modelId stringlengths 4 62 | sha null | lastModified null | pipeline_tag stringclasses 9
values | author null | securityStatus null | likes int64 0 1.03k | downloads int64 0 62.4M | dataset sequence | arxiv sequence | license sequence | tags sequence | doi sequence | card stringlengths 0 14k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
albert-base-v1 | null | null | fill-mask | null | null | 1 | 41,336 | [
"bookcorpus",
"wikipedia"
] | [
"1909.11942"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"transformers",
"exbert",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 50 | 4,543,047 | [
"bookcorpus",
"wikipedia"
] | [
"1909.11942"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"albert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 0 | 651 | [
"bookcorpus",
"wikipedia"
] | [
"1909.11942"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 11 | 12,476 | [
"bookcorpus",
"wikipedia"
] | [
"1909.11942"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 0 | 385 | [
"bookcorpus",
"wikipedia"
] | [
"1909.11942"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 3 | 3,124 | [
"bookcorpus",
"wikipedia"
] | [
"1909.11942"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 2 | 8,119 | [
"bookcorpus",
"wikipedia"
] | [
"1909.11942"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 9 | 40,731 | [
"bookcorpus",
"wikipedia"
] | [
"1909.11942"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"transformers",
"exbert",
"autotrain_compatible",
"has_space"
] | null |
# 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-finetuned-mrpc | null | null | fill-mask | null | null | 0 | 9,686 | null | null | null | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | null | |
bert-base-cased | null | null | fill-mask | null | null | 104 | 7,716,025 | [
"bookcorpus",
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"transformers",
"exbert",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 358 | 2,273,140 | null | [
"1810.04805"
] | null | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"zh",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 Descri... |
bert-base-german-cased | null | null | fill-mask | null | null | 31 | 112,445 | null | null | [
"mit"
] | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"de",
"transformers",
"exbert",
"autotrain_compatible",
"has_space"
] | null |
<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 | null | fill-mask | null | null | 0 | 2,071 | null | null | [
"mit"
] | [
"pytorch",
"jax",
"bert",
"fill-mask",
"de",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
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 | null | fill-mask | null | null | 2 | 50,194 | null | null | [
"mit"
] | [
"pytorch",
"jax",
"safetensors",
"bert",
"fill-mask",
"de",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
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 | null | fill-mask | null | null | 157 | 5,672,763 | [
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"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",
... | null |
# 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 | null | fill-mask | null | null | 38 | 257,915 | [
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"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",
... | null |
# 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 | null | fill-mask | null | null | 839 | 62,377,709 | [
"bookcorpus",
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"bert",
"fill-mask",
"en",
"transformers",
"exbert",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | question-answering | null | null | 0 | 11,494 | [
"bookcorpus",
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"bert",
"question-answering",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 3 | 3,774 | [
"bookcorpus",
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 7 | 342,338 | [
"bookcorpus",
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | question-answering | null | null | 85 | 519,563 | [
"bookcorpus",
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"question-answering",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 6 | 61,415 | [
"bookcorpus",
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 26 | 1,076,096 | [
"bookcorpus",
"wikipedia"
] | [
"1810.04805"
] | [
"apache-2.0"
] | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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 | null | fill-mask | null | null | 36 | 1,247,645 | [
"oscar"
] | [
"1911.03894"
] | [
"mit"
] | [
"pytorch",
"tf",
"safetensors",
"camembert",
"fill-mask",
"fr",
"transformers",
"autotrain_compatible",
"has_space"
] | null |
# 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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