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albert-base-v1 | null | albert | 8 | 74,071 | transformers | 1 | fill-mask | true | true | false | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['exbert'] | false | true | true | 9,789 |
# ALBERT Base v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not make... |
albert-base-v2 | null | albert | 10 | 3,819,536 | transformers | 38 | fill-mask | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 1 | 1 | 0 | 0 | 1 | 0 | 1 | [] | false | true | true | 9,643 |
# ALBERT Base v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not make... |
albert-large-v1 | null | albert | 9 | 645 | transformers | 0 | fill-mask | true | true | false | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 9,681 |
# ALBERT Large v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not mak... |
albert-large-v2 | null | albert | 8 | 36,311 | transformers | 8 | fill-mask | true | true | false | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 9,682 |
# ALBERT Large v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not mak... |
albert-xlarge-v1 | null | albert | 8 | 222,319 | transformers | 0 | fill-mask | true | true | false | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 9,689 |
# ALBERT XLarge v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not ma... |
albert-xlarge-v2 | null | albert | 8 | 275,390 | transformers | 3 | fill-mask | true | true | false | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 9,690 |
# ALBERT XLarge v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not ma... |
albert-xxlarge-v1 | null | albert | 8 | 4,163 | transformers | 2 | fill-mask | true | true | false | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | [] | false | true | true | 9,698 |
# ALBERT XXLarge v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not m... |
albert-xxlarge-v2 | null | albert | 8 | 64,439 | transformers | 7 | fill-mask | true | true | false | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['exbert'] | false | true | true | 9,849 |
# ALBERT XXLarge v2
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not m... |
bert-base-cased | null | bert | 10 | 6,492,277 | transformers | 73 | fill-mask | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 2 | 0 | 1 | 1 | 0 | 0 | 0 | ['exbert'] | false | true | true | 8,891 |
# BERT base model (cased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is case-sensitive: it makes a difference bet... |
bert-base-chinese | null | bert | 10 | 1,938,936 | transformers | 211 | fill-mask | true | true | true | null | ['zh'] | null | null | 4 | 1 | 2 | 1 | 3 | 2 | 1 | [] | false | true | true | 1,753 |
# Bert-base-chinese
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [How to Get Started With the Model](#how-to-get-started-with-the-model)
# Model Details
- **Model Descript... |
bert-base-german-cased | null | bert | 9 | 452,070 | transformers | 28 | fill-mask | true | true | true | mit | ['de'] | null | null | 2 | 1 | 0 | 1 | 0 | 0 | 0 | ['exbert'] | false | true | true | 4,053 |
<a href="https://huggingface.co/exbert/?model=bert-base-german-cased">
<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
</a>
# German BERT
## Overview
**Language model:** bert-base-cased
**L... |
bert-base-german-dbmdz-cased | null | bert | 8 | 979 | transformers | 0 | fill-mask | true | false | true | mit | ['de'] | null | null | 1 | 0 | 1 | 0 | 1 | 1 | 0 | [] | false | true | true | 240 |
This model is the same as [dbmdz/bert-base-german-cased](https://huggingface.co/dbmdz/bert-base-german-cased). See the [dbmdz/bert-base-german-cased model card](https://huggingface.co/dbmdz/bert-base-german-cased) for details on the model. |
bert-base-german-dbmdz-uncased | null | bert | 8 | 10,564 | transformers | 2 | fill-mask | true | false | true | mit | ['de'] | null | null | 1 | 0 | 1 | 0 | 1 | 1 | 0 | [] | false | true | true | 247 |
This model is the same as [dbmdz/bert-base-german-uncased](https://huggingface.co/dbmdz/bert-base-german-uncased). See the [dbmdz/bert-base-german-cased model card](https://huggingface.co/dbmdz/bert-base-german-uncased) for details on the model.
|
bert-base-multilingual-cased | null | bert | 10 | 2,628,611 | transformers | 87 | fill-mask | true | true | true | apache-2.0 | ['multilingual', 'af', 'sq', 'ar', 'an', 'hy', 'ast', 'az', 'ba', 'eu', 'bar', 'be', 'bn', 'inc', 'bs', 'br', 'bg', 'my', 'ca', 'ceb', 'ce', 'zh', 'cv', 'hr', 'cs', 'da', 'nl', 'en', 'et', 'fi', 'fr', 'gl', 'ka', 'de', 'el', 'gu', 'ht', 'he', 'hi', 'hu', 'is', 'io', 'id', 'ga', 'it', 'ja', 'jv', 'kn', 'kk', 'ky', 'ko',... | ['wikipedia'] | null | 2 | 0 | 2 | 0 | 1 | 1 | 0 | [] | false | true | true | 6,498 |
# BERT multilingual base model (cased)
Pretrained model on the top 104 languages with the largest Wikipedia using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model... |
bert-base-multilingual-uncased | null | bert | 9 | 577,315 | transformers | 30 | fill-mask | true | true | true | apache-2.0 | ['multilingual', 'af', 'sq', 'ar', 'an', 'hy', 'ast', 'az', 'ba', 'eu', 'bar', 'be', 'bn', 'inc', 'bs', 'br', 'bg', 'my', 'ca', 'ceb', 'ce', 'zh', 'cv', 'hr', 'cs', 'da', 'nl', 'en', 'et', 'fi', 'fr', 'gl', 'ka', 'de', 'el', 'gu', 'ht', 'he', 'hi', 'hu', 'is', 'io', 'id', 'ga', 'it', 'ja', 'jv', 'kn', 'kk', 'ky', 'ko',... | ['wikipedia'] | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | [] | false | true | true | 8,334 |
# BERT multilingual base model (uncased)
Pretrained model on the top 102 languages with the largest Wikipedia using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This mod... |
bert-base-uncased | null | bert | 12 | 33,665,287 | transformers | 499 | fill-mask | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 10 | 0 | 5 | 5 | 11 | 11 | 0 | ['exbert'] | false | true | true | 10,426 |
# BERT base model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is uncased: it does not make a difference
... |
bert-large-cased-whole-word-masking-finetuned-squad | null | bert | 11 | 60,887 | transformers | 0 | question-answering | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 6,043 |
# BERT large model (cased) whole word masking finetuned on SQuAD
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is ca... |
bert-large-cased-whole-word-masking | null | bert | 9 | 1,884 | transformers | 2 | fill-mask | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 9,603 |
# BERT large model (cased) whole word masking
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is cased: it makes a dif... |
bert-large-cased | null | bert | 10 | 160,722 | transformers | 4 | fill-mask | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 9,138 |
# BERT large model (cased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is cased: it makes a difference
between eng... |
bert-large-uncased-whole-word-masking-finetuned-squad | null | bert | 10 | 1,097,869 | transformers | 59 | question-answering | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 6,164 |
# BERT large model (uncased) whole word masking finetuned on SQuAD
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is ... |
bert-large-uncased-whole-word-masking | null | bert | 9 | 65,422 | transformers | 4 | fill-mask | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 9,687 |
# BERT large model (uncased) whole word masking
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is uncased: it does no... |
bert-large-uncased | null | bert | 11 | 1,151,242 | transformers | 17 | fill-mask | true | true | true | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | [] | false | true | true | 8,885 |
# BERT large model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/bert). This model is uncased: it does not make a difference... |
camembert-base | null | camembert | 7 | 908,145 | transformers | 26 | fill-mask | true | true | false | mit | ['fr'] | ['oscar'] | null | 1 | 0 | 1 | 0 | 1 | 1 | 0 | [] | false | true | true | 6,917 |
# CamemBERT: a Tasty French Language Model
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Citation Information](#citation-information)
- [How to Get Started With the Model](#... |
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