modelId stringlengths 4 112 | sha stringlengths 40 40 | lastModified stringlengths 24 24 | tags list | pipeline_tag stringclasses 29
values | private bool 1
class | author stringlengths 2 38 ⌀ | config null | id stringlengths 4 112 | downloads float64 0 36.8M ⌀ | likes float64 0 712 ⌀ | library_name stringclasses 17
values | __index_level_0__ int64 0 38.5k | readme stringlengths 0 186k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
cambridgeltl/sst_distilbert-base-uncased | fde3ca1b6ad8e5468c2f79396dc054c7c9133e6d | 2022-03-14T10:27:44.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | cambridgeltl | null | cambridgeltl/sst_distilbert-base-uncased | 15 | null | transformers | 9,600 | Entry not found |
RobertoMCA97/xlm-roberta-base-finetuned-panx-fr | e96d13944859e199d637d1bd4c5c0ab0e5fac36e | 2022-03-16T12:40:56.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | RobertoMCA97 | null | RobertoMCA97/xlm-roberta-base-finetuned-panx-fr | 15 | null | transformers | 9,601 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-fr
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.fr
metrics:
- name:... |
Guen/guen_test_prompt_generation | f68fe0b1ddb9b2145491b2a1b4771e9b6459664f | 2022-03-16T22:33:29.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Guen | null | Guen/guen_test_prompt_generation | 15 | null | transformers | 9,602 | A small language generation head to generate text from a prompt.
Fine-tuned on the t5-base model with the aeslc dataset. |
IIC/beto-base-spanish-sqac | e74bc7eeae45fa19b5a6f37c438ebdad1eacb9a8 | 2022-04-02T15:10:05.000Z | [
"pytorch",
"bert",
"question-answering",
"es",
"dataset:PlanTL-GOB-ES/SQAC",
"arxiv:2107.07253",
"transformers",
"model-index",
"autotrain_compatible"
] | question-answering | false | IIC | null | IIC/beto-base-spanish-sqac | 15 | 1 | transformers | 9,603 | ---
language:
- es
tags:
- question-answering # Example: audio
datasets:
- PlanTL-GOB-ES/SQAC
metrics:
- f1
# Optional. Add this if you want to encode your eval results in a structured way.
model-index:
- name: beto-base-spanish_sqac
results:
- task:
type: question-answering # Required. Example: automatic-s... |
Graphcore/roberta-base-squad | 270a133d717f6135c9319146d241b1cbe1442518 | 2022-05-25T18:34:13.000Z | [
"pytorch",
"roberta",
"question-answering",
"dataset:squad",
"arxiv:1907.11692",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | Graphcore | null | Graphcore/roberta-base-squad | 15 | null | transformers | 9,604 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: Graphcore/roberta-base-squad
results: []
---
# Graphcore/roberta-base-squad
BERT (Bidirectional Encoder Representations from Transformers) is a transformers model which is designed to pretrain bidirectional representation... |
agdsga/bert-base-chinese-finetuned-ner | f95e5267f291c474e9fcb4ec5f1684a008676246 | 2022-03-24T12:52:39.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | agdsga | null | agdsga/bert-base-chinese-finetuned-ner | 15 | null | transformers | 9,605 | Entry not found |
l3cube-pune/hing-gpt-devanagari | 9b164b142a274ec0608329ac134aa4b9f267bdf3 | 2022-06-26T15:11:27.000Z | [
"pytorch",
"gpt2",
"text-generation",
"hi",
"en",
"dataset:L3Cube-HingCorpus",
"arxiv:2204.08398",
"transformers",
"codemix",
"license:cc-by-4.0"
] | text-generation | false | l3cube-pune | null | l3cube-pune/hing-gpt-devanagari | 15 | null | transformers | 9,606 | ---
license: cc-by-4.0
language:
- hi
- en
tags:
- hi
- en
- codemix
datasets:
- L3Cube-HingCorpus
---
## HingGPT-Devanagari
HingGPT-Devanagari is a Hindi-English code-mixed GPT model trained on Devanagari text. It is a GPT2 model trained on L3Cube-HingCorpus.
<br>
[dataset link] (https://github.com/l3cube-pune/code-... |
danhsf/distilbert-base-uncased-finetuned-emotion | 2f993e57a11f857b435572fab823c0f80ae0c82a | 2022-03-31T02:39:15.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | danhsf | null | danhsf/distilbert-base-uncased-finetuned-emotion | 15 | null | transformers | 9,607 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
KeithHorgan/TweetClimateAnalysis | e2ed0bc3ab4cd9462fc6e34ff7334a4638f537f5 | 2022-03-29T10:01:24.000Z | [
"pytorch",
"roberta",
"text-classification",
"unk",
"dataset:KeithHorgan98/autotrain-data-TweetClimateAnalysis",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | KeithHorgan | null | KeithHorgan/TweetClimateAnalysis | 15 | null | transformers | 9,608 | ---
tags: autotrain
language: unk
widget:
- text: "Climate Change is a hoax"
- text: "It is freezing, where is global warming"
datasets:
- KeithHorgan98/autotrain-data-TweetClimateAnalysis
co2_eq_emissions: 133.19491276284793
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 6... |
asafaya/hubert-xlarge-turkish | 81076860defe06bb56875f07cfcea720f2f1c320 | 2022-03-29T13:07:20.000Z | [
"pytorch",
"hubert",
"feature-extraction",
"transformers",
"license:cc-by-nc-4.0"
] | feature-extraction | false | asafaya | null | asafaya/hubert-xlarge-turkish | 15 | null | transformers | 9,609 | ---
license: cc-by-nc-4.0
---
|
Suyogyart/nepali-16-newsgroups-classification | acf4e369beed85101a8785869fff6c0ad04fb2b2 | 2022-03-31T15:28:37.000Z | [
"pytorch",
"distilbert",
"text-classification",
"ne",
"transformers",
"multiclass-classification",
"newsgroup",
"nepali",
"license:apache-2.0"
] | text-classification | false | Suyogyart | null | Suyogyart/nepali-16-newsgroups-classification | 15 | null | transformers | 9,610 | ---
license: apache-2.0
language: ne
tags:
- multiclass-classification
- newsgroup
- nepali
---
# Nepali 16 News Group Classification
This model is suitable for classifying news categories in Nepali language into 16 different groups. It is fine-tuned on a pretrained DistilBERT model with ... |
alina1997/en_de_translation | 5dc8f4117e6f6f13f6d46d528cf7ff286cb72d5a | 2022-04-03T09:54:04.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | alina1997 | null | alina1997/en_de_translation | 15 | null | transformers | 9,611 | Entry not found |
hackathon-pln-es/readability-es-paragraphs | 87e56e2f678e8d2aaec9050dec9843a53c8fa168 | 2022-04-04T10:41:36.000Z | [
"pytorch",
"roberta",
"text-classification",
"es",
"transformers",
"spanish",
"bertin",
"license:cc-by-4.0"
] | text-classification | false | hackathon-pln-es | null | hackathon-pln-es/readability-es-paragraphs | 15 | null | transformers | 9,612 | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
- bertin
pipeline_tag: text-classification
widget:
- text: La cueva de Zaratustra en el Pretil de los Consejos. Rimeros de libros hacen escombro y cubren las paredes. Empapelan los cuatro vidrios de una puerta cuatro cromos espeluznantes de un novelón por en... |
emon1521/wav2vec2-try | 9802952bf93a9ee41995c4a31909c13752e2f2c3 | 2022-04-08T05:21:43.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | emon1521 | null | emon1521/wav2vec2-try | 15 | null | transformers | 9,613 | Entry not found |
lysandre/test-bert-sharded | b7b840edf060f398daed50ee4285d42ca935b44d | 2022-04-07T17:15:21.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | lysandre | null | lysandre/test-bert-sharded | 15 | null | transformers | 9,614 | Entry not found |
rycont/KoQuestionBART | 348afe0407e1a11ad537646775b26fb4d154dbfa | 2022-04-09T11:24:28.000Z | [
"pytorch",
"bart",
"text2text-generation",
"ko",
"dataset:KorQuad 1.0",
"transformers",
"KoBART",
"BART",
"Korean",
"QG",
"Question",
"KorQuad",
"license:gpl",
"autotrain_compatible"
] | text2text-generation | false | rycont | null | rycont/KoQuestionBART | 15 | 1 | transformers | 9,615 | ---
language:
- ko
tags:
- KoBART
- BART
- Korean
- QG
- Question
- KorQuad
license: gpl
datasets:
- KorQuad 1.0
widget:
- text: "키워드 추출: 5<unused1>1943년 10월 당시, 반응로 B는 초기 가동에서 250 MW의 전력을 생산하도록 설계되었다. 맨해튼 계획은 반응로에 A에서 F까지 일련번호를 부여하였다. 이 반응로들은 모두 한 장소에 지어졌다. 반응로의 건설에는 390 톤의 강철이 소요되었으며, 13,300 m에 달하는 5만개의 콘크리트 벽돌을 사... |
sepidmnorozy/parsbert-finetuned-pos | ada6e7b6ab2d82a2d80586eaf85f510a4dcdee54 | 2022-04-12T09:57:27.000Z | [
"pytorch",
"bert",
"token-classification",
"dataset:udpos28",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | sepidmnorozy | null | sepidmnorozy/parsbert-finetuned-pos | 15 | null | transformers | 9,616 | ---
tags:
- generated_from_trainer
datasets:
- udpos28
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: parsbert-finetuned-pos
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: udpos28
type: udpos28
args: fa
metrics:
- n... |
SiriusRen/OH_my-rubbish-model | 6e462efdab835cb381676e57fd468c5f763f7c7e | 2022-04-14T09:35:39.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | SiriusRen | null | SiriusRen/OH_my-rubbish-model | 15 | null | transformers | 9,617 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
model-index:
- name: OH_my-rubbish-model
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. -->
... |
ccdv/lsg-distilcamembert-base-4096 | 7a01dbaaca7a958262d9a99ff6912a04f8b7deb3 | 2022-07-25T05:35:56.000Z | [
"pytorch",
"camembert",
"fill-mask",
"fr",
"transformers",
"long context",
"autotrain_compatible"
] | fill-mask | false | ccdv | null | ccdv/lsg-distilcamembert-base-4096 | 15 | 1 | transformers | 9,618 | ---
language: fr
tags:
- long context
pipeline_tag: fill-mask
---
# LSG model
**Transformers >= 4.18.0**\
**This model relies on a custom modeling file, you need to add trust_remote_code=True**\
**See [\#13467](https://github.com/huggingface/transformers/pull/13467)**
* [Usage](#usage)
* [Parameters](#parameters)
* [... |
ysharma/bert-finetuned-ner | edcb7f843376ad26576ca391d021d49fdc4eba30 | 2022-04-18T15:06:22.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | ysharma | null | ysharma/bert-finetuned-ner | 15 | null | transformers | 9,619 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
uw-madison/nystromformer-2048 | 23032017be28060be224adb388c366a2340f122f | 2022-04-18T16:27:47.000Z | [
"pytorch",
"nystromformer",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uw-madison | null | uw-madison/nystromformer-2048 | 15 | null | transformers | 9,620 | Nystromformer for sequence length 2048 trained on WikiText-103 v1. |
SeNSiTivE/Learning-sentiment-analysis-through-imdb-ds | fbd65af213867e8899b230945e3b3542273e769d | 2022-04-19T11:21:52.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | SeNSiTivE | null | SeNSiTivE/Learning-sentiment-analysis-through-imdb-ds | 15 | null | transformers | 9,621 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: Learning-sentiment-analysis-through-imdb-ds
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
... |
Intel/distilbert-base-uncased-finetuned-conll03-english-int8-static | 127e325bdd4352fc9c87c525e5ae8d8d7544e39d | 2022-06-10T02:40:14.000Z | [
"pytorch",
"distilbert",
"token-classification",
"en",
"dataset:conll2003",
"transformers",
"token-classfication",
"int8",
"Intel® Neural Compressor",
"PostTrainingStatic",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | Intel | null | Intel/distilbert-base-uncased-finetuned-conll03-english-int8-static | 15 | null | transformers | 9,622 | ---
language:
- en
license: apache-2.0
tags:
- token-classfication
- int8
- Intel® Neural Compressor
- PostTrainingStatic
datasets:
- conll2003
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-conll03-english-int8-static
results:
- task:
name: Token Classification
type: token-c... |
Intel/bart-large-mrpc-int8-dynamic | cc68488634343a5b4da4a67797065263595f7498 | 2022-06-10T02:41:57.000Z | [
"pytorch",
"bart",
"text-classification",
"en",
"dataset:glue",
"transformers",
"text-classfication",
"int8",
"Intel® Neural Compressor",
"PostTrainingDynamic",
"license:apache-2.0",
"model-index"
] | text-classification | false | Intel | null | Intel/bart-large-mrpc-int8-dynamic | 15 | null | transformers | 9,623 | ---
language:
- en
license: apache-2.0
tags:
- text-classfication
- int8
- Intel® Neural Compressor
- PostTrainingDynamic
datasets:
- glue
metrics:
- f1
model-index:
- name: bart-large-mrpc-int8-static
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRP... |
clapika2010/soccer_predictions | 4e6bdeb3c7f647d261d4f60d61370fb9ebc2b6ea | 2022-04-22T19:31:02.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | clapika2010 | null | clapika2010/soccer_predictions | 15 | null | transformers | 9,624 | Entry not found |
praptishadmaan/finetuning-sentiment-model-3000-samples | 07c0b819bd9a98809c74018ed92e64c9287f4a36 | 2022-04-24T17:16:19.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | praptishadmaan | null | praptishadmaan/finetuning-sentiment-model-3000-samples | 15 | null | transformers | 9,625 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
met... |
Pavithra/autopilot-madgrad2_54 | 9160b593bf7480bbf6de2e0affc43c8b71b64942 | 2022-04-24T05:23:05.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | Pavithra | null | Pavithra/autopilot-madgrad2_54 | 15 | null | transformers | 9,626 | Entry not found |
Akarsh3053/potter-chat-bot | 091f2fee869920fc84837a886af416976dace321 | 2022-04-24T06:55:04.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"chatBot"
] | conversational | false | Akarsh3053 | null | Akarsh3053/potter-chat-bot | 15 | null | transformers | 9,627 | ---
tags:
- conversational
- chatBot
---
# Harry Potter DialoGPT Model |
jsoutherland/distilbert-base-uncased-finetuned-emotion | 6db4a918b0670c76ff231aefb23512ca2bc9893e | 2022-07-15T13:48:49.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | jsoutherland | null | jsoutherland/distilbert-base-uncased-finetuned-emotion | 15 | null | transformers | 9,628 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model_index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
manueltonneau/bert-twitter-en-lost-job | 5770560a055e342e429a09d2443a057c05597bdb | 2022-04-26T15:58:32.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"arxiv:2203.09178",
"transformers"
] | text-classification | false | manueltonneau | null | manueltonneau/bert-twitter-en-lost-job | 15 | null | transformers | 9,629 | ---
language: en # <-- my language
widget:
- text: "Just lost my job..."
---
# Detection of employment status disclosures on Twitter
## Model main characteristics:
- class: Lost Job (1), else (0)
- country: US
- language: English
- architecture: BERT base
## Model description
This model is a version of `D... |
cogint/in-boxbart | 4c6812f8d97ab0b4dfeff5b21655cfbe710d0298 | 2022-04-27T00:22:39.000Z | [
"pytorch",
"bart",
"text2text-generation",
"arxiv:2204.07600",
"transformers",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | cogint | null | cogint/in-boxbart | 15 | null | transformers | 9,630 | ---
license: mit
---
In-BoXBART
=============
An instruction-based unified model for performing various biomedical tasks.
You may want to check out
* Our paper (NAACL 2022 Findings): [In-BoXBART: Get Instructions into Biomedical Multi-Task Learning](https://arxiv.org/abs/2204.07600)
* GitHub: [Click Here](https://g... |
it5/it5-efficient-small-el32-question-answering | 798064db0afbf348a21f66d999b7e3a31980d195 | 2022-04-29T14:28:58.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:squad_it",
"arxiv:2203.03759",
"transformers",
"Italian",
"efficient",
"sequence-to-sequence",
"squad_it",
"text2text-question-answering",
"license:apache-2.0",
"model-index",
"autotrain_compatible"... | text2text-generation | false | it5 | null | it5/it5-efficient-small-el32-question-answering | 15 | null | transformers | 9,631 | ---
language:
- it
license: apache-2.0
datasets:
- squad_it
tags:
- Italian
- efficient
- sequence-to-sequence
- squad_it
- text2text-question-answering
- text2text-generation
widget:
- text: "In seguito all' evento di estinzione del Cretaceo-Paleogene, l' estinzione dei dinosauri e il clima umido possono aver permesso... |
it5/it5-efficient-small-el32-wiki-summarization | 9bd8552c054a0ba59366d108bcaeb18dbaff7d68 | 2022-04-29T15:16:27.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:wits",
"arxiv:2203.03759",
"arxiv:2109.10686",
"transformers",
"italian",
"sequence-to-sequence",
"wikipedia",
"summarization",
"efficient",
"wits",
"license:apache-2.0",
"model-index",
"autotra... | summarization | false | it5 | null | it5/it5-efficient-small-el32-wiki-summarization | 15 | null | transformers | 9,632 | ---
language:
- it
license: apache-2.0
datasets:
- wits
tags:
- italian
- sequence-to-sequence
- wikipedia
- summarization
- efficient
- wits
widget:
- text: "La 5ª Commissione ha competenza per i disegni di legge riguardanti le specifiche materie del bilancio, del personale e dei servizi del Ministero dell'economia, n... |
Yehor/wav2vec2-xls-r-1b-uk-with-binary-news-lm | f43d0b1be48b4e776365144f85daa0dd1ccb72a3 | 2022-07-30T07:00:30.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"uk",
"transformers",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0"
] | automatic-speech-recognition | false | Yehor | null | Yehor/wav2vec2-xls-r-1b-uk-with-binary-news-lm | 15 | null | transformers | 9,633 | ---
language:
- uk
license: cc-by-nc-sa-4.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- uk
xdatasets:
- mozilla-foundation/common_voice_7_0
---
# Ukrainian STT model (with the Big Language Model formed on News Dataset)
🇺🇦 Join Ukrainian Speech Recognition Co... |
dragonSwing/viwav2vec2-base-3k | 4b455411460e8e8492db7c39d832f778de5d1a58 | 2022-05-17T15:15:13.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"vi",
"arxiv:2006.11477",
"transformers",
"speech",
"automatic-speech-recognition",
"license:cc-by-sa-4.0"
] | automatic-speech-recognition | false | dragonSwing | null | dragonSwing/viwav2vec2-base-3k | 15 | 0 | transformers | 9,634 | ---
license: cc-by-sa-4.0
language: vi
tags:
- speech
- automatic-speech-recognition
---
# Wav2Vec2 base model trained of 3K hours of Vietnamese speech
The base model is pre-trained on 16kHz sampled speech audio from Vietnamese speech corpus containing 3K hours of spontaneous, reading, and broadcasting speech. When usi... |
datauma/bert-finetuned-ner | 9c2004bed7e925eb220c13118107eff7368f06cf | 2022-05-03T11:52:53.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | datauma | null | datauma/bert-finetuned-ner | 15 | null | transformers | 9,635 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
Ghost1/bert-base-uncased-finetuned_for_sentiment_analysis1-sst2 | f4148265c1ef20d83bf9632823c388024350368d | 2022-05-05T17:34:44.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Ghost1 | null | Ghost1/bert-base-uncased-finetuned_for_sentiment_analysis1-sst2 | 15 | null | transformers | 9,636 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned_for_sentiment_analysis1-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: sst2
... |
peter2000/distilbert-base-uncased-finetuned-osdg | d9f3548e8c5f4417784dd073d1f2f91b2a4586a4 | 2022-05-25T11:50:55.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | peter2000 | null | peter2000/distilbert-base-uncased-finetuned-osdg | 15 | null | transformers | 9,637 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-osdg
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 remo... |
CEBaB/gpt2.CEBaB.sa.2-class.exclusive.seed_42 | cc15ff085432d596f3c9f5eb36a2b07fdb0efb0b | 2022-05-10T23:32:05.000Z | [
"pytorch",
"gpt2",
"transformers"
] | null | false | CEBaB | null | CEBaB/gpt2.CEBaB.sa.2-class.exclusive.seed_42 | 15 | null | transformers | 9,638 | Entry not found |
Wanjiru/ag_based_ner | f50e41de2b9e0022d9d73b94fddd484431a79697 | 2022-05-11T11:41:53.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Wanjiru | null | Wanjiru/ag_based_ner | 15 | null | transformers | 9,639 | Fine tuned recobo/agriculture-bert-uncased for custom NER entities. |
enoriega/kw_pubmed_10000_0.0003 | a3573e2f928f690712c563199f612a57dcefb757 | 2022-05-12T14:21:59.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | enoriega | null | enoriega/kw_pubmed_10000_0.0003 | 15 | null | transformers | 9,640 | Entry not found |
tanviraumi/meeting-summary | 73ad6cf93848732492830fefac80756500fea724 | 2022-05-13T23:09:04.000Z | [
"pytorch",
"bart",
"text2text-generation",
"dataset:samsum",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | tanviraumi | null | tanviraumi/meeting-summary | 15 | null | transformers | 9,641 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- samsum
model-index:
- name: meeting-summary
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. -->
# meeting... |
anwesham/imdb-sentiment-baseline-distilbert | ec16ec2953883c6700a9a91c7b59f01b22ffeb16 | 2022-05-14T03:58:39.000Z | [
"pytorch",
"distilbert",
"text-classification",
"unk",
"dataset:anwesham/autotrain-data-imdb-sentiment-analysis",
"transformers"
] | text-classification | false | anwesham | null | anwesham/imdb-sentiment-baseline-distilbert | 15 | null | transformers | 9,642 | ---
language: unk
datasets:
- anwesham/autotrain-data-imdb-sentiment-analysis
---
## Description
- Problem type: Binary Classification
## Validation Metrics
- Loss: 0.17481304705142975
- Accuracy: 0.936
- Precision: 0.9526578073089701
- Recall: 0.9176
- AUC: 0.9841454399999999
- F1: 0.93480032599837
## Usage
You ca... |
kushaljoseph/bert-to-distilbert-NER | c65c2bd819d25fd216e571e216310caba3332785 | 2022-05-16T15:38:42.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | kushaljoseph | null | kushaljoseph/bert-to-distilbert-NER | 15 | null | transformers | 9,643 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- conll2003
model-index:
- name: bert-to-distilbert-NER
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. -->
... |
Tititun/consumer_category | 4b597908de6e07943cbfb1d889be8f81cc89ac5f | 2022-05-15T05:18:30.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | false | Tititun | null | Tititun/consumer_category | 15 | 1 | transformers | 9,644 | Entry not found |
ali-issa/3-wav2vec2-arabic-gpu-colab-similar-to-german-more-warm-2 | 9474e2229d2bea762f174a65b4bec22c2d10c700 | 2022-05-14T23:07:29.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | ali-issa | null | ali-issa/3-wav2vec2-arabic-gpu-colab-similar-to-german-more-warm-2 | 15 | null | transformers | 9,645 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-arabic-gpu-colab-similar-to-german-more-warm-2
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 ... |
miyagawaorj/distilbert-base-uncased-finetuned-emotion | fba706e0f7e485c29e7f256fdfd17f0bac6c4940 | 2022-06-06T11:44:31.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | miyagawaorj | null | miyagawaorj/distilbert-base-uncased-finetuned-emotion | 15 | null | transformers | 9,646 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
JoanTirant/bert-finetuned-ner | 03020eea055c576fd587bce1f34dc9c3672d08cc | 2022-05-17T10:40:14.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | JoanTirant | null | JoanTirant/bert-finetuned-ner | 15 | null | transformers | 9,647 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
nqcccccc/phobert-social-media-text-classify | 4e7654c7428dfe43ebd7ce61a4c3a0240e87d9cf | 2022-05-20T08:06:40.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | nqcccccc | null | nqcccccc/phobert-social-media-text-classify | 15 | null | transformers | 9,648 | Entry not found |
connectivity/bert_ft_qqp-1 | 74eb955efe01aa28752278c6ac625dfb8d66e763 | 2022-05-21T16:31:03.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | connectivity | null | connectivity/bert_ft_qqp-1 | 15 | null | transformers | 9,649 | Entry not found |
connectivity/bert_ft_qqp-7 | 604fdcd389061d4a9bf972e4cb432a1bb9e11b2f | 2022-05-21T16:31:30.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | connectivity | null | connectivity/bert_ft_qqp-7 | 15 | null | transformers | 9,650 | Entry not found |
Dani-91/bert-finetuned-ner | f1049b82a2d4af20d2fe5c954c669424fe929613 | 2022-05-21T13:25:58.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | Dani-91 | null | Dani-91/bert-finetuned-ner | 15 | null | transformers | 9,651 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
aspis/gpt2-genre-story-generation | 101975f472682ab718168d84ac1902e065e90848 | 2022-05-23T10:36:32.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"license:apache-2.0"
] | text-generation | false | aspis | null | aspis/gpt2-genre-story-generation | 15 | null | transformers | 9,652 | ---
language:
- en
tags:
- text-generation
license: apache-2.0
---
# GPT-2 fine-tuned for short story generation
Gpt-2 for short story generation with genres.
## Model description
Gpt-2 model fine-tuned on sample of BookCorpus dataset for short story generation, allows for the following genres (tokens to use as inp... |
BM-K/KoSimCSE-bert | e479c50e3cba18fc557207f856d12a5b2e456b3e | 2022-06-03T01:47:13.000Z | [
"pytorch",
"bert",
"feature-extraction",
"ko",
"transformers",
"korean"
] | feature-extraction | false | BM-K | null | BM-K/KoSimCSE-bert | 15 | 1 | transformers | 9,653 | ---
language: ko
tags:
- korean
---
https://github.com/BM-K/Sentence-Embedding-is-all-you-need
# Korean-Sentence-Embedding
🍭 Korean sentence embedding repository. You can download the pre-trained models and inference right away, also it provides environments where individuals can train models.
## Quick tour
```py... |
LianZhang/finetuning-sentiment-model-3000-samples | cac56de27e297ce641002cbea567d9511a414b21 | 2022-07-13T22:32:06.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | LianZhang | null | LianZhang/finetuning-sentiment-model-3000-samples | 15 | null | transformers | 9,654 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
met... |
neuralmagic/oBERT-3-upstream-pretrained-dense | 0609a50ec6a3ccd7c3b103141838ac352884c693 | 2022-06-20T11:36:52.000Z | [
"pytorch",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:2203.07259",
"bert",
"oBERT",
"sparsity",
"pruning",
"compression"
] | null | false | neuralmagic | null | neuralmagic/oBERT-3-upstream-pretrained-dense | 15 | null | null | 9,655 | ---
tags:
- bert
- oBERT
- sparsity
- pruning
- compression
language: en
datasets:
- bookcorpus
- wikipedia
---
# oBERT-3-upstream-pretrained-dense
This model is obtained with [The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models](https://arxiv.org/abs/2203.07259).
It corresp... |
tartuNLP/mtee-domain-detection | b0203dd9ab497de587c50f064a0d7e381c67ed1c | 2022-05-26T22:38:39.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"et",
"en",
"ru",
"de",
"transformers"
] | text-classification | false | tartuNLP | null | tartuNLP/mtee-domain-detection | 15 | null | transformers | 9,656 | ---
language:
- et
- en
- ru
- de
tags:
- text-classification
widget:
- text: "Täna lõppes Valgamaa õppuse Siil aktiivne lahingutegevus, mille käigus pidi täielikult formeeritud 2. jalaväebrigaad kaitsma end vastase pealetungi eest."
---
A domain detection model for the MTee machine translation platform... |
Rebreak/autotrain-News-916530070 | b77d4199c92582eca460978433b96defb7f3f547 | 2022-05-27T05:12:30.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:Rebreak/autotrain-data-News",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | Rebreak | null | Rebreak/autotrain-News-916530070 | 15 | null | transformers | 9,657 | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- Rebreak/autotrain-data-News
co2_eq_emissions: 62.61326668998836
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 916530070
- CO2 Emissions (in grams): 62.61326668998836
## Validation Metrics
- Los... |
Jeevesh8/init_bert_ft_qqp-44 | e91e1d668d5362aab64271c3c2ff620674b9cecf | 2022-06-02T12:39:28.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Jeevesh8 | null | Jeevesh8/init_bert_ft_qqp-44 | 15 | null | transformers | 9,658 | Entry not found |
Ce/bert-finetuned-ner | a2d8c285614dc341e0303c63ead014655c3c774b | 2022-06-02T14:29:56.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | Ce | null | Ce/bert-finetuned-ner | 15 | null | transformers | 9,659 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
Evelyn18/legalectra-base-spanish-finetuned-squad | dea97c61d5db921e2b629e9abee91cc0b851070b | 2022-06-06T06:22:06.000Z | [
"pytorch",
"tensorboard",
"electra",
"question-answering",
"dataset:squad_es",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | Evelyn18 | null | Evelyn18/legalectra-base-spanish-finetuned-squad | 15 | null | transformers | 9,660 | ---
tags:
- generated_from_trainer
datasets:
- squad_es
model-index:
- name: legalectra-base-spanish-finetuned-squad
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. -... |
Anery/legalbert_beneficiary_single | f32800e877872680e587d3f34cde105278ddabaf | 2022-06-08T06:45:36.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Anery | null | Anery/legalbert_beneficiary_single | 15 | null | transformers | 9,661 | Entry not found |
candra/punctuatorid | 97023ae7368a92be8597922baa61e9c25359db42 | 2022-06-09T08:18:01.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | token-classification | false | candra | null | candra/punctuatorid | 15 | null | transformers | 9,662 | ---
license: afl-3.0
---
|
ghadeermobasher/Original-SciBERT-BC5CDR-Chemical | c7722f5b2a261da89ff229bb0244dfd68cc91f4b | 2022-06-09T12:19:05.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-SciBERT-BC5CDR-Chemical | 15 | null | transformers | 9,663 | Entry not found |
ghadeermobasher/Original-PubMedBERT-BC4CHEMD | 9e5eb97a1577ac32e8a1902d15f6c202f5dd087b | 2022-06-09T12:39:13.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-PubMedBERT-BC4CHEMD | 15 | null | transformers | 9,664 | Entry not found |
ghadeermobasher/Original-BlueBERT-BC4CHEMD | 432744847a43e7ad5dcb4497232852c6ab28f0b3 | 2022-06-09T17:16:38.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-BlueBERT-BC4CHEMD | 15 | null | transformers | 9,665 | Entry not found |
ghadeermobasher/Original-BlueBERT-BC2GM | 10e28baadfaeab55ce70934916845469d173272f | 2022-06-09T14:11:56.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-BlueBERT-BC2GM | 15 | null | transformers | 9,666 | Entry not found |
ghadeermobasher/Original-PubMedBERT-BC2GM | f3a086e6149e65493c518d837f477d115c9eec96 | 2022-06-10T16:57:18.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-PubMedBERT-BC2GM | 15 | null | transformers | 9,667 | Entry not found |
ghadeermobasher/Original-SciBERT-BC2GM | e2a432b4ee1a072a603ef0274abd12056dc1a51d | 2022-06-09T16:41:10.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-SciBERT-BC2GM | 15 | null | transformers | 9,668 | Entry not found |
ghadeermobasher/Original-BlueBERT-Linnaeus | c3354669dfd2efe02443a563daecf818b148e66b | 2022-06-10T14:41:07.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-BlueBERT-Linnaeus | 15 | null | transformers | 9,669 | Entry not found |
ghadeermobasher/Original-SciBERT-Linnaeus | cfa3d3a835004e589cb06af3f9808dbb25f4933c | 2022-06-10T14:17:53.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-SciBERT-Linnaeus | 15 | null | transformers | 9,670 | Entry not found |
ghadeermobasher/Original-SciBERT-BC5CDR-Chemical-T | 7002a4d88a34a017f086add1ec8915ac69d8f71e | 2022-06-09T18:04:01.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-SciBERT-BC5CDR-Chemical-T | 15 | null | transformers | 9,671 | Entry not found |
ghadeermobasher/Original-SciBERT-BC5CDR-Chemical-T1 | b6fb6dce7e12bcc9ba688e330d7ea4ac02b876a8 | 2022-06-09T18:15:28.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-SciBERT-BC5CDR-Chemical-T1 | 15 | null | transformers | 9,672 | Entry not found |
rsuwaileh/IDRISI-LMR-HD-TL-partition | 0d76606a580dbc0e27009cc0f2cdb1e7553b2c70 | 2022-07-18T09:16:12.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | rsuwaileh | null | rsuwaileh/IDRISI-LMR-HD-TL-partition | 15 | null | transformers | 9,673 | This model is a BERT-based Location Mention Recognition model that is adopted from the [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/).
The model is trained using Hurricane Dorian 2019 event (training data is used for training) from [IDRISI-R dataset](https://github.com/rsuwaileh/IDRISI) under the Type-less L... |
QCRI/bert-base-cased-sem | a44a4cc969b3ce93bae590cd03aa9ab5a42b286c | 2022-06-13T06:02:07.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | token-classification | false | QCRI | null | QCRI/bert-base-cased-sem | 15 | null | transformers | 9,674 | ---
license: cc-by-nc-4.0
---
|
ghadeermobasher/BC4CHEMD-Chem-Original-BlueBERT-512 | 982beaef243c5fd73e860efa6144d5c2b03145f9 | 2022-06-14T10:13:04.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4CHEMD-Chem-Original-BlueBERT-512 | 15 | null | transformers | 9,675 | Entry not found |
Seema09/finetuning-sentiment-model-Test | f7e2f2033d6c011220549de8670f844b353c6382 | 2022-06-16T13:25:48.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Seema09 | null | Seema09/finetuning-sentiment-model-Test | 15 | null | transformers | 9,676 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-Test
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
... |
aditya22/bert-finetuned-ner | 720faba12b79e083155ff45b7bae2a1ea5b7faea | 2022-06-17T07:18:13.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | aditya22 | null | aditya22/bert-finetuned-ner | 15 | null | transformers | 9,677 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
Nonzerophilip/bert-finetuned-ner_swedish_test_NUMb_2 | f09f63214190a7c5f7c5a04d3da6ad5c937dd281 | 2022-06-17T12:12:55.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | Nonzerophilip | null | Nonzerophilip/bert-finetuned-ner_swedish_test_NUMb_2 | 15 | null | transformers | 9,678 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner_swedish_test_NUMb_2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, the... |
Jeevesh8/std_0pnt2_bert_ft_cola-7 | a23ee45d9608c80211e627db57635f02e88f11a5 | 2022-06-21T13:28:05.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Jeevesh8 | null | Jeevesh8/std_0pnt2_bert_ft_cola-7 | 15 | null | transformers | 9,679 | Entry not found |
raphaelsty/semanlink_all_mpnet_base_v2 | ca788f7899e7958a200c78f3abfd302517a390ae | 2022-06-28T09:28:05.000Z | [
"pytorch",
"mpnet",
"feature-extraction",
"en",
"fr",
"sentence-transformers",
"sentence-similarity",
"license:apache-2.0"
] | sentence-similarity | false | raphaelsty | null | raphaelsty/semanlink_all_mpnet_base_v2 | 15 | null | sentence-transformers | 9,680 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language:
- en
- fr
license: apache-2.0
---
## `semanlink_all_mpnet_base_v2`
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for ... |
Laure996/bert-finetuned-ner | 500eb7ea67e026d6160dc4565aa656537f045e5d | 2022-06-27T10:00:55.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | Laure996 | null | Laure996/bert-finetuned-ner | 15 | null | transformers | 9,681 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
projecte-aina/roberta-base-ca-v2-cased-tc | b629591dc6762ce358e72f9d1640ea8966f19ca8 | 2022-07-25T06:50:52.000Z | [
"pytorch",
"roberta",
"text-classification",
"ca",
"dataset:projecte-aina/tecla",
"arxiv:1907.11692",
"transformers",
"catalan",
"text classification",
"tecla",
"CaText",
"Catalan Textual Corpus",
"model-index"
] | text-classification | false | projecte-aina | null | projecte-aina/roberta-base-ca-v2-cased-tc | 15 | null | transformers | 9,682 | ---
language:
- ca
tags:
- "catalan"
- "text classification"
- "tecla"
- "CaText"
- "Catalan Textual Corpus"
datasets:
- "projecte-aina/tecla"
metrics:
- accuracy
model-index:
- name: roberta-base-ca-v2-cased-tc
results:
- task:
type: text-classification
dataset:
name: TeCla
type: ... |
emen/distilbert-base-uncased-finetuned-emotion | 14ca05ff278d294dcfa855991fc1a881757c004a | 2022-06-30T12:17:01.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | emen | null | emen/distilbert-base-uncased-finetuned-emotion | 15 | null | transformers | 9,683 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
Luojike/autotrain-test-4-macbert-1071837613 | d1cbf0c6b2e6b5702f5be3abc9b139238c9422f1 | 2022-07-01T15:45:50.000Z | [
"pytorch",
"bert",
"text-classification",
"unk",
"dataset:Luojike/autotrain-data-test-4-macbert",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | Luojike | null | Luojike/autotrain-test-4-macbert-1071837613 | 15 | null | transformers | 9,684 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- Luojike/autotrain-data-test-4-macbert
co2_eq_emissions: 0.012225117907336358
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1071837613
- CO2 Emissions (in grams): 0.012225117907336358
## Validat... |
FabianWillner/bert-base-uncased-finetuned-squad-finetuned-triviaqa | 5b78483053301a335e2bf0935c9e8ca22df11a4b | 2022-07-02T11:26:20.000Z | [
"pytorch",
"tensorboard",
"bert",
"question-answering",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | FabianWillner | null | FabianWillner/bert-base-uncased-finetuned-squad-finetuned-triviaqa | 15 | null | transformers | 9,685 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-finetuned-squad-finetuned-triviaqa
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 thi... |
steven123/Check_GoodBad_Teeth | 4734185760da914ecbed1e8bf26a0a92e440bcdc | 2022-07-05T03:52:40.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | steven123 | null | steven123/Check_GoodBad_Teeth | 15 | null | transformers | 9,686 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: Check_GoodBad_Teeth
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 1.0
---
# Check_GoodBad_Teeth
Autogen... |
ghadeermobasher/Original-BlueBERT-BioRED-Chem | fb4acad62b0f87d3f896c92d5b78abdb821bec7c | 2022-07-06T15:04:13.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-BlueBERT-BioRED-Chem | 15 | null | transformers | 9,687 | Entry not found |
ScarlettSun9/autotrain-ZuoZhuan-1100540143 | 05fd59835631b55becb980b296d5d3799b475380 | 2022-07-07T07:11:00.000Z | [
"pytorch",
"roberta",
"token-classification",
"unk",
"dataset:ScarlettSun9/autotrain-data-ZuoZhuan",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | token-classification | false | ScarlettSun9 | null | ScarlettSun9/autotrain-ZuoZhuan-1100540143 | 15 | null | transformers | 9,688 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- ScarlettSun9/autotrain-data-ZuoZhuan
co2_eq_emissions: 14.50120424968173
---
# Model Trained Using AutoTrain
- Problem type: Entity Extraction
- Model ID: 1100540143
- CO2 Emissions (in grams): 14.50120424968173
## Validation Metrics... |
danielreales00/results | 35c9e7e82449883915d4f88297340c6986763475 | 2022-07-10T19:13:18.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | danielreales00 | null | danielreales00/results | 15 | null | transformers | 9,689 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: results
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. -->
# results
This model is a fi... |
luffycodes/t5_small_v1_bb | 8a4ea7dc2b457061e4c981e8748651b4e6801421 | 2022-07-11T08:11:20.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | luffycodes | null | luffycodes/t5_small_v1_bb | 15 | null | transformers | 9,690 | Entry not found |
agarwalchaitanya/muril-unified-ei-infotabs-btnli | c1f1543bb3f03bd0cb40f9276b64afa9fdab25d3 | 2022-07-11T19:46:25.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:apache-2.0"
] | text-classification | false | agarwalchaitanya | null | agarwalchaitanya/muril-unified-ei-infotabs-btnli | 15 | null | transformers | 9,691 | ---
license: apache-2.0
---
|
Chirayu/mt5-multilingual-sentiment | 2823503f4d2ac52f228c1ff061b891a6abea77ab | 2022-07-12T10:24:23.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Chirayu | null | Chirayu/mt5-multilingual-sentiment | 15 | null | transformers | 9,692 | # This model predicts the sentiment('Negative'/'Positive') for the input sentence. It is fine-tuned mt5-small
The present model supports 6 languages -
1) English
2) Hindi
3) German
4) Korean
5) Japanese
6) Portuguese
Here is how to use this model
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqL... |
morenolq/thext-cs-scibert | 76a6fb0ce53c390002a615e3359fe2d2fd331627 | 2022-07-13T16:59:05.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"transformers",
"regression"
] | text-classification | false | morenolq | null | morenolq/thext-cs-scibert | 15 | null | transformers | 9,693 | ---
language: "en"
tags:
- bert
- regression
- pytorch
pipeline:
- text-classification
widget:
- text: "We propose a new approach, based on Transformer-based encoding, to highlight extraction. To the best of our knowledge, this is the first attempt to use transformer architectures to address automatic highlight generat... |
jgriffi/bart_abstract_summarization | d1f31aff41111ae819df6938e87087894c7b7b0f | 2022-07-14T12:28:07.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | jgriffi | null | jgriffi/bart_abstract_summarization | 15 | null | transformers | 9,694 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: bart_abstract_summarization
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. -->
# bart_abstract_... |
nvidia/speakerverification_en_titanet_large | 3c99844ecb1a732dde2d438f762068a4aa6a72ab | 2022-07-15T19:38:45.000Z | [
"nemo",
"en",
"dataset:VOXCELEB-1",
"dataset:VOXCELEB-2",
"dataset:FISHER",
"dataset:switchboard",
"dataset:librispeech_asr",
"dataset:SRE (2004-2010)",
"speaker",
"speech",
"audio",
"speaker-verification",
"speaker-recognition",
"speaker-diarization",
"titanet",
"NeMo",
"pytorch",
... | null | false | nvidia | null | nvidia/speakerverification_en_titanet_large | 15 | 1 | nemo | 9,695 | ---
language:
- en
library_name: nemo
datasets:
- VOXCELEB-1
- VOXCELEB-2
- FISHER
- switchboard
- librispeech_asr
- SRE (2004-2010)
thumbnail: null
tags:
- speaker
- speech
- audio
- speaker-verification
- speaker-recognition
- speaker-diarization
- titanet
- NeMo
- pytorch
license: cc-by-4.0
widget:
- src: https://h... |
nloc2578/3.2 | 4ebb1d3c1d608db3433c57f253179e4f063353b0 | 2022-07-16T11:12:19.000Z | [
"pytorch",
"tensorboard",
"pegasus",
"text2text-generation",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | nloc2578 | null | nloc2578/3.2 | 15 | null | transformers | 9,696 | ---
tags:
- generated_from_trainer
model-index:
- name: '3.2'
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. -->
# 3.2
This model is a fine-tuned version of [googl... |
lewiswu1209/gpt2-chinese-composition | fff00b9206eb6aad66da0356f70b58f11bff56c1 | 2022-07-17T10:52:23.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"license:mit"
] | text-generation | false | lewiswu1209 | null | lewiswu1209/gpt2-chinese-composition | 15 | null | transformers | 9,697 | ---
license: mit
---
引自<https://github.com/yangjianxin1/CPM#model_share> |
olgaduchovny/t5-base-qa-ner-conll | 7720f6eca6e1b86199e25720240868edbda8e392 | 2022-07-18T19:10:01.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:conll2003",
"arxiv:2203.03903",
"transformers",
"ner",
"qa",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | olgaduchovny | null | olgaduchovny/t5-base-qa-ner-conll | 15 | null | transformers | 9,698 | ---
language:
- en
tags:
- pytorch
- ner
- qa
inference: false
license: mit
datasets:
- conll2003
metrics:
- f1
---
# t5-base-qa-ner-conll
Unofficial implementation of [InstructionNER](https://arxiv.org/pdf/2203.03903v1.pdf).
t5-base model tuned on conll2003 dataset.
https://github.com/ovbystrova/InstructionN... |
rajpurkarlab/biobert-finetuned-change-classification | f8bae5e2cf3ea809b82183100ad6888ee59f99e4 | 2022-07-25T23:25:30.000Z | [
"pytorch",
"bert",
"text-classification",
"py",
"transformers"
] | text-classification | false | rajpurkarlab | null | rajpurkarlab/biobert-finetuned-change-classification | 15 | 1 | transformers | 9,699 | ---
language:
- py
metrics:
- f1
---
To use our fine-tuned BioBERT model to predict whether a sentence from a radiology reports makes reference to priors, run the following:
```python
from transformers import AutoTokenizer, AutoModelForTokenClassification
modelname = "rajpurkarlab/biobert-finetuned-change-class... |
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