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621ffdc036468d709f174355 | google-t5/t5-3b | google-t5 | null | 533,672 | 18,445,256 | False | 2022-03-02T23:29:04Z | 2024-01-29T15:44:49Z | transformers | 52 | 0 | null | translation | {"parameters": {"F32": 2851599360}, "total": 2851599360} | [
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# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bi... | null | [
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621ffdc036468d709f174356 | google-t5/t5-base | google-t5 | null | 1,828,271 | 158,702,634 | False | 2022-03-02T23:29:04Z | 2024-02-14T17:21:55Z | transformers | 770 | 0 | null | translation | null | [
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# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [... | null | [
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621ffdc036468d709f174365 | FacebookAI/xlm-roberta-large-finetuned-conll02-dutch | FacebookAI | null | 874 | 66,167 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:48:36Z | transformers | 5 | 0 | null | fill-mask | null | [
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"... | null | {"architectures": ["XLMRobertaForMaskedLM"], "model_type": "xlm-roberta", "tokenizer_config": {}} | {
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# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training](#training)
5. [Evaluation](#evaluation)
6. [Environmental Impact](#environmental-impact)
7. [Technical Specifications](#tech... | null | null | null | [
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621ffdc036468d709f174366 | FacebookAI/xlm-roberta-large-finetuned-conll02-spanish | FacebookAI | null | 102 | 17,797 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:48:44Z | transformers | 2 | 0 | null | fill-mask | {"parameters": {"F32": 559899657}, "total": 559899657} | [
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... | null | {"architectures": ["XLMRobertaForMaskedLM"], "model_type": "xlm-roberta", "tokenizer_config": {}} | {
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# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training](#training)
5. [Evaluation](#evaluation)
6. [Environmental Impact](#environmental-impact)
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621ffdc036468d709f174367 | FacebookAI/xlm-roberta-large-finetuned-conll03-english | FacebookAI | null | 88,231 | 51,181,739 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:48:53Z | transformers | 183 | 0 | null | token-classification | {"parameters": {"F32": 559898632}, "total": 559898632} | [
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"pipeline_tag": "token-classification",
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# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training](#training)
5. [Evaluation](#evaluation)
6. [Environmental Impact](#environmental-impact)
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621ffdc036468d709f174368 | FacebookAI/xlm-roberta-large-finetuned-conll03-german | FacebookAI | null | 8,361 | 860,975 | False | 2022-03-02T23:29:04Z | 2024-02-19T12:49:00Z | transformers | 14 | 0 | null | token-classification | null | [
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# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training](#training)
5. [Evaluation](#evaluation)
6. [Environmental Impact](#environmental-impact)
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621ffdc036468d709f17436a | xlnet/xlnet-base-cased | xlnet | null | 527,654 | 21,059,561 | False | 2022-03-02T23:29:04Z | 2023-01-24T14:50:31Z | transformers | 81 | 0 | null | text-generation | null | [
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XLNet model pre-trained on English language. It was introduced in the paper [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://arxiv.org/abs/1906.08237) by Yang et al. and first released in [this repository](https://github.com/zihangdai/xlnet/).
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621ffdc036468d709f17436b | xlnet/xlnet-large-cased | xlnet | null | 2,219 | 3,465,489 | False | 2022-03-02T23:29:04Z | 2023-01-24T14:50:34Z | transformers | 24 | 0 | null | text-generation | null | [
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XLNet model pre-trained on English language. It was introduced in the paper [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://arxiv.org/abs/1906.08237) by Yang et al. and first released in [this repository](https://github.com/zihangdai/xlnet/).
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} | {"datasets": ["glue"], "license": "apache-2.0", "metrics": ["matthews_correlation"], "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "ar... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | null | [
"apache-2.0"
] | [
"glue"
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621ffdc036468d709f174375 | 0xDEADBEA7/DialoGPT-small-rick | 0xDEADBEA7 | null | 11 | 6,192 | False | 2022-03-02T23:29:04Z | 2022-02-22T05:30:23Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f174387 | 123abhiALFLKFO/distilbert-base-uncased-finetuned-cola | 123abhiALFLKFO | null | 22 | 1,720 | False | 2022-03-02T23:29:04Z | 2021-08-05T08:57:03Z | transformers | 0 | 0 | null | text-classification | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | null | [
"apache-2.0"
] | [
"glue"
] | null | null | null | [
"matthews_correlation"
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"text-classification"
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"text"
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"text"
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"logits"
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621ffdc036468d709f17438f | 13on/gpt2-wishes | 13on | null | 15 | 1,346 | False | 2022-03-02T23:29:04Z | 2022-02-17T16:06:44Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f174390 | 13on/kw2t-wishes | 13on | null | 2 | 1,326 | False | 2022-03-02T23:29:04Z | 2022-02-28T09:46:28Z | transformers | 0 | 0 | null | null | null | [
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621ffdc036468d709f17439c | 1Basco/DialoGPT-small-jake | 1Basco | null | 13 | 1,703 | False | 2022-03-02T23:29:04Z | 2021-09-22T03:32:39Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f1743a3 | 2early4coffee/DialoGPT-medium-deadpool | 2early4coffee | null | 11 | 5,506 | False | 2022-03-02T23:29:04Z | 2021-10-30T20:46:16Z | transformers | 1 | 0 | null | text-generation | null | [
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621ffdc036468d709f1743a4 | 2early4coffee/DialoGPT-small-deadpool | 2early4coffee | null | 12 | 1,347 | False | 2022-03-02T23:29:04Z | 2021-10-28T17:14:26Z | transformers | 0 | 0 | null | text-generation | null | [
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"text-generation-inference",
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
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621ffdc036468d709f1743a7 | 2umm3r/distilbert-base-uncased-finetuned-cola | 2umm3r | null | 9 | 1,552 | False | 2022-03-02T23:29:04Z | 2021-10-23T11:46:51Z | transformers | 0 | 0 | [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "glue", "type": "glue", "args": "cola"}, "metrics": [{"name": "Matthews Correlation", "type": "matthews_correlation", "value": 0.5155709926752544, "verified": fals... | text-classification | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | null | [
"apache-2.0"
] | [
"glue"
] | null | null | null | [
"matthews_correlation"
] | [
"DistilBertForSequenceClassification",
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"AutoModelForSequenceClassification"
] | [
"text-classification"
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621ffdc036468d709f1743d1 | 9pinus/macbert-base-chinese-medical-collation | 9pinus | null | 12 | 2,939 | False | 2022-03-02T23:29:04Z | 2022-02-25T10:26:38Z | transformers | 11 | 0 | null | token-classification | null | [
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] | 6cddc419b86a546bfab115dd05a3782a43beb1e0 | [
"transformers",
"pytorch",
"bert",
"token-classification",
"Token Classification",
"zh",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": "zh", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["Token Classification"]} | ## Model description
This model is a fine-tuned version of macbert for the purpose of spell checking in medical application scenarios. We fine-tuned macbert Chinese base version on a 300M dataset including 60K+ authorized medical articles. We proposed to randomly confuse 30% sentences of these articles by adding noi... | null | [
"apache-2.0"
] | null | [
"zh"
] | null | null | [
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] | [
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621ffdc036468d709f1743d2 | 9pinus/macbert-base-chinese-medicine-recognition | 9pinus | null | 12 | 2,141 | False | 2022-03-02T23:29:04Z | 2022-03-02T09:20:41Z | transformers | 5 | 0 | null | token-classification | null | [
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"vocab.txt"
] | 3a20f1d5d353ee11ce93f9ca885b3d7d859eb33e | [
"transformers",
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"bert",
"token-classification",
"Token Classification",
"zh",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["zh"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["Token Classification"]} | ## Model description
This model is a fine-tuned version of bert-base-chinese for the purpose of medicine name recognition. We fine-tuned bert-base-chinese on a 500M dataset including 100K+ authorized medical articles on which we labeled all the medicine names. The model achieves 92% accuracy on our test dataset.
##... | null | [
"apache-2.0"
] | null | [
"zh"
] | null | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
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621ffdc036468d709f1743e2 | ABBHISHEK/DialoGPT-small-harrypotter | ABBHISHEK | null | 8 | 1,543 | False | 2022-03-02T23:29:04Z | 2021-09-19T10:23:22Z | transformers | 0 | 0 | null | text-generation | null | [
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"pytorch_model.bin",
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"tokenizer_config.json",
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] | 55264c63ce90e4221506aff8f18075fa821416eb | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
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621ffdc036468d709f1743f1 | AI-Nordics/bert-large-swedish-cased | AI-Nordics | null | 32 | 9,744 | False | 2022-03-02T23:29:04Z | 2022-02-15T16:52:53Z | transformers | 11 | 0 | null | fill-mask | null | [
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"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
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] | b7925d4c25c2ec8ebc0e73493c18180e5875d34e | [
"transformers",
"pytorch",
"megatron-bert",
"fill-mask",
"sv",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MegatronBertForMaskedLM"], "model_type": "megatron-bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "sv", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # A Swedish Bert model
## Model description
This model follows the Bert Large model architecture as implemented in [Megatron-LM framework](https://github.com/NVIDIA/Megatron-LM). It was trained with a batch size of 512 in 600k steps. The model contains following parameters:
<figure>
| Hyperparameter | Value ... | null | null | null | [
"sv"
] | null | null | null | [
"MegatronBertForMaskedLM",
"megatron-bert",
"AutoModelForMaskedLM"
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] | [
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] | [
"logits"
] |
621ffdc036468d709f1743f6 | AI4Sec/cyner-xlm-roberta-base | AI4Sec | null | 14 | 3,584 | False | 2022-03-02T23:29:04Z | 2022-02-22T16:23:17Z | transformers | 0 | 0 | null | token-classification | null | [
".gitattributes",
"README.md",
"config.json",
"parameter.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"tokenizer.json",
"tokenizer_config.json"
] | 1e400729cac0561170f8f441d35791768b661201 | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaForTokenClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": fals... | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | null | null | [
"mit"
] | null | null | null | null | null | [
"XLMRobertaForTokenClassification",
"AutoModelForTokenClassification",
"xlm-roberta"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1743f9 | AIDA-UPM/MSTSb_paraphrase-multilingual-MiniLM-L12-v2 | AIDA-UPM | null | 3 | 1,037 | False | 2022-03-02T23:29:04Z | 2021-07-21T18:02:53Z | sentence-transformers | 0 | 0 | null | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"eval/similarity_evaluation_sts-dev_results.csv",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
... | 28fc8ed60064fd7984e0feebafec601426ce14cc | [
"sentence-transformers",
"pytorch",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | null | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "tr... | # {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when y... | null | null | null | null | null | null | null | [
"AutoModel"
] | [
null,
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f1743fa | AIDA-UPM/MSTSb_paraphrase-xlm-r-multilingual-v1 | AIDA-UPM | null | 9 | 1,466 | False | 2022-03-02T23:29:04Z | 2021-11-07T08:25:22Z | sentence-transformers | 1 | 0 | null | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"eval/.ipynb_checkpoints/similarity_evaluation_sts-dev_results-checkpoint.csv",
"eval/similarity_evaluation_sts-dev_results.csv",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.j... | fc4842f09face5ffc4fca4fa56f2651991023b1e | [
"sentence-transformers",
"pytorch",
"xlm-roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaModel"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": ... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "tr... | # AIDA-UPM/MSTSb_paraphrase-xlm-r-multilingual-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.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
U... | null | null | null | null | null | null | null | [
"XLMRobertaModel",
"AutoModel",
"xlm-roberta"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f1743fb | AIDA-UPM/MSTSb_stsb-xlm-r-multilingual | AIDA-UPM | null | 10 | 3,051 | False | 2022-03-02T23:29:04Z | 2021-07-21T18:32:31Z | sentence-transformers | 1 | 0 | null | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"eval/.ipynb_checkpoints/similarity_evaluation_sts-dev_results-checkpoint.csv",
"eval/similarity_evaluation_sts-dev_results.csv",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.j... | eea01579b009257faffea3516c0da1f89f2d99ba | [
"sentence-transformers",
"pytorch",
"xlm-roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaModel"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": ... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "tr... | # {MODEL_NAME}
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.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when y... | null | null | null | null | null | null | null | [
"XLMRobertaModel",
"AutoModel",
"xlm-roberta"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f1743fd | AIDA-UPM/mstsb-paraphrase-multilingual-mpnet-base-v2 | AIDA-UPM | null | 1,491 | 292,953 | False | 2022-03-02T23:29:04Z | 2021-07-13T14:12:45Z | transformers | 12 | 0 | null | sentence-similarity | null | [
".gitattributes",
"1_Pooling/config.json",
"README.md",
"config.json",
"config_sentence_transformers.json",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 7c1614a46aa544de7d3bfecf05de0734cc72d0ed | [
"transformers",
"pytorch",
"xlm-roberta",
"feature-extraction",
"sentence-similarity",
"multilingual",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaModel"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": ... | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "multilingual", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "sentence-similarity", "tags": ["feature-extraction", "sentence-similarity", "transformers", "m... | # mstsb-paraphrase-multilingual-mpnet-base-v2
This is a fine-tuned version of `paraphrase-multilingual-mpnet-base-v2` from [sentence-transformers](https://www.SBERT.net) model with [Semantic Textual Similarity Benchmark](http://ixa2.si.ehu.eus/stswiki/index.php/Main_Page) extended to 15 languages: It maps sentences & ... | null | null | null | [
"multilingual"
] | null | null | null | [
"XLMRobertaModel",
"AutoModel",
"xlm-roberta"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f1743ff | AIDynamics/DialoGPT-medium-MentorDealerGuy | AIDynamics | null | 9 | 1,056 | False | 2022-03-02T23:29:04Z | 2021-11-17T22:23:49Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | e9b9b778eb51765576c4cc022be27bd052ff3c30 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174400 | AJ/DialoGPT-small-ricksanchez | AJ | null | 10 | 1,340 | False | 2022-03-02T23:29:04Z | 2021-09-27T00:10:49Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 7b8045b6dfdccf9a10bcc70229a18acde13f91ff | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174403 | AJ/rick-discord-bot | AJ | null | 7 | 6,256 | False | 2022-03-02T23:29:04Z | 2021-09-27T01:03:33Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 31fec11b7ffa06a6398c78e5bf0a452efd2e8746 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"humor",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational", "humor"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174405 | AJ-Dude/DialoGPT-small-harrypotter | AJ-Dude | null | 7 | 4,687 | False | 2022-03-02T23:29:04Z | 2021-10-22T08:26:19Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 4eeb993a4c143906c2510c93b417cd7af752095f | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174417 | AK270802/DialoGPT-small-harrypotter | AK270802 | null | 9 | 21,152 | False | 2022-03-02T23:29:04Z | 2022-01-16T11:19:05Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 5e5434fd66c852ebf69cc07279d85f55a645768e | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174437 | ARTeLab/it5-summarization-fanpage-64 | ARTeLab | null | 11 | 249 | False | 2022-03-02T23:29:04Z | 2021-10-25T12:47:09Z | transformers | 1 | 0 | [{"name": "summarization_fanpage", "results": []}] | summarization | null | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"generated_predictions.txt",
"predict_results.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"train_results.json",
"trainer_state.json",
"training_args.... | a77dfd5184efc188df5327f5302e502a5024934d | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"summarization",
"it",
"dataset:ARTeLab/fanpage",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["ARTeLab/fanpage"], "eval_results": [], "language": ["it"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": "summarization_fanpage", "pipeline_tag": null, "tags": ["summarization"]} | null | null | null | [
"ARTeLab/fanpage"
] | [
"it"
] | null | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174438 | ARTeLab/it5-summarization-fanpage | ARTeLab | {
"models": [
{
"_id": "621ffdc136468d709f17b862",
"id": "gsarti/it5-base"
}
],
"relation": "finetune"
} | 1,516 | 5,967 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:43:22Z | transformers | 2 | 0 | [{"name": "summarization_fanpage128", "results": []}] | summarization | {"parameters": {"F32": 247539456}, "total": 247539456} | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"generated_predictions.txt",
"model.safetensors",
"predict_results.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"train_results.json",
"trainer_state.j... | 00817af3dfc268b8fac86a047ed0e7546439c468 | [
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"summarization",
"it",
"dataset:ARTeLab/fanpage",
"base_model:gsarti/it5-base",
"base_model:finetune:gsarti/it5-base",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "gsarti/it5-base", "datasets": ["ARTeLab/fanpage"], "eval_results": [], "language": ["it"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": "summarization_fanpage128", "pipeline_tag": null, "tags": ["summarization"]} | # summarization_fanpage128
This model is a fine-tuned version of [gsarti/it5-base](https://huggingface.co/gsarti/it5-base) on Fanpage dataset for Abstractive Summarization.
It achieves the following results:
- Loss: 1.5348
- Rouge1: 34.1882
- Rouge2: 15.7866
- Rougel: 25.141
- Rougelsum: 28.4882
- Gen Len: 69.3041
#... | null | null | [
"ARTeLab/fanpage"
] | [
"it"
] | 247,539,456 | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174439 | ARTeLab/it5-summarization-ilpost | ARTeLab | {
"models": [
{
"_id": "621ffdc136468d709f17b862",
"id": "gsarti/it5-base"
}
],
"relation": "finetune"
} | 78 | 2,385 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:43:14Z | transformers | 0 | 0 | [{"name": "summarization_ilpost", "results": []}] | summarization | {"parameters": {"F32": 247539456}, "total": 247539456} | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"events.out.tfevents.1633958968.meterreader.12204.0.v2",
"events.out.tfevents.1633959348.meterreader.15458.0.v2",
"events.out.tfevents.1633959595.meterreader.18291.0.v2",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map... | 1d02f91e730e526252c2070101c6afd9a596f56a | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"summarization",
"it",
"dataset:ARTeLab/ilpost",
"base_model:gsarti/it5-base",
"base_model:finetune:gsarti/it5-base",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "gsarti/it5-base", "datasets": ["ARTeLab/ilpost"], "eval_results": [], "language": ["it"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": "summarization_ilpost", "pipeline_tag": null, "tags": ["summarization"]} | # summarization_ilpost
This model is a fine-tuned version of [gsarti/it5-base](https://huggingface.co/gsarti/it5-base) on IlPost dataset for Abstractive Summarization.
It achieves the following results:
- Loss: 1.6020
- Rouge1: 33.7802
- Rouge2: 16.2953
- Rougel: 27.4797
- Rougelsum: 30.2273
- Gen Len: 45.3175
## Us... | null | null | [
"ARTeLab/ilpost"
] | [
"it"
] | 247,539,456 | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17443a | ARTeLab/it5-summarization-mlsum | ARTeLab | {
"models": [
{
"_id": "621ffdc136468d709f17b862",
"id": "gsarti/it5-base"
}
],
"relation": "finetune"
} | 43 | 2,442 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:43:07Z | transformers | 0 | 0 | [{"name": "summarization_mlsum", "results": []}] | summarization | {"parameters": {"F32": 247539456}, "total": 247539456} | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"generated_predictions.txt",
"model.safetensors",
"predict_results.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"train_results.json",
"trainer_state.j... | f0c0674041ff37b73bce8870a157e04d51356c04 | [
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"summarization",
"it",
"dataset:ARTeLab/mlsum-it",
"base_model:gsarti/it5-base",
"base_model:finetune:gsarti/it5-base",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "gsarti/it5-base", "datasets": ["ARTeLab/mlsum-it"], "eval_results": [], "language": ["it"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": "summarization_mlsum", "pipeline_tag": null, "tags": ["summarization"]} | # summarization_mlsum
This model is a fine-tuned version of [gsarti/it5-base](https://huggingface.co/gsarti/it5-base) on MLSum-it for Abstractive Summarization.
It achieves the following results:
- Loss: 2.0190
- Rouge1: 19.3739
- Rouge2: 5.9753
- Rougel: 16.691
- Rougelsum: 16.7862
- Gen Len: 32.5268
## Usage
```p... | null | null | [
"ARTeLab/mlsum-it"
] | [
"it"
] | 247,539,456 | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17443c | ARTeLab/mbart-summarization-fanpage | ARTeLab | {
"models": [
{
"_id": "621ffdc136468d709f17ae06",
"id": "facebook/mbart-large-cc25"
}
],
"relation": "finetune"
} | 12 | 3,333 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:43:38Z | transformers | 0 | 0 | [{"name": "summarization_mbart_fanpage4epoch", "results": []}] | summarization | {"parameters": {"F32": 611101867}, "total": 611101867} | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"generated_predictions.txt",
"model.safetensors",
"predict_results.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"train_resu... | dccbc6609cf7e3085ac46e668c99a2244dc855e4 | [
"transformers",
"pytorch",
"safetensors",
"mbart",
"text2text-generation",
"summarization",
"it",
"dataset:ARTeLab/fanpage",
"base_model:facebook/mbart-large-cc25",
"base_model:finetune:facebook/mbart-large-cc25",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MBartForConditionalGeneration"], "model_type": "mbart", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "norma... | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "facebook/mbart-large-cc25", "datasets": ["ARTeLab/fanpage"], "eval_results": [], "language": ["it"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": "summarization_mbart_fanpage4epoch", "pipeline_tag": null, "tags": ["summarization"]... | # mbart-summarization-fanpage
This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on Fanpage dataset for Abstractive Summarization.
It achieves the following results:
- Loss: 2.1833
- Rouge1: 36.5027
- Rouge2: 17.4428
- Rougel: 26.1734
- Rougelsum: 30.26... | null | null | [
"ARTeLab/fanpage"
] | [
"it"
] | 611,101,867 | null | [
"rouge"
] | [
"AutoModelForSeq2SeqLM",
"MBartForConditionalGeneration",
"mbart"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17443d | ARTeLab/mbart-summarization-ilpost | ARTeLab | {
"models": [
{
"_id": "621ffdc136468d709f17ae06",
"id": "facebook/mbart-large-cc25"
}
],
"relation": "finetune"
} | 10 | 3,030 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:42:56Z | transformers | 0 | 0 | [{"name": "summarization_mbart_ilpost", "results": []}] | summarization | {"parameters": {"F32": 611101867}, "total": 611101867} | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"generated_predictions.txt",
"model.safetensors",
"predict_results.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"train_resu... | 83be7fb6c5d6f697d45d32bd370c315832de7012 | [
"transformers",
"pytorch",
"safetensors",
"mbart",
"text2text-generation",
"summarization",
"it",
"dataset:ARTeLab/ilpost",
"base_model:facebook/mbart-large-cc25",
"base_model:finetune:facebook/mbart-large-cc25",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MBartForConditionalGeneration"], "model_type": "mbart", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "norma... | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "facebook/mbart-large-cc25", "datasets": ["ARTeLab/ilpost"], "eval_results": [], "language": ["it"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": "summarization_mbart_ilpost", "pipeline_tag": null, "tags": ["summarization"]} | # mbart_summarization_ilpost
This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on IlPost dataset for Abstractive Summarization.
It achieves the following results:
- Loss: 2.3640
- Rouge1: 38.9101
- Rouge2: 21.384
- Rougel: 32.0517
- Rougelsum: 35.0743
... | null | null | [
"ARTeLab/ilpost"
] | [
"it"
] | 611,101,867 | null | [
"rouge"
] | [
"AutoModelForSeq2SeqLM",
"MBartForConditionalGeneration",
"mbart"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17443e | ARTeLab/mbart-summarization-mlsum | ARTeLab | {
"models": [
{
"_id": "621ffdc136468d709f17ae06",
"id": "facebook/mbart-large-cc25"
}
],
"relation": "finetune"
} | 16 | 6,123 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:43:29Z | transformers | 2 | 0 | [{"name": "summarization_mbart_mlsum", "results": []}] | summarization | {"parameters": {"F32": 611101867}, "total": 611101867} | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"generated_predictions.txt",
"model.safetensors",
"predict_results.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"train_resu... | 81dc940d047ece62a3084f252c4ef4145da8d647 | [
"transformers",
"pytorch",
"safetensors",
"mbart",
"text2text-generation",
"summarization",
"it",
"dataset:ARTeLab/mlsum-it",
"base_model:facebook/mbart-large-cc25",
"base_model:finetune:facebook/mbart-large-cc25",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MBartForConditionalGeneration"], "model_type": "mbart", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "norma... | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": "facebook/mbart-large-cc25", "datasets": ["ARTeLab/mlsum-it"], "eval_results": [], "language": ["it"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": "summarization_mbart_mlsum", "pipeline_tag": null, "tags": ["summarization"]} | # mbart_summarization_mlsum
This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on mlsum-it for Abstractive Summarization.
It achieves the following results:
- Loss: 3.3336
- Rouge1: 19.3489
- Rouge2: 6.4028
- Rougel: 16.3497
- Rougelsum: 16.5387
- Gen L... | null | null | [
"ARTeLab/mlsum-it"
] | [
"it"
] | 611,101,867 | null | [
"rouge"
] | [
"AutoModelForSeq2SeqLM",
"MBartForConditionalGeneration",
"mbart"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174440 | ASCCCCCCCC/PENGMENGJIE-finetuned-emotion | ASCCCCCCCC | null | 3 | 890 | False | 2022-03-02T23:29:04Z | 2022-02-08T03:32:48Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Feb08_10-06-47_pengmengjie/1644286188.6766713/events.out.tfevents.1644286188.pengmengjie.43976.1",
"runs/Feb08_10-06-47_pengmengjie/1644288630.256366/events.out.tfevents.1644288630.pengmengjie.43976.3",
"runs/Feb08_... | db44886a0596deadd82e6f8f82c87d2123da59fc | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "PENGMENGJIE-finetuned-emotion... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# PENGMENGJIE-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-b... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174443 | ASCCCCCCCC/bert-base-chinese-finetuned-amazon_zh | ASCCCCCCCC | null | 14 | 1,318 | False | 2022-03-02T23:29:04Z | 2022-02-21T20:21:21Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
".gitignore",
"config.json",
"pytorch_model.bin",
"runs/Feb21_09-47-06_3d31d9260f25/1645436841.591132/events.out.tfevents.1645436841.3d31d9260f25.34.1",
"runs/Feb21_09-47-06_3d31d9260f25/events.out.tfevents.1645436841.3d31d9260f25.34.0",
"special_tokens_map.json",
"tokenizer.json",
... | 9d8fd0b4dd669e42ba21f3fb1579e1debfa856cd | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174444 | ASCCCCCCCC/bert-base-chinese-finetuned-amazon_zh_20000 | ASCCCCCCCC | null | 9 | 1,368 | False | 2022-03-02T23:29:04Z | 2022-02-22T02:51:29Z | transformers | 0 | 0 | [{"name": "bert-base-chinese-finetuned-amazon_zh_20000", "results": []}] | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Feb22_01-40-52_b1838846cd90/1645494101.653156/events.out.tfevents.1645494101.b1838846cd90.33.1",
"runs/Feb22_01-40-52_b1838846cd90/1645497023.3316605/events.out.tfevents.1645497023.b1838846cd90.33.3",
"runs/Feb22_01... | d2e02f3763d37568022bfdae9b07e4e6b27e81fa | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["accuracy", "f1"], "model_name": "bert-base-chinese-finetuned-amazon_zh_20000", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-chinese-finetuned-amazon_zh_20000
This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert... | null | null | null | null | null | null | [
"accuracy",
"f1"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174445 | ASCCCCCCCC/distilbert-base-chinese-amazon_zh_20000 | ASCCCCCCCC | null | 47 | 2,376 | False | 2022-03-02T23:29:04Z | 2022-02-25T06:26:43Z | transformers | 1 | 0 | [{"name": "distilbert-base-chinese-amazon_zh_20000", "results": []}] | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Feb25_05-56-14_df0abd199a2c/1645768700.883807/events.out.tfevents.1645768700.df0abd199a2c.33.1",
"runs/Feb25_05-56-14_df0abd199a2c/events.out.tfevents.1645768700.df0abd199a2c.33.0",
"special_tokens_map.json",
"tok... | 85a8784ff4156fc7d36a8717b7a58d58e42620f2 | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": "distilbert-base-chinese-amazon_zh_20000", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-chinese-amazon_zh_20000
This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-bas... | null | null | null | null | null | null | [
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174446 | ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000 | ASCCCCCCCC | null | 8 | 936 | False | 2022-03-02T23:29:04Z | 2022-02-25T07:33:20Z | transformers | 0 | 0 | [{"name": "distilbert-base-multilingual-cased-amazon_zh_20000", "results": []}] | text-classification | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilbert-base-multilingual-cased-amazon_zh_20000
This model is a fine-tuned version of [distilbert-base-multilingual-cased](htt... | null | [
"apache-2.0"
] | null | null | null | null | [
"accuracy"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174447 | ASCCCCCCCC/distilbert-base-uncased-finetuned-amazon_zh_20000 | ASCCCCCCCC | null | 7 | 913 | False | 2022-03-02T23:29:04Z | 2022-02-25T03:38:48Z | transformers | 0 | 0 | [{"name": "distilbert-base-uncased-finetuned-amazon_zh_20000", "results": []}] | text-classification | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-amazon_zh_20000
This model is a fine-tuned version of [distilbert-base-uncased](https://hugging... | null | [
"apache-2.0"
] | null | null | null | null | [
"accuracy"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174448 | ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc | ASCCCCCCCC | null | 11 | 1,260 | False | 2022-03-02T23:29:04Z | 2022-02-14T08:54:32Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Feb14_13-46-43_pengmengjie/1644817646.227422/events.out.tfevents.1644817646.pengmengjie.53468.1",
"runs/Feb14_13-46-43_pengmengjie/events.out.tfevents.1644817646.pengmengjie.53468.0",
"runs/Feb14_14-11-20_pengmengji... | 2689640b989d6fb96b5e64afaad6fc428c76cfc1 | [
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"generated_from_trainer",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
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] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "distilbert-base-uncased-finet... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-clinc
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17444d | ATGdev/DialoGPT-small-harrypotter | ATGdev | null | 8 | 2,461 | False | 2022-03-02T23:29:04Z | 2021-10-23T04:38:29Z | transformers | 1 | 0 | null | text-generation | null | [
".gitattributes",
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"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 2657935d4bb1c929ea53121b50b35786e10e610c | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
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] | [
"text"
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621ffdc036468d709f174453 | AVSilva/bertimbau-large-fine-tuned-md | AVSilva | null | 9 | 727 | False | 2022-03-02T23:29:04Z | 2022-02-03T17:19:02Z | transformers | 0 | 0 | [{"name": "result", "results": []}] | fill-mask | null | [
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"tokenizer_config.json",
"train_results.json",
"trainer_state.json",
"training_args.bin",
"vocab.txt"
] | 23de596a0b7fb907eb74fcc3e2a5195ff3e83912 | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "result", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# result
This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-larg... | null | [
"mit"
] | null | null | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174454 | AVSilva/bertimbau-large-fine-tuned-sd | AVSilva | null | 1 | 742 | False | 2022-03-02T23:29:04Z | 2021-12-15T20:43:17Z | transformers | 1 | 0 | [{"name": "result", "results": []}] | fill-mask | null | [
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"config.json",
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"pytorch_model.bin",
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"tokenizer.json",
"tokenizer_config.json",
"train_results.json",
"trainer_state.json",
"training_args.bin",
"vocab.txt"
] | 3659caf43a0ff417c814280813d2a1566c5bd515 | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "result", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# result
This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-larg... | null | [
"mit"
] | null | null | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174455 | AVeryRealHuman/DialoGPT-small-TonyStark | AVeryRealHuman | null | 1,497 | 74,594 | False | 2022-03-02T23:29:04Z | 2021-10-08T08:27:15Z | transformers | 0 | 0 | null | text-generation | null | [
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"README.md",
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"checkpoint-3500/optimizer.pt",
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"checkpoint-3500/scheduler.pt",
"checkpoint-3500/special_tokens_map.json",
"checkpoint-3500/tokenizer.json",
"checkpoint-3500/tokenizer_c... | 58f3a7114d51dfc283d71221fff75563d8eb7444 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
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] | [
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] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174472 | AbderrahimRezki/HarryPotterBot | AbderrahimRezki | null | 2 | 897 | False | 2022-03-02T23:29:04Z | 2021-09-01T16:12:33Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 53718f8988201cce701c94831eb1f019fe54faac | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174474 | Abdou/arabert-base-algerian | Abdou | null | 14 | 1,924 | False | 2022-03-02T23:29:04Z | 2023-11-06T10:45:03Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | c02463dc86c6c574916fe025cc27c067d6d8d1ab | [
"transformers",
"pytorch",
"bert",
"text-classification",
"ar",
"dataset:Abdou/dz-sentiment-yt-comments",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Abdou/dz-sentiment-yt-comments"], "eval_results": null, "language": ["ar"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": ["f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": null} | # BERT Models Fine-tuned on Algerian Dialect Sentiment Analysis
These are different BERT models (BERT Arabic models are initialized from [AraBERT](https://huggingface.co/aubmindlab/bert-large-arabertv02)) fine-tuned on the [Algerian Dialect Sentiment Analysis](https://huggingface.co/datasets/Abdou/dz-sentiment-yt-comme... | null | [
"mit"
] | [
"Abdou/dz-sentiment-yt-comments"
] | [
"ar"
] | null | null | [
"f1",
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174475 | Abdou/arabert-large-algerian | Abdou | null | 19 | 4,451 | False | 2022-03-02T23:29:04Z | 2023-11-06T10:46:01Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 4f0fb7ba88945fe250cffdb367293c5e0a9701a0 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"ar",
"dataset:Abdou/dz-sentiment-yt-comments",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Abdou/dz-sentiment-yt-comments"], "eval_results": null, "language": ["ar"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": ["f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": null} | # BERT Models Fine-tuned on Algerian Dialect Sentiment Analysis
These are different BERT models (BERT Arabic models are initialized from [AraBERT](https://huggingface.co/aubmindlab/bert-large-arabertv02)) fine-tuned on the [Algerian Dialect Sentiment Analysis](https://huggingface.co/datasets/Abdou/dz-sentiment-yt-comme... | null | [
"mit"
] | [
"Abdou/dz-sentiment-yt-comments"
] | [
"ar"
] | null | null | [
"f1",
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174476 | Abdou/arabert-medium-algerian | Abdou | null | 5 | 986 | False | 2022-03-02T23:29:04Z | 2023-11-06T10:44:25Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
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] | 16eaa6b90760b12bdebeaa2d6d4da50d5506e8df | [
"transformers",
"pytorch",
"bert",
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"ar",
"dataset:Abdou/dz-sentiment-yt-comments",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Abdou/dz-sentiment-yt-comments"], "eval_results": null, "language": ["ar"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": ["f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": null} | # BERT Models Fine-tuned on Algerian Dialect Sentiment Analysis
These are different BERT models (BERT Arabic models are initialized from [AraBERT](https://huggingface.co/aubmindlab/bert-large-arabertv02)) fine-tuned on the [Algerian Dialect Sentiment Analysis](https://huggingface.co/datasets/Abdou/dz-sentiment-yt-comme... | null | [
"mit"
] | [
"Abdou/dz-sentiment-yt-comments"
] | [
"ar"
] | null | null | [
"f1",
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174477 | Abdou/arabert-mini-algerian | Abdou | null | 4 | 914 | False | 2022-03-02T23:29:04Z | 2023-11-06T10:42:41Z | transformers | 1 | 0 | null | text-classification | null | [
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"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
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] | f4de5bf5a394a432ee0e495a77d599869b5ab52d | [
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"ar",
"dataset:Abdou/dz-sentiment-yt-comments",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Abdou/dz-sentiment-yt-comments"], "eval_results": null, "language": ["ar"], "library_name": "transformers", "license": "mit", "license_name": null, "license_link": null, "metrics": ["f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": null} | # BERT Models Fine-tuned on Algerian Dialect Sentiment Analysis
These are different BERT models (BERT Arabic models are initialized from [AraBERT](https://huggingface.co/aubmindlab/bert-large-arabertv02)) fine-tuned on the [Algerian Dialect Sentiment Analysis](https://huggingface.co/datasets/Abdou/dz-sentiment-yt-comme... | null | [
"mit"
] | [
"Abdou/dz-sentiment-yt-comments"
] | [
"ar"
] | null | null | [
"f1",
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174480 | AbhinavSaiTheGreat/DialoGPT-small-harrypotter | AbhinavSaiTheGreat | null | 0 | 881 | False | 2022-03-02T23:29:04Z | 2021-08-31T05:39:57Z | transformers | 0 | 0 | null | text-generation | null | [
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] | 159497eacaa099a2be9406d68740edc3e7ee70dd | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
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"text"
] | [
"text"
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621ffdc036468d709f174481 | Abhishek4/Cuad_Finetune_roberta | Abhishek4 | null | 3 | 681 | False | 2022-03-02T23:29:04Z | 2022-02-13T23:18:24Z | transformers | 0 | 0 | null | token-classification | null | [
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] | b0da9f5eb4c652783b7e49ccc7cd1aaf4537be92 | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForTokenClassification"], "model_type": "roberta", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
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} | null | null | null | null | null | null | null | null | null | [
"roberta",
"AutoModelForTokenClassification",
"RobertaForTokenClassification"
] | [
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"text"
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621ffdc036468d709f17449b | Abirate/bert_fine_tuned_cola | Abirate | null | 13 | 3,002 | False | 2022-03-02T23:29:04Z | 2021-11-21T16:41:00Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 6affdebddc7120fc72e5f30fa3658f34e8790ce0 | [
"transformers",
"tf",
"bert",
"text-classification",
"arxiv:1810.04805",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | null | ## Petrained Model BERT: base model (cased)
BERT base model (cased) is a 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... | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
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621ffdc036468d709f1744a2 | Abirate/code_net_similarity_model_sub23_fbert | Abirate | null | 9 | 1,243 | False | 2022-03-02T23:29:04Z | 2022-01-27T21:09:31Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
"config.json",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | bb5a21f985dee86e069917c47d322507aff9b1cf | [
"transformers",
"tf",
"bert",
"text-classification",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
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] | [
"text"
] | [
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] |
621ffdc036468d709f1744a5 | Abirate/gpt_3_finetuned_multi_x_science | Abirate | null | 12 | 5,882 | False | 2022-03-02T23:29:04Z | 2022-01-15T06:16:57Z | transformers | 2 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 82ac4e2d59cb09b91bc63c0f3e2f4b242533a3b8 | [
"transformers",
"pytorch",
"endpoints_compatible",
"region:us"
] | null | null | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "0": "Text Generation", "1": "PyTorch", "2": "Transformers", "3": "gpt_neo", "4": "te... | ## Petrained Model Description: Open Source Version of GPT-3
Generative Pre-trained Transformer 3 (GPT-3) is an autoregressive language model that uses deep learning to produce human-like text.
It is the third-generation language prediction model in the GPT-n series (and the successor to GPT-2) created by OpenAI
GPT-N... | null | null | null | null | null | null | null | [
"AutoModel"
] | [
null
] | null | null | null |
621ffdc036468d709f1744de | ActivationAI/distilbert-base-uncased-finetuned-emotion | ActivationAI | null | 14 | 2,930,916 | False | 2022-03-02T23:29:04Z | 2022-03-02T03:40:08Z | transformers | 1 | 0 | [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "emotion", "type": "emotion", "args": "default"}, "metrics": [{"name": "Accuracy", "type": "accuracy", "value": 0.928, "verified": false}, {"name": "F1", "type"... | text-classification | null | [
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] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["emotion"], "license": "apache-2.0", "metrics": ["accuracy", "f1"], "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | null | [
"apache-2.0"
] | [
"emotion"
] | null | null | null | [
"accuracy",
"f1"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
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621ffdc036468d709f17455c | AdharshJolly/HarryPotterBot-Model | AdharshJolly | null | 7 | 1,373 | False | 2022-03-02T23:29:04Z | 2024-07-17T09:35:04Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"F32": 124439808, "U8": 12582912}, "total": 137022720} | [
".gitattributes",
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"pytorch_model.bin",
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"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
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] | 031d1a134a272da755691e946503293d57eaeb47 | [
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"safetensors",
"gpt2",
"text-generation",
"conversational",
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"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | 137,022,720 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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621ffdc036468d709f17455e | Adi2K/Priv-Consent | Adi2K | null | 4 | 1,008 | False | 2022-03-02T23:29:04Z | 2021-09-24T12:53:04Z | transformers | 1 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
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"pytorch_model.bin",
"sample_input.pkl",
"special_tokens_map.json",
"tokenizer.json",
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"vocab.txt"
] | f14517d90a670e6dfb3614a489d7ea688f93ffe0 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"eng",
"dataset:Adi2K/autonlp-data-Priv-Consent",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Adi2K/autonlp-data-Priv-Consent"], "eval_results": null, "language": "eng", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "You can control cookies and trac... | # Model
- Problem type: Binary Classification
- Model ID: 12592372
## Validation Metrics
- Loss: 0.23033875226974487
- Accuracy: 0.9138655462184874
- Precision: 0.9087136929460581
- Recall: 0.9201680672268907
- AUC: 0.9690346726926065
- F1: 0.9144050104384133
## Usage
You can use cURL to access this model:
```
$ ... | null | null | [
"Adi2K/autonlp-data-Priv-Consent"
] | [
"eng"
] | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17457b | AdrianGzz/DialoGPT-small-harrypotter | AdrianGzz | null | 5 | 862 | False | 2022-03-02T23:29:04Z | 2021-10-11T21:52:30Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
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"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 3e2781dc40e8779c3a6ee0367de4baf038efdbdb | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17457e | Aero/Tsubomi-Haruno | Aero | null | 11 | 1,331 | False | 2022-03-02T23:29:04Z | 2021-06-14T22:21:24Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 4addf3eff55db676e4d299df43ffed770d60bf4d | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"], "thumbnail": "https://huggingface.co/front/thumbnails/dialogpt.png"} | # DialoGPT Trained on the Speech of a Game Character
```python
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("r3dhummingbird/DialoGPT-medium-joshua")
model = AutoModelWithLMHead.from_pretrained("r3dhummingbird/DialoGPT-medium-joshua")
# Let's chat for 4 lines
f... | null | [
"mit"
] | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174583 | AethiQs-Max/AethiQs_GemBERT_bertje_50k | AethiQs-Max | null | 2 | 812 | False | 2022-03-02T23:29:04Z | 2021-06-23T14:59:15Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 7eac1013243a6e9225338e69bebc8b156b0591db | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174585 | AethiQs-Max/aethiqs-base_bertje-data_rotterdam-epochs_10 | AethiQs-Max | null | 3 | 543 | False | 2022-03-02T23:29:04Z | 2021-08-04T21:27:39Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 4e6166bbb295df51cfb2103d78d62cc591499c6e | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
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"text"
] | [
"text"
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621ffdc036468d709f174586 | AethiQs-Max/aethiqs-base_bertje-data_rotterdam-epochs_30-epoch_30 | AethiQs-Max | null | 4 | 567 | False | 2022-03-02T23:29:04Z | 2021-08-05T14:23:09Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 83c63a5086c0ae8f4cdf8834d66351ce9e053534 | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
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] | [
"text"
] | [
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] |
621ffdc036468d709f174588 | AethiQs-Max/s3-v1-20_epochs | AethiQs-Max | null | 5 | 595 | False | 2022-03-02T23:29:04Z | 2021-08-08T15:36:00Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 6be8b14979bd2bec7e10fd029baa7731925a0b20 | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17458f | Ahmad/parsT5-base | Ahmad | null | 27 | 8,929 | False | 2022-03-02T23:29:04Z | 2021-11-03T13:47:07Z | transformers | 6 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | cfcb398d4d33113e3b8c63f15875e52c6be62077 | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | null | A monolingual T5 model for Persian trained on OSCAR 21.09 (https://oscar-corpus.com/) corpus with self-supervised method. 35 Gig deduplicated version of Persian data was used for pre-training the model.
It's similar to the English T5 model but just for Persian. You may need to fine-tune it on your specific task.
Exa... | null | null | null | null | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc036468d709f174590 | Ahmad/parsT5 | Ahmad | null | 3 | 1,412 | False | 2022-03-02T23:29:04Z | 2021-11-04T05:16:46Z | transformers | 2 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"evaluation.json",
"flax_model.msgpack",
"opt_state.msgpack",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_state.json"
] | 1fa3bad1c3a9280da07cbe151642d572f3904cbf | [
"transformers",
"jax",
"t5",
"text2text-generation",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | null | A checkpoint for training Persian T5 model. This repository can be cloned and pre-training can be resumed. This model uses flax and is for training.
For more information and getting the training code please refer to:
https://github.com/puraminy/parsT5 | null | null | null | null | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc036468d709f1745ad | Ahren09/distilbert-base-uncased-finetuned-cola | Ahren09 | null | 3 | 938 | False | 2022-03-02T23:29:04Z | 2021-11-28T02:27:26Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
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"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
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"pipeline_tag": "text-classification",
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} | null | null | null | null | null | null | null | null | null | [
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621ffdc036468d709f1745ae | AiPorter/DialoGPT-small-Back_to_the_future | AiPorter | null | 6 | 1,056 | False | 2022-03-02T23:29:04Z | 2022-02-23T00:04:53Z | transformers | 1 | 0 | null | text-generation | null | [
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"tokenizer_config.json",
"training_args.bin",
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] | c9d68d55cce14c41c64dec7d13e8745e20cdd2a3 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f1745af | Aibox/DialoGPT-small-rick | Aibox | null | 6 | 4,857 | False | 2022-03-02T23:29:04Z | 2021-08-31T00:01:30Z | transformers | 1 | 0 | null | text-generation | null | [
".gitattributes",
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"tokenizer_config.json",
"training_args.bin",
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] | 75340709dc60ab3a6e7bfc6ce5c82b6f783ba449 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
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"text"
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621ffdc036468d709f1745bd | Aimendo/autonlp-triage-35248482 | Aimendo | null | 4 | 1,039 | False | 2022-03-02T23:29:04Z | 2021-11-23T08:03:14Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sample_input.pkl",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 528497d7ac1681046865517f84c8792e878da274 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"en",
"dataset:Aimendo/autonlp-data-triage",
"co2_eq_emissions",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Aimendo/autonlp-data-triage"], "eval_results": null, "language": "en", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_... | # Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 35248482
- CO2 Emissions (in grams): 7.989144645413398
## Validation Metrics
- Loss: 0.13783401250839233
- Accuracy: 0.9728654124457308
- Macro F1: 0.949537871674076
- Micro F1: 0.9728654124457308
- Weighted F1: 0.9732422812610365
-... | null | null | [
"Aimendo/autonlp-data-triage"
] | [
"en"
] | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1745cd | Ajay191191/autonlp-Test-530014983 | Ajay191191 | null | 7 | 996 | False | 2022-03-02T23:29:04Z | 2022-01-25T22:28:49Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sample_input.pkl",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 9b8f7775d2be4452bb72308398b2a0794a7a185b | [
"transformers",
"pytorch",
"bert",
"text-classification",
"en",
"dataset:Ajay191191/autonlp-data-Test",
"co2_eq_emissions",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Ajay191191/autonlp-data-Test"], "eval_results": null, "language": "en", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2... | # Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 530014983
- CO2 Emissions (in grams): 55.10196329868386
## Validation Metrics
- Loss: 0.23171618580818176
- Accuracy: 0.9298837645294338
- Precision: 0.9314414866901055
- Recall: 0.9279459594696022
- AUC: 0.979447403984557
- F1: 0.929690... | null | null | [
"Ajay191191/autonlp-data-Test"
] | [
"en"
] | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
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] | [
"text"
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621ffdc036468d709f1745ce | Ajaykannan6/autonlp-manthan-16122692 | Ajaykannan6 | null | 2 | 567 | False | 2022-03-02T23:29:04Z | 2021-10-08T13:52:19Z | transformers | 0 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"sample_input.pkl",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 8c1bc189faf33ae5f75c1274611c60e178da0fe5 | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"unk",
"dataset:Ajaykannan6/autonlp-data-manthan",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BartForConditionalGeneration"], "model_type": "bart", "tokenizer_config": {"unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "n... | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Ajaykannan6/autonlp-data-manthan"], "eval_results": null, "language": "unk", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "I love AutoNLP \ud83e\udd17"}]} | # Model Trained Using AutoNLP
- Problem type: Summarization
- Model ID: 16122692
## Validation Metrics
- Loss: 1.1877621412277222
- Rouge1: 42.0713
- Rouge2: 23.3043
- RougeL: 37.3755
- RougeLsum: 37.8961
- Gen Len: 60.7117
## Usage
You can use cURL to access this model:
```
$ curl -X POST -H "Authorization: Bear... | null | null | [
"Ajaykannan6/autonlp-data-manthan"
] | [
"unk"
] | null | null | null | [
"bart",
"BartForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc036468d709f1745ec | Akari/albert-base-v2-finetuned-squad | Akari | null | 14 | 1,539 | False | 2022-03-02T23:29:04Z | 2021-12-02T05:36:13Z | transformers | 1 | 0 | [{"name": "albert-base-v2-finetuned-squad", "results": []}] | question-answering | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Dec01_00-48-07_bigtensor/1638337713.570339/events.out.tfevents.1638337713.bigtensor.55473.1",
"runs/Dec01_00-48-07_bigtensor/events.out.tfevents.1638337713.bigtensor.55473.0",
"runs/Dec01_00-55-10_bigtensor/16383381... | cc24dc48164a747296f80f831cc9353e2470705e | [
"transformers",
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"tensorboard",
"albert",
"question-answering",
"generated_from_trainer",
"dataset:squad_v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["AlbertForQuestionAnswering"], "model_type": "albert", "tokenizer_config": {"bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "<unk>", "sep_token": "[SEP]", "pad_token": "<pad>", "cls_token": "[CLS]", "mask_token": {"content": "[MASK]", "single_word": false, "lstrip": true, "rstrip": false, "n... | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad_v2"], "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "albert-base-v2-finetuned-squad", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# albert-base-v2-finetuned-squad
This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on t... | null | [
"apache-2.0"
] | [
"squad_v2"
] | null | null | null | null | [
"AutoModelForQuestionAnswering",
"albert",
"AlbertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f1745ee | Akash7897/distilbert-base-uncased-finetuned-cola | Akash7897 | null | 7 | 990 | False | 2022-03-02T23:29:04Z | 2022-03-02T08:29:47Z | transformers | 0 | 0 | [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "glue", "type": "glue", "args": "cola"}, "metrics": [{"name": "Matthews Correlation", "type": "matthews_correlation", "value": 0.522211073949747, "verified": false... | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Mar02_07-19-51_91bf675fdfb2/1646206200.008335/events.out.tfevents.1646206200.91bf675fdfb2.83.1",
"runs/Mar02_07-19-51_91bf675fdfb2/events.out.tfevents.1646206199.91bf675fdfb2.83.0",
"runs/Mar02_07-19-51_91bf675fdfb2... | e25f95dffc22db6cbe5102f5f59aeeba04e901b0 | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["glue"], "license": "apache-2.0", "metrics": ["matthews_correlation"], "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "ar... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | null | [
"apache-2.0"
] | [
"glue"
] | null | null | null | [
"matthews_correlation"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1745ef | Akash7897/distilbert-base-uncased-finetuned-sst2 | Akash7897 | null | 30 | 1,082 | False | 2022-03-02T23:29:04Z | 2022-03-03T08:57:39Z | transformers | 0 | 0 | [{"name": "distilbert-base-uncased-finetuned-sst2", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "glue", "type": "glue", "args": "sst2"}, "metrics": [{"name": "Accuracy", "type": "accuracy", "value": 0.9036697247706422, "verified": false}]}]}] | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Mar02_19-09-10_4d3fd8a82b8e/1646248190.2862866/events.out.tfevents.1646248190.4d3fd8a82b8e.73.1",
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"runs/Mar02_19-10-32_4d3fd8a82b8... | 0f3e476bb26b0ed34c676b9db35ad06d5c1e5323 | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"datasets": ["glue"], "license": "apache-2.0", "metrics": ["accuracy"], "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-sst2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "args": "sst2"}... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-sst2
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | null | [
"apache-2.0"
] | [
"glue"
] | null | null | null | [
"accuracy"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
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621ffdc036468d709f1745f1 | Akash7897/gpt2-wikitext2 | Akash7897 | null | 7 | 1,213 | False | 2022-03-02T23:29:04Z | 2022-02-28T19:32:20Z | transformers | 0 | 0 | [{"name": "gpt2-wikitext2", "results": []}] | text-generation | null | [
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"gpt2",
"text-generation",
"generated_from_trainer",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "gpt2-wikitext2", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2-wikitext2
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the fol... | null | [
"mit"
] | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174610 | Akjder/DialoGPT-small-harrypotter | Akjder | null | 3 | 39 | False | 2022-03-02T23:29:04Z | 2021-09-21T06:07:16Z | transformers | 0 | 0 | null | text-generation | null | [
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"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | b8d3156e5a427a5eb86cc079380ebd89f2879676 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
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"processor": "AutoTokenizer"
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"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
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621ffdc036468d709f17461b | AkshaySg/gramCorrection | AkshaySg | null | 2 | 2,371 | False | 2022-03-02T23:29:04Z | 2021-07-15T08:56:11Z | transformers | 0 | 0 | null | null | null | [
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"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin"
] | 04edb6a4c1ef4f02eaf8d315231f9c5500501929 | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["T5ForConditionalGeneration"], "model_type": "t5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
"custom_class": null,
"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc036468d709f174648 | AlbertHSU/BertTEST | AlbertHSU | null | 1 | 515 | False | 2022-03-02T23:29:04Z | 2022-01-10T13:58:47Z | transformers | 1 | 0 | null | null | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | d2f33bbfb1afeb8bfe3a8af327e0129483fda679 | [
"transformers",
"pytorch",
"endpoints_compatible",
"region:us"
] | null | null | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | null | null | null | null | null | null | null | null | null | [
"AutoModel"
] | [
null
] | null | null | null |
621ffdc036468d709f174649 | AlbertHSU/ChineseFoodBert | AlbertHSU | null | 3 | 898 | False | 2022-03-02T23:29:04Z | 2022-01-12T17:26:51Z | transformers | 1 | 0 | null | feature-extraction | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | f07e72878cb15caf04eecdd983e41854ed3a90c4 | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"BertModel",
"AutoModel",
"bert"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
621ffdc036468d709f17466f | Aleksandar/bert-srb-base-cased-oscar | Aleksandar | null | 16 | 679 | False | 2022-03-02T23:29:04Z | 2025-01-09T09:50:12Z | transformers | 0 | 0 | null | fill-mask | {"parameters": {"I64": 512, "F32": 108340804}, "total": 108341316} | [
".gitattributes",
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"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 11dc8c23781359247ee383cc8233f758fedcb445 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"fill-mask",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "bert-srb-base-cased-oscar", "results"... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-srb-base-cased-oscar
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
## Model descri... | null | null | null | null | 108,341,316 | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174671 | Aleksandar/bert-srb-ner-setimes | Aleksandar | null | 5 | 912 | False | 2022-03-02T23:29:04Z | 2024-12-18T10:00:41Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"I64": 512, "F32": 107727370}, "total": 107727882} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 2ff910f4edf34c096469d6c559a571a452ea1767 | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-srb-ner-setimes
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation... | null | null | null | null | 107,727,882 | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174672 | Aleksandar/bert-srb-ner | Aleksandar | null | 5 | 873 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:05:15Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"I64": 512, "F32": 107725063}, "total": 107725575} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 57bc402fa5d97738278a99809f9668ab6fa8b6c3 | [
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"pytorch",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:wikiann",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
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"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["wikiann"], "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"n... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-srb-ner
This model was trained from scratch on the wikiann dataset.
It achieves the following results on the evaluation set:... | null | null | [
"wikiann"
] | null | 107,725,575 | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174673 | Aleksandar/distilbert-srb-base-cased-oscar | Aleksandar | null | 5 | 726 | False | 2022-03-02T23:29:04Z | 2025-02-21T02:54:50Z | transformers | 0 | 0 | null | fill-mask | {"parameters": {"F32": 65812036}, "total": 65812036} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 6f3cc8c424cd4dcb31117a9d61bbec42b3e3a198 | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"fill-mask",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForMaskedLM"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "distilbert-srb-base-cased-oscar", "re... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-srb-base-cased-oscar
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
## Model ... | null | null | null | null | 65,812,036 | null | null | [
"distilbert",
"AutoModelForMaskedLM",
"DistilBertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174675 | Aleksandar/distilbert-srb-ner-setimes | Aleksandar | null | 8 | 682 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:05:25Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"F32": 81527050}, "total": 81527050} | [
".gitattributes",
".gitignore",
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"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 94d69708f5c992c225edf115eae359f7e54d3b71 | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"token-classification",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForTokenClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
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"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-srb-ner-setimes
This model was trained from scratch on the None dataset.
It achieves the following results on the eval... | null | null | null | null | 81,527,050 | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174676 | Aleksandar/distilbert-srb-ner | Aleksandar | null | 9 | 782 | False | 2022-03-02T23:29:04Z | 2021-09-09T06:27:16Z | transformers | 0 | 0 | null | token-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 5d3c89f63aed4e52c2016b682c1fb329447fe8d0 | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"generated_from_trainer",
"sr",
"dataset:wikiann",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForTokenClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
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"pipeline_tag": "token-classification",
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} | {"base_model": null, "datasets": ["wikiann"], "eval_results": null, "language": ["sr"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-srb-ner
This model was trained from scratch on the wikiann dataset.
It achieves the following results on the evaluatio... | null | null | [
"wikiann"
] | [
"sr"
] | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174678 | Aleksandar/electra-srb-ner-setimes | Aleksandar | null | 6 | 698 | False | 2022-03-02T23:29:04Z | 2023-09-12T13:05:34Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"I64": 512, "F32": 108899338}, "total": 108899850} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | cf7e5395b9d61b86a3bff10212b74ad94658d789 | [
"transformers",
"pytorch",
"safetensors",
"electra",
"token-classification",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ElectraForTokenClassification"], "model_type": "electra", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# electra-srb-ner-setimes
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluat... | null | null | null | null | 108,899,850 | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"ElectraForTokenClassification",
"AutoModelForTokenClassification",
"electra"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174679 | Aleksandar/electra-srb-ner | Aleksandar | null | 6 | 1,007 | False | 2022-03-02T23:29:04Z | 2023-05-04T08:14:22Z | transformers | 0 | 0 | null | token-classification | {"parameters": {"I64": 512, "F32": 108897031}, "total": 108897543} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | e83fe807b39efaaad029073991a89683937c0e9a | [
"transformers",
"pytorch",
"safetensors",
"electra",
"token-classification",
"generated_from_trainer",
"dataset:wikiann",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ElectraForTokenClassification"], "model_type": "electra", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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} | {"base_model": null, "datasets": ["wikiann"], "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"n... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# electra-srb-ner
This model was trained from scratch on the wikiann dataset.
It achieves the following results on the evaluation s... | null | null | [
"wikiann"
] | null | 108,897,543 | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"ElectraForTokenClassification",
"AutoModelForTokenClassification",
"electra"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17467a | Aleksandar/electra-srb-oscar | Aleksandar | null | 22 | 626 | False | 2022-03-02T23:29:04Z | 2025-01-09T09:50:22Z | transformers | 0 | 0 | null | fill-mask | {"parameters": {"I64": 512, "F32": 109514298}, "total": 109514810} | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 0ae24a291478a61df632418a69a3ae2c924052f1 | [
"transformers",
"pytorch",
"safetensors",
"electra",
"fill-mask",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ElectraForMaskedLM"], "model_type": "electra", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "electra-srb-oscar", "results": [{"tas... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# electra-srb-oscar
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
## Model description
M... | null | null | null | null | 109,514,810 | null | null | [
"ElectraForMaskedLM",
"AutoModelForMaskedLM",
"electra"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174684 | Aleksandra/herbert-base-cased-finetuned-squad | Aleksandra | null | 20 | 1,350 | False | 2022-03-02T23:29:04Z | 2022-01-20T13:14:11Z | transformers | 0 | 0 | [{"name": "herbert-base-cased-finetuned-squad", "results": []}] | question-answering | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"runs/Jan20_12-34-32_5ec4d896b877/1642682111.6865454/events.out.tfevents.1642682111.5ec4d896b877.72.1",
"runs/Jan20_12-34-32_5ec4d896b877/events.out.tfevents.1642682111.5ec4d896b877.72.0",
"special_tokens_... | 4cbf8e1987f9367451c884520c75022619d2111a | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForQuestionAnswering"], "model_type": "bert", "tokenizer_config": {"cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "sep_token": "</s>", "bos_token": "<s>"}} | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "herbert-base-cased-finetuned-squad", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# herbert-base-cased-finetuned-squad
This model is a fine-tuned version of [allegro/herbert-base-cased](https://huggingface.co/alle... | null | [
"cc-by-4.0"
] | null | null | null | null | null | [
"AutoModelForQuestionAnswering",
"bert",
"BertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174686 | adorkin/xlm-roberta-en-ru-emoji | adorkin | null | 7 | 1,303 | False | 2022-03-02T23:29:04Z | 2023-03-23T18:42:15Z | transformers | 0 | 0 | null | text-classification | {"parameters": {"I64": 514, "F32": 339804180}, "total": 339804694} | [
".gitattributes",
"README.md",
"config.json",
"model.safetensors",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | c33abdb41be1b53129a08ae0eecbab1308d69868 | [
"transformers",
"pytorch",
"safetensors",
"xlm-roberta",
"text-classification",
"en",
"ru",
"dataset:tweet_eval",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["XLMRobertaForSequenceClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": f... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["tweet_eval"], "eval_results": null, "language": ["en", "ru"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "model_index": [{"name": "xlm-roberta-en-ru-emoji", "results": [{"t... | # xlm-roberta-en-ru-emoji
- Problem type: Multi-class Classification | null | null | [
"tweet_eval"
] | [
"en",
"ru"
] | 339,804,694 | null | null | [
"AutoModelForSequenceClassification",
"XLMRobertaForSequenceClassification",
"xlm-roberta"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174687 | AlekseyKorshuk/bert | AlekseyKorshuk | null | 3 | 821 | False | 2022-03-02T23:29:04Z | 2023-03-18T18:35:39Z | transformers | 0 | 0 | [{"name": "bert", "results": []}] | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 7f34478e40dce96385b7850519e8f52d597b8fea | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"cls_token": "[CLS]", "mask_token": "[MASK]", "pad_token": "[PAD]", "sep_token": "[SEP]", "unk_token": "[UNK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": "bert", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknow... | null | [
"apache-2.0"
] | null | null | null | null | [
"accuracy"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f174692 | Alerosae/SocratesGPT-2 | Alerosae | null | 6 | 1,098 | False | 2022-03-02T23:29:04Z | 2021-12-20T12:36:38Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 38449e4d6b86ddf4db3a010aef572eee4a899bac | [
"transformers",
"pytorch",
"gpt2",
"feature-extraction",
"text-generation",
"en",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPT2Model"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "en", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["text-generation"], "widget": [{"text": "The Gods"}, {"text": "What is"}]} | This is a fine-tuned version of GPT-2, trained with the entire corpus of Plato's works. By generating text samples you should be able to generate ancient Greek philosophy on the fly! | null | null | null | [
"en"
] | null | null | null | [
"gpt2",
"GPT2Model",
"AutoModel"
] | [
"feature-extraction",
"text-generation"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"text",
"embeddings"
] |
621ffdc036468d709f174696 | AlexKay/xlm-roberta-large-qa-multilingual-finedtuned-ru | AlexKay | null | 423 | 418,900 | False | 2022-03-02T23:29:04Z | 2022-07-19T15:33:20Z | transformers | 50 | 0 | null | question-answering | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json"
] | 6cc14366f0cc95428a695d30594a93dd6935d800 | [
"transformers",
"pytorch",
"xlm-roberta",
"question-answering",
"en",
"ru",
"multilingual",
"arxiv:1912.09723",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["XLMRobertaForQuestionAnswering"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false,... | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en", "ru", "multilingual"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # XLM-RoBERTa large model whole word masking finetuned on SQuAD
Pretrained model using a masked language modeling (MLM) objective.
Fine tuned on English and Russian QA datasets
## Used QA Datasets
SQuAD + SberQuAD
[SberQuAD original paper](https://arxiv.org/pdf/1912.09723.pdf) is here! Recommend to read!
## Evaluat... | null | [
"apache-2.0"
] | null | [
"en",
"ru",
"multilingual"
] | null | null | null | [
"AutoModelForQuestionAnswering",
"XLMRobertaForQuestionAnswering",
"xlm-roberta"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f174698 | AlexMaclean/sentence-compression | AlexMaclean | null | 7 | 1,191 | False | 2022-03-02T23:29:04Z | 2021-12-04T08:10:24Z | transformers | 2 | 0 | [{"name": "sentence-compression", "results": []}] | token-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json",
"vocab.txt"
] | d0bd05865437a846e4d309e470489c31d04b461a | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForTokenClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy", "f1", "precision", "recall"], "model_name": "sentence-compression", "pipeline_tag": null, "tags": ["generated_from_trainer"]} | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sentence-compression
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) ... | null | [
"apache-2.0"
] | null | null | null | null | [
"accuracy",
"f1",
"precision",
"recall"
] | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1746a1 | Alexander-Learn/bert-finetuned-ner-accelerate | Alexander-Learn | null | 4 | 676 | False | 2022-03-02T23:29:04Z | 2022-01-28T09:54:04Z | transformers | 0 | 0 | null | token-classification | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 6ee59b8a7c2d378653f972793eb895be41f217ae | [
"transformers",
"pytorch",
"bert",
"token-classification",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
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