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621ffdc036468d709f175396 | EhsanYB/distilbert-finetuned-ner | EhsanYB | null | 4 | 518 | False | 2022-03-02T23:29:04Z | 2022-01-14T10:09:06Z | transformers | 0 | 0 | null | token-classification | null | [
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621ffdc036468d709f175398 | Einmalumdiewelt/PegasusXSUM_GNAD | Einmalumdiewelt | null | 32 | 11,968 | False | 2022-03-02T23:29:04Z | 2022-08-26T15:53:31Z | transformers | 1 | 0 | [{"name": "PegasusXSUM_GNAD", "results": []}] | summarization | null | [
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] | null | {"architectures": ["PegasusForConditionalGeneration"], "model_type": "pegasus", "tokenizer_config": {"eos_token": "</s>", "mask_token": "<mask_2>", "pad_token": "<pad>", "unk_token": "<unk>"}} | {
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should probably proofread and complete it, then remove this comment. -->
# PegasusXSUM_GNAD
This model is a fine-tuned version of [Einmalumdiewelt/PegasusXSUM_GNAD](https://huggingface.co/Einmalumdiewelt/... | null | null | null | [
"de"
] | null | null | [
"rouge"
] | [
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"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175399 | Einmalumdiewelt/T5-Base_GNAD | Einmalumdiewelt | null | 87 | 446,802 | False | 2022-03-02T23:29:04Z | 2022-08-26T15:55:55Z | transformers | 22 | 0 | [{"name": "T5-Base_GNAD", "results": []}] | summarization | null | [
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should probably proofread and complete it, then remove this comment. -->
# T5-Base_GNAD
This model is a fine-tuned version of [Einmalumdiewelt/T5-Base_GNAD](https://huggingface.co/Einmalumdiewelt/T5-Base_... | null | null | null | [
"de"
] | null | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation",
"summarization"
] | [
"text"
] | [
"text"
] | [
"text"
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621ffdc036468d709f1753bc | EleutherAI/gpt-neo-125m | EleutherAI | null | 529,162 | 7,937,002 | False | 2022-03-02T23:29:04Z | 2024-01-31T20:29:39Z | transformers | 227 | 0 | null | text-generation | {"parameters": {"F32": 125198592, "U8": 25165824}, "total": 150364416} | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
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"model.safetensors",
"pytorch_model.bin",
"rust_model.ot",
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"tokenizer.json",
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"vocab.json"
] | 21def0189f5705e2521767faed922f1f15e7d7db | [
"transformers",
"pytorch",
"jax",
"rust",
"safetensors",
"gpt_neo",
"text-generation",
"text generation",
"causal-lm",
"en",
"dataset:EleutherAI/pile",
"arxiv:2101.00027",
"license:mit",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["GPTNeoForCausalLM"], "model_type": "gpt_neo", "tokenizer_config": {"bos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normalized": true, "rstrip": false, "single_word": false}, "eos_token": {"__type": "AddedToken", "content": "<|endoftext|>", "lstrip": false, "normal... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["EleutherAI/pile"], "eval_results": null, "language": ["en"], "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["text generation", "pytorch", "causal-lm"]} | # GPT-Neo 125M
## Model Description
GPT-Neo 125M is a transformer model designed using EleutherAI's replication of the GPT-3 architecture. GPT-Neo refers to the class of models, while 125M represents the number of parameters of this particular pre-trained model.
## Training data
GPT-Neo 125M was trained on the Pile... | null | [
"mit"
] | [
"EleutherAI/pile"
] | [
"en"
] | 150,364,416 | null | null | [
"gpt_neo",
"AutoModelForCausalLM",
"GPTNeoForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f1753d2 | Elron/bleurt-base-128 | Elron | null | 9,214 | 627,005 | False | 2022-03-02T23:29:04Z | 2021-10-04T13:24:42Z | transformers | 3 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 3dabe1a4ba7ca2041f5455262780ab797f0f7d0b | [
"transformers",
"pytorch",
"bert",
"text-classification",
"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"
} | null | \n## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](http... | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1753d3 | Elron/bleurt-base-512 | Elron | null | 61,713 | 269,828 | False | 2022-03-02T23:29:04Z | 2021-10-04T13:23:33Z | 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"
] | 4f4abeeba7c29ded45fc90b8a66eb49c8569f587 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"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"
} | null | \n## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](http... | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1753d4 | Elron/bleurt-large-128 | Elron | null | 7 | 44,237 | False | 2022-03-02T23:29:04Z | 2021-10-04T13:21:56Z | transformers | 2 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 17bb269ba6cede0f50f3831f444fdb7222147ceb | [
"transformers",
"pytorch",
"bert",
"text-classification",
"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"
} | null | \n## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](http... | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1753d5 | Elron/bleurt-large-512 | Elron | null | 81 | 133,685 | False | 2022-03-02T23:29:04Z | 2021-12-15T01:57:26Z | 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"
] | 00397b0917e464c5ca1a45db156d0b836cd65e97 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"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"
} | null | ## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](https:... | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1753d6 | Elron/bleurt-tiny-128 | Elron | null | 10 | 4,539 | False | 2022-03-02T23:29:04Z | 2021-10-04T13:27:02Z | transformers | 2 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 1607b0b88c88390663970418ac61d4ff95ecf594 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"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"
} | null | \n## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](http... | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1753d7 | Elron/bleurt-tiny-512 | Elron | null | 52,031 | 3,157,036 | False | 2022-03-02T23:29:04Z | 2022-11-26T15:13:43Z | transformers | 4 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 82430b75718a0647fc49b9216ccdd9f0b30dfa72 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"arxiv:1910.09700",
"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": 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": ["text-classification", "bert"]} | # Model Card for bleurt-tiny-512
# Model Details
## Model Description
Pytorch version of the original BLEURT models from ACL paper
- **Developed by:** Elron Bandel, Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research
- **Shared by [Optional]:** Elron Bandel
- **Model type:** Text Classificatio... | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1753d8 | Elzen7/DialoGPT-medium-harrypotter | Elzen7 | null | 6 | 672 | False | 2022-03-02T23:29:04Z | 2021-10-19T07:54:41Z | 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"
] | 840c6f973ad0398b2c6308150baca7a4036923ce | [
"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"
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621ffdc036468d709f1753f5 | Emanuel/autonlp-pos-tag-bosque | Emanuel | null | 15 | 3,991 | False | 2022-03-02T23:29:04Z | 2021-10-19T12:09:29Z | transformers | 3 | 0 | null | token-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"sample_input.pkl",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 145a83cb3b508cd334eae8dcfa370ed653a9308d | [
"transformers",
"pytorch",
"bert",
"token-classification",
"pt",
"dataset:Emanuel/autonlp-data-pos-tag-bosque",
"co2_eq_emissions",
"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": ["Emanuel/autonlp-data-pos-tag-bosque"], "eval_results": null, "language": "pt", "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: Entity Extraction
- Model ID: 21124427
- CO2 Emissions (in grams): 6.2107269129101805
## Validation Metrics
- Loss: 0.09813392907381058
- Accuracy: 0.9714309035997062
- Precision: 0.9721275936822545
- Recall: 0.9735345807918949
- F1: 0.9728305785123967
## Usage
You can... | null | null | [
"Emanuel/autonlp-data-pos-tag-bosque"
] | [
"pt"
] | null | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1753f8 | Emanuel/roebrta-base-val-test | Emanuel | null | 3 | 487 | False | 2022-03-02T23:29:04Z | 2022-01-23T15:12:04Z | transformers | 0 | 0 | [{"name": "language-modeling", "results": []}] | fill-mask | null | [
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"trainer_state.json",
"training_args.bin",
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] | ebaec6c4ae89212cd7c1e5c449813f9182f1943a | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForMaskedLM"], "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>"}} | {
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"pipeline_tag": "fill-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": "language-modeling", "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. -->
# language-modeling
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
... | null | [
"mit"
] | null | null | null | null | null | [
"roberta",
"AutoModelForMaskedLM",
"RobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1753ff | Emi2160/DialoGPT-small-Neku | Emi2160 | null | 6 | 6 | False | 2022-03-02T23:29:04Z | 2021-06-03T14:04:12Z | 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"
] | 23b31e63815f7d61ff93e377c836a9015eae67c9 | [
"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"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175400 | EmileAjar/DialoGPT-small-harrypotter | EmileAjar | null | 4 | 608 | False | 2022-03-02T23:29:04Z | 2021-08-28T00:29:03Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
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"config.json",
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"pytorch_model.bin",
"special_tokens_map.json",
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"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 0ecbbd86635a65c31225d7fbc6e6b4e55096a4e1 | [
"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"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175401 | EmileAjar/DialoGPT-small-peppapig | EmileAjar | null | 11 | 11 | False | 2022-03-02T23:29:04Z | 2021-08-28T13:49:05Z | 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"
] | f731e4e1c8b812f0d66d6c9c6aa9a457b805f26e | [
"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"
] |
621ffdc036468d709f175404 | Emily/fyp | Emily | null | 5 | 705 | False | 2022-03-02T23:29:04Z | 2022-01-22T06:02:10Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 26241a2ffd2db16b9a9be6f1ff287c0101f96b16 | [
"transformers",
"pytorch",
"bert",
"text-classification",
"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"
} | null | null | null | null | null | null | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175409 | Emmanuel/bert-finetuned-ner | Emmanuel | null | 5 | 604 | False | 2022-03-02T23:29:04Z | 2021-12-01T11:05:45Z | transformers | 0 | 0 | [{"name": "bert-finetuned-ner", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "conll2003", "type": "conll2003", "args": "conll2003"}, "metrics": [{"name": "Precision", "type": "precision", "value": 0.9317394888705688, "verified": false}, {"name": "Recall", "t... | token-classification | null | [
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"README.md",
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"pytorch_model.bin",
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"runs/Dec01_10-25-57_d118394a288... | a6e1e133d710c8cbd1c251326c220fd6a366098f | [
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"bert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"model-index",
"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"
} | {"datasets": ["conll2003"], "license": "apache-2.0", "metrics": ["precision", "recall", "f1", "accuracy"], "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type": "c... | <!-- 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-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll20... | null | [
"apache-2.0"
] | [
"conll2003"
] | null | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17541b | EnsarEmirali/distilbert-base-uncased-finetuned-emotion | EnsarEmirali | null | 7 | 766 | False | 2022-03-02T23:29:04Z | 2022-02-21T05:53:26Z | transformers | 0 | 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": 0.9265, "verified": false}, {"name": "F1", "type... | text-classification | null | [
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"README.md",
"config.json",
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"runs/Feb20_12-38-26_ensars-mbp/1645350542.35106/events.out.tfevents.1645350542.ensars-mbp.9091.1",
"runs/Feb20_12-38-26_ensars-mbp/events.out.tfevents.1645350542.ensars-mbp.9091.0",
"special_tokens_map.json",
"tokenize... | 7d13520ba2e005fbc05dd35a810e032dc9c5473a | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"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": ["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"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175423 | Erfan/mT5-base_Farsi_Title_Generator | Erfan | null | 6 | 761 | False | 2022-03-02T23:29:04Z | 2022-01-30T18:00:42Z | transformers | 2 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | ed8751a5c39c542be15e48e9fdc3b499b0ab77ba | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"Title-Generation",
"fa",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MT5ForConditionalGeneration"], "model_type": "mt5", "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": null, "eval_results": null, "language": ["fa"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["ROUGH"], "model_name": null, "pipeline_tag": null, "tags": ["Title-Generation"]} | null | null | null | [
"fa"
] | null | null | [
"ROUGH"
] | [
"mt5",
"MT5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null | |
621ffdc036468d709f175424 | Erfan/mT5-base_Farsi_Title_Generator_plus | Erfan | null | 5 | 465 | False | 2022-03-02T23:29:04Z | 2022-02-10T13:43:30Z | transformers | 2 | 0 | null | null | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | e56692735a2b28617161def5247f99310a773f64 | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MT5ForConditionalGeneration"], "model_type": "mt5", "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 | [
"mt5",
"MT5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc036468d709f175425 | Erfan/mT5-small_Farsi_Title_Generator | Erfan | null | 5 | 617 | False | 2022-03-02T23:29:04Z | 2023-10-24T08:50:09Z | transformers | 1 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tokenizer.json",
"tokenizer_config.json"
] | 4a35152f7abd0b122e1f84d3a2467cf20877c856 | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"Title-Generation",
"en",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["MT5ForConditionalGeneration"], "model_type": "mt5", "tokenizer_config": {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForSeq2SeqLM",
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"pipeline_tag": "text2text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": ["en"], "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": ["ROUGH"], "model_name": null, "pipeline_tag": null, "tags": ["Title-Generation"]} | null | null | null | [
"en"
] | null | null | [
"ROUGH"
] | [
"mt5",
"MT5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null | |
621ffdc036468d709f17542f | Erikaka/DialoGPT-small-loki | Erikaka | null | 9 | 5,032 | False | 2022-03-02T23:29:04Z | 2021-09-10T13:32:41Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
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"eval_results.txt",
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"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 7e6f8ce678ddb35c5f5124c65742f6e15cf9b04b | [
"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"
] |
621ffdc036468d709f17543a | EstoyDePaso/DialoGPT-small-harrypotter | EstoyDePaso | null | 6 | 636 | False | 2022-03-02T23:29:04Z | 2021-09-19T19:04:42Z | 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"
] | 503c7390ce9ff0b81da7fe28bcc01f9fe90e5145 | [
"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"
] |
621ffdc036468d709f17543c | EthanChen0418/domain-cls-nine-classes | EthanChen0418 | null | 7 | 1,530 | False | 2022-03-02T23:29:04Z | 2021-09-27T04:35:15Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 79acb0f68d410dc5e495ae9c3350c970802c1fb0 | [
"transformers",
"pytorch",
"bart",
"text-classification",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BartForSequenceClassification"], "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, "... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"BartForSequenceClassification",
"bart",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17543d | EthanChen0418/few-shot-model-five-classes | EthanChen0418 | null | 9 | 1,399 | False | 2022-03-02T23:29:04Z | 2021-08-04T13:04:58Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
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621ffdc036468d709f17543e | EthanChen0418/intent_cls | EthanChen0418 | null | 8 | 1,840 | False | 2022-03-02T23:29:04Z | 2021-08-30T04:42:18Z | transformers | 0 | 0 | null | text-classification | null | [
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621ffdc036468d709f17543f | EthanChen0418/seven-classed-domain-cls | EthanChen0418 | null | 8 | 942 | False | 2022-03-02T23:29:04Z | 2021-08-26T07:05:04Z | transformers | 0 | 0 | null | text-classification | null | [
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621ffdc036468d709f175440 | EthanChen0418/six-classed-domain-cls | EthanChen0418 | null | 6 | 659 | False | 2022-03-02T23:29:04Z | 2021-08-21T17:25:56Z | transformers | 0 | 0 | null | text-classification | null | [
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621ffdc036468d709f175442 | Eugenia/roberta-base-bne-finetuned-amazon_reviews_multi | Eugenia | null | 124 | 1,481 | False | 2022-03-02T23:29:04Z | 2021-11-16T00:32:57Z | transformers | 0 | 0 | null | text-classification | null | [
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621ffdc036468d709f175447 | Eunooeh/mnmt_gpt2 | Eunooeh | null | 6 | 640 | False | 2022-03-02T23:29:04Z | 2021-12-13T02:53:13Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f175449 | EuropeanTurtle/DialoGPT-small-mrcobb | EuropeanTurtle | null | 11 | 5,078 | False | 2022-03-02T23:29:04Z | 2021-11-13T10:14:38Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f17544e | Evgen/model_awara_text | Evgen | null | 4 | 603 | False | 2022-03-02T23:29:04Z | 2022-02-09T07:56:40Z | transformers | 0 | 0 | null | feature-extraction | null | [
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621ffdc036468d709f17544f | Evgeneus/distilbert-base-uncased-finetuned-ner | Evgeneus | null | 7 | 562 | False | 2022-03-02T23:29:04Z | 2021-12-13T11:57:39Z | transformers | 0 | 0 | [{"name": "distilbert-base-uncased-finetuned-ner", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "conll2003", "type": "conll2003", "args": "conll2003"}, "metrics": [{"name": "Precision", "type": "precision", "value": 0.875445994161531, "verified": false}, {"n... | token-classification | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dist... | null | [
"apache-2.0"
] | [
"conll2003"
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621ffdc036468d709f17545b | Exilon/DialoGPT-large-quirk | Exilon | null | 4 | 852 | False | 2022-03-02T23:29:04Z | 2021-12-08T09:37:40Z | transformers | 0 | 0 | null | text-generation | null | [
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] | 02c8b42ceda9fb042ee4b5434c6e18e32eb6d3f1 | [
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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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621ffdc036468d709f175464 | EzioDD/house | EzioDD | null | 7 | 640 | False | 2022-03-02T23:29:04Z | 2021-12-31T09:41:57Z | transformers | 0 | 0 | null | text-generation | null | [
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"vocab.json"
] | 820d408b33d56e1dd9358063666d5d2d030dad5c | [
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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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621ffdc036468d709f175467 | FFF000/dialogpt-FFF | FFF000 | null | 6 | 652 | False | 2022-03-02T23:29:04Z | 2021-12-22T13:21:00Z | transformers | 0 | 0 | null | text-generation | null | [
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} | null | null | null | null | null | null | null | null | null | [
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621ffdc036468d709f175469 | FOFer/distilbert-base-uncased-finetuned-squad | FOFer | null | 5 | 485 | False | 2022-03-02T23:29:04Z | 2022-02-23T04:37:46Z | transformers | 0 | 0 | [{"name": "distilbert-base-uncased-finetuned-squad", "results": []}] | question-answering | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | null | [
"apache-2.0"
] | [
"squad_v2"
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"AutoModelForQuestionAnswering",
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] | [
"text"
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621ffdc036468d709f17546f | FabioDataGeek/distilbert-base-uncased-finetuned-emotion | FabioDataGeek | null | 6 | 756 | False | 2022-03-02T23:29:04Z | 2022-07-22T16:02:35Z | transformers | 0 | 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": 0.926, "verified": false}, {"name": "F1", "type"... | text-classification | null | [
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} | {"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"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17547b | Fan-s/reddit-tc-bert | Fan-s | null | 25 | 2,285 | False | 2022-03-02T23:29:04Z | 2022-02-22T05:25:39Z | transformers | 0 | 0 | {"error": "Schema validation error. \"model-index[0].results\" is required"} | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"trainer_state.json",
"training_args.bin",
"vocab.txt"
] | 1ac96d442a0162b9574dea6c692be64b460b446b | [
"transformers",
"pytorch",
"bert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"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": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": null, "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-uncased-base
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an Reddi... | null | [
"apache-2.0"
] | null | null | null | null | [
"accuracy"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17547d | FangLee/DialoGPT-small-Kirito | FangLee | null | 11 | 11 | False | 2022-03-02T23:29:04Z | 2021-09-04T14:25:26Z | 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"
] | b367d8ac8cbfabbaeb96bfd98a3f4550687daa99 | [
"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"
] |
621ffdc036468d709f17547f | FardinSaboori/bert-finetuned-squad | FardinSaboori | null | 5 | 1,288 | False | 2022-03-02T23:29:04Z | 2022-02-28T06:22:27Z | transformers | 0 | 0 | [{"name": "bert-finetuned-squad", "results": []}] | question-answering | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Feb28_04-34-40_47a69c317bc8/1646022892.7258244/events.out.tfevents.1646022892.47a69c317bc8.83.1",
"runs/Feb28_04-34-40_47a69c317bc8/events.out.tfevents.1646022892.47a69c317bc8.83.0",
"special_tokens_map.json",
"to... | 3223050ad77224f1c2a9b26dea136bbac8010605 | [
"transformers",
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"bert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForQuestionAnswering"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad"], "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "bert-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. -->
# bert-finetuned-squad
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the squad... | null | [
"apache-2.0"
] | [
"squad"
] | null | null | null | null | [
"AutoModelForQuestionAnswering",
"bert",
"BertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17548e | Fauzan/autonlp-judulberita-32517788 | Fauzan | null | 6 | 664 | False | 2022-03-02T23:29:04Z | 2021-11-13T15:12:57Z | 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"
] | 93beb34a46b5cdee79e82440fa936500cc58271c | [
"transformers",
"pytorch",
"bert",
"text-classification",
"unk",
"dataset:Fauzan/autonlp-data-judulberita",
"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": ["Fauzan/autonlp-data-judulberita"], "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: Binary Classification
- Model ID: 32517788
- CO2 Emissions (in grams): 0.9413042739759596
## Validation Metrics
- Loss: 0.32112351059913635
- Accuracy: 0.8641304347826086
- Precision: 0.8055555555555556
- Recall: 0.8405797101449275
- AUC: 0.9493383742911153
- F1: 0.82269... | null | null | [
"Fauzan/autonlp-data-judulberita"
] | [
"unk"
] | null | null | null | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1754d1 | Fiddi/distilbert-base-uncased-finetuned-ner | Fiddi | null | 9 | 642 | False | 2022-03-02T23:29:04Z | 2021-10-10T20:08:19Z | transformers | 0 | 0 | [{"name": "distilbert-base-uncased-finetuned-ner", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "conll2003", "type": "conll2003", "args": "conll2003"}, "metrics": [{"name": "Precision", "type": "precision", "value": 0.9290544285555925, "verified": false}, {"... | token-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Oct05_22-56-58_094518a13661/1633474633.9027689/events.out.tfevents.1633474633.094518a13661.76.1",
"runs/Oct05_22-56-58_094518a13661/events.out.tfevents.1633474633.094518a13661.76.0",
"runs/Oct05_22-56-58_094518a1366... | e7cdeec3384018959d1468961a46ebedc4228290 | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"model-index",
"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"
} | {"datasets": ["conll2003"], "license": "apache-2.0", "metrics": ["precision", "recall", "f1", "accuracy"], "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "con... | <!-- 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-ner
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dist... | null | [
"apache-2.0"
] | [
"conll2003"
] | null | null | null | [
"precision",
"recall",
"f1",
"accuracy"
] | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1754d8 | Filosofas/DialoGPT-medium-PALPATINE | Filosofas | null | 21 | 67,313 | False | 2022-03-02T23:29:04Z | 2022-02-08T11:50:03Z | transformers | 1 | 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"
] | 321b76cbcf40d9c9efa7776ba1eb80be7946211a | [
"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"
] |
621ffdc036468d709f1754dd | Finnish-NLP/convbert-base-finnish | Finnish-NLP | null | 17 | 5,554 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:15:25Z | transformers | 2 | 0 | null | feature-extraction | null | [
".gitattributes",
"README.md",
"build_data.sh",
"config.json",
"configure_pretraining.py",
"dataset_to_sentences.py",
"pytorch_model.bin",
"runs/events.out.tfevents.1641404286.t1v-n-8eba1090-w-0",
"special_tokens_map.json",
"tf_model.h5",
"tf_rename_checkpoint_variables.py",
"tokenizer.json",
... | 7ca436faf91f685e3a8137bec726012cf88fcbcf | [
"transformers",
"pytorch",
"tf",
"tensorboard",
"convbert",
"feature-extraction",
"finnish",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"arxiv:2008.02496",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["ConvBertModel"], "model_type": "convbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": "feature-extraction",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Finnish-NLP/mc4_fi_cleaned", "wikipedia"], "eval_results": null, "language": ["fi"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finnish", "convbert"]} | # ConvBERT for Finnish
Pretrained ConvBERT model on Finnish language using a replaced token detection (RTD) objective. ConvBERT was introduced in
[this paper](https://arxiv.org/abs/2008.02496)
and first released at [this page](https://github.com/yitu-opensource/ConvBert).
**Note**: this model is the ConvBERT discrimi... | null | [
"apache-2.0"
] | [
"Finnish-NLP/mc4_fi_cleaned",
"wikipedia"
] | [
"fi"
] | null | null | null | [
"ConvBertModel",
"AutoModel",
"convbert"
] | [
"feature-extraction"
] | [
"multimodal"
] | [
"text"
] | [
"embeddings"
] |
621ffdc036468d709f1754de | Finnish-NLP/convbert-base-generator-finnish | Finnish-NLP | null | 12 | 647 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:15:42Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"convert_original_convbert_tf_checkpoint_to_generator_pytorch.py",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 4e05e88b590ad06f57c36df4410e5475387c30dc | [
"transformers",
"pytorch",
"convbert",
"fill-mask",
"finnish",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"arxiv:2008.02496",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["ConvBertForMaskedLM"], "model_type": "convbert", "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": ["Finnish-NLP/mc4_fi_cleaned", "wikipedia"], "eval_results": null, "language": ["fi"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finnish", "convbert"], "widget": [{"text... | # ConvBERT for Finnish
Pretrained ConvBERT model on Finnish language using a replaced token detection (RTD) objective. ConvBERT was introduced in
[this paper](https://arxiv.org/abs/2008.02496)
and first released at [this page](https://github.com/yitu-opensource/ConvBert).
**Note**: this model is the ConvBERT generato... | null | [
"apache-2.0"
] | [
"Finnish-NLP/mc4_fi_cleaned",
"wikipedia"
] | [
"fi"
] | null | null | null | [
"ConvBertForMaskedLM",
"AutoModelForMaskedLM",
"convbert"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1754e0 | Finnish-NLP/electra-base-discriminator-finnish | Finnish-NLP | null | 7 | 513 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:14:27Z | transformers | 1 | 0 | null | null | null | [
".gitattributes",
"README.md",
"config.json",
"configure_pretraining.py",
"pytorch_model.bin",
"runs/1M/events.out.tfevents.1644944635.t1v-n-9798b699-w-0",
"runs/900k/events.out.tfevents.1642860661.t1v-n-8eba1090-w-0",
"special_tokens_map.json",
"tf_rename_checkpoint_variables.py",
"tokenizer.json... | cea3059be27d2b56aeae92e58e92b8fbbfd62f44 | [
"transformers",
"pytorch",
"tensorboard",
"electra",
"pretraining",
"finnish",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["ElectraForPreTraining"], "model_type": "electra", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForPreTraining",
"custom_class": null,
"pipeline_tag": "pretraining",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Finnish-NLP/mc4_fi_cleaned", "wikipedia"], "eval_results": null, "language": ["fi"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finnish", "electra"]} | # ELECTRA for Finnish
Pretrained ELECTRA model on Finnish language using a replaced token detection (RTD) objective. ELECTRA was introduced in
[this paper](https://openreview.net/pdf?id=r1xMH1BtvB)
and first released at [this page](https://github.com/google-research/electra).
**Note**: this model is the ELECTRA discr... | null | [
"apache-2.0"
] | [
"Finnish-NLP/mc4_fi_cleaned",
"wikipedia"
] | [
"fi"
] | null | null | null | [
"ElectraForPreTraining",
"AutoModelForPreTraining",
"electra"
] | [
"pretraining"
] | null | null | null |
621ffdc036468d709f1754e1 | Finnish-NLP/electra-base-generator-finnish | Finnish-NLP | null | 4 | 501 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:14:44Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 5e18a40e71b475212511eef55e538f0db186970d | [
"transformers",
"pytorch",
"electra",
"fill-mask",
"finnish",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"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": ["Finnish-NLP/mc4_fi_cleaned", "wikipedia"], "eval_results": null, "language": ["fi"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finnish", "electra"], "widget": [{"text"... | # ELECTRA for Finnish
Pretrained ELECTRA model on Finnish language using a replaced token detection (RTD) objective. ELECTRA was introduced in
[this paper](https://openreview.net/pdf?id=r1xMH1BtvB)
and first released at [this page](https://github.com/google-research/electra).
**Note**: this model is the ELECTRA gener... | null | [
"apache-2.0"
] | [
"Finnish-NLP/mc4_fi_cleaned",
"wikipedia"
] | [
"fi"
] | null | null | null | [
"ElectraForMaskedLM",
"AutoModelForMaskedLM",
"electra"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f1754e3 | Finnish-NLP/gpt2-finnish | Finnish-NLP | null | 26 | 9,152 | False | 2022-03-02T23:29:04Z | 2025-07-24T17:51:28Z | transformers | 2 | 0 | null | text-generation | {"parameters": {"F32": 124439808, "U8": 12582912}, "total": 137022720} | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"distributed_shampoo.py",
"flax_model.msgpack",
"flax_model_to_pytorch.py",
"merges.txt",
"model.safetensors",
"pytorch_model.bin",
"replace_token_script.py",
"run_clm_flax.py",
"runs/events.out.tfevents.1642236904.t1v-n-4214... | 9c5d6d38a4b2b4066b11be8e3195aab4bba00c86 | [
"transformers",
"pytorch",
"jax",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"finnish",
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": ["Finnish-NLP/mc4_fi_cleaned", "wikipedia"], "eval_results": null, "language": ["fi"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finnish", "gpt2"], "widget": [{"text": "... | null | null | [
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621ffdc036468d709f1754e7 | Finnish-NLP/gpt2-large-finnish | Finnish-NLP | null | 4,439 | 8,287 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:14:00Z | transformers | 2 | 0 | null | text-generation | null | [
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}} | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": ["Finnish-NLP/mc4_fi_cleaned", "wikipedia"], "eval_results": null, "language": ["fi"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finnish", "gpt2"], "widget": [{"text": "... | # GPT-2 large for Finnish
Pretrained GPT-2 large model on Finnish language using a causal language modeling (CLM) objective. GPT-2 was introduced in
[this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)
and first released at [this page](https:/... | null | [
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621ffdc036468d709f1754e8 | Finnish-NLP/gpt2-medium-finnish | Finnish-NLP | null | 13 | 5,399 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:14:13Z | transformers | 3 | 0 | null | text-generation | null | [
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Pretrained GPT-2 medium model on Finnish language using a causal language modeling (CLM) objective. GPT-2 was introduced in
[this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)
and first released at [this page](https... | null | [
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621ffdc036468d709f1754ea | Finnish-NLP/roberta-large-finnish-v2 | Finnish-NLP | null | 6 | 2,452 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:11:54Z | transformers | 0 | 0 | null | fill-mask | null | [
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"runs/128_1/events.out.tfevents.1637935644.t1v-n-8eba1090-w-0.892912.0.v... | 968ba8c12c1513ca4d57ddf40f24c6c40817280f | [
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"region:us"
] | null | {"architectures": ["RobertaForMaskedLM"], "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": "AutoModelForMaskedLM",
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} | {"base_model": null, "datasets": ["Finnish-NLP/mc4_fi_cleaned", "wikipedia"], "eval_results": null, "language": ["fi"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finnish", "roberta"], "widget": [{"text"... | # RoBERTa large model for Finnish
This **Finnish-NLP/roberta-large-finnish-v2** model is a new version of the previously trained [Finnish-NLP/roberta-large-finnish](https://huggingface.co/Finnish-NLP/roberta-large-finnish) model. Training hyperparameters were same but the training dataset was cleaned better with the g... | null | [
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"fi"
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621ffdc036468d709f1754ec | Finnish-NLP/roberta-large-finnish | Finnish-NLP | null | 16 | 2,552 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:13:07Z | transformers | 5 | 0 | null | fill-mask | null | [
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"pipeline_tag": "fill-mask",
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Pretrained RoBERTa model on Finnish language using a masked language modeling (MLM) objective. RoBERTa was introduced in
[this paper](https://arxiv.org/abs/1907.11692) and first released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/roberta). This model ... | null | [
"apache-2.0"
] | [
"Finnish-NLP/mc4_fi_cleaned",
"wikipedia"
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"fi"
] | null | null | null | [
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621ffdc036468d709f1754ed | Finnish-NLP/roberta-large-wechsel-finnish | Finnish-NLP | null | 7 | 1,249 | False | 2022-03-02T23:29:04Z | 2022-06-13T16:13:27Z | transformers | 1 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
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"merges.txt",
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"runs/512/events.out.tfevents.1640023857.t1v-n-8eba10... | d12d05c3dd60b277728436a5cea6e50262f2d749 | [
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"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForMaskedLM"], "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": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["Finnish-NLP/mc4_fi_cleaned", "wikipedia"], "eval_results": null, "language": ["fi"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["finnish", "roberta"], "widget": [{"text"... | # RoBERTa large model trained with WECHSEL method for Finnish
Pretrained RoBERTa model on Finnish language using a masked language modeling (MLM) objective with WECHSEL method. RoBERTa was introduced in
[this paper](https://arxiv.org/abs/1907.11692) and first released in
[this repository](https://github.com/pytorch/fa... | null | [
"apache-2.0"
] | [
"Finnish-NLP/mc4_fi_cleaned",
"wikipedia"
] | [
"fi"
] | null | null | null | [
"roberta",
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"RobertaForMaskedLM"
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] | [
"text"
] | [
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621ffdc036468d709f1754ef | Fiona99/distilbert-base-uncased-finetuned-cola | Fiona99 | null | 7 | 662 | False | 2022-03-02T23:29:04Z | 2021-12-10T08:05:41Z | transformers | 0 | 0 | null | 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]"}} | {
"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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621ffdc036468d709f1754f0 | Firat/albert-base-v2-finetuned-squad | Firat | null | 4 | 712 | False | 2022-03-02T23:29:04Z | 2022-01-11T09:15:49Z | transformers | 0 | 0 | [{"name": "albert-base-v2-finetuned-squad", "results": []}] | question-answering | null | [
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] | b069240bc30bdd0d6d2126fa5274d75d8a4e1f84 | [
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] | 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... | {
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"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad"], "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"
] | null | null | null | null | [
"AutoModelForQuestionAnswering",
"albert",
"AlbertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f1754f1 | Firat/distilbert-base-uncased-finetuned-squad | Firat | null | 4 | 477 | False | 2022-03-02T23:29:04Z | 2022-01-26T19:05:23Z | transformers | 0 | 0 | [{"name": "distilbert-base-uncased-finetuned-squad", "results": []}] | question-answering | null | [
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"special_token... | 8f1fb3d867effd2f9d7f71fabb2299f28451e297 | [
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"dataset:squad",
"license:apache-2.0",
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] | null | {"architectures": ["DistilBertForQuestionAnswering"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForQuestionAnswering",
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"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad"], "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": "distilbert-base-uncased-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. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | null | [
"apache-2.0"
] | [
"squad"
] | null | null | null | null | [
"AutoModelForQuestionAnswering",
"distilbert",
"DistilBertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f1754f2 | Firat/roberta-base-finetuned-squad | Firat | null | 5 | 630 | False | 2022-03-02T23:29:04Z | 2022-01-09T22:12:48Z | transformers | 0 | 0 | [{"name": "roberta-base-finetuned-squad", "results": []}] | question-answering | null | [
".gitattributes",
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"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 19505872759531fd835455069fa3ae50175907dd | [
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"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
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] | null | {"architectures": ["RobertaForQuestionAnswering"], "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": "AutoModelForQuestionAnswering",
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"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad"], "eval_results": [], "language": null, "library_name": null, "license": "mit", "license_name": null, "license_link": null, "metrics": null, "model_name": "roberta-base-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. -->
# roberta-base-finetuned-squad
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the squ... | null | [
"mit"
] | [
"squad"
] | null | null | null | null | [
"roberta",
"AutoModelForQuestionAnswering",
"RobertaForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f1754ff | Flampt/DialoGPT-medium-Sheldon | Flampt | null | 4 | 4 | False | 2022-03-02T23:29:04Z | 2021-08-28T14:17:44Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
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"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
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] | 424d62c7b7f1cc602c38aa1a0303cc5ee08e3137 | [
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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"]} | # Sheldon Cooper from The Big Bang Theory Show DialoGPT Model | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17551c | For/sheldonbot | For | null | 5 | 821 | False | 2022-03-02T23:29:04Z | 2021-06-02T15:54:07Z | 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"
] | 8e6de275bbf08d6e8ff7400adb97d9eb2eef21bf | [
"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"
] | [
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] | [
"text"
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"text"
] |
621ffdc036468d709f175520 | ForutanRad/bert-fa-QA-v1 | ForutanRad | null | 6 | 2,196 | False | 2022-03-02T23:29:04Z | 2021-07-26T03:51:47Z | transformers | 2 | 0 | null | question-answering | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Jul25_11-42-32_ea93e63c112a/1627213414.518686/events.out.tfevents.1627213414.ea93e63c112a.61.1",
"runs/Jul25_11-42-32_ea93e63c112a/events.out.tfevents.1627213414.ea93e63c112a.61.0",
"runs/Jul25_12-43-49_ea93e63c112a... | 2f4043b809c6745b6c83cdb81c8e831b0e5df137 | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"arxiv:2005.12515",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["BertForQuestionAnswering"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"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": "bert-fa-QA-v1", "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-fa-QA-v1
Persian Question and answer Model Based on Bert Model
This model is a fine-tuned version of [ParsBERT](https://arxi... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"AutoModelForQuestionAnswering",
"bert",
"BertForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175521 | FosterPatch/GoT-test | FosterPatch | null | 6 | 6 | False | 2022-03-02T23:29:04Z | 2021-10-22T22:22:19Z | 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"
] | c7ea37e4ef7593eba404a6bff29c30590e7ca726 | [
"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"
] |
621ffdc036468d709f175537 | FranzStrauss/ponet-base-uncased | FranzStrauss | null | 5 | 332 | False | 2022-03-02T23:29:04Z | 2021-12-31T17:14:32Z | transformers | 0 | 0 | null | null | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 3b4adf28ad56c7ac6e866bbf75157d8e09803208 | [
"transformers",
"pytorch",
"ponet",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["PoNetModel"], "model_type": "ponet", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModel",
"custom_class": null,
"pipeline_tag": null,
"processor": null
} | null | null | null | null | null | null | null | null | null | [
"AutoModel",
"PoNetModel",
"ponet"
] | [
null
] | null | null | null |
621ffdc036468d709f175540 | Frederick0291/t5-small-finetuned-billsum | Frederick0291 | null | 10 | 18,181 | False | 2022-03-02T23:29:04Z | 2021-09-21T08:33:18Z | transformers | 0 | 0 | [{"name": "t5-small-finetuned-billsum", "results": [{"task": {"name": "Sequence-to-sequence Language Modeling", "type": "text2text-generation"}, "dataset": {"name": "billsum", "type": "billsum", "args": "default"}, "metrics": [{"name": "Rouge1", "type": "rouge", "value": 16.6044, "verified": false}]}]}] | null | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"runs/Sep21_06-27-20_31eb754fbddc/1632205701.5717394/events.out.tfevents.1632205701.31eb754fbddc.75.1",
"runs/Sep21_06-27-20_31eb754fbddc/events.out.tfevents.1632205701.31eb754fbddc.75.0",
"special_tokens_map.json",
"sp... | be9187abf042c6fe559f5002187ce42b2550190e | [
"transformers",
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"tensorboard",
"t5",
"text2text-generation",
"generated_from_trainer",
"dataset:billsum",
"license:apache-2.0",
"model-index",
"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"
} | {"datasets": ["billsum"], "license": "apache-2.0", "metrics": ["rouge"], "tags": ["generated_from_trainer"], "model-index": [{"name": "t5-small-finetuned-billsum", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "billsum", "type": "billsum", "... | <!-- 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. -->
# t5-small-finetuned-billsum
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum datas... | null | [
"apache-2.0"
] | [
"billsum"
] | null | null | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc036468d709f175542 | Frederick0291/t5-small-finetuned-xsum | Frederick0291 | null | 8 | 9,615 | False | 2022-03-02T23:29:04Z | 2021-09-20T12:01:37Z | transformers | 0 | 0 | {"error": "Schema validation error. \"model-index[0].results[0].metrics\" is required"} | null | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin"
] | 474139923b2abd64e49cb3ec2da8f5d4479816c7 | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"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": 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"]} | <!-- 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. -->
# t5-small-finetuned-xsum-finetuned-billsum
This model is a fine-tuned version of [Frederick0291/t5-small-finetuned-xsum](https://h... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc036468d709f175555 | Fu10k/DialoGPT-medium-Rick | Fu10k | null | 10 | 5,044 | False | 2022-03-02T23:29:04Z | 2021-09-02T07:16:34Z | 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"
] | b7541f8a67ecb56110267c0f035ca674ac41e556 | [
"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"
] |
621ffdc036468d709f175559 | FuriouslyAsleep/markuplm-large-finetuned-qa | FuriouslyAsleep | null | 7 | 1,702 | False | 2022-03-02T23:29:04Z | 2022-02-10T20:30:55Z | transformers | 1 | 0 | null | question-answering | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"merges.txt",
"pytorch_model.bin",
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"vocab.json"
] | ed8e8dd012ad26dcfac4b7edbf8b192d5b0e5e1d | [
"transformers",
"pytorch",
"markuplm",
"question-answering",
"arxiv:2110.08518",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MarkupLMForQuestionAnswering"], "model_type": "markuplm", "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... | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoProcessor"
} | null | ---------------------------------------------------------------------------
**Fine-tuned Multimodal (text +markup language) pre-training for [Document AI](https://www.microsoft.com/en-us/research/project/document-ai/)**
## Introduction (From Microsoft MarkupLM Large Model Card)
MarkupLM is a simple but effective mu... | null | null | null | null | null | null | null | [
"AutoModelForQuestionAnswering",
"MarkupLMForQuestionAnswering",
"markuplm"
] | [
"question-answering"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17557d | GKLMIP/roberta-hindi-romanized | GKLMIP | null | 12 | 2,570 | False | 2022-03-02T23:29:04Z | 2021-10-13T13:46:13Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | cc3e71e4199aae4f1dd10236ee7bc1aa428a9e4b | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForMaskedLM"], "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": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | If you use our model, please consider citing our paper:
```
@InProceedings{,
author="Huang, Xixuan
and Lin, Nankai
and Li, Kexin
and Wang, Lianxi
and Gan SuiFu",
title="HinPLMs: Pre-trained Language Models for Hindi",
booktitle="The International Conference on Asian Language Processing",
year="2021",
publisher="IEEE Xp... | null | null | null | null | null | null | null | [
"roberta",
"AutoModelForMaskedLM",
"RobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f17557e | GKLMIP/roberta-hindi-devanagari | GKLMIP | null | 14 | 3,034 | False | 2022-03-02T23:29:04Z | 2021-10-13T13:44:42Z | transformers | 0 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 01638bde90af5e599d33b30502208648a874b64f | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForMaskedLM"], "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": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | null | If you use our model, please consider citing our paper:
```
@InProceedings{,
author="Huang, Xixuan
and Lin, Nankai
and Li, Kexin
and Wang, Lianxi
and Gan SuiFu",
title="HinPLMs: Pre-trained Language Models for Hindi",
booktitle="The International Conference on Asian Language Processing",
year="2021",
publisher="IEEE Xp... | null | null | null | null | null | null | null | [
"roberta",
"AutoModelForMaskedLM",
"RobertaForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175581 | GPL/bioasq-1m-msmarco-distilbert-gpl | GPL | null | 7 | 1,097 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:18:19Z | sentence-transformers | 0 | 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",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 92084c813b36ebb8637dbd8a4b70efff5fa2b823 | [
"sentence-transformers",
"pytorch",
"distilbert",
"feature-extraction",
"sentence-similarity",
"transformers",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["DistilBertModel"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f175582 | GPL/bioasq-1m-tsdae-msmarco-distilbert-gpl | GPL | null | 5 | 1,022 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:29:33Z | sentence-transformers | 0 | 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",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 2e5d388b8a477fed576d3013d2bc11459ca1f8cc | [
"sentence-transformers",
"pytorch",
"distilbert",
"feature-extraction",
"sentence-similarity",
"transformers",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["DistilBertModel"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f175583 | GPL/bioasq-1m-tsdae-msmarco-distilbert-margin-mse | GPL | null | 5 | 897 | False | 2022-03-02T23:29:04Z | 2022-04-19T16:49:04Z | transformers | 0 | 0 | null | feature-extraction | null | [
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621ffdc036468d709f175584 | GPL/cqadupstack-msmarco-distilbert-gpl | GPL | null | 3 | 3 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:19:20Z | sentence-transformers | 0 | 0 | null | sentence-similarity | null | [
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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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
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621ffdc036468d709f175585 | GPL/cqadupstack-tsdae-msmarco-distilbert-gpl | GPL | null | 2 | 998 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:30:49Z | sentence-transformers | 0 | 0 | null | sentence-similarity | null | [
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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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
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621ffdc036468d709f175586 | GPL/cqadupstack-tsdae-msmarco-distilbert-margin-mse | GPL | null | 7 | 900 | False | 2022-03-02T23:29:04Z | 2022-04-19T16:50:27Z | transformers | 0 | 0 | null | feature-extraction | null | [
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621ffdc036468d709f175587 | GPL/fiqa-msmarco-distilbert-gpl | GPL | null | 4 | 1,736 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:17:19Z | sentence-transformers | 0 | 0 | null | sentence-similarity | null | [
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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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
"sentence-similarity",
"feature-extraction"
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"logits",
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621ffdc036468d709f175588 | GPL/fiqa-tsdae-msmarco-distilbert-gpl | GPL | null | 3 | 932 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:28:28Z | sentence-transformers | 0 | 0 | null | sentence-similarity | null | [
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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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
"sentence-similarity",
"feature-extraction"
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621ffdc036468d709f175589 | GPL/fiqa-tsdae-msmarco-distilbert-margin-mse | GPL | null | 8 | 8,556 | False | 2022-03-02T23:29:04Z | 2022-04-19T16:47:51Z | transformers | 0 | 0 | null | feature-extraction | null | [
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621ffdc036468d709f17558a | GPL/msmarco-distilbert-margin-mse | GPL | null | 11 | 13,153 | False | 2022-03-02T23:29:04Z | 2021-12-15T04:10:19Z | transformers | 1 | 0 | null | feature-extraction | null | [
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} | null | This is the zero-shot baseline model in the paper ["GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval"](https://arxiv.org/abs/2112.07577)
The training setup:
1. Start from `distilbert-base-uncased`;
2. Mine 50 hard negatives for each query on MS MARCO with `sentence-transformers/msm... | null | null | null | null | null | null | null | [
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621ffdc036468d709f17558b | GPL/robust04-msmarco-distilbert-gpl | GPL | null | 6 | 1,039 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:19:47Z | sentence-transformers | 0 | 0 | null | sentence-similarity | null | [
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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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
"sentence-similarity",
"feature-extraction"
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"multimodal"
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"text"
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"embeddings"
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621ffdc036468d709f17558c | GPL/robust04-tsdae-msmarco-distilbert-gpl | GPL | null | 2 | 977 | False | 2022-03-02T23:29:04Z | 2022-04-19T16:30:20Z | sentence-transformers | 0 | 0 | null | sentence-similarity | null | [
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"endpoints_compatible",
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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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
"sentence-similarity",
"feature-extraction"
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621ffdc036468d709f17558d | GPL/robust04-tsdae-msmarco-distilbert-margin-mse | GPL | null | 5 | 927 | False | 2022-03-02T23:29:04Z | 2022-04-19T16:50:54Z | transformers | 0 | 0 | null | feature-extraction | null | [
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621ffdc036468d709f17558e | GPL/scifact-msmarco-distilbert-gpl | GPL | null | 5 | 4,095 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:17:48Z | sentence-transformers | 1 | 0 | null | sentence-similarity | null | [
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"endpoints_compatible",
"deploy:azure",
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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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
"sentence-similarity",
"feature-extraction"
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"multimodal"
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"text"
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"embeddings"
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621ffdc036468d709f175590 | GPL/scifact-tsdae-msmarco-distilbert-margin-mse | GPL | null | 7 | 1,213 | False | 2022-03-02T23:29:04Z | 2022-04-19T16:48:19Z | transformers | 0 | 0 | null | feature-extraction | null | [
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"distilbert",
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"endpoints_compatible",
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621ffdc036468d709f175591 | GPL/trec-covid-v2-msmarco-distilbert-gpl | GPL | null | 5 | 1,192 | False | 2022-03-02T23:29:04Z | 2022-04-19T15:18:49Z | sentence-transformers | 0 | 0 | null | sentence-similarity | null | [
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"feature-extraction",
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"endpoints_compatible",
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] | null | {"architectures": ["DistilBertModel"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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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 | [
"AutoModel",
"distilbert",
"DistilBertModel"
] | [
"sentence-similarity",
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"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f175593 | GPL/trec-covid-v2-tsdae-msmarco-distilbert-margin-mse | GPL | null | 5 | 844 | False | 2022-03-02T23:29:04Z | 2022-04-19T16:49:32Z | transformers | 0 | 0 | null | feature-extraction | null | [
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621ffdc036468d709f17559b | GabbyDaBUNBUN/DialoGPT-medium-PinkiePie | GabbyDaBUNBUN | null | 6 | 815 | False | 2022-03-02T23:29:04Z | 2022-02-02T03:24:51Z | transformers | 0 | 0 | null | text-generation | null | [
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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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621ffdc036468d709f1755c0 | Galaxy/DialoGPT-small-hermoine | Galaxy | null | 7 | 7 | False | 2022-03-02T23:29:04Z | 2021-08-28T07:25:00Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f1755c2 | Galuh/id-journal-gpt2 | Galuh | null | 11 | 1,918 | False | 2022-03-02T23:29:04Z | 2021-08-01T14:07:43Z | transformers | 1 | 0 | null | text-generation | null | [
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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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This is the [Indonesian gpt2-small model](https://huggingface.co/flax-community/gpt2-small-indonesian) fine-tuned to abstracts of Indonesian academic journals. All training was done on a TPUv2-8 VM sponsored by [TPU Research Cloud](https://sites.research.goog... | null | null | null | [
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621ffdc036468d709f1755c5 | GamerMan02/DialoGPT-medium-gamerbot | GamerMan02 | null | 9 | 9 | False | 2022-03-02T23:29:04Z | 2021-09-22T00:52:35Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f1755c7 | GammaPTest/e_bot | GammaPTest | null | 6 | 641 | False | 2022-03-02T23:29:04Z | 2021-11-19T18:29:45Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f1755dd | Courecta/DialoGPT-small-Zhongli | Courecta | null | 11 | 1,098 | False | 2022-03-02T23:29:04Z | 2021-09-06T02:34:12Z | transformers | 0 | 0 | null | text-generation | null | [
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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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621ffdc036468d709f1755f6 | Gayathri/distilbert-base-uncased-finetuned-squad | Gayathri | null | 4 | 424 | False | 2022-03-02T23:29:04Z | 2021-10-19T20:36:57Z | transformers | 0 | 0 | null | question-answering | null | [
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} | null | null | null | null | null | null | null | null | null | [
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621ffdc036468d709f1755f9 | Geezy/DialoGPT-small-guy | Geezy | null | 8 | 4,854 | False | 2022-03-02T23:29:04Z | 2021-08-31T15:29:36Z | transformers | 0 | 0 | null | text-generation | null | [
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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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621ffdc036468d709f1755ff | GenDelport/DialoGPT-small-harrypotter | GenDelport | null | 5 | 617 | False | 2022-03-02T23:29:04Z | 2021-09-03T10:59:02Z | transformers | 0 | 0 | null | text-generation | null | [
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] | fb1f22b02d751dd7cc1569751c1d4c352464fa05 | [
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621ffdc036468d709f175601 | GeniusVoice/bert-base-dutch-cased-finetuned-gem | GeniusVoice | null | 3 | 616 | False | 2022-03-02T23:29:04Z | 2023-07-03T12:58:44Z | transformers | 1 | 0 | null | fill-mask | {"parameters": {"I64": 512, "F32": 109169017}, "total": 109169529} | [
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] | 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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should probably proofread and complete it, then remove this comment. -->
# bert-base-dutch-cased-finetuned-gem
This model is a fine-tuned version of [GroNLP/bert-base-dutch-cased](https://huggingface.co/G... | null | null | null | [
"nl"
] | 109,169,529 | null | null | [
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621ffdc036468d709f175602 | GeniusVoice/bot-selector | GeniusVoice | null | 5 | 937 | False | 2022-03-02T23:29:04Z | 2023-07-03T12:58:27Z | transformers | 0 | 0 | null | text-classification | {"parameters": {"I64": 514, "F32": 116764419}, "total": 116764933} | [
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] | 0e4be2f92cb6500f8ad04fda419f0d3d132c3eb7 | [
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] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "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": fa... | {
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} | null | null | null | null | null | null | 116,764,933 | null | null | [
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621ffdc036468d709f175603 | GeniusVoice/gv-semanticsearch-dutch-cased | GeniusVoice | null | 2 | 994 | False | 2022-03-02T23:29:04Z | 2021-08-29T20:28:09Z | sentence-transformers | 2 | 0 | null | sentence-similarity | null | [
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"README.md",
"config.json",
"config_sentence_transformers.json",
"modules.json",
"pytorch_model.bin",
"sentence_bert_config.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 0e39cd6d29c9218739f00f72d7115100a53abde2 | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertModel"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"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 | [
"BertModel",
"AutoModel",
"bert"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f175699 | GermanT5/german-t5-oscar-ep1-prompted-germanquad | GermanT5 | null | 10 | 4,258 | False | 2022-03-02T23:29:04Z | 2023-04-27T19:28:13Z | transformers | 0 | 0 | [{"name": "test-german-t5-prompted-germanquad", "results": []}] | null | {"parameters": {"F32": 247539456}, "total": 247539456} | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
"model.safetensors",
"pytorch_model.bin",
"runs/Jan24_15-40-29_ip-172-31-12-71/1643038833.5809927/events.out.tfevents.1643038833.ip-172-31-12-71.74475.1",
"runs/Jan24_15-40-29_ip-172-31-12-71/events.out.tfevents.1643038833.ip-172-31-12-... | deafed3c1222bf38a3d22675f752874b6cc2955a | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"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": null, "eval_results": [], "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": "test-german-t5-prompted-germanquad", "pipeline_tag": null, "tags": ["generated_from_trainer"], "widget": [{"text": "Philipp ist ... | <!-- 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. -->
# test-german-t5-prompted-germanquad
eval_loss = 0.5907255411148071
eval_rouge1 = 62.0922
eval_rouge2 = 47.2761
eval_rougeL =... | null | null | null | null | 247,539,456 | null | null | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
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