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621ffdc036468d709f17569a | GermanT5/t5-base-german-3e | GermanT5 | null | 8 | 1,234 | False | 2022-03-02T23:29:04Z | 2022-02-11T21:37:12Z | transformers | 1 | 0 | null | null | null | [
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621ffdc036468d709f17569b | GermanT5/t5-efficient-gc4-german-base-nl36-old | GermanT5 | null | 9 | 579 | False | 2022-03-02T23:29:04Z | 2025-02-24T08:28:10Z | transformers | 1 | 0 | null | text-generation | {"parameters": {"F32": 619357440}, "total": 619357440} | [
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621ffdc036468d709f17569c | GermanT5/t5-efficient-gc4-german-small-el32 | GermanT5 | null | 10 | 1,325 | False | 2022-03-02T23:29:04Z | 2023-07-28T12:20:28Z | transformers | 5 | 0 | null | null | {"parameters": {"F32": 142322176}, "total": 142322176} | [
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621ffdc036468d709f17569d | GermanT5/t5-efficient-oscar-german-small-el32 | GermanT5 | null | 8 | 1,540 | False | 2022-03-02T23:29:04Z | 2023-08-11T15:08:27Z | transformers | 2 | 0 | null | null | {"parameters": {"F32": 142322176}, "total": 142322176} | [
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621ffdc036468d709f17569f | Gerwin/bert-for-pac | Gerwin | null | 7 | 4,564 | False | 2022-03-02T23:29:04Z | 2022-07-21T08:59:38Z | transformers | 0 | 0 | null | text-classification | null | [
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] | 0b2f6225499890eb49f58658db00706ea3d3e8d2 | [
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] | null | {"architectures": ["BertForSequenceClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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### Lijdende en Bedrijvende vorm classificatie voor zinnen
#### Examples
Try the following examples in the Hosted inference API:
1. Jan werd opgehaald door zijn moeder.
2. Wie niet weg is, is gezien
3. Ik ben van plan om morgen te gaan werken
4. De mak... | null | [
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621ffdc036468d709f1756ad | Giannipinelli/xlm-roberta-base-finetuned-marc-en | Giannipinelli | null | 8 | 929 | False | 2022-03-02T23:29:04Z | 2021-12-16T14:34:58Z | transformers | 0 | 0 | [{"name": "xlm-roberta-base-finetuned-marc-en", "results": []}] | text-classification | null | [
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should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-marc-en
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-ba... | null | [
"mit"
] | [
"amazon_reviews_multi"
] | null | null | null | null | [
"AutoModelForSequenceClassification",
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621ffdc036468d709f1756e2 | GnomeX/mt5-small-finetuned-amazon-en-es | GnomeX | null | 6 | 432 | False | 2022-03-02T23:29:04Z | 2021-12-07T02:44:47Z | transformers | 0 | 0 | null | null | null | [
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"training_args.bin"
] | a23a4224234abe7df78017ec08362dddaba98738 | [
"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 | [
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"MT5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
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621ffdc036468d709f1756e8 | Gonalb/xlm-roberta-base-finetuned-panx-de | Gonalb | null | 6 | 500 | False | 2022-03-02T23:29:04Z | 2023-02-20T03:38:30Z | transformers | 0 | 0 | [{"name": "xlm-roberta-base-finetuned-panx-de", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "args": "PAN-X.de"}, "metrics": [{"name": "F1", "type": "f1", "value": 0.8629840546697038, "verified": false}]}]}] | token-classification | null | [
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} | {"datasets": ["xtreme"], "license": "mit", "metrics": ["f1"], "tags": ["generated_from_trainer"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "args": "PAN-X.de"}, "me... | <!-- 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. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-ba... | null | [
"mit"
] | [
"xtreme"
] | null | null | null | [
"f1"
] | [
"XLMRobertaForTokenClassification",
"AutoModelForTokenClassification",
"xlm-roberta"
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621ffdc036468d709f1756f1 | Gowtham25/DialoGPT-small-jackie | Gowtham25 | null | 9 | 9 | False | 2022-03-02T23:29:04Z | 2021-08-28T10:31:52Z | transformers | 1 | 0 | null | text-generation | null | [
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] | 1d550d04195b1e7c16fdf4742589abae316ffd1b | [
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"pytorch",
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"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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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
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621ffdc036468d709f17570d | Gregor-Davies/DialoGPT-small-rick | Gregor-Davies | null | 9 | 789 | False | 2022-03-02T23:29:04Z | 2022-01-23T13:15:35Z | transformers | 0 | 0 | null | text-generation | null | [
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] | bad252226ba9192e914f8812c5c811346642d31f | [
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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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621ffdc036468d709f175712 | Greysan/DialoGPT-medium-TOH | Greysan | null | 5 | 594 | False | 2022-03-02T23:29:04Z | 2021-08-27T08:53:29Z | transformers | 0 | 0 | null | text-generation | null | [
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] | 3b696c69b2d04c3fcd9485f470450053814831ea | [
"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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621ffdc036468d709f175731 | GroNLP/gpt2-medium-dutch-embeddings | GroNLP | null | 864 | 9,252 | False | 2022-03-02T23:29:04Z | 2023-09-11T08:56:08Z | transformers | 3 | 0 | null | text-generation | {"parameters": {"F32": 344320000, "U8": 25165824}, "total": 369485824} | [
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"README.md",
"config.json",
"flax_model.msgpack",
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"pytorch_model.bin",
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] | a7ea2d4a0dfc0a36b5fb11b93be9f63bf9cc89fb | [
"transformers",
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"tf",
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"nl",
"arxiv:2012.05628",
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}} | {
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"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "nl", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": "text-generation", "tags": ["adaption", "recycled", "gpt2-medium"]} | # GPT-2 recycled for Dutch (medium, adapted lexical embeddings)
[Wietse de Vries](https://www.semanticscholar.org/author/Wietse-de-Vries/144611157) •
[Malvina Nissim](https://www.semanticscholar.org/author/M.-Nissim/2742475)
## Model description
This model is based on the medium OpenAI GPT-2 ([`gpt2-medium`](https://... | null | null | null | [
"nl"
] | 369,485,824 | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
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] | [
"text"
] | [
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621ffdc036468d709f17573e | Guard-SK/DialoGPT-medium-ricksanchez | Guard-SK | null | 5 | 659 | False | 2022-03-02T23:29:04Z | 2021-09-01T11:09:15Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f17573f | Guard-SK/DialoGPT-small-ricksanchez | Guard-SK | null | 4 | 605 | False | 2022-03-02T23:29:04Z | 2021-08-31T21:10:38Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f175744 | GunjanPantha/DialoGPT-small-gameofthrones | GunjanPantha | null | 9 | 9 | False | 2022-03-02T23:29:04Z | 2021-08-27T17:39:14Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f175747 | Gunulhona/tbbcmodel | Gunulhona | null | 23 | 10,033 | False | 2022-03-02T23:29:04Z | 2022-01-06T07:01:22Z | transformers | 0 | 0 | null | text-classification | null | [
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"bart",
"text-classification",
"endpoints_compatible",
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"auto_model": "AutoModelForSequenceClassification",
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} | null | null | null | null | null | null | null | null | null | [
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621ffdc036468d709f175771 | GusNicho/bert-base-cased-finetuned | GusNicho | null | 5 | 471 | False | 2022-03-02T23:29:04Z | 2022-01-12T07:38:10Z | transformers | 0 | 0 | null | fill-mask | null | [
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621ffdc036468d709f175772 | GusNicho/distilbert-base-cased-finetuned | GusNicho | null | 4 | 470 | False | 2022-03-02T23:29:04Z | 2022-01-12T07:41:34Z | transformers | 0 | 0 | [{"name": "distilbert-base-cased-finetuned", "results": []}] | fill-mask | null | [
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should probably proofread and complete it, then remove this comment. -->
# distilbert-base-cased-finetuned
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-b... | null | [
"apache-2.0"
] | null | null | null | null | null | [
"distilbert",
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] |
621ffdc036468d709f175773 | GusNicho/roberta-base-finetuned | GusNicho | null | 5 | 475 | False | 2022-03-02T23:29:04Z | 2022-01-12T08:31:17Z | transformers | 0 | 0 | [{"name": "roberta-base-finetuned", "results": []}] | fill-mask | null | [
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"generated_from_trainer",
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] | 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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should probably proofread and complete it, then remove this comment. -->
# roberta-base-finetuned
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown da... | null | [
"mit"
] | null | null | null | null | null | [
"roberta",
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621ffdc036468d709f17577b | Guy0/DialoGPT-small-Batmanbotty | Guy0 | null | 6 | 6 | False | 2022-03-02T23:29:04Z | 2021-09-05T16:52:37Z | transformers | 0 | 0 | null | text-generation | null | [
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] | ebcc0a6b26c782487ddf33778105f68d89d1beaf | [
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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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621ffdc036468d709f175781 | HAttORi/DialoGPT-Medium-zerotwo | HAttORi | null | 10 | 10 | False | 2022-03-02T23:29:04Z | 2021-08-23T17:12:33Z | transformers | 3 | 0 | null | text-generation | null | [
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] | ce72032c419638325d5c837d7c40a9aece456330 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
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621ffdc036468d709f1757c0 | HackMIT/double-agent | HackMIT | null | 8 | 6,510 | False | 2022-03-02T23:29:04Z | 2021-08-04T06:43:07Z | transformers | 1 | 0 | null | text-classification | null | [
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] | 6e8169d3cc13546fa7fcff796157a9b00055ba91 | [
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"bert",
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} | null | null | null | null | null | null | null | null | null | [
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621ffdc036468d709f1757c1 | HackyHackyMan/DialoGPT-small-harrypotter | HackyHackyMan | null | 17 | 4,529 | False | 2022-03-02T23:29:04Z | 2021-09-28T21:39:35Z | transformers | 0 | 0 | null | text-generation | null | [
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] | bdb8208f3f7a22daa500c059977aeb617254be33 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
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621ffdc036468d709f1757c2 | Hadron/DialoGPT-medium-nino | Hadron | null | 7 | 767 | False | 2022-03-02T23:29:04Z | 2021-06-04T20:30:21Z | transformers | 0 | 0 | null | text-generation | null | [
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] | ed521ace99688b86aba15a7693dde959bcd38534 | [
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"pytorch",
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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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621ffdc036468d709f1757c3 | hchang/t5-small-finetuned-xsum | hchang | null | 7 | 306 | False | 2022-03-02T23:29:04Z | 2022-01-21T12:15:28Z | transformers | 0 | 0 | null | null | null | [
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621ffdc036468d709f1757ce | Hallzy/Peterbot | Hallzy | null | 6 | 6 | False | 2022-03-02T23:29:04Z | 2022-02-26T23:33:57Z | transformers | 0 | 0 | null | text-generation | null | [
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] | 5b71700f504933b2d6a928e4692a016d8f92f99f | [
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621ffdc036468d709f1757cf | Hamas/DialoGPT-large-jake | Hamas | null | 6 | 769 | False | 2022-03-02T23:29:04Z | 2021-09-26T05:28:55Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f1757d0 | Hamas/DialoGPT-large-jake2 | Hamas | null | 10 | 1,357 | False | 2022-03-02T23:29:04Z | 2023-07-22T10:28:12Z | transformers | 0 | 0 | null | text-generation | {"parameters": {"F32": 124439808, "U8": 12582912}, "total": 137022720} | [
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621ffdc036468d709f1757d1 | Hamas/DialoGPT-large-jake3 | Hamas | null | 12 | 1,419 | False | 2022-03-02T23:29:04Z | 2021-09-30T19:12:43Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f1757d2 | Hamas/DialoGPT-large-jake4 | Hamas | null | 6 | 838 | False | 2022-03-02T23:29:04Z | 2022-01-23T10:14:47Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f1757d3 | Hamhams/DialoGPT-small-rick | Hamhams | null | 10 | 5,026 | False | 2022-03-02T23:29:04Z | 2022-02-25T04:21:26Z | transformers | 0 | 0 | null | text-generation | null | [
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"training_args.bin",
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] | 8729e8a982f304dd9bd0861ede88c9f7a42bbd14 | [
"transformers",
"pytorch",
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"gpt2"
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621ffdc036468d709f1757e6 | HamidRezaAttar/gpt2-product-description-generator | HamidRezaAttar | null | 1,448 | 12,672 | False | 2022-03-02T23:29:04Z | 2024-06-03T11:17:25Z | transformers | 14 | 0 | null | text-generation | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"dls_eng_Batch4.pkl",
"history_epoch1.csv",
"pytorch_model.bin",
"tokenizer.json"
] | ce23aa7f341153b4b2280398b2df31d9fa990391 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"en",
"arxiv:1706.03762",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2"} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "en", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["text-generation"], "widget": [{"text": "Maximize your bedroom space without sacri... | ## GPT2-Home
This model is fine-tuned using GPT-2 on amazon home products metadata.
It can generate descriptions for your **home** products by getting a text prompt.
https://github.com/HamidRezaAttar/GPT2-Home
### Model description
[GPT-2](https://openai.com/blog/better-language-models/) is a large [transformer](h... | null | [
"apache-2.0"
] | null | [
"en"
] | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
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"text-generation"
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"text"
] | [
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] |
621ffdc036468d709f1757f0 | Hank/distilbert-base-uncased-finetuned-ner | Hank | null | 7 | 577 | False | 2022-03-02T23:29:04Z | 2021-08-02T01:04:09Z | transformers | 0 | 0 | null | token-classification | null | [
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"runs/Aug02_00-59-18_4325ab0e4b9... | a02bcf29183a2d44540ba7448c67fcb1757c4235 | [
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"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
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] | null | {"architectures": ["DistilBertForTokenClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
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"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["conll2003"], "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["precision", "recall", "f1", "accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_in... | <!-- 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"
] |
621ffdc036468d709f1757f3 | HansAnonymous/DialoGPT-medium-rick | HansAnonymous | null | 9 | 6,878 | False | 2022-03-02T23:29:04Z | 2021-08-28T23:56:07Z | transformers | 1 | 0 | null | text-generation | null | [
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"merges.txt",
"pytorch_model.bin",
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"vocab.json"
] | afd8cbee4a08b246cbedfe94d2ffd0fd65db7428 | [
"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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"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
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621ffdc036468d709f1757f4 | HansAnonymous/DialoGPT-small-shrek | HansAnonymous | null | 8 | 27,534 | False | 2022-03-02T23:29:04Z | 2021-09-02T04:24:57Z | transformers | 0 | 0 | null | text-generation | null | [
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"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | a2260161a6c331cc154dff971d6d6d96dc8130ed | [
"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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"pipeline_tag": "text-generation",
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} | {"base_model": null, "datasets": null, "eval_results": null, "language": null, "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["conversational"]} | null | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f17580e | HarryPuttar/HarryPotterDC | HarryPuttar | null | 7 | 617 | False | 2022-03-02T23:29:04Z | 2022-01-28T16:39:22Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
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"pytorch_model.bin",
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"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | 66c824ccf06515d948d5402961e6a1128885a9b8 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
"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"
] |
621ffdc036468d709f175811 | Harshal6927/Jack_Sparrow_GPT | Harshal6927 | null | 6 | 760 | False | 2022-03-02T23:29:04Z | 2021-08-29T15:30:11Z | 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"
] | e1b8d8a3cdb4a09375a8ddac5880e5bfed35bee2 | [
"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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"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"
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621ffdc036468d709f175812 | Harshal6927/Tony_Stark_GPT | Harshal6927 | null | 7 | 746 | False | 2022-03-02T23:29:04Z | 2021-08-29T07:39:33Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | adaee44120d9520e143b52e8ef642cc7b8998b67 | [
"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"]} | # Tony Stark GPT
My first AI model still learning, used small dataset so don't expect much | null | null | null | null | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175824 | Harshveer/autonlp-formality_scoring_2-32597818 | Harshveer | null | 8 | 1,663 | False | 2022-03-02T23:29:04Z | 2021-11-14T06:46:39Z | transformers | 0 | 0 | null | text-classification | null | [
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"sample_input.pkl",
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"tokenizer_config.json",
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] | 0683aa8fe9feb6b9824e38a256f6258aaaf79f34 | [
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"text-classification",
"en",
"dataset:Harshveer/autonlp-data-formality_scoring_2",
"co2_eq_emissions",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "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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} | {"base_model": null, "datasets": ["Harshveer/autonlp-data-formality_scoring_2"], "eval_results": null, "language": "en", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "I love AutoNLP \ud83e\... | # Model Trained Using AutoNLP
- Problem type: Single Column Regression
- Model ID: 32597818
- CO2 Emissions (in grams): 8.655894631203154
## Validation Metrics
- Loss: 0.5410276651382446
- MSE: 0.5410276651382446
- MAE: 0.5694561004638672
- R2: 0.6830431129198475
- RMSE: 0.735545814037323
- Explained Variance: 0.683... | null | null | [
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621ffdc036468d709f175846 | Hasanmuradbuet/dummy-model | Hasanmuradbuet | null | 4 | 436 | False | 2022-03-02T23:29:04Z | 2021-11-24T13:10:09Z | transformers | 0 | 0 | null | fill-mask | null | [
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621ffdc036468d709f175860 | Havokx/DialoGPT-small-Rick | Havokx | null | 10 | 10 | False | 2022-03-02T23:29:04Z | 2021-08-31T23:00:24Z | transformers | 0 | 0 | null | text-generation | null | [
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621ffdc036468d709f175862 | Hax/filipino-text-version1 | Hax | null | 5 | 667 | False | 2022-03-02T23:29:04Z | 2021-07-07T07:31:03Z | transformers | 0 | 0 | null | text-classification | null | [
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] | 25064575d84d2e77e729da0a91b574dc36e04f53 | [
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621ffdc036468d709f175873 | Hellisotherpeople/T5_Reassuring_Parables | Hellisotherpeople | null | 7 | 2,325 | False | 2022-03-02T23:29:04Z | 2023-06-23T16:00:57Z | transformers | 0 | 0 | null | null | {"parameters": {"F32": 222903552}, "total": 222903552} | [
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621ffdc036468d709f175db6 | HenryAI/KerasBERTv1 | HenryAI | null | 4 | 1,372 | False | 2022-03-02T23:29:04Z | 2021-12-17T03:20:18Z | transformers | 7 | 0 | null | fill-mask | null | [
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] | 926606ccf88f02751d9784533e78a144c97c83f3 | [
"transformers",
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] | null | {"architectures": ["RobertaForMaskedLM"], "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": false, "normaliz... | {
"auto_model": "AutoModelForMaskedLM",
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"pipeline_tag": "fill-mask",
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} | null | Thanks for checking this out! <br />
This video explains the ideas behind KerasBERT (still very much a work in progress)
https://www.youtube.com/watch?v=J3P8WLAELqk | null | null | null | null | null | null | null | [
"roberta",
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621ffdc036468d709f175db7 | HenryHXR/t5-base-finetuned-scitldr | HenryHXR | null | 1 | 1,178 | False | 2022-03-02T23:29:04Z | 2022-02-05T05:48:10Z | transformers | 0 | 0 | [{"name": "t5-base-finetuned-scitldr", "results": []}] | null | null | [
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} | {"base_model": null, "datasets": null, "eval_results": [], "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": "t5-base-finetuned-scitldr", "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-base-finetuned-scitldr
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
... | null | [
"apache-2.0"
] | null | null | null | null | [
"rouge"
] | [
"t5",
"T5ForConditionalGeneration",
"AutoModelForSeq2SeqLM"
] | [
"text2text-generation"
] | null | null | null |
621ffdc036468d709f175db9 | Herais/pred_genre | Herais | null | 7 | 1,013 | False | 2022-03-02T23:29:04Z | 2022-02-27T05:26:29Z | transformers | 1 | 0 | null | text-classification | null | [
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] | ec5f0318f7519e4b73c4915a0bd32a5a805c37d8 | [
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"zh",
"dataset:Custom",
"license:apache-2.0",
"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": ["Custom"], "eval_results": null, "language": ["zh"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": null, "pipeline_tag": null, "tags": ["classification"]} | This model predicts the time period given a synopsis of about 200 Chinese characters.
The model is trained on TV and Movie datasets and takes simplified Chinese as input.
We trained the model from the "hfl/chinese-bert-wwm-ext" checkpoint.
#### Sample Usage
from transformers import BertTokenizer, BertForSequenceC... | null | [
"apache-2.0"
] | [
"Custom"
] | [
"zh"
] | null | null | [
"rouge"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
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] | [
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621ffdc036468d709f175dba | Herais/pred_timeperiod | Herais | null | 6 | 1,210 | False | 2022-03-02T23:29:04Z | 2023-03-21T17:03:01Z | transformers | 0 | 0 | null | text-classification | {"parameters": {"I64": 512, "F32": 102271493}, "total": 102272005} | [
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"model.safetensors",
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] | 396b5783e82495e465af79d7dbfabe433151a47d | [
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"license:apache-2.0",
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] | 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": ["Custom"], "eval_results": null, "language": ["zh"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["rouge"], "model_name": null, "pipeline_tag": null, "tags": ["classification"]} | This model predicts the time period given a synopsis of about 200 Chinese characters.
The model is trained on TV and Movie datasets and takes simplified Chinese as input.
We trained the model from the "hfl/chinese-bert-wwm-ext" checkpoint.
#### Sample Usage
from transformers import BertTokenizer, BertForSequenceC... | null | [
"apache-2.0"
] | [
"Custom"
] | [
"zh"
] | 102,272,005 | null | [
"rouge"
] | [
"BertForSequenceClassification",
"bert",
"AutoModelForSequenceClassification"
] | [
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621ffdc036468d709f175dc2 | HeyLucasLeao/gpt-neo-small-emo-lyrics | HeyLucasLeao | null | 11 | 2,337 | False | 2022-03-02T23:29:04Z | 2021-08-19T14:07:03Z | transformers | 2 | 0 | null | text-generation | null | [
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"tokenizer_config.json",
"vocab.json"
] | 31d33a826154409f3b6da1d61c72ff1143e98c50 | [
"transformers",
"pytorch",
"gpt_neo",
"text-generation",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPTNeoForCausalLM"], "model_type": "gpt_neo", "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":... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | Create README.md
## Emo Bot
#### Model Description
This is a finetuned version from GPT-Neo-125M for Generating Music Lyrics by Emo Genre.
#### Training data
It was trained with 2381 songs by 15 bands that were important to emo culture in the early 2000s, not necessary directly playing on the genre.
#### Training Pr... | null | null | null | null | null | null | null | [
"gpt_neo",
"AutoModelForCausalLM",
"GPTNeoForCausalLM"
] | [
"text-generation"
] | [
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] | [
"text"
] | [
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621ffdc036468d709f175dc3 | HeyLucasLeao/gpt-neo-small-portuguese | HeyLucasLeao | null | 26 | 8,947 | False | 2022-03-02T23:29:04Z | 2021-06-19T20:51:57Z | transformers | 7 | 0 | null | text-generation | null | [
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] | 6c55098b12753c7a0848203d33195f6fa07cd092 | [
"transformers",
"pytorch",
"gpt_neo",
"text-generation",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPTNeoForCausalLM"], "model_type": "gpt_neo", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|startoftext|>", "single_word": false, "lstrip": false, "rstrip... | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | null | ## GPT-Neo Small Portuguese
#### Model Description
This is a finetuned version from GPT-Neo 125M by EletheurAI to Portuguese language.
#### Training data
It was trained from 227,382 selected texts from a PTWiki Dump. You can found all the data from here: https://archive.org/details/ptwiki-dump-20210520
#### Trainin... | null | null | null | null | null | null | null | [
"gpt_neo",
"AutoModelForCausalLM",
"GPTNeoForCausalLM"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175dca | HieuLV3/QA_UIT_xlm_roberta_large | HieuLV3 | null | 3 | 1,653 | False | 2022-03-02T23:29:04Z | 2021-10-18T07:48:26Z | transformers | 0 | 0 | null | question-answering | null | [
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"config.json",
"pytorch_model.bin",
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"tokenizer_config.json",
"unigram.json"
] | 86dbe60e37c40c971f21cee3bce1b7ad93f803d1 | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"endpoints_compatible",
"deploy:azure",
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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": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "norma... | {
"auto_model": "AutoModelForQuestionAnswering",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"roberta",
"AutoModelForQuestionAnswering",
"RobertaForQuestionAnswering"
] | [
"question-answering"
] | [
"text"
] | [
"text"
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"text"
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621ffdc036468d709f175dd4 | Hinova/distilbert-base-uncased-finetuned-cola | Hinova | null | 4 | 610 | False | 2022-03-02T23:29:04Z | 2021-08-26T02:55:21Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
".gitignore",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.txt"
] | 0d1a004024889728ff4490330bec2341fea77e2f | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForSequenceClassification",
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"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["glue"], "eval_results": null, "language": null, "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["matthews_correlation"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "disti... | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | null | [
"apache-2.0"
] | [
"glue"
] | null | null | null | [
"matthews_correlation"
] | [
"DistilBertForSequenceClassification",
"distilbert",
"AutoModelForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175dd8 | Hoang/distilbert-base-uncased-finetuned-squad | Hoang | null | 4 | 498 | False | 2022-03-02T23:29:04Z | 2021-09-02T07:32:09Z | transformers | 0 | 0 | {"error": "Schema validation error. \"model-index[0].results[0].metrics\" is required"} | question-answering | null | [
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"endpoints_compatible",
"region:us"
] | 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",
"custom_class": null,
"pipeline_tag": "question-answering",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["squad"], "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. -->
# 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"
] |
621ffdc036468d709f175de3 | MagnusChase7/DialoGPT-medium-harrypotter | MagnusChase7 | null | 7 | 2,550 | False | 2022-03-02T23:29:04Z | 2021-10-03T09:35:47Z | 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"
] | c7a849a63595340f9d95c375197ebfeeee9fae2b | [
"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"
] |
621ffdc036468d709f175de8 | HooshvareLab/albert-fa-zwnj-base-v2-ner | HooshvareLab | null | 5 | 5,113 | False | 2022-03-02T23:29:04Z | 2021-03-21T14:25:09Z | transformers | 0 | 0 | null | token-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json"
] | 54971e5dd35e3177efcf39fc6e50a7bd520c41b3 | [
"transformers",
"pytorch",
"tf",
"albert",
"token-classification",
"fa",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForTokenClassification"], "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, ... | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # AlbertNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wikiann/) that covered ten ... | null | null | null | [
"fa"
] | null | null | null | [
"AlbertForTokenClassification",
"AutoModelForTokenClassification",
"albert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175de9 | HooshvareLab/albert-fa-zwnj-base-v2 | HooshvareLab | null | 6 | 207,143 | False | 2022-03-02T23:29:04Z | 2021-03-16T16:36:38Z | transformers | 5 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"spiece.model",
"spiece.vocab",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"unigram.json"
] | 2315c0d4ddd6bd68f7703c5651978706bf8aff37 | [
"transformers",
"pytorch",
"tf",
"albert",
"fill-mask",
"fa",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["AlbertForMaskedLM"], "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": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ALBERT-Persian
A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
> میتونی بهش بگی برت_کوچولو
> Call it little_berty
### BibTeX entry and citation info
Please cite in your publication as the following:
```bibtex
@misc{ALBERTPersian,
author = {Hooshvare Team},
titl... | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"albert",
"AutoModelForMaskedLM",
"AlbertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175df7 | HooshvareLab/bert-fa-zwnj-base-ner | HooshvareLab | null | 114 | 1,801,857 | False | 2022-03-02T23:29:04Z | 2021-05-18T21:04:35Z | transformers | 5 | 0 | null | token-classification | null | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 17d4928f28c36fd74864c221a27134da8b6bf9bc | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"fa",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # BertNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wikiann/) that covered ten ty... | null | null | null | [
"fa"
] | null | null | null | [
"AutoModelForTokenClassification",
"BertForTokenClassification",
"bert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175df8 | HooshvareLab/bert-fa-zwnj-base | HooshvareLab | null | 76 | 408,505 | False | 2022-03-02T23:29:04Z | 2021-05-18T21:05:42Z | transformers | 18 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 3880fac085e1a338e9564907cba0adeb9e14bc72 | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"fa",
"arxiv:2005.12515",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # ParsBERT (v3.0)
A Transformer-based Model for Persian Language Understanding
The new version of BERT v3.0 for Persian is available today and can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Introduction
Pars... | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"AutoModelForMaskedLM",
"bert",
"BertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175df9 | HooshvareLab/distilbert-fa-zwnj-base-ner | HooshvareLab | null | 11 | 639,549 | False | 2022-03-02T23:29:04Z | 2021-03-21T14:32:29Z | transformers | 4 | 0 | null | token-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 36ccd9aa3dd64c3a83c76de0b8cc5b3f6fa3dc30 | [
"transformers",
"pytorch",
"tf",
"distilbert",
"token-classification",
"fa",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["DistilBertForTokenClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # DistilbertNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wikiann/) that covered ... | null | null | null | [
"fa"
] | null | null | null | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175dfa | HooshvareLab/distilbert-fa-zwnj-base | HooshvareLab | null | 12 | 37,902 | False | 2022-03-02T23:29:04Z | 2021-03-16T16:30:29Z | transformers | 2 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | e8b934b8c81b17c5e4a1a90325f5f25ced94e8d6 | [
"transformers",
"pytorch",
"tf",
"distilbert",
"fill-mask",
"fa",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["DistilBertForMaskedLM"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}} | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # DistilBERT
This model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Questions?
Post a Github issue on the [ParsBERT Issues](https://github.com/hooshvare/parsbert/issues) repo. | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"distilbert",
"AutoModelForMaskedLM",
"DistilBertForMaskedLM"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175dfb | HooshvareLab/gpt2-fa-comment | HooshvareLab | null | 11 | 4,185 | False | 2022-03-02T23:29:04Z | 2021-05-21T10:47:25Z | transformers | 2 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"flax_model.msgpack",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | a11c3401aa46429b13184a6c94088bd43728c7fd | [
"transformers",
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"fa",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "<s>\u0646\u0645\u0648\u0646\u0647 \u062f\u06cc\u062f\u06... | # Persian Comment Generator
The model can generate comments based on your aspects, and the model was fine-tuned on [persiannlp/parsinlu](https://github.com/persiannlp/parsinlu). Currently, the model only supports aspects in the food and movie scope. You can see the whole aspects in the following section.
## Comment... | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175dfc | HooshvareLab/gpt2-fa-poetry | HooshvareLab | null | 33 | 5,953 | False | 2022-03-02T23:29:04Z | 2021-05-21T10:50:14Z | transformers | 2 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"flax_model.msgpack",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 35d19a3dba707d9d1ca075e35340f0477c8d9e0b | [
"transformers",
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"fa",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "<pad>"}} | {
"auto_model": "AutoModelForCausalLM",
"custom_class": null,
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "<s>\u0631\u0648\u062f\u06a9\u06cc<|startoftext|>"}, {"te... | # Persian Poet GPT2
## Poets
The model can generate poetry based on your favorite poet, and you need to add one of the following lines as the input the box on the right side or follow the [fine-tuning notebook](https://colab.research.google.com/github/hooshvare/parsgpt/blob/master/notebooks/Persian_Poetry_FineTuning.... | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175dfd | HooshvareLab/gpt2-fa | HooshvareLab | null | 1,846 | 138,246 | False | 2022-03-02T23:29:04Z | 2021-05-21T10:51:23Z | transformers | 19 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"added_tokens.json",
"config.json",
"flax_model.msgpack",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 9c1fa5edb93f30ca93df0d1f1abcc44bcc73e5d1 | [
"transformers",
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"fa",
"license:apache-2.0",
"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": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "\u062f\u0631 \u06cc\u06a9 \u0627\u062a\u0641\u0627\u0642... | # ParsGPT2
### BibTeX entry and citation info
Please cite in publications as the following:
```bibtex
@misc{ParsGPT2,
author = {Hooshvare Team},
title = {ParsGPT2 the Persian version of GPT2},
year = {2021},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/hoo... | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"GPT2LMHeadModel",
"AutoModelForCausalLM",
"gpt2"
] | [
"text-generation"
] | [
"text"
] | [
"text"
] | [
"text"
] |
621ffdc036468d709f175dfe | HooshvareLab/roberta-fa-zwnj-base-ner | HooshvareLab | null | 4 | 18,489 | False | 2022-03-02T23:29:04Z | 2021-05-20T11:55:34Z | transformers | 1 | 0 | null | token-classification | null | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | eb045188128311055e23e2ac0941e76071fcdbd6 | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"token-classification",
"fa",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForTokenClassification"], "model_type": "roberta", "tokenizer_config": {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>"}} | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": null, "eval_results": null, "language": "fa", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # RobertaNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wikiann/) that covered ten... | null | null | null | [
"fa"
] | null | null | null | [
"roberta",
"AutoModelForTokenClassification",
"RobertaForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175dff | HooshvareLab/roberta-fa-zwnj-base | HooshvareLab | null | 44 | 132,265 | False | 2022-03-02T23:29:04Z | 2023-02-15T19:52:24Z | transformers | 7 | 0 | null | fill-mask | null | [
".gitattributes",
"README.md",
"config.json",
"flax_model.msgpack",
"merges.txt",
"pytorch_model.bin",
"special_tokens_map.json",
"tf_model.h5",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json"
] | 94c154f693ad41718aa259085aaf11c7684309a6 | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"fill-mask",
"fa",
"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": null, "eval_results": null, "language": "fa", "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null} | # Roberta
This model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Questions?
Post a Github issue on the [ParsRoBERTa Issues](https://github.com/hooshvare/parsbert/issues) repo. | null | [
"apache-2.0"
] | null | [
"fa"
] | null | null | null | [
"roberta",
"AutoModelForMaskedLM",
"RobertaForMaskedLM"
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"fill-mask"
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] | [
"text"
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621ffdc036468d709f175e01 | Hormigo/roberta-base-bne-finetuned-amazon_reviews_multi | Hormigo | null | 13 | 1,051 | False | 2022-03-02T23:29:04Z | 2021-08-30T11:08:21Z | transformers | 0 | 0 | null | text-classification | null | [
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"special_tokens_... | 3a4dcddcadff337f6e080c97bc3b193098eca04e | [
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"pytorch",
"tensorboard",
"roberta",
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"generated_from_trainer",
"dataset:amazon_reviews_multi",
"license:cc-by-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | 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... | {
"auto_model": "AutoModelForSequenceClassification",
"custom_class": null,
"pipeline_tag": "text-classification",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["amazon_reviews_multi"], "eval_results": null, "language": null, "library_name": null, "license": "cc-by-4.0", "license_name": null, "license_link": null, "metrics": ["accuracy"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "ro... | <!-- 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-bne-finetuned-amazon_reviews_multi
This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://hugging... | null | [
"cc-by-4.0"
] | [
"amazon_reviews_multi"
] | null | null | null | [
"accuracy"
] | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175e09 | Htenn/DialoGPT-small-spongebob | Htenn | null | 2 | 461 | False | 2022-03-02T23:29:04Z | 2022-02-18T09:13:38Z | transformers | 0 | 0 | null | text-generation | null | [
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"checkpoint-10500/scheduler.pt",
"checkpoint-10500/special_tokens_map.json",
"checkpoint-10500/tokenizer.json",
"checkpoint-10500/tok... | f94e48816e5eb54bdae169793820ad8675b403b1 | [
"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"
] |
621ffdc036468d709f175e0a | Htenn/DialoGPT-small-spongebobv2 | Htenn | null | 1 | 1 | False | 2022-03-02T23:29:04Z | 2022-02-26T13:25:59Z | transformers | 0 | 0 | null | text-generation | null | [
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"checkpoint-10500/scheduler.pt",
"checkpoint-10500/special_tokens_map.json",
"checkpoint-10500/tokenizer.json",
"checkpoint-10500/tok... | 1e132a054dd524629682977a47c386b7ee23a037 | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"text-generation-inference",
"endpoints_compatible",
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] | null | {"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": fals... | {
"auto_model": "AutoModelForCausalLM",
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"pipeline_tag": "text-generation",
"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"
] |
621ffdc036468d709f175e1a | HueJanus/DialoGPT-small-ricksanchez | HueJanus | null | 1 | 1 | False | 2022-03-02T23:29:04Z | 2021-09-25T18:46:02Z | transformers | 0 | 0 | null | text-generation | null | [
".gitattributes",
"README.md",
"config.json",
"eval_results.txt",
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"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin",
"vocab.json"
] | cc030aec9364bb415b0cead09f6880eff7c1885c | [
"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"
] |
621ffdc036468d709f175e1d | HueyNemud/berties | HueyNemud | null | 6 | 2,464 | False | 2022-03-02T23:29:04Z | 2022-02-08T08:47:31Z | transformers | 1 | 0 | null | token-classification | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"training_args.bin"
] | 449ee926f5b7b92d0388c6a03575dad62f748ba9 | [
"transformers",
"pytorch",
"camembert",
"token-classification",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["CamembertForTokenClassification"], "model_type": "camembert", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, ... | {
"auto_model": "AutoModelForTokenClassification",
"custom_class": null,
"pipeline_tag": "token-classification",
"processor": "AutoTokenizer"
} | null | null | null | null | null | null | null | null | null | [
"CamembertForTokenClassification",
"AutoModelForTokenClassification",
"camembert"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175e1e | HueyNemud/das22-10-camembert_pretrained | HueyNemud | null | 3 | 1,206 | False | 2022-03-02T23:29:04Z | 2022-05-19T12:05:12Z | transformers | 0 | 0 | [{"name": "CamemBERT pretrained on french trade directories from the XIXth century", "results": []}] | fill-mask | null | [
".gitattributes",
"README.md",
"all_results.json",
"config.json",
"eval_results.json",
"pytorch_model.bin",
"sentencepiece.bpe.model",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"train_results.json",
"trainer_state.json",
"training_args.bin"
] | a54f5177528f2e319b97b1f3960d0a00fd9e3ef3 | [
"transformers",
"pytorch",
"camembert",
"fill-mask",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | {"architectures": ["CamembertForMaskedLM"], "model_type": "camembert", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized... | {
"auto_model": "AutoModelForMaskedLM",
"custom_class": null,
"pipeline_tag": "fill-mask",
"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": "CamemBERT pretrained on french trade directories from the XIXth century", "pipeline_tag": null, "tags": ["generated_from_trainer... | # CamemBERT pretrained on french trade directories from the XIXth century
This mdoel is part of the material of the paper
> Abadie, N., Carlinet, E., Chazalon, J., Duménieu, B. (2022). A
> Benchmark of Named Entity Recognition Approaches in Historical
> Documents Application to 19𝑡ℎ Century French Directories. In: Uc... | null | null | null | null | null | null | null | [
"CamembertForMaskedLM",
"AutoModelForMaskedLM",
"camembert"
] | [
"fill-mask"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175e1f | Huffon/klue-roberta-base-nli | Huffon | null | 301 | 43,332 | False | 2022-03-02T23:29:04Z | 2021-06-20T17:32:53Z | transformers | 5 | 0 | null | text-classification | null | [
".gitattributes",
"README.md",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 3778d23ecb30a63babb17f5efb37b1493b08d975 | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"nli",
"ko",
"dataset:klue",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["RobertaForSequenceClassification"], "model_type": "roberta", "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",
"processor": "AutoTokenizer"
} | {"base_model": null, "datasets": ["klue"], "eval_results": null, "language": "ko", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["roberta", "nli"]} | null | null | [
"klue"
] | [
"ko"
] | null | null | null | [
"roberta",
"AutoModelForSequenceClassification",
"RobertaForSequenceClassification"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] | |
621ffdc036468d709f175e20 | Huffon/qnli | Huffon | null | 3 | 632 | False | 2022-03-02T23:29:04Z | 2021-07-07T03:26:20Z | transformers | 0 | 0 | null | text-classification | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | ada3b36bf4346b219c49f4445bb7e657db07588d | [
"transformers",
"pytorch",
"electra",
"text-classification",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["ElectraForSequenceClassification"], "model_type": "electra", "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 | [
"ElectraForSequenceClassification",
"AutoModelForSequenceClassification",
"electra"
] | [
"text-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175e3e | Humair/all-mpnet-base-v2-finetuned-v2 | Humair | null | 5 | 2,278 | False | 2022-03-02T23:29:04Z | 2022-01-11T12:26:56Z | 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"
] | 8bb08950736f608a4dba7c0bbf8047e255dbb459 | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"transformers",
"text-embeddings-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | {"architectures": ["MPNetModel"], "model_type": "mpnet", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "[UNK]", "pad_token": "<pad>", "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... | # Humair/all-mpnet-base-v2-finetuned-v2
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 ... | null | null | null | null | null | null | null | [
"MPNetModel",
"AutoModel",
"mpnet"
] | [
"sentence-similarity",
"feature-extraction"
] | [
"text",
"multimodal"
] | [
"text"
] | [
"logits",
"embeddings"
] |
621ffdc036468d709f175e4e | HungChau/bert_concept_extraction | HungChau | null | 2 | 585 | False | 2022-03-02T23:29:04Z | 2021-09-03T19:23:40Z | transformers | 1 | 0 | null | token-classification | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | df0c5b53cd8673d99a95a2cdf6b2b19fc0dfdcb1 | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"endpoints_compatible",
"deploy:azure",
"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"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175e4f | HungChau/bert_concept_extraction_iir_from_kp20k_v1.1 | HungChau | null | 0 | 524 | False | 2022-03-02T23:29:04Z | 2021-10-06T14:38:09Z | transformers | 0 | 0 | null | token-classification | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | baa092caeb8f51807aa45d681bf933331b08fe0a | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"endpoints_compatible",
"deploy:azure",
"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"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
] | [
"token-classification"
] | [
"text"
] | [
"text"
] | [
"logits"
] |
621ffdc036468d709f175e50 | HungChau/bert_concept_extraction_kp20k_from_iir_v1.1 | HungChau | null | 2 | 532 | False | 2022-03-02T23:29:04Z | 2021-10-06T15:51:21Z | transformers | 0 | 0 | null | token-classification | null | [
".gitattributes",
"config.json",
"pytorch_model.bin",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.txt"
] | 1ad0900d465ec5dcd808f816da5824868b8b4d22 | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"endpoints_compatible",
"deploy:azure",
"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"
} | null | null | null | null | null | null | null | null | null | [
"AutoModelForTokenClassification",
"distilbert",
"DistilBertForTokenClassification"
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621ffdc036468d709f175e62 | HungChau/distilbert-base-cased-concept-extraction-wikipedia-v1.2 | HungChau | null | 1 | 528 | False | 2022-03-02T23:29:04Z | 2021-11-16T20:44:17Z | transformers | 0 | 0 | null | token-classification | null | [
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621ffdc036468d709f175e63 | HungChau/distilbert-base-uncased-concept-extraction-iir-v1.0-concept-extraction-truncated-3edbbc | HungChau | null | 0 | 416 | False | 2022-03-02T23:29:04Z | 2021-11-02T18:53:48Z | transformers | 0 | 0 | null | token-classification | null | [
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621ffdc036468d709f175e64 | HungChau/distilbert-base-uncased-concept-extraction-iir-v1.0-concept-extraction-kp20k-v1.0 | HungChau | null | 1 | 584 | False | 2022-03-02T23:29:04Z | 2021-09-25T01:32:32Z | transformers | 0 | 0 | null | token-classification | null | [
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621ffdc036468d709f175e65 | HungChau/distilbert-base-uncased-concept-extraction-iir-v1.0-concept-extraction-kp20k-v1.3 | HungChau | null | 3 | 469 | False | 2022-03-02T23:29:04Z | 2021-11-19T10:49:03Z | transformers | 0 | 0 | null | token-classification | null | [
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621ffdc036468d709f175e66 | HungChau/distilbert-base-uncased-concept-extraction-iir-v1.0-concept-extraction-kp20k-v1.4 | HungChau | null | 1 | 476 | False | 2022-03-02T23:29:04Z | 2021-11-19T19:41:47Z | transformers | 0 | 0 | null | token-classification | null | [
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621ffdc036468d709f175e67 | HungChau/distilbert-base-uncased-concept-extraction-iir-v1.0-concept-extraction-wikipedia-v1.0 | HungChau | null | 1 | 530 | False | 2022-03-02T23:29:04Z | 2021-11-01T17:23:38Z | transformers | 0 | 0 | null | token-classification | null | [
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621ffdc036468d709f175e68 | HungChau/distilbert-base-uncased-concept-extraction-iir-v1.0 | HungChau | null | 2 | 1,043 | False | 2022-03-02T23:29:04Z | 2021-09-04T20:57:35Z | transformers | 0 | 0 | null | token-classification | null | [
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