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621ffdc036468d709f1746a2
Alexander-Learn/bert-finetuned-ner
Alexander-Learn
null
9
602
False
2022-03-02T23:29:04Z
2022-01-28T08:29:45Z
transformers
0
0
null
token-classification
null
[ ".gitattributes", ".gitignore", "config.json", "pytorch_model.bin", "runs/Jan28_00-46-41_DESKTOP-R5PDHFI/1643302044.8226619/events.out.tfevents.1643302044.DESKTOP-R5PDHFI.4780.1", "runs/Jan28_00-46-41_DESKTOP-R5PDHFI/events.out.tfevents.1643302044.DESKTOP-R5PDHFI.4780.0", "runs/Jan28_16-05-36_DESKTOP-R5...
e689b6a614c2578786bc150d878f082caedcb6c7
[ "transformers", "pytorch", "tensorboard", "bert", "token-classification", "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" }
null
null
null
null
null
null
null
null
null
[ "AutoModelForTokenClassification", "BertForTokenClassification", "bert" ]
[ "token-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746a4
Alexander-Learn/bert-finetuned-squad
Alexander-Learn
null
18
33,804
False
2022-03-02T23:29:04Z
2022-01-29T09:16:44Z
transformers
0
0
null
question-answering
null
[ ".gitattributes", ".gitignore", "config.json", "pytorch_model.bin", "runs/Jan28_23-16-43_DESKTOP-R5PDHFI/1643383022.1804411/events.out.tfevents.1643383022.DESKTOP-R5PDHFI.29920.1", "runs/Jan28_23-16-43_DESKTOP-R5PDHFI/events.out.tfevents.1643383022.DESKTOP-R5PDHFI.29920.0", "runs/Jan29_09-53-27_DESKTOP-...
4a8f1adebf1f241f0f14682ea3d44f950b31dabc
[ "transformers", "pytorch", "tensorboard", "bert", "question-answering", "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" }
null
null
null
null
null
null
null
null
null
[ "AutoModelForQuestionAnswering", "bert", "BertForQuestionAnswering" ]
[ "question-answering" ]
[ "text" ]
[ "text" ]
[ "text" ]
621ffdc036468d709f1746ba
Alireza1044/albert-base-v2-cola
Alireza1044
null
7
1,650
False
2022-03-02T23:29:04Z
2021-07-25T16:25:10Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "runs/Jul25_15-59-21_ba9036c8942d/1627228785.3837032/events.out.tfevents.1627228785.ba9036c8942d.497.1", "runs/Jul25_15-59-21_ba9036c8942d/events.out.tfevents.1627228785.ba9036c8...
7b3d1e47bc6ad26f49e79ccd3bfb56bf1179528e
[ "transformers", "pytorch", "tensorboard", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "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": "col...
<!-- 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. --> # cola This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE COLA dataset. It a...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "matthews_correlation" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746bb
Alireza1044/albert-base-v2-mnli
Alireza1044
null
58
144,869
False
2022-03-02T23:29:04Z
2021-07-27T21:10:33Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "special_tokens_map.json", "spiece.model", "tokenizer.json", "tokenizer_config.json", "train_results.json", "trainer_state.json", "training_args.bin" ]
ce8224e1445a916d9d9b9f721bed8dad382f35f0
[ "transformers", "pytorch", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "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"], "model_index": [{"name": "mnli", "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. --> # mnli This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE MNLI dataset. It a...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "accuracy" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746bc
Alireza1044/albert-base-v2-mrpc
Alireza1044
null
9
1,449
False
2022-03-02T23:29:04Z
2021-07-26T11:46:48Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "runs/Jul26_11-40-40_578c7831d7ba/1627299664.304798/events.out.tfevents.1627299664.578c7831d7ba.479.1", "runs/Jul26_11-40-40_578c7831d7ba/events.out.tfevents.1627299664.578c7831d...
a12ece8e4cf73d08d4242e016e3ca4685555aff4
[ "transformers", "pytorch", "tensorboard", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy", "f1"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "mrpc", "r...
<!-- 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. --> # mrpc This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE MRPC dataset. It a...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "accuracy", "f1" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746bd
Alireza1044/albert-base-v2-qnli
Alireza1044
null
8
2,356
False
2022-03-02T23:29:04Z
2021-07-27T15:39:56Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "runs/Jul27_12-11-25_nlp992/1627387922.7176468/events.out.tfevents.1627387922.nlp992", "runs/Jul27_12-11-25_nlp992/events.out.tfevents.1627387922.nlp992", "runs/Jul27_12-11-25_...
69a25402725c8a1bfac50d24d3cbd0e779918061
[ "transformers", "pytorch", "tensorboard", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "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"], "model_index": [{"name": "qnli", "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. --> # qnli This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE QNLI dataset. It a...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "accuracy" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746be
Alireza1044/albert-base-v2-qqp
Alireza1044
null
5
1,683
False
2022-03-02T23:29:04Z
2021-07-28T02:04:17Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "special_tokens_map.json", "spiece.model", "tokenizer.json", "tokenizer_config.json", "train_results.json", "trainer_state.json", "training_args.bin" ]
529530efc4e7a27c184e280e7e31dc1177c2c229
[ "transformers", "pytorch", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["accuracy", "f1"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "qqp", "re...
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # qqp This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE QQP dataset. It ach...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "accuracy", "f1" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746bf
Alireza1044/albert-base-v2-rte
Alireza1044
null
9
1,193
False
2022-03-02T23:29:04Z
2021-07-26T12:02:09Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "runs/Jul26_11-58-06_578c7831d7ba/1627300699.7322412/events.out.tfevents.1627300699.578c7831d7ba.628.1", "runs/Jul26_11-58-06_578c7831d7ba/events.out.tfevents.1627300699.578c7831...
42fcb4ff92c3189e5b0193aad2ccd3b62c9e7155
[ "transformers", "pytorch", "tensorboard", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "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"], "model_index": [{"name": "rte", "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. --> # rte This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE RTE dataset. It ach...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "accuracy" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746c0
Alireza1044/albert-base-v2-sst2
Alireza1044
null
264
15,339
False
2022-03-02T23:29:04Z
2021-07-26T14:02:35Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "runs/Jul26_12-21-38_578c7831d7ba/1627302117.7817998/events.out.tfevents.1627302117.578c7831d7ba.805.1", "runs/Jul26_12-21-38_578c7831d7ba/events.out.tfevents.1627302117.578c7831...
e406771b99e1913921a68fbb95d121b582d1ecb7
[ "transformers", "pytorch", "tensorboard", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "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"], "model_index": [{"name": "sst2", "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. --> # sst2 This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE SST2 dataset. It a...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "accuracy" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746c1
Alireza1044/albert-base-v2-stsb
Alireza1044
null
13
1,075
False
2022-03-02T23:29:04Z
2021-07-26T10:57:27Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "runs/Jul26_10-48-21_87e5b6406975/1627296525.161824/events.out.tfevents.1627296525.87e5b6406975.485.1", "runs/Jul26_10-48-21_87e5b6406975/events.out.tfevents.1627296525.87e5b6406...
1fb5f36aefaf6c8d4c037b7648c182836497f6a0
[ "transformers", "pytorch", "tensorboard", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": ["spearmanr"], "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "stsb", "result...
<!-- 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. --> # stsb This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE STSB dataset. It a...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "spearmanr" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746c2
Alireza1044/albert-base-v2-wnli
Alireza1044
null
6
1,283
False
2022-03-02T23:29:04Z
2021-07-28T07:30:04Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "all_results.json", "config.json", "eval_results.json", "pytorch_model.bin", "special_tokens_map.json", "spiece.model", "tokenizer.json", "tokenizer_config.json", "train_results.json", "trainer_state.json", "training_args.bin" ]
2fe5cc30189491cd586095a635f22cd2b723317f
[ "transformers", "pytorch", "albert", "text-classification", "generated_from_trainer", "en", "dataset:glue", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["AlbertForSequenceClassification"], "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": fals...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["glue"], "eval_results": null, "language": ["en"], "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"], "model_index": [{"name": "wnli", "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. --> # wnli This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the GLUE WNLI dataset. It a...
null
[ "apache-2.0" ]
[ "glue" ]
[ "en" ]
null
null
[ "accuracy" ]
[ "AlbertForSequenceClassification", "albert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746c3
Alireza1044/bert_classification_lm
Alireza1044
null
2
926
False
2022-03-02T23:29:04Z
2021-07-09T08:50:58Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", "README.md", "config.json", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "vocab.txt" ]
e44960e937ebbd66268001dc99b679e195ece584
[ "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
A simple model trained on dialogues of characters in NBC series, `The Office`. The model can do a binary classification between `Michael Scott` and `Dwight Shrute`'s dialogues. <style type="text/css"> .tg {border-collapse:collapse;border-spacing:0;} .tg td{border-color:black;border-style:solid;border-width:1px;font-f...
null
null
null
null
null
null
null
[ "BertForSequenceClassification", "bert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1746c4
Alireza1044/dwight_bert_lm
Alireza1044
null
10
3,508
False
2022-03-02T23:29:04Z
2021-07-08T16:54:30Z
transformers
1
0
null
text-generation
null
[ ".gitattributes", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "vocab.json" ]
8869ddafc6f3899e5584aee95495930a54affd01
[ "transformers", "pytorch", "gpt2", "text-generation", "text-generation-inference", "endpoints_compatible", "region:us" ]
null
{"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}}
{ "auto_model": "AutoModelForCausalLM", "custom_class": null, "pipeline_tag": "text-generation", "processor": "AutoTokenizer" }
null
null
null
null
null
null
null
null
null
[ "GPT2LMHeadModel", "AutoModelForCausalLM", "gpt2" ]
[ "text-generation" ]
[ "text" ]
[ "text" ]
[ "text" ]
621ffdc036468d709f1746c5
Alireza1044/michael_bert_lm
Alireza1044
null
7
1,252
False
2022-03-02T23:29:04Z
2021-07-08T16:48:19Z
transformers
0
0
null
text-generation
null
[ ".gitattributes", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "vocab.json" ]
9711c0726453982106d91dbd5e8319e70b45fbd9
[ "transformers", "pytorch", "gpt2", "text-generation", "text-generation-inference", "endpoints_compatible", "region:us" ]
null
{"architectures": ["GPT2LMHeadModel"], "model_type": "gpt2", "tokenizer_config": {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>"}}
{ "auto_model": "AutoModelForCausalLM", "custom_class": null, "pipeline_tag": "text-generation", "processor": "AutoTokenizer" }
null
null
null
null
null
null
null
null
null
[ "GPT2LMHeadModel", "AutoModelForCausalLM", "gpt2" ]
[ "text-generation" ]
[ "text" ]
[ "text" ]
[ "text" ]
621ffdc036468d709f1746c6
AlirezaBaneshi/testPersianQA
AlirezaBaneshi
null
8
584
False
2022-03-02T23:29:04Z
2022-02-01T13:39:46Z
transformers
0
0
null
question-answering
null
[ ".gitattributes", ".ipynb_checkpoints/config-checkpoint.json", ".ipynb_checkpoints/special_tokens_map-checkpoint.json", ".ipynb_checkpoints/tokenizer-checkpoint.json", ".ipynb_checkpoints/tokenizer_config-checkpoint.json", ".ipynb_checkpoints/trainer_state-checkpoint.json", "config.json", "optimizer.p...
b9da3f9d0312318991945208d445a20fce7a4ccd
[ "transformers", "pytorch", "bert", "question-answering", "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" }
null
null
null
null
null
null
null
null
null
[ "AutoModelForQuestionAnswering", "bert", "BertForQuestionAnswering" ]
[ "question-answering" ]
[ "text" ]
[ "text" ]
[ "text" ]
621ffdc036468d709f1746ea
AllwynJ/HarryBoy
AllwynJ
null
7
883
False
2022-03-02T23:29:04Z
2021-09-07T17:42:32Z
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" ]
51794f2dbc5aac3b32d62d0c067eec4527967a96
[ "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" ]
621ffdc036468d709f1746f0
Aloka/mbart50-ft-si-en
Aloka
null
2
570
False
2022-03-02T23:29:04Z
2021-08-29T13:11:14Z
transformers
0
0
null
null
null
[ ".gitattributes", ".gitignore", "README.md", "config.json", "logs/1630242154.849394/events.out.tfevents.1630242154.NLPC-Sita-MLM.222817.1", "logs/events.out.tfevents.1630242154.NLPC-Sita-MLM.222817.0", "pytorch_model.bin", "sentencepiece.bpe.model", "special_tokens_map.json", "tokenizer.json", "...
1c9a9b49487da24bde843d634f8ad81409a8cc20
[ "transformers", "pytorch", "tensorboard", "mbart", "text2text-generation", "generated_from_trainer", "endpoints_compatible", "region:us" ]
null
{"architectures": ["MBartForConditionalGeneration"], "model_type": "mbart", "tokenizer_config": {"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": true, "__typ...
{ "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": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["generated_from_trainer"], "model_index": [{"name": "mbart50-ft-si-en", "results": [{"task...
<!-- 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. --> # mbart50-ft-si-en This model was trained from scratch on an unkown dataset. It achieves the following results on the evaluation se...
null
null
null
null
null
null
null
[ "AutoModelForSeq2SeqLM", "MBartForConditionalGeneration", "mbart" ]
[ "text2text-generation" ]
null
null
null
621ffdc036468d709f1746f4
Alstractor/distilbert-base-uncased-finetuned-cola
Alstractor
null
9
1,039
False
2022-03-02T23:29:04Z
2021-11-04T21:34:27Z
transformers
0
0
[{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "glue", "type": "glue", "args": "cola"}, "metrics": [{"name": "Matthews Correlation", "type": "matthews_correlation", "value": 0.5343023846000738, "verified": fals...
text-classification
null
[ ".gitattributes", ".gitignore", "README.md", "config.json", "pytorch_model.bin", "runs/Nov04_19-44-34_766471bd4f81/1636055080.479724/events.out.tfevents.1636055080.766471bd4f81.65.1", "runs/Nov04_19-44-34_766471bd4f81/events.out.tfevents.1636055080.766471bd4f81.65.0", "runs/Nov04_19-44-34_766471bd4f81...
186e5e4e33fb7f948b8b9a39e0afe317b08ec5ca
[ "transformers", "pytorch", "tensorboard", "distilbert", "text-classification", "generated_from_trainer", "dataset:glue", "license:apache-2.0", "model-index", "text-embeddings-inference", "endpoints_compatible", "region:us" ]
null
{"architectures": ["DistilBertForSequenceClassification"], "model_type": "distilbert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}}
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"datasets": ["glue"], "license": "apache-2.0", "metrics": ["matthews_correlation"], "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "ar...
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis...
null
[ "apache-2.0" ]
[ "glue" ]
null
null
null
[ "matthews_correlation" ]
[ "DistilBertForSequenceClassification", "distilbert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1748be
Amirosein/distilbert_v1
Amirosein
null
3
602
False
2022-03-02T23:29:04Z
2021-09-13T16:37:16Z
transformers
0
0
null
fill-mask
null
[ ".gitattributes", "config.json", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "vocab.txt" ]
382004181c6c1560886773d6b87286fdbf071ed6
[ "transformers", "pytorch", "distilbert", "fill-mask", "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" }
null
null
null
null
null
null
null
null
null
[ "distilbert", "AutoModelForMaskedLM", "DistilBertForMaskedLM" ]
[ "fill-mask" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1748bf
Amirosein/roberta
Amirosein
null
6
1,142
False
2022-03-02T23:29:04Z
2021-09-06T13:41:15Z
transformers
0
0
null
fill-mask
null
[ ".gitattributes", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "vocab.json" ]
d2f41324b98cb1a9dd59f43f305c5e5c0ed0403e
[ "transformers", "pytorch", "roberta", "fill-mask", "endpoints_compatible", "deploy:azure", "region:us" ]
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", "custom_class": null, "pipeline_tag": "fill-mask", "processor": "AutoTokenizer" }
null
null
null
null
null
null
null
null
null
[ "roberta", "AutoModelForMaskedLM", "RobertaForMaskedLM" ]
[ "fill-mask" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1748e5
Anamika/autonlp-Feedback1-479512837
Anamika
null
6
836
False
2022-03-02T23:29:04Z
2022-01-06T10:05:22Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", "README.md", "config.json", "pytorch_model.bin", "sample_input.pkl", "sentencepiece.bpe.model", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json" ]
a5bb03ff52dd6e41f84962bfc14b4e1424e7bc40
[ "transformers", "pytorch", "xlm-roberta", "text-classification", "unk", "dataset:Anamika/autonlp-data-Feedback1", "co2_eq_emissions", "text-embeddings-inference", "endpoints_compatible", "region:us" ]
null
{"architectures": ["XLMRobertaForSequenceClassification"], "model_type": "xlm-roberta", "tokenizer_config": {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": f...
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["Anamika/autonlp-data-Feedback1"], "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: Multi-class Classification - Model ID: 479512837 - CO2 Emissions (in grams): 123.88023112815048 ## Validation Metrics - Loss: 0.6220805048942566 - Accuracy: 0.7961119332705503 - Macro F1: 0.7616345204219084 - Micro F1: 0.7961119332705503 - Weighted F1: 0.795387503907883 ...
null
null
[ "Anamika/autonlp-data-Feedback1" ]
[ "unk" ]
null
null
null
[ "AutoModelForSequenceClassification", "XLMRobertaForSequenceClassification", "xlm-roberta" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f1748f5
Anamika/autonlp-fa-473312409
Anamika
null
5
817
False
2022-03-02T23:29:04Z
2022-01-04T20:08:00Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", "README.md", "config.json", "merges.txt", "pytorch_model.bin", "sample_input.pkl", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "vocab.json" ]
30f4541f49f67d3887c5f2161a2513c6a2741e55
[ "transformers", "pytorch", "roberta", "text-classification", "en", "dataset:Anamika/autonlp-data-fa", "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>"}}
{ "auto_model": "AutoModelForSequenceClassification", "custom_class": null, "pipeline_tag": "text-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["Anamika/autonlp-data-fa"], "eval_results": null, "language": "en", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": null, "widget": [{"text": "I love AutoNLP \ud83e\udd17"}], "co2_eq_e...
# Model Trained Using AutoNLP - Problem type: Multi-class Classification - Model ID: 473312409 - CO2 Emissions (in grams): 25.128735714898614 ## Validation Metrics - Loss: 0.6010786890983582 - Accuracy: 0.7990650945370823 - Macro F1: 0.7429662929144928 - Micro F1: 0.7990650945370823 - Weighted F1: 0.7977660363770382...
null
null
[ "Anamika/autonlp-data-fa" ]
[ "en" ]
null
null
null
[ "roberta", "AutoModelForSequenceClassification", "RobertaForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174912
Andranik/TestPytorchClassification
Andranik
null
5
867
False
2022-03-02T23:29:04Z
2022-02-17T12:49:56Z
transformers
0
0
null
text-classification
null
[ ".gitattributes", "config.json", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "trainer_state.json", "training_args.bin", "vocab.txt" ]
73b294c609be1d24afd9d9c22cf7532416b616a7
[ "transformers", "pytorch", "distilbert", "text-classification", "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" }
null
null
null
null
null
null
null
null
null
[ "DistilBertForSequenceClassification", "distilbert", "AutoModelForSequenceClassification" ]
[ "text-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174915
AndreLiu1225/t5-news-summarizer
AndreLiu1225
null
4
1,937
False
2022-03-02T23:29:04Z
2021-10-26T02:45:12Z
transformers
1
0
null
null
null
[ ".gitattributes", "config.json", "pytorch_model.bin", "tokenizer.json" ]
6e9436cab957ec608164ab041bcbaeed12dcb357
[ "transformers", "pytorch", "t5", "text2text-generation", "text-generation-inference", "endpoints_compatible", "region:us" ]
null
{"architectures": ["T5ForConditionalGeneration"], "model_type": "t5"}
{ "auto_model": "AutoModelForSeq2SeqLM", "custom_class": null, "pipeline_tag": "text2text-generation", "processor": "AutoTokenizer" }
null
null
null
null
null
null
null
null
null
[ "t5", "T5ForConditionalGeneration", "AutoModelForSeq2SeqLM" ]
[ "text2text-generation" ]
null
null
null
621ffdc036468d709f174916
AndreLiu1225/t5-news
AndreLiu1225
null
9
1,327
False
2022-03-02T23:29:04Z
2021-10-26T02:49:39Z
transformers
0
0
null
null
null
[ ".gitattributes", "README.md", "config.json", "pytorch_model.bin", "tokenizer.json" ]
687ebc613881f80d2dbf047080a4629793f303c4
[ "transformers", "pytorch", "t5", "text2text-generation", "text-generation-inference", "endpoints_compatible", "region:us" ]
null
{"architectures": ["T5ForConditionalGeneration"], "model_type": "t5"}
{ "auto_model": "AutoModelForSeq2SeqLM", "custom_class": null, "pipeline_tag": "text2text-generation", "processor": "AutoTokenizer" }
null
This is a pretrained model that was loaded from t5-base. It has been adapted and changed by changing the max_length and summary_length.
null
null
null
null
null
null
null
[ "t5", "T5ForConditionalGeneration", "AutoModelForSeq2SeqLM" ]
[ "text2text-generation" ]
null
null
null
621ffdc036468d709f17491d
AndrewChar/model-QA-5-epoch-RU
AndrewChar
null
26
8,283
False
2022-03-02T23:29:04Z
2022-11-29T19:36:19Z
transformers
17
0
[{"name": "model-QA-5-epoch-RU", "results": []}]
question-answering
null
[ ".gitattributes", "README.md", "config.json", "special_tokens_map.json", "tf_model.h5", "tokenizer.json", "tokenizer_config.json", "vocab.txt" ]
f11caf9b13c71759fe68edab2114f46018ef4c97
[ "transformers", "tf", "distilbert", "question-answering", "generated_from_keras_callback", "ru", "dataset:sberquad", "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": ["sberquad"], "eval_results": [], "language": "ru", "library_name": null, "license": null, "license_name": null, "license_link": null, "metrics": null, "model_name": "model-QA-5-epoch-RU", "pipeline_tag": null, "tags": ["generated_from_keras_callback"]}
<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # model-QA-5-epoch-RU This model is a fine-tuned version of [AndrewChar/diplom-prod-epoch-4-datast-sber-QA](https://huggingface.co/Andrew...
null
null
[ "sberquad" ]
[ "ru" ]
null
null
null
[ "AutoModelForQuestionAnswering", "distilbert", "DistilBertForQuestionAnswering" ]
[ "question-answering" ]
[ "text" ]
[ "text" ]
[ "text" ]
621ffdc036468d709f174936
Andrey1989/mbert-finetuned-ner
Andrey1989
null
5
2,599
False
2022-03-02T23:29:04Z
2022-06-13T19:46:59Z
transformers
0
0
[{"name": "mbert-finetuned-ner", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "wikiann", "type": "wikiann", "args": "lv"}, "metrics": [{"name": "Precision", "type": "precision", "value": 0.9304986338797814, "verified": false}, {"name": "Recall", "type": "rec...
token-classification
null
[ ".gitattributes", ".gitignore", "README.md", "config.json", "pytorch_model.bin", "runs/Jun13_19-19-13_8f81cefabf14/1655147982.5574117/events.out.tfevents.1655147982.8f81cefabf14.73.1", "runs/Jun13_19-19-13_8f81cefabf14/events.out.tfevents.1655147982.8f81cefabf14.73.0", "runs/Jun13_19-19-13_8f81cefabf1...
a60a40c0f4842458f777c5a1a13f53c4d36174b2
[ "transformers", "pytorch", "tensorboard", "bert", "token-classification", "generated_from_trainer", "dataset:wikiann", "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": ["wikiann"], "license": "apache-2.0", "metrics": ["precision", "recall", "f1", "accuracy"], "tags": ["generated_from_trainer"], "model-index": [{"name": "mbert-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "wikiann", "type": "wiki...
<!-- 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. --> # mbert-finetuned-ner This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multili...
null
[ "apache-2.0" ]
[ "wikiann" ]
null
null
null
[ "precision", "recall", "f1", "accuracy" ]
[ "AutoModelForTokenClassification", "BertForTokenClassification", "bert" ]
[ "token-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f17493d
Andrija/M-bert-NER
Andrija
null
5
1,137
False
2022-03-02T23:29:04Z
2023-01-01T14:31:58Z
transformers
0
0
null
token-classification
null
[ ".gitattributes", "README.md", "config.json", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "training_args.bin", "vocab.txt" ]
fa5e0d0cc072e7c0f62a58969d0a012bb534c2b5
[ "transformers", "pytorch", "bert", "token-classification", "hr", "sr", "multilingual", "dataset:hr500k", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["BertForTokenClassification"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}}
{ "auto_model": "AutoModelForTokenClassification", "custom_class": null, "pipeline_tag": "token-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["hr500k"], "eval_results": null, "language": ["hr", "sr", "multilingual"], "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": "Moje ime je Aleksandar i z...
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges. Abbreviation|Description -|- O|Outside of a named entity B-MIS |Beginning of a miscellaneous entity right after another miscellaneous entity I-MIS | Miscellaneous entity B-PER |Beginning of a person's name right after another person'...
null
[ "apache-2.0" ]
[ "hr500k" ]
[ "hr", "sr", "multilingual" ]
null
null
null
[ "AutoModelForTokenClassification", "BertForTokenClassification", "bert" ]
[ "token-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f17493f
Andrija/SRoBERTa-F
Andrija
null
6
2,393
False
2022-03-02T23:29:04Z
2023-01-03T20:49:02Z
transformers
2
0
null
fill-mask
null
[ ".gitattributes", "README.md", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tensorboard/runs/Sep17_08-48-51/1631861373.8012724/events.out.tfevents.1631861373.DESKTOP-GORLUXOR.14768.1", "tensorboard/runs/Sep17_08-48-51/events.out.tfevents.1631861373.DESKTOP-GORLUXOR.147...
75e99c47e05870f5d933c6c445826e51a8058c53
[ "transformers", "pytorch", "tensorboard", "roberta", "fill-mask", "masked-lm", "hr", "sr", "multilingual", "dataset:oscar", "dataset:srwac", "dataset:leipzig", "dataset:cc100", "dataset:hrwac", "license:apache-2.0", "endpoints_compatible", "region:us" ]
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", "custom_class": null, "pipeline_tag": "fill-mask", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["oscar", "srwac", "leipzig", "cc100", "hrwac"], "eval_results": null, "language": ["hr", "sr", "multilingual"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["masked-lm"], "...
# Transformer language model for Croatian and Serbian Trained on 43GB datasets that contain Croatian and Serbian language for one epochs (9.6 mil. steps, 3 epochs). Leipzig Corpus, OSCAR, srWac, hrWac, cc100-hr and cc100-sr datasets Validation number of exampels run for perplexity:1620487 sentences Perplexity:6.02 St...
null
[ "apache-2.0" ]
[ "oscar", "srwac", "leipzig", "cc100", "hrwac" ]
[ "hr", "sr", "multilingual" ]
null
null
null
[ "roberta", "AutoModelForMaskedLM", "RobertaForMaskedLM" ]
[ "fill-mask" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174940
Andrija/SRoBERTa-L-NER
Andrija
null
9
1,383
False
2022-03-02T23:29:04Z
2023-01-01T14:52:27Z
transformers
0
0
null
token-classification
null
[ ".gitattributes", "README.md", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "training_args.bin", "vocab.json" ]
8ed39d3123797275ff8e05e8128da4436a4dfe59
[ "transformers", "pytorch", "roberta", "token-classification", "hr", "sr", "multilingual", "dataset:hr500k", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["RobertaForTokenClassification"], "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...
{ "auto_model": "AutoModelForTokenClassification", "custom_class": null, "pipeline_tag": "token-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["hr500k"], "eval_results": null, "language": ["hr", "sr", "multilingual"], "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": "Moje ime je Aleksandar i z...
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges. Abbreviation|Description -|- O|Outside of a named entity B-MIS |Beginning of a miscellaneous entity right after another miscellaneous entity I-MIS | Miscellaneous entity B-PER |Beginning of a person’s name right after another person’...
null
[ "apache-2.0" ]
[ "hr500k" ]
[ "hr", "sr", "multilingual" ]
null
null
null
[ "roberta", "AutoModelForTokenClassification", "RobertaForTokenClassification" ]
[ "token-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174941
Andrija/SRoBERTa-L
Andrija
null
5
1,475
False
2022-03-02T23:29:04Z
2023-01-01T14:51:44Z
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", "training_args.bin", "vocab.json" ]
fbaa893ff99611980a78a64b549138c113216830
[ "transformers", "pytorch", "roberta", "fill-mask", "masked-lm", "hr", "sr", "multilingual", "dataset:oscar", "dataset:srwac", "dataset:leipzig", "license:apache-2.0", "endpoints_compatible", "region:us" ]
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", "custom_class": null, "pipeline_tag": "fill-mask", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["oscar", "srwac", "leipzig"], "eval_results": null, "language": ["hr", "sr", "multilingual"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["masked-lm"], "widget": [{"text":...
# Transformer language model for Croatian and Serbian Trained on 6GB datasets that contain Croatian and Serbian language for two epochs (500k steps). Leipzig, OSCAR and srWac datasets | Model | #params | Arch. | Training data | |----------------------...
null
[ "apache-2.0" ]
[ "oscar", "srwac", "leipzig" ]
[ "hr", "sr", "multilingual" ]
null
null
null
[ "roberta", "AutoModelForMaskedLM", "RobertaForMaskedLM" ]
[ "fill-mask" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174942
Andrija/SRoBERTa-NER
Andrija
null
5
1,325
False
2022-03-02T23:29:04Z
2023-01-01T14:52:19Z
transformers
0
0
null
token-classification
null
[ ".gitattributes", "README.md", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "training_args.bin", "vocab.json" ]
792c62905c5011f10b3e6deeeab176380678e5f3
[ "transformers", "pytorch", "roberta", "token-classification", "hr", "sr", "multilingual", "dataset:hr500k", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["RobertaForTokenClassification"], "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...
{ "auto_model": "AutoModelForTokenClassification", "custom_class": null, "pipeline_tag": "token-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["hr500k"], "eval_results": null, "language": ["hr", "sr", "multilingual"], "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": "Moje ime je Aleksandar i z...
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges. Abbreviation|Description -|- O|Outside of a named entity B-MIS |Beginning of a miscellaneous entity right after another miscellaneous entity I-MIS | Miscellaneous entity B-PER |Beginning of a person’s name right after another person’...
null
[ "apache-2.0" ]
[ "hr500k" ]
[ "hr", "sr", "multilingual" ]
null
null
null
[ "roberta", "AutoModelForTokenClassification", "RobertaForTokenClassification" ]
[ "token-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174943
Andrija/SRoBERTa-NLP
Andrija
null
5
1,152
False
2022-03-02T23:29:04Z
2021-07-08T13:25:21Z
transformers
0
0
null
token-classification
null
[ ".gitattributes", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "training_args.bin", "vocab.json" ]
3d92ea3db1161f2cd8d590a2cefd9290a5f72d1c
[ "transformers", "pytorch", "roberta", "token-classification", "endpoints_compatible", "region:us" ]
null
{"architectures": ["RobertaForTokenClassification"], "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...
{ "auto_model": "AutoModelForTokenClassification", "custom_class": null, "pipeline_tag": "token-classification", "processor": "AutoTokenizer" }
null
null
null
null
null
null
null
null
null
[ "roberta", "AutoModelForTokenClassification", "RobertaForTokenClassification" ]
[ "token-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174944
Andrija/SRoBERTa-XL-NER
Andrija
null
11
1,348
False
2022-03-02T23:29:04Z
2023-01-01T14:51:37Z
transformers
0
0
null
token-classification
null
[ ".gitattributes", "README.md", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "training_args.bin", "vocab.json" ]
ad019943cf582906df7269d19c09e7dc414cdb47
[ "transformers", "pytorch", "roberta", "token-classification", "hr", "sr", "multilingual", "dataset:hr500k", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["RobertaForTokenClassification"], "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...
{ "auto_model": "AutoModelForTokenClassification", "custom_class": null, "pipeline_tag": "token-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["hr500k"], "eval_results": null, "language": ["hr", "sr", "multilingual"], "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": "Moje ime je Aleksandar i z...
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges. Abbreviation|Description -|- O|Outside of a named entity B-MIS |Beginning of a miscellaneous entity right after another miscellaneous entity I-MIS | Miscellaneous entity B-PER |Beginning of a person's name right after another person'...
null
[ "apache-2.0" ]
[ "hr500k" ]
[ "hr", "sr", "multilingual" ]
null
null
null
[ "roberta", "AutoModelForTokenClassification", "RobertaForTokenClassification" ]
[ "token-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174945
Andrija/SRoBERTa-XL
Andrija
null
5
1,808
False
2022-03-02T23:29:04Z
2023-01-01T14:52:12Z
transformers
2
0
null
fill-mask
null
[ ".gitattributes", "README.md", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "training_args.bin", "vocab.json" ]
98ef316b48c50ca00f7402431440811327396195
[ "transformers", "pytorch", "roberta", "fill-mask", "masked-lm", "hr", "sr", "multilingual", "dataset:oscar", "dataset:srwac", "dataset:leipzig", "dataset:cc100", "dataset:hrwac", "license:apache-2.0", "endpoints_compatible", "region:us" ]
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", "custom_class": null, "pipeline_tag": "fill-mask", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["oscar", "srwac", "leipzig", "cc100", "hrwac"], "eval_results": null, "language": ["hr", "sr", "multilingual"], "library_name": null, "license": "apache-2.0", "license_name": null, "license_link": null, "metrics": null, "model_name": null, "pipeline_tag": null, "tags": ["masked-lm"], "...
# Transformer language model for Croatian and Serbian Trained on 28GB datasets that contain Croatian and Serbian language for one epochs (3 mil. steps). Leipzig Corpus, OSCAR, srWac, hrWac, cc100-hr and cc100-sr datasets | Model | #params | Arch. | Training data ...
null
[ "apache-2.0" ]
[ "oscar", "srwac", "leipzig", "cc100", "hrwac" ]
[ "hr", "sr", "multilingual" ]
null
null
null
[ "roberta", "AutoModelForMaskedLM", "RobertaForMaskedLM" ]
[ "fill-mask" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174946
Andrija/SRoBERTa-base-NER
Andrija
null
5
1,272
False
2022-03-02T23:29:04Z
2023-01-01T14:51:52Z
transformers
0
0
null
token-classification
null
[ ".gitattributes", "README.md", "config.json", "merges.txt", "pytorch_model.bin", "special_tokens_map.json", "tokenizer.json", "tokenizer_config.json", "training_args.bin", "vocab.json" ]
aab36d368ca0b9d8c02719b7ee582e0180f8ff20
[ "transformers", "pytorch", "roberta", "token-classification", "hr", "sr", "multilingual", "dataset:hr500k", "license:apache-2.0", "endpoints_compatible", "region:us" ]
null
{"architectures": ["RobertaForTokenClassification"], "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...
{ "auto_model": "AutoModelForTokenClassification", "custom_class": null, "pipeline_tag": "token-classification", "processor": "AutoTokenizer" }
{"base_model": null, "datasets": ["hr500k"], "eval_results": null, "language": ["hr", "sr", "multilingual"], "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": "Moje ime je Aleksandar i z...
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges. Abbreviation|Description -|- O|Outside of a named entity B-MIS |Beginning of a miscellaneous entity right after another miscellaneous entity I-MIS | Miscellaneous entity B-PER |Beginning of a person’s name right after another person’...
null
[ "apache-2.0" ]
[ "hr500k" ]
[ "hr", "sr", "multilingual" ]
null
null
null
[ "roberta", "AutoModelForTokenClassification", "RobertaForTokenClassification" ]
[ "token-classification" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f17494f
AndyJ/prompt_finetune
AndyJ
null
2
596
False
2022-03-02T23:29:04Z
2022-02-17T01:25:00Z
transformers
0
0
null
fill-mask
null
[ ".gitattributes", "config.json", "pytorch_model.bin", "tokenizer.json", "tokenizer_config.json", "vocab.txt" ]
9f06e8b528686a6bbd412ca861e1eceaf3e58902
[ "transformers", "pytorch", "bert", "fill-mask", "endpoints_compatible", "deploy:azure", "region:us" ]
null
{"architectures": ["BertForMaskedLM"], "model_type": "bert", "tokenizer_config": {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}}
{ "auto_model": "AutoModelForMaskedLM", "custom_class": null, "pipeline_tag": "fill-mask", "processor": "AutoTokenizer" }
null
null
null
null
null
null
null
null
null
[ "AutoModelForMaskedLM", "bert", "BertForMaskedLM" ]
[ "fill-mask" ]
[ "text" ]
[ "text" ]
[ "logits" ]
621ffdc036468d709f174950
AndyyyCai/bert-base-uncased-finetuned-copa
AndyyyCai
null
28
704
False
2022-03-02T23:29:04Z
2022-03-01T01:57:06Z
transformers
0
0
null
multiple-choice
null
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0bb6de71cc070a8941075d0aee15e6ac07f1a35f
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null
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null
null
null
null
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null
null
null
null
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null
null
null
621ffdc036468d709f174970
tensor-trek/distilbert-base-uncased-finetuned-emotion
tensor-trek
null
5
804
False
2022-03-02T23:29:04Z
2023-09-18T15:43:40Z
transformers
0
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null
text-classification
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436d59563dd5f7e2a4b646430a8d4fda69d2f404
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null
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null
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null
null
null
66,958,086
null
null
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621ffdc036468d709f174977
Ann2020/distilbert-base-uncased-finetuned-ner
Ann2020
null
7
681
False
2022-03-02T23:29:04Z
2021-08-29T21:13:47Z
transformers
0
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null
token-classification
null
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3282a339ef223c6d92a19a99bbf89034ac0d2ff2
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null
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<!-- 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" ]
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null
null
null
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621ffdc036468d709f174983
AnonARR/qqp-bert
AnonARR
null
1
858
False
2022-03-02T23:29:04Z
2021-11-15T21:25:04Z
transformers
0
0
null
text-classification
null
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4e29cc176eba764a341e5bf18854c634a1334e73
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null
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null
null
null
null
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null
null
null
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621ffdc036468d709f17498d
AnonymousSub/AR_EManuals-BERT
AnonymousSub
null
2
787
False
2022-03-02T23:29:04Z
2022-01-12T11:32:11Z
transformers
0
0
null
feature-extraction
null
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ddf509723349598a7d6f23e9a69bd846a09c9bed
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null
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null
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null
null
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621ffdc036468d709f17498e
AnonymousSub/AR_EManuals-RoBERTa
AnonymousSub
null
3
689
False
2022-03-02T23:29:04Z
2022-01-12T11:38:46Z
transformers
0
0
null
feature-extraction
null
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0993104955b4a40dc0d9be443af1338d74cd48fc
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null
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null
null
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null
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621ffdc036468d709f17498f
AnonymousSub/AR_SDR_HF_model_base
AnonymousSub
null
3
652
False
2022-03-02T23:29:04Z
2022-01-11T21:48:47Z
transformers
0
0
null
feature-extraction
null
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2ca620015458f285b6d37b67e14f7c477afd6f98
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null
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null
null
null
null
null
null
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621ffdc036468d709f174990
AnonymousSub/AR_bert-base-uncased
AnonymousSub
null
2
805
False
2022-03-02T23:29:04Z
2022-01-12T11:46:29Z
transformers
0
0
null
feature-extraction
null
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0d8cf9911bc0d76b7c396d5c86960122c3e406bd
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null
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null
null
null
null
null
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null
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621ffdc036468d709f174991
AnonymousSub/AR_cline
AnonymousSub
null
1
709
False
2022-03-02T23:29:04Z
2022-01-12T11:50:55Z
transformers
0
0
null
feature-extraction
null
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1d20e3384b8135523ca500eca7315332f0781440
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null
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621ffdc036468d709f174992
AnonymousSub/AR_consert
AnonymousSub
null
3
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False
2022-03-02T23:29:04Z
2022-01-12T12:04:53Z
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0
0
null
feature-extraction
null
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e561e0a3a07658d1cc4e9bf2faa0d403d2c8709b
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null
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null
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621ffdc036468d709f174993
AnonymousSub/AR_declutr
AnonymousSub
null
1
687
False
2022-03-02T23:29:04Z
2022-01-12T12:09:19Z
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0
0
null
feature-extraction
null
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null
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621ffdc036468d709f174994
AnonymousSub/AR_rule_based_bert_quadruplet_epochs_1_shard_1
AnonymousSub
null
4
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False
2022-03-02T23:29:04Z
2022-01-11T00:05:10Z
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null
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null
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fa2dc9306ac53153f270a5c5d80daf6c98b2402c
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null
null
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null
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621ffdc036468d709f174995
AnonymousSub/AR_rule_based_bert_triplet_epochs_1_shard_1
AnonymousSub
null
1
718
False
2022-03-02T23:29:04Z
2022-01-10T23:12:46Z
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0
0
null
feature-extraction
null
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9dc04a82bd49757cff625f995f559270b934e656
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null
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null
null
null
null
null
null
null
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null
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621ffdc036468d709f174996
AnonymousSub/AR_rule_based_hier_quadruplet_epochs_1_shard_1
AnonymousSub
null
5
4,563
False
2022-03-02T23:29:04Z
2022-01-10T22:20:52Z
transformers
0
0
null
feature-extraction
null
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2e3de1d312bfc6095360785a4bd7b9fa5b0fdab4
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null
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null
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null
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null
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621ffdc036468d709f174997
AnonymousSub/AR_rule_based_hier_triplet_epochs_1_shard_1
AnonymousSub
null
2
644
False
2022-03-02T23:29:04Z
2022-01-11T02:24:42Z
transformers
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null
feature-extraction
null
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be8acb687c0ed327d53967e21e4cb3d06e2f575f
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null
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null
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621ffdc036468d709f174998
AnonymousSub/AR_rule_based_only_classfn_epochs_1_shard_1
AnonymousSub
null
4
687
False
2022-03-02T23:29:04Z
2022-01-11T00:40:06Z
transformers
0
0
null
feature-extraction
null
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b724746a40834c06050f53a7c659453551e14192
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null
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null
null
null
null
null
null
null
null
null
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621ffdc036468d709f174999
AnonymousSub/AR_rule_based_only_classfn_twostage_epochs_1_shard_1
AnonymousSub
null
1
578
False
2022-03-02T23:29:04Z
2022-01-11T01:50:15Z
transformers
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0
null
feature-extraction
null
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b2e118d50c6477837ff04cf24bc7a56132963a25
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null
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null
null
null
null
null
null
null
null
null
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621ffdc036468d709f17499a
AnonymousSub/AR_rule_based_roberta_bert_quadruplet_epochs_1_shard_1
AnonymousSub
null
1
612
False
2022-03-02T23:29:04Z
2022-01-06T13:53:01Z
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0
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null
feature-extraction
null
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89e8b8ff7aab0d9767610cd76694d424725a6e1e
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null
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null
null
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null
null
null
null
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621ffdc036468d709f17499b
AnonymousSub/AR_rule_based_roberta_bert_quadruplet_epochs_1_shard_10
AnonymousSub
null
1
543
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2022-03-02T23:29:04Z
2022-01-06T14:29:39Z
transformers
0
0
null
feature-extraction
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AnonymousSub/AR_rule_based_twostage_quadruplet_epochs_1_shard_1
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AnonymousSub/AR_rule_based_twostagequadruplet_hier_epochs_1_shard_1
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AnonymousSub/AR_rule_based_twostagetriplet_epochs_1_shard_1
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AnonymousSub/AR_rule_based_twostagetriplet_hier_epochs_1_shard_1
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AnonymousSub/AR_specter
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AnonymousSub/SDR_HF_model_base
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AnonymousSub/SR_EManuals-BERT
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AnonymousSub/SR_EManuals-RoBERTa
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AnonymousSub/SR_SDR_HF_model_base
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AnonymousSub/SR_bert-base-uncased
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AnonymousSub/SR_cline
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AnonymousSub/SR_consert
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AnonymousSub/SR_declutr
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AnonymousSub/SR_rule_based_bert_quadruplet_epochs_1_shard_1
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AnonymousSub/SR_rule_based_bert_triplet_epochs_1_shard_1
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AnonymousSub/SR_rule_based_hier_quadruplet_epochs_1_shard_1
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AnonymousSub/SR_rule_based_hier_triplet_epochs_1_shard_1
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AnonymousSub/SR_rule_based_only_classfn_epochs_1_shard_1
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AnonymousSub/SR_rule_based_only_classfn_twostage_epochs_1_shard_1
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AnonymousSub/SR_rule_based_roberta_bert_quadruplet_epochs_1_shard_1
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AnonymousSub/SR_rule_based_roberta_bert_quadruplet_epochs_1_shard_10
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AnonymousSub/SR_rule_based_roberta_bert_triplet_epochs_1_shard_1
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AnonymousSub/SR_rule_based_roberta_bert_triplet_epochs_1_shard_10
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AnonymousSub/SR_rule_based_roberta_hier_quadruplet_epochs_1_shard_1
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AnonymousSub/SR_rule_based_roberta_hier_quadruplet_epochs_1_shard_10
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AnonymousSub/SR_rule_based_roberta_hier_triplet_epochs_1_shard_1
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