modelId stringlengths 4 81 | tags sequence | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k | embedding sequence |
|---|---|---|---|---|---|---|---|
albert-base-v1 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
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},
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"no_repeat_ngram_... | 38,156 | 2019-12-20T12:28:51 | ---
tags:
- exbert
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# 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... | [
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albert-base-v2 | [
"pytorch",
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"jax",
"rust",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
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"no_repeat_ngram_... | 4,785,283 | 2019-11-04T16:00:52 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# 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-rese... | [
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albert-large-v1 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
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"no_repeat_ngram_... | 687 | 2019-12-20T12:28:51 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# 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-res... | [
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albert-large-v2 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
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"task_specific_params": {
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},
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"no_repeat_ngram_... | 26,792 | 2019-11-04T16:00:53 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# 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-res... | [
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albert-xlarge-v1 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
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},
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"no_repeat_ngram_... | 341 | 2019-12-20T12:28:51 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# 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-re... | [
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albert-xlarge-v2 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 2,973 | 2019-11-04T16:00:53 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# 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-re... | [
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... |
albert-xxlarge-v1 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 7,091 | 2019-12-20T12:28:51 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# 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-r... | [
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albert-xxlarge-v2 | ["pytorch","tf","safetensors","albert","fill-mask","en","dataset:bookcorpus","dataset:wikipedia","ar(...TRUNCATED) | fill-mask | {"architectures":["AlbertForMaskedLM"],"model_type":"albert","task_specific_params":{"conversational(...TRUNCATED) | 42,640 | 2019-11-04T16:00:52 | "---\ntags:\n- exbert\nlanguage: en\nlicense: apache-2.0\ndatasets:\n- bookcorpus\n- wikipedia\n---\(...TRUNCATED) | [-0.019903937354683876,0.008878600783646107,-0.02040528692305088,0.06702258437871933,0.0376590751111(...TRUNCATED) |
bert-base-cased | ["pytorch","tf","jax","safetensors","bert","fill-mask","en","dataset:bookcorpus","dataset:wikipedia"(...TRUNCATED) | fill-mask | {"architectures":["BertForMaskedLM"],"model_type":"bert","task_specific_params":{"conversational":{"(...TRUNCATED) | 8,621,271 | 2018-11-14T23:35:08 | "---\nlanguage: en\ntags:\n- exbert\nlicense: apache-2.0\ndatasets:\n- bookcorpus\n- wikipedia\n---\(...TRUNCATED) | [-0.005537884775549173,0.0068740639835596085,-0.01787860319018364,0.06503400951623917,0.026847530156(...TRUNCATED) |
bert-base-chinese | ["pytorch","tf","jax","safetensors","bert","fill-mask","zh","arxiv:1810.04805","transformers","autot(...TRUNCATED) | fill-mask | {"architectures":["BertForMaskedLM"],"model_type":"bert","task_specific_params":{"conversational":{"(...TRUNCATED) | 3,377,486 | 2018-11-14T23:35:08 | "---\nlanguage: zh\n---\n\n# Bert-base-chinese\n\n## Table of Contents\n- [Model Details](#model-det(...TRUNCATED) | [-0.027363037690520287,-0.012506258673965931,-0.0041877892799675465,0.06901980191469193,0.0159092675(...TRUNCATED) |
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