | [
"TAGS\n#arxiv-2002.08910 #region-us \n",
"# Covid19 Related Question Answering (Closed book question answering)\n\nIn 2020, COVID-19 which is caused by a coronavirus called SARS-CoV-2 took over the world. It touched the lives of many people and caused a lot of hardship for humanity. There are still many questions... |
text2text-generation | transformers | # T5 model for sentence splitting in English
Sentence Split is the task of dividing a long sentence into multiple sentences.
E.g.:
```
Mary likes to play football in her freetime whenever she meets with her friends that are very nice people.
```
could be split into
```
Mary likes to play football in her freetime whene... | {"datasets": ["wiki_split"], "widget": [{"text": "Mary likes to play football in her freetime whenever she meets with her friends that are very nice people."}]} | flax-community/t5-large-wikisplit | null | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"dataset:wiki_split",
"arxiv:1907.12461",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1907.12461"
] | [] | TAGS
#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #dataset-wiki_split #arxiv-1907.12461 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| T5 model for sentence splitting in English
==========================================
Sentence Split is the task of dividing a long sentence into multiple sentences.
E.g.:
could be split into
How to use it in your code:
---------------------------
Datasets:
---------
Wiki\_Split
Current Basline from paper
-... | [] | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #dataset-wiki_split #arxiv-1907.12461 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n"
] |
text2text-generation | transformers |
# Chef Transformer (T5)
> This is part of the
[Flax/Jax Community Week](https://discuss.huggingface.co/t/recipe-generation-model/7475), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.
Want to give it a try? Then what's the wait, head over to Hug... | {"language": "en", "tags": ["seq2seq", "t5", "text-generation", "recipe-generation"], "pipeline_tag": "text2text-generation", "widget": [{"text": "provolone cheese, bacon, bread, ginger"}, {"text": "sugar, crunchy jif peanut butter, cornflakes"}, {"text": "sweet butter, confectioners sugar, flaked coconut, condensed mi... | flax-community/t5-recipe-generation | null | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"seq2seq",
"text-generation",
"recipe-generation",
"en",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #tensorboard #safetensors #t5 #text2text-generation #seq2seq #text-generation #recipe-generation #en #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| !avatar
Chef Transformer (T5)
=====================
>
> This is part of the
> Flax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.
>
>
>
Want to give it a try? Then what's the wait, head over to Hugging Face Spaces here.
Team Members
------------
* Mehrdad Farahani (m3hrda... | [
"### Example\n\n\nHow To Use\n----------\n\n\nOutput:\n\n\nEvaluation\n----------\n\n\nSince the test set is not available, we will evaluate the model based on a shared test set. This test set consists of 5% of the whole test (*= 5,000 records*),\nand we will generate five recipes for each input(*= 25,000 records*)... | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #safetensors #t5 #text2text-generation #seq2seq #text-generation #recipe-generation #en #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"### Example\n\n\nHow To Use\n----------\n\n\nOutput:\n\n\nEvaluation\n-----... |
text2text-generation | transformers | # T5 model for sentence splitting in English
Sentence Split is the task of dividing a long sentence into multiple sentences.
E.g.:
```
Mary likes to play football in her freetime whenever she meets with her friends that are very nice people.
```
could be split into
```
Mary likes to play football in her freetime when... | {"datasets": ["wiki_split"], "widget": [{"text": "Mary likes to play football in her freetime whenever she meets with her friends that are very nice people."}]} | flax-community/t5-v1_1-base-wikisplit | null | [
"transformers",
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"dataset:wiki_split",
"arxiv:1907.12461",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1907.12461"
] | [] | TAGS
#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #dataset-wiki_split #arxiv-1907.12461 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| T5 model for sentence splitting in English
==========================================
Sentence Split is the task of dividing a long sentence into multiple sentences.
E.g.:
could be split into
How to use it in your code:
---------------------------
Datasets:
---------
Wiki\_Split
Current Basline from paper
-... | [] | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #dataset-wiki_split #arxiv-1907.12461 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n"
] |
null | transformers |
# T5-VAE-Python (flax)
A Transformer-VAE made using flax.
Try the [demo](https://huggingface.co/spaces/flax-community/t5-vae)!
It has been trained to interpolate on lines of Python code from the [python-lines dataset](https://huggingface.co/datasets/Fraser/python-lines).
Done as part of Huggingface community train... | {"language": "python", "license": "apache-2.0", "tags": "vae", "datasets": "Fraser/python-lines"} | flax-community/t5-vae-python | null | [
"transformers",
"jax",
"transformer_vae",
"vae",
"dataset:Fraser/python-lines",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"python"
] | TAGS
#transformers #jax #transformer_vae #vae #dataset-Fraser/python-lines #license-apache-2.0 #endpoints_compatible #has_space #region-us
|
# T5-VAE-Python (flax)
A Transformer-VAE made using flax.
Try the demo!
It has been trained to interpolate on lines of Python code from the python-lines dataset.
Done as part of Huggingface community training (see forum post).
Builds on T5, using an autoencoder to convert it into an MMD-VAE (more info).
## How t... | [
"# T5-VAE-Python (flax)\n\nA Transformer-VAE made using flax.\n\nTry the demo!\n\nIt has been trained to interpolate on lines of Python code from the python-lines dataset.\n\nDone as part of Huggingface community training (see forum post).\n\nBuilds on T5, using an autoencoder to convert it into an MMD-VAE (more in... | [
"TAGS\n#transformers #jax #transformer_vae #vae #dataset-Fraser/python-lines #license-apache-2.0 #endpoints_compatible #has_space #region-us \n",
"# T5-VAE-Python (flax)\n\nA Transformer-VAE made using flax.\n\nTry the demo!\n\nIt has been trained to interpolate on lines of Python code from the python-lines datas... |
null | transformers |
# T5-VAE-Wiki (flax)
A Transformer-VAE made using flax.
It has been trained to interpolate on sentences form wikipedia.
Done as part of Huggingface community training ([see forum post](https://discuss.huggingface.co/t/train-a-vae-to-interpolate-on-english-sentences/7548)).
Builds on T5, using an autoencoder to con... | {"language": "en", "license": "apache-2.0", "tags": "vae"} | flax-community/t5-vae-wiki | null | [
"transformers",
"jax",
"transformer_vae",
"vae",
"en",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #jax #transformer_vae #vae #en #license-apache-2.0 #endpoints_compatible #has_space #region-us
|
# T5-VAE-Wiki (flax)
A Transformer-VAE made using flax.
It has been trained to interpolate on sentences form wikipedia.
Done as part of Huggingface community training (see forum post).
Builds on T5, using an autoencoder to convert it into an MMD-VAE (more info).
## How to use from the /transformers library
Add m... | [
"# T5-VAE-Wiki (flax)\n\nA Transformer-VAE made using flax.\n\nIt has been trained to interpolate on sentences form wikipedia.\n\nDone as part of Huggingface community training (see forum post).\n\nBuilds on T5, using an autoencoder to convert it into an MMD-VAE (more info).",
"## How to use from the /transformer... | [
"TAGS\n#transformers #jax #transformer_vae #vae #en #license-apache-2.0 #endpoints_compatible #has_space #region-us \n",
"# T5-VAE-Wiki (flax)\n\nA Transformer-VAE made using flax.\n\nIt has been trained to interpolate on sentences form wikipedia.\n\nDone as part of Huggingface community training (see forum post)... |
null | null | # Transformer-VAE (flax) (WIP)
A Transformer-VAE made using flax.
Done as part of Huggingface community training ([see forum post](https://discuss.huggingface.co/t/train-a-vae-to-interpolate-on-english-sentences/7548)).
Builds on T5, using an autoencoder to convert it into an MMD-VAE.
[See training logs.](https://w... | {} | flax-community/transformer-vae | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
| # Transformer-VAE (flax) (WIP)
A Transformer-VAE made using flax.
Done as part of Huggingface community training (see forum post).
Builds on T5, using an autoencoder to convert it into an MMD-VAE.
See training logs.
## ToDo
- [ ] Basic training script working. (Fraser + Theo)
- [ ] Add MMD loss (Theo)
- [ ] Save... | [
"# Transformer-VAE (flax) (WIP)\n\nA Transformer-VAE made using flax.\n\nDone as part of Huggingface community training (see forum post).\n\nBuilds on T5, using an autoencoder to convert it into an MMD-VAE.\n\nSee training logs.",
"## ToDo\n\n- [ ] Basic training script working. (Fraser + Theo)\n- [ ] Add MMD los... | [
"TAGS\n#region-us \n",
"# Transformer-VAE (flax) (WIP)\n\nA Transformer-VAE made using flax.\n\nDone as part of Huggingface community training (see forum post).\n\nBuilds on T5, using an autoencoder to convert it into an MMD-VAE.\n\nSee training logs.",
"## ToDo\n\n- [ ] Basic training script working. (Fraser +... |
null | null | # 🖼️ When ViT meets GPT-2 📝
An image captioning model [ViT-GPT2](https://huggingface.co/flax-community/vit-gpt2/tree/main) by combining the ViT model and a French GPT2 model.
Part of the [Huggingface JAX/Flax event](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/).
... | {} | flax-community/vit-gpt2 | null | [
"tensorboard",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#tensorboard #region-us
| # ️ When ViT meets GPT-2
An image captioning model ViT-GPT2 by combining the ViT model and a French GPT2 model.
Part of the Huggingface JAX/Flax event.
The GPT2 model source code is modified so it can accept an encoder's output.
The pretained weights of both models are loaded, with a set of randomly initialized cr... | [
"# ️ When ViT meets GPT-2 \n\nAn image captioning model ViT-GPT2 by combining the ViT model and a French GPT2 model.\n\nPart of the Huggingface JAX/Flax event.\n\nThe GPT2 model source code is modified so it can accept an encoder's output.\nThe pretained weights of both models are loaded, with a set of randomly in... | [
"TAGS\n#tensorboard #region-us \n",
"# ️ When ViT meets GPT-2 \n\nAn image captioning model ViT-GPT2 by combining the ViT model and a French GPT2 model.\n\nPart of the Huggingface JAX/Flax event.\n\nThe GPT2 model source code is modified so it can accept an encoder's output.\nThe pretained weights of both models... |
null | transformers | ## VQGAN-f16-16384
### Model Description
This is a Flax/JAX implementation of VQGAN, which learns a codebook of context-rich visual parts by leveraging both the use of convolutional methods and transformers. It was introduced in [Taming Transformers for High-Resolution Image Synthesis](https://compvis.github.io/tamin... | {} | flax-community/vqgan_f16_16384 | null | [
"transformers",
"jax",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #jax #endpoints_compatible #has_space #region-us
| ## VQGAN-f16-16384
### Model Description
This is a Flax/JAX implementation of VQGAN, which learns a codebook of context-rich visual parts by leveraging both the use of convolutional methods and transformers. It was introduced in Taming Transformers for High-Resolution Image Synthesis (CVPR paper).
The model allows t... | [
"## VQGAN-f16-16384",
"### Model Description\n\nThis is a Flax/JAX implementation of VQGAN, which learns a codebook of context-rich visual parts by leveraging both the use of convolutional methods and transformers. It was introduced in Taming Transformers for High-Resolution Image Synthesis (CVPR paper).\n\nThe m... | [
"TAGS\n#transformers #jax #endpoints_compatible #has_space #region-us \n",
"## VQGAN-f16-16384",
"### Model Description\n\nThis is a Flax/JAX implementation of VQGAN, which learns a codebook of context-rich visual parts by leveraging both the use of convolutional methods and transformers. It was introduced in T... |
null | transformers |
# Wav2Vec2 4 Persian
> This is part of the
[Flax/Jax Community Week](https://discuss.huggingface.co/t/pretrain-wav2vec2-in-persian/8180), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.
## Team Members
- Mehrdad Farahani ([m3hrdadfi](https://huggingface.co/m3hrdadfi))
## Datas... | {"language": "fa", "license": "apache-2.0", "tags": ["speech"], "datasets": ["common_voice"]} | flax-community/wav2vec2-base-persian | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"wav2vec2",
"pretraining",
"speech",
"fa",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #jax #tensorboard #wav2vec2 #pretraining #speech #fa #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
|
# Wav2Vec2 4 Persian
> This is part of the
Flax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.
## Team Members
- Mehrdad Farahani (m3hrdadfi)
## Dataset TODO: Update
## How To Use TODO: Update
## Demo TODO: Update
## Evaluation TODO: Update | [
"# Wav2Vec2 4 Persian\n> This is part of the\nFlax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.",
"## Team Members\n- Mehrdad Farahani (m3hrdadfi)",
"## Dataset TODO: Update",
"## How To Use TODO: Update",
"## Demo TODO: Update",
"## Evaluation TODO: Update"
] | [
"TAGS\n#transformers #pytorch #jax #tensorboard #wav2vec2 #pretraining #speech #fa #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Wav2Vec2 4 Persian\n> This is part of the\nFlax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.",
"## Team Members... |
null | null | # wav2vec2-base-turkish | {} | flax-community/wav2vec2-base-turkish | null | [
"tensorboard",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#tensorboard #region-us
| # wav2vec2-base-turkish | [
"# wav2vec2-base-turkish"
] | [
"TAGS\n#tensorboard #region-us \n",
"# wav2vec2-base-turkish"
] |
automatic-speech-recognition | transformers |
# Wav2Vec2 Dhivehi
Wav2vec2 pre-pretrained from scratch using common voice dhivehi dataset. The model was trained with Flax during the [Flax/Jax Community Week](https://discss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104) organised by HuggingFace.
## Model description
The mod... | {"language": "dv", "tags": ["automatic-speech-recognition"], "datasets": ["common_voice"]} | flax-community/wav2vec2-dhivehi | null | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"wav2vec2",
"pretraining",
"automatic-speech-recognition",
"dv",
"dataset:common_voice",
"arxiv:2006.11477",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2006.11477"
] | [
"dv"
] | TAGS
#transformers #pytorch #jax #tensorboard #wav2vec2 #pretraining #automatic-speech-recognition #dv #dataset-common_voice #arxiv-2006.11477 #endpoints_compatible #region-us
|
# Wav2Vec2 Dhivehi
Wav2vec2 pre-pretrained from scratch using common voice dhivehi dataset. The model was trained with Flax during the Flax/Jax Community Week organised by HuggingFace.
## Model description
The model used for training is Wav2Vec2 by FacebookAI. It was introduced in the paper
"wav2vec 2.0: A Framewo... | [
"# Wav2Vec2 Dhivehi\n\nWav2vec2 pre-pretrained from scratch using common voice dhivehi dataset. The model was trained with Flax during the Flax/Jax Community Week organised by HuggingFace.",
"## Model description\n\nThe model used for training is Wav2Vec2 by FacebookAI. It was introduced in the paper \n\"wav2vec ... | [
"TAGS\n#transformers #pytorch #jax #tensorboard #wav2vec2 #pretraining #automatic-speech-recognition #dv #dataset-common_voice #arxiv-2006.11477 #endpoints_compatible #region-us \n",
"# Wav2Vec2 Dhivehi\n\nWav2vec2 pre-pretrained from scratch using common voice dhivehi dataset. The model was trained with Flax dur... |
null | transformers |
# Wav2Vec2-german model
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/)
The base model pretrained on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. Note that this model should be fine-tuned on... | {"language": "de", "license": "apache-2.0", "tags": ["speech"], "datasets": ["librispeech_asr"]} | flax-community/wav2vec2-german | null | [
"transformers",
"tensorboard",
"wav2vec2",
"pretraining",
"speech",
"de",
"dataset:librispeech_asr",
"arxiv:2006.11477",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2006.11477"
] | [
"de"
] | TAGS
#transformers #tensorboard #wav2vec2 #pretraining #speech #de #dataset-librispeech_asr #arxiv-2006.11477 #license-apache-2.0 #endpoints_compatible #region-us
|
# Wav2Vec2-german model
Facebook's Wav2Vec2
The base model pretrained on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. Note that this model should be fine-tuned on a downstream task, like Automatic Speech Recognition. Check out this blog for more informat... | [
"# Wav2Vec2-german model\n\nFacebook's Wav2Vec2\n\nThe base model pretrained on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. Note that this model should be fine-tuned on a downstream task, like Automatic Speech Recognition. Check out this blog for more ... | [
"TAGS\n#transformers #tensorboard #wav2vec2 #pretraining #speech #de #dataset-librispeech_asr #arxiv-2006.11477 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# Wav2Vec2-german model\n\nFacebook's Wav2Vec2\n\nThe base model pretrained on 16kHz sampled speech audio. When using the model make sure that ... |
automatic-speech-recognition | transformers |
# Wav2Vec2 Spanish
Wav2Vec2 model pre-trained using the Spanish portion of the Common Voice dataset. The model is trained with Flax and using TPUs sponsored by Google since this is part of the [Flax/Jax Community Week](https://discss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104... | {"language": "es", "tags": ["audio", "automatic-speech-recognition"], "datasets": ["common_voice"]} | flax-community/wav2vec2-spanish | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"pretraining",
"audio",
"automatic-speech-recognition",
"es",
"dataset:common_voice",
"arxiv:2006.11477",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2006.11477"
] | [
"es"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #pretraining #audio #automatic-speech-recognition #es #dataset-common_voice #arxiv-2006.11477 #endpoints_compatible #region-us
|
# Wav2Vec2 Spanish
Wav2Vec2 model pre-trained using the Spanish portion of the Common Voice dataset. The model is trained with Flax and using TPUs sponsored by Google since this is part of the Flax/Jax Community Week organised by HuggingFace.
## Model description
The model used for training is Wav2Vec2 by FacebookA... | [
"# Wav2Vec2 Spanish\n\nWav2Vec2 model pre-trained using the Spanish portion of the Common Voice dataset. The model is trained with Flax and using TPUs sponsored by Google since this is part of the Flax/Jax Community Week organised by HuggingFace.",
"## Model description\n\nThe model used for training is Wav2Vec2 ... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #pretraining #audio #automatic-speech-recognition #es #dataset-common_voice #arxiv-2006.11477 #endpoints_compatible #region-us \n",
"# Wav2Vec2 Spanish\n\nWav2Vec2 model pre-trained using the Spanish portion of the Common Voice dataset. The model is trained with Flax a... |
sentence-similarity | sentence-transformers |
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained [`MiniLM-L12`](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) model and fine-tuned in on a
1B sentence pairs datase... | {"language": "en", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/all_datasets_v3_MiniLM-L12 | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.08727",
"1810.09305",
"2102.07033",
"1904.06472"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us
| Model description
=================
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained 'MiniLM-L12' model and fine-tuned in on a
1B sentence pairs dataset. We use a contrastive learning objective: giv... | [
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch s... |
sentence-similarity | sentence-transformers |
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained ['MiniLM-L6-H384-uncased'](https://huggingface.co/nreimers/MiniLM-L6-H384-uncased) model and fine-tuned in on a
1B sentence pai... | {"language": "en", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/all_datasets_v3_MiniLM-L6 | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.08727",
"1810.09305",
"2102.07033",
"1904.06472"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #has_space #region-us
| Model description
=================
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained 'MiniLM-L6-H384-uncased' model and fine-tuned in on a
1B sentence pairs dataset. We use a contrastive learning ob... | [
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #has_space #region-us \n",
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps usin... |
sentence-similarity | sentence-transformers |
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained [`distilroberta-base`](https://huggingface.co/distilroberta-base) model and fine-tuned in on a
1B sentence pairs dataset. We u... | {"language": "en", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/all_datasets_v3_distilroberta-base | null | [
"sentence-transformers",
"pytorch",
"roberta",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.08727",
"1810.09305",
"2102.07033",
"1904.06472"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #roberta #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us
| Model description
=================
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained 'distilroberta-base' model and fine-tuned in on a
1B sentence pairs dataset. We use a contrastive learning object... | [
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is... | [
"TAGS\n#sentence-transformers #pytorch #roberta #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batc... |
sentence-similarity | sentence-transformers |
# all-mpnet-base-v1
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have [sentence-transformers]... | {"language": "en", "license": "apache-2.0", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/all_datasets_v3_mpnet-base | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:1904.06472",
"arxiv:2102.07033",
"arxiv:2104.08727",
"arxiv:1704.05179",
"arxiv:1810.09305",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1904.06472",
"2102.07033",
"2104.08727",
"1704.05179",
"1810.09305"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #en #arxiv-1904.06472 #arxiv-2102.07033 #arxiv-2104.08727 #arxiv-1704.05179 #arxiv-1810.09305 #license-apache-2.0 #endpoints_compatible #has_space #region-us
| all-mpnet-base-v1
=================
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
Usage (Sentence-Transformers)
-----------------------------
Using this model becomes easy when you have se... | [
"### Pre-training\n\n\nWe use the pretrained 'microsoft/mpnet-base'. Please refer to the model card for more detailed information about the pre-training procedure.",
"### Fine-tuning\n\n\nWe fine-tune the model using a contrastive objective. Formally, we compute the cosine similarity from each possible sentence p... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #en #arxiv-1904.06472 #arxiv-2102.07033 #arxiv-2104.08727 #arxiv-1704.05179 #arxiv-1810.09305 #license-apache-2.0 #endpoints_compatible #has_space #region-us \n",
"### Pre-training\n\n\nWe use the pretrained 'microsoft/mpnet-ba... |
sentence-similarity | sentence-transformers |
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained [`roberta-large`](https://huggingface.co/roberta-large) model and fine-tuned in on a
1B sentence pairs dataset. We use a contr... | {"language": "en", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/all_datasets_v3_roberta-large | null | [
"sentence-transformers",
"pytorch",
"roberta",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.08727",
"1810.09305",
"2102.07033",
"1904.06472"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #roberta #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us
| Model description
=================
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained 'roberta-large' model and fine-tuned in on a
1B sentence pairs dataset. We use a contrastive learning objective: ... | [
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is... | [
"TAGS\n#sentence-transformers #pytorch #roberta #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batc... |
sentence-similarity | sentence-transformers |
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained ['MiniLM-L12'](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) model and fine-tuned in on a
1B sentence pairs dataset... | {"language": "en", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/all_datasets_v4_MiniLM-L12 | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.08727",
"1810.09305",
"2102.07033",
"1904.06472"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us
| Model description
=================
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained 'MiniLM-L12' model and fine-tuned in on a
1B sentence pairs dataset. We use a contrastive learning objective: giv... | [
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch s... |
sentence-similarity | sentence-transformers |
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained ['MiniLM-L6-H384-uncased'](https://huggingface.co/nreimers/MiniLM-L6-H384-uncased) model and fine-tuned in on a
1B sentence pai... | {"language": "en", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/all_datasets_v4_MiniLM-L6 | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.08727",
"1810.09305",
"2102.07033",
"1904.06472"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #has_space #region-us
| Model description
=================
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained 'MiniLM-L6-H384-uncased' model and fine-tuned in on a
1B sentence pairs dataset. We use a contrastive learning ob... | [
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #has_space #region-us \n",
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps usin... |
sentence-similarity | sentence-transformers |
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained ['mpnet-base'](https://huggingface.co/microsoft/mpnet-base) model and fine-tuned in on a
1B sentence pairs dataset. We use a co... | {"language": "en", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/all_datasets_v4_mpnet-base | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.08727",
"1810.09305",
"2102.07033",
"1904.06472"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us
| Model description
=================
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained 'mpnet-base' model and fine-tuned in on a
1B sentence pairs dataset. We use a contrastive learning objective: giv... | [
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #en #arxiv-2104.08727 #arxiv-1810.09305 #arxiv-2102.07033 #arxiv-1904.06472 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained ou model on a TPU v3-8. We train the model during 540k steps using a batch ... |
sentence-similarity | sentence-transformers |
# mpnet_stackexchange_v1
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used a pretrained [mpnet-base](https://hu... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/mpnet_stackexchange_v1 | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"arxiv:2104.08727",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2104.08727 #endpoints_compatible #has_space #region-us
| mpnet\_stackexchange\_v1
========================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We ... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2104.08727 #endpoints_compatible #has_space #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learn... |
sentence-similarity | sentence-transformers | # multi-QA_v1-mpnet-asymmetric-A
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used two separate pretrained [mpne... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/multi-QA_v1-mpnet-asymmetric-A | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"arxiv:2102.07033",
"arxiv:2104.08727",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.07033",
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #has_space #region-us
| multi-QA\_v1-mpnet-asymmetric-A
===============================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and ot... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #has_space #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core... |
sentence-similarity | sentence-transformers | # multi-QA_v1-mpnet-asymmetric-Q
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used two separate pretrained [mpnet-... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/multi-QA_v1-mpnet-asymmetric-Q | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"arxiv:2102.07033",
"arxiv:2104.08727",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.07033",
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #has_space #region-us
| multi-QA\_v1-mpnet-asymmetric-Q
===============================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and ot... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #has_space #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core... |
sentence-similarity | sentence-transformers |
# multi-qa_v1-MiniLM-L6-cls_dot
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used a pretrained [nreimers/MiniLM... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/multi-qa_v1-MiniLM-L6-cls_dot | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"arxiv:2102.07033",
"arxiv:2104.08727",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.07033",
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us
| multi-qa\_v1-MiniLM-L6-cls\_dot
===============================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and ot... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a... |
sentence-similarity | sentence-transformers |
# multi-qa_v1-MiniLM-L6-mean_cos
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used a pretrained [nreimers/MiniL... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/multi-qa_v1-MiniLM-L6-mean_cos | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"arxiv:2102.07033",
"arxiv:2104.08727",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.07033",
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us
| multi-qa\_v1-MiniLM-L6-mean\_cos
================================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and ... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a... |
sentence-similarity | sentence-transformers |
# multi-qa_v1-distilbert-cls_dot
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used a pretrained [distilbert-bas... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/multi-qa_v1-distilbert-cls_dot | null | [
"sentence-transformers",
"pytorch",
"distilbert",
"feature-extraction",
"sentence-similarity",
"arxiv:2102.07033",
"arxiv:2104.08727",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.07033",
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #distilbert #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #has_space #region-us
| multi-qa\_v1-distilbert-cls\_dot
================================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and ... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #distilbert #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #has_space #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU... |
sentence-similarity | sentence-transformers |
# multi-qa_v1-distilbert-mean_cos
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used a pretrained [distilbert-ba... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/multi-qa_v1-distilbert-mean_cos | null | [
"sentence-transformers",
"pytorch",
"distilbert",
"feature-extraction",
"sentence-similarity",
"arxiv:2102.07033",
"arxiv:2104.08727",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.07033",
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #distilbert #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us
| multi-qa\_v1-distilbert-mean\_cos
=================================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search an... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #distilbert #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe... |
sentence-similarity | sentence-transformers |
# multi-qa_v1-mpnet-cls_dot
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used a pretrained [microsoft/mpnet-bas... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/multi-qa_v1-mpnet-cls_dot | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"arxiv:2102.07033",
"arxiv:2104.08727",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.07033",
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us
| multi-qa\_v1-mpnet-cls\_dot
===========================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other task... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use ... |
sentence-similarity | sentence-transformers |
# multi-qa_v1-mpnet-mean_cos
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other tasks. We used a pretrained [microsoft/mpnet-ba... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | flax-sentence-embeddings/multi-qa_v1-mpnet-mean_cos | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"arxiv:2102.07033",
"arxiv:2104.08727",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2102.07033",
"2104.08727"
] | [] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us
| multi-qa\_v1-mpnet-mean\_cos
============================
Model Description
-----------------
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence embeddings can be utilized for Clustering, Semantic Search and other ta... | [
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use a learning rate warm up of 500. The sequence length was limited to 128 tokens. We used the AdamW optimizer with\na 2e-5 learning rate. The full training script is ... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #arxiv-2102.07033 #arxiv-2104.08727 #endpoints_compatible #region-us \n",
"### Hyper parameters\n\n\nWe trained on model on a TPU v3-8. We train the model during 80k steps using a batch size of 1024 (128 per TPU core).\nWe use ... |
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