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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
RaghuramKol/distilbert-base-uncased-finetuned-emotion | 1f124f372ea0c9d60f816da702877a2c2e4ba209 | 2022-03-15T19:56:43.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | RaghuramKol | null | RaghuramKol/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,700 | ---
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... |
mikeadimech/bart-large-cnn-qmsum-meeting-summarization | 989963e829b7f1e76bec83205a0a1d7f588c80e1 | 2022-03-18T19:00:43.000Z | [
"pytorch",
"bart",
"text2text-generation",
"dataset:yawnick/QMSum",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | mikeadimech | null | mikeadimech/bart-large-cnn-qmsum-meeting-summarization | 12 | null | transformers | 10,701 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-qmsum-meeting-summarization
results: []
datasets:
- yawnick/QMSum
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
cb2-kai/finetuning-sentiment-model-3000-samples | 978f74804799a8a02dcbfc113279eb9a709edcd9 | 2022-03-21T18:34:27.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | cb2-kai | null | cb2-kai/finetuning-sentiment-model-3000-samples | 12 | null | transformers | 10,702 | ---
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... |
Ameer05/distilbart-cnn-12-6-finetuned-resume-summarizer | 0236fc2c55ae96171fe407186bba2038ea4e9914 | 2022-03-21T19:35:06.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"summarization",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | summarization | false | Ameer05 | null | Ameer05/distilbart-cnn-12-6-finetuned-resume-summarizer | 12 | null | transformers | 10,703 | ---
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: distilbart-cnn-12-6-finetuned-resume-summarizer
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 re... |
asahi417/tner-roberta-large-tweet-2020 | 9f2d61fc46ffb48b627f79a536cdb70631a6b09f | 2022-05-06T11:17:35.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | asahi417 | null | asahi417/tner-roberta-large-tweet-2020 | 12 | null | transformers | 10,704 | Entry not found |
gayanin/t5-small-med-term-conditional-masking | f3dbc58d0e6311392d8b5a17dbcfe176bff97c50 | 2022-03-24T14:54:49.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | gayanin | null | gayanin/t5-small-med-term-conditional-masking | 12 | null | transformers | 10,705 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-med-term-conditional-masking
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. -->
... |
Helsinki-NLP/opus-mt-tc-big-zle-de | 1cfb0609e012e563bd0778d589ef1b68de59456f | 2022-06-01T13:09:52.000Z | [
"pytorch",
"marian",
"text2text-generation",
"be",
"de",
"ru",
"uk",
"zle",
"transformers",
"translation",
"opus-mt-tc",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-tc-big-zle-de | 12 | null | transformers | 10,706 | ---
language:
- be
- de
- ru
- uk
- zle
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-zle-de
results:
- task:
name: Translation rus-deu
type: translation
args: rus-deu
dataset:
name: flores101-devtest
type: flores_101
args: rus deu de... |
agdsga/chinese-roberta-wwm-ext-large | 4517ed210722c3f6594f54d7ee096a94e8461e82 | 2022-03-25T03:05:07.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | agdsga | null | agdsga/chinese-roberta-wwm-ext-large | 12 | null | transformers | 10,707 | Entry not found |
TeamFnord/manga-ocr | 1d0bb748d3b7551b2c556f406157459949ad32bc | 2022-02-10T07:50:15.000Z | [
"pytorch",
"vision-encoder-decoder",
"ja",
"dataset:manga109s",
"transformers",
"image-to-text",
"license:apache-2.0"
] | image-to-text | false | TeamFnord | null | TeamFnord/manga-ocr | 12 | null | transformers | 10,708 | ---
language: ja
tags:
- image-to-text
license: apache-2.0
datasets:
- manga109s
---
# Manga OCR
Optical character recognition for Japanese text, with the main focus being Japanese manga.
It uses [Vision Encoder Decoder](https://huggingface.co/docs/transformers/model_doc/visionencoderdecoder) framework.
Manga OCR c... |
DMetaSoul/sbert-chinese-general-v1 | a3bebbf20c355066c73ad1cb05f5342d254be9e2 | 2022-04-04T07:22:58.000Z | [
"pytorch",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers",
"semantic-search",
"chinese"
] | sentence-similarity | false | DMetaSoul | null | DMetaSoul/sbert-chinese-general-v1 | 12 | null | sentence-transformers | 10,709 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- semantic-search
- chinese
---
# DMetaSoul/sbert-chinese-general-v1
此模型基于 [bert-base-chinese](https://huggingface.co/bert-base-chinese) 版本 BERT 模型，在 NLI、PAWS-X、PKU-Paraphrase-Bank、STS 等语义相似数据... |
DMetaSoul/sbert-chinese-qmc-domain-v1 | 25a28159ba2986912df1f5553c0d7b50202f9530 | 2022-04-04T07:24:17.000Z | [
"pytorch",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers",
"semantic-search",
"chinese"
] | sentence-similarity | false | DMetaSoul | null | DMetaSoul/sbert-chinese-qmc-domain-v1 | 12 | null | sentence-transformers | 10,710 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- semantic-search
- chinese
---
# DMetaSoul/sbert-chinese-qmc-domain-v1
此模型基于 [bert-base-chinese](https://huggingface.co/bert-base-chinese) 版本 BERT 模型，在百度知道问题匹配数据集（[LCQMC](http://icrc.hitsz.ed... |
hackathon-pln-es/jurisbert-tsdae-sentence-transformer | 6354a1034e0e83573469da0c22da5d6e422a6450 | 2022-03-30T16:47:04.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"es",
"dataset:scjnugacj/scjn_dataset_corpus_tesis",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | hackathon-pln-es | null | hackathon-pln-es/jurisbert-tsdae-sentence-transformer | 12 | 3 | sentence-transformers | 10,711 | ---
widget:
- text: "interés superior del menor"
- text: "interés superior del infante"
- text: "interés superior de la niñez"
pipeline_tag: sentence-similarity
language: es
datasets: scjnugacj/scjn_dataset_corpus_tesis
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# juri... |
nikhedward/t5-small-finetuned-multi-news | a278da69a13f159e20323b140ce12c3d5b06b806 | 2022-03-26T04:31:49.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"dataset:multi_news",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | nikhedward | null | nikhedward/t5-small-finetuned-multi-news | 12 | null | transformers | 10,712 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: t5-small-finetuned-multi-news
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: multi_news
type: multi_news
args... |
avb/bert-base-uncased-finetuned-cola | ec6845f0c0f49023d4e77c47cb0a8fc1e8a3b08a | 2022-04-05T22:52:25.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | avb | null | avb/bert-base-uncased-finetuned-cola | 12 | null | transformers | 10,713 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: bert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
metrics:
... |
rahulacj/bertweet-base-finetuned-sentiment-analysis | 3fb8a77a51fbf049f42fbb2f5533dbd113d413ad | 2022-03-31T16:21:16.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | rahulacj | null | rahulacj/bertweet-base-finetuned-sentiment-analysis | 12 | null | transformers | 10,714 | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bertweet-base-finetuned-sentiment-analysis
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 com... |
JNK789/distilbert-base-uncased-finetuned-emotion | a32fb3f537e2b5d71c08dec1d32e15a9f046bbff | 2022-04-01T17:30:59.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | JNK789 | null | JNK789/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,715 | ---
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... |
hackathon-pln-es/roberta-base-bne-squad2-es | fa89a2130f209e946c6dc4ebef9a7f3ff9097cbd | 2022-04-02T03:46:40.000Z | [
"pytorch",
"roberta",
"question-answering",
"es",
"dataset:squad_es",
"transformers",
"autotrain_compatible"
] | question-answering | false | hackathon-pln-es | null | hackathon-pln-es/roberta-base-bne-squad2-es | 12 | null | transformers | 10,716 | ---
language: es
datasets:
- squad_es
---
# roberta-base es for QA
This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on the [squad_es(v2)](https://huggingface.co/datasets/squad_es) training dataset.
## Hyperparameters
The hyperparameters we... |
Denzil/distilbert-base-uncased-finetuned-emotion | 7282904b942a2f42e38ae22c68972150dc114c72 | 2022-04-02T14:27:32.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Denzil | null | Denzil/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,717 | ---
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... |
facebook/data2vec-audio-large-100h | b76675f9baf73c95727a01ac3fb53e4cdc53b9e3 | 2022-04-18T16:24:44.000Z | [
"pytorch",
"data2vec-audio",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"arxiv:2202.03555",
"transformers",
"speech",
"license:apache-2.0"
] | automatic-speech-recognition | false | facebook | null | facebook/data2vec-audio-large-100h | 12 | null | transformers | 10,718 | ---
language: en
datasets:
- librispeech_asr
tags:
- speech
license: apache-2.0
---
# Data2Vec-Audio-Large-100h
[Facebook's Data2Vec](https://ai.facebook.com/research/data2vec-a-general-framework-for-self-supervised-learning-in-speech-vision-and-language/)
The large model pretrained and fine-tuned on 100 hours of L... |
LIA-AvignonUniversity/IWSLT2022-tamasheq-only | 4794ce98aaf3e745e659420a6da5841bf68d88ed | 2022-05-11T09:32:21.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"arxiv:2201.05051",
"transformers"
] | null | false | LIA-AvignonUniversity | null | LIA-AvignonUniversity/IWSLT2022-tamasheq-only | 12 | null | transformers | 10,719 | ## Model and data descriptions
This is a wav2vec 2.0 base model trained on 243 hours of Tamasheq speech from the corpus presented in [Boito et al., 2022](https://arxiv.org/abs/2201.05051).
## Intended uses & limitations
Pretrained wav2vec2 models are distributed under the Apache-2.0 license. Hence, they can be reuse... |
nielsr/segformer-finetuned-sidewalk | 202fb6869965dc04c859449f942acc01a9691a8a | 2022-04-06T13:38:20.000Z | [
"pytorch",
"segformer",
"dataset:segments/sidewalk-semantic",
"transformers",
"vision",
"image-segmentation",
"license:apache-2.0"
] | image-segmentation | false | nielsr | null | nielsr/segformer-finetuned-sidewalk | 12 | null | transformers | 10,720 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
datasets:
- segments/sidewalk-semantic
widget:
- src: https://segmentsai-prod.s3.eu-west-2.amazonaws.com/assets/admin-tobias/439f6843-80c5-47ce-9b17-0b2a1d54dbeb.jpg
example_title: Brugge
---
# Segformer-b0, fine-tuned on Sidewalk
This repository contains ... |
GioReg/notiBERTo | 024dce56175259f6734194dd063ab4217c062e43 | 2022-06-09T17:08:29.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | GioReg | null | GioReg/notiBERTo | 12 | null | transformers | 10,721 | language:
- it
Si è creato un modello, chiamato notiBERTo, svolgendo la fase di addestramento e utilizzando per la creazione e il tuning dei pesi del modello l’algoritmo non supervisionato di masked-language modeling (MLM); questo non richiede l’utilizzo di testo con etichettatura. L’idea e stata quella di ottener... |
vocab-transformers/distilbert-tokenizer_256k-MLM_1M | 477ba8ed1a70b84a6a2703beb589a62134a3322e | 2022-04-07T20:06:32.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | vocab-transformers | null | vocab-transformers/distilbert-tokenizer_256k-MLM_1M | 12 | null | transformers | 10,722 | # DistilBERT with 256k token embeddings
This model was initialized with a word2vec token embedding matrix with 256k entries, but these token embeddings were updated during MLM. The word2vec was trained on 100GB data from C4, MSMARCO, News, Wikipedia, S2ORC, for 3 epochs.
Then the model was trained on this dataset wit... |
jaumefib/datathon-against-racism | b2eaf2e0bc03eee89ed0d7a45f895d98405293e9 | 2022-04-09T13:56:56.000Z | [
"pytorch",
"bert",
"text-classification",
"es",
"transformers",
"license:mit"
] | text-classification | false | jaumefib | null | jaumefib/datathon-against-racism | 12 | 1 | transformers | 10,723 | ---
license: mit
language: es
widget:
- text: "Los mejores libros de Abdulrazak Gurnah, el ganador del Nobel de Literatura."
example_title: "Non-racist example"
- text: "Ya están detenidos dos rumanos señalados de cometer fraudes bancarios."
example_title: "Racist example"
---
Model that automatically classifies ... |
course5i/SEAD-L-6_H-256_A-8-sst2 | c192a4180ae57623bef4471d76a469b53afe2229 | 2022-06-12T19:43:45.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"en",
"dataset:glue",
"dataset:sst2",
"arxiv:1910.01108",
"arxiv:1909.10351",
"arxiv:2002.10957",
"arxiv:1810.04805",
"arxiv:1804.07461",
"arxiv:1905.00537",
"transformers",
"SEAD",
"license:apache-2.0"
] | text-classification | false | course5i | null | course5i/SEAD-L-6_H-256_A-8-sst2 | 12 | null | transformers | 10,724 | ---
language:
- en
license: apache-2.0
tags:
- SEAD
datasets:
- glue
- sst2
---
## Paper
## [SEAD: SIMPLE ENSEMBLE AND KNOWLEDGE DISTILLATION FRAMEWORK FOR NATURAL LANGUAGE UNDERSTANDING](https://www.adasci.org/journals/lattice-35309407/?volumes=true&open=621a3b18edc4364e8a96cb63)
Aurthors: *Moyan Mei*, *Rohit Sroch*... |
JminJ/koElectra_base_Bad_Sentence_Classifier | 51a4437b0ed0920c0c41de4fb9e09dab50e1cdff | 2022-04-11T01:50:27.000Z | [
"pytorch",
"electra",
"text-classification",
"arxiv:2003.10555",
"transformers"
] | text-classification | false | JminJ | null | JminJ/koElectra_base_Bad_Sentence_Classifier | 12 | null | transformers | 10,725 | # Bad_text_classifier
## Model 소개
인터넷 상에 퍼져있는 여러 댓글, 채팅이 민감한 내용인지 아닌지를 판별하는 모델을 공개합니다. 해당 모델은 공개데이터를 사용해 label을 수정하고 데이터들을 합쳐 구성해 finetuning을 진행하였습니다. 해당 모델이 언제나 모든 문장을 정확히 판단이 가능한 것은 아니라는 점 양해해 주시면 감사드리겠습니다.
```
NOTE)
공개 데이터의 저작권 문제로 인해 모델 학습에 사용된 변형된 데이터는 공개 불가능하다는 점을 밝힙니다.
또한 해당 모델의 의견은 제 의견과 무관하다는 점을 미리 밝힙니다.
```
... |
CellsInACell/faster_rcnn_count_cho_cells | f4cfa5022ee206a8b7a782b2393ae9c8c64e290d | 2022-04-11T10:57:01.000Z | [
"pytorch",
"resnet",
"transformers",
"object-detection"
] | object-detection | false | CellsInACell | null | CellsInACell/faster_rcnn_count_cho_cells | 12 | null | transformers | 10,726 | ---
tags:
- object-detection
- pytorch
---
Model for counting CHO cells
|
Seethal/general_sentiment_model | fb00e5af49772a47e109c4ba952576d57663826a | 2022-04-11T17:58:16.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | Seethal | null | Seethal/general_sentiment_model | 12 | null | transformers | 10,727 | Entry not found |
lewtun/sagemaker-distilbert-emotion | e2206a20be366ded280b7365cc5518c983dfbe18 | 2022-07-03T05:14:27.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | lewtun | null | lewtun/sagemaker-distilbert-emotion | 12 | null | transformers | 10,728 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: sagemaker-distilbert-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metrics:
... |
Salesforce/codegen-6B-nl | f849d0d3e3b085afeba9e3c729836693fd69deda | 2022-06-28T17:44:34.000Z | [
"pytorch",
"codegen",
"text-generation",
"arxiv:2203.13474",
"transformers",
"license:bsd-3-clause"
] | text-generation | false | Salesforce | null | Salesforce/codegen-6B-nl | 12 | null | transformers | 10,729 | ---
license: bsd-3-clause
---
# CodeGen (CodeGen-NL 6B)
## Model description
CodeGen is a family of autoregressive language models for **program synthesis** from the paper: [A Conversational Paradigm for Program Synthesis](https://arxiv.org/abs/2203.13474) by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang... |
ABrinkmann/sbert_xtremedistil-l6-h256-uncased-mean-cosine-h32 | f24845ed1345fce0b699406babc6f6bb31682e98 | 2022-04-13T15:45:07.000Z | [
"pytorch",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity"
] | sentence-similarity | false | ABrinkmann | null | ABrinkmann/sbert_xtremedistil-l6-h256-uncased-mean-cosine-h32 | 12 | null | sentence-transformers | 10,730 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# ABrinkmann/sbert_xtremedistil-l6-h256-uncased-mean-cosine-h32
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 32 dimensional dense vector space and c... |
Adrian/distilbert-base-uncased-finetuned-emotion | e57ae4c3dddd6af85d98dde9aad13a1440d75678 | 2022-04-14T22:11:34.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Adrian | null | Adrian/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,731 | ---
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... |
Manishkalra/finetuning-sentiment-model-4000-samples | ce1155d930c025c1e9e134a7b8eacdf241b96ab2 | 2022-04-15T05:05:50.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Manishkalra | null | Manishkalra/finetuning-sentiment-model-4000-samples | 12 | null | transformers | 10,732 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-4000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
met... |
schhwmn/mt5-base-finetuned-ukr-gec | b0c565b77431bffa00cd680fe0f7f3b40a8e9e91 | 2022-05-23T07:56:33.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"uk",
"arxiv:2103.16997",
"transformers",
"gec",
"autotrain_compatible"
] | text2text-generation | false | schhwmn | null | schhwmn/mt5-base-finetuned-ukr-gec | 12 | 1 | transformers | 10,733 | ---
language: uk
tags:
- gec
widget:
- text: "я й не думав що комп'ютерна лінгвістика це легкоо."
---
This model was finetuned on errorful sentences from the `train` subset of [UA-GEC](https://github.com/grammarly/ua-gec) corpus, introduced in [UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian... |
choondrise/antonio | a6c62faa669ed601f9910840d07f5d6bbc1cf35d | 2022-04-16T10:36:34.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | choondrise | null | choondrise/antonio | 12 | null | transformers | 10,734 | Entry not found |
Xuan-Rui/ipet-1000-all | da1f05062a28e0653800c81aded38cf32d1c85f8 | 2022-04-17T14:58:25.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Xuan-Rui | null | Xuan-Rui/ipet-1000-all | 12 | null | transformers | 10,735 | Entry not found |
4m1g0/wav2vec2-large-xls-r-300m-gl-jupyter4 | 52e4767cf21404859922d779752ec25eea378955 | 2022-04-18T19:59:47.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | 4m1g0 | null | 4m1g0/wav2vec2-large-xls-r-300m-gl-jupyter4 | 12 | null | transformers | 10,736 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-gl-jupyter4
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. -->
... |
sujitpal/clip-imageclef | b01520a1986989f179bab4738f79f6fee256cda8 | 2022-04-18T22:24:45.000Z | [
"pytorch",
"clip",
"feature-extraction",
"en",
"transformers",
"multimodal",
"language",
"vision",
"image-search",
"license:mit"
] | feature-extraction | false | sujitpal | null | sujitpal/clip-imageclef | 12 | 1 | transformers | 10,737 | ---
language:
- en
tags:
- multimodal
- language
- vision
- image-search
- pytorch
license:
- mit
metrics:
- MRR
---
### Model Card: clip-imageclef
### Model Details
[OpenAI CLIP model](https://openai.com/blog/clip/) fine-tuned using image-caption pairs from the [Caption Prediction dataset](https://www.imageclef.org... |
Intel/bert-base-uncased-mrpc-int8-static | 3241dc5bf9958c1576bfb6abaded5ce71da559e0 | 2022-06-10T02:40:01.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:mrpc",
"transformers",
"text-classfication",
"int8",
"Intel® Neural Compressor",
"PostTrainingStatic",
"license:apache-2.0"
] | text-classification | false | Intel | null | Intel/bert-base-uncased-mrpc-int8-static | 12 | null | transformers | 10,738 | ---
language: en
license: apache-2.0
tags:
- text-classfication
- int8
- Intel® Neural Compressor
- PostTrainingStatic
datasets:
- mrpc
metrics:
- f1
---
# INT8 BERT base uncased finetuned MRPC
### Post-training static quantization
This is an INT8 PyTorch model quantized with [Intel® Neural Compressor](https://git... |
nielsr/segformer-finetuned-sidewalk-10k-steps | afb242aa33339ebcec7481c977e23df9e72798ff | 2022-04-20T15:43:58.000Z | [
"pytorch",
"tensorboard",
"segformer",
"transformers",
"image-segmentation",
"vision",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-segmentation | false | nielsr | null | nielsr/segformer-finetuned-sidewalk-10k-steps | 12 | 1 | transformers | 10,739 | ---
license: apache-2.0
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-sidewalk-50-epochs
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it,... |
PDM/finetuning-sentiment-model-3000-samples | aa5d883f2dfbbff2b2b15e739a6902fe5f9fac98 | 2022-04-22T09:18:16.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | PDM | null | PDM/finetuning-sentiment-model-3000-samples | 12 | null | transformers | 10,740 | ---
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... |
PaulTran/vietnamese_essay_identify | 4495aeb914bef2688cae4114a1912a4b7d249c79 | 2022-06-15T12:05:28.000Z | [
"pytorch",
"roberta",
"text-classification",
"vi",
"Vietnamese",
"arxiv:2003.00744",
"transformers",
"essay category"
] | text-classification | false | PaulTran | null | PaulTran/vietnamese_essay_identify | 12 | null | transformers | 10,741 | ---
language:
- vi
- Vietnamese
tags:
- essay category
- text-classification
widget:
- text: "Cái đồng hồ của em cao hơn 30 cm. Đế của nó được làm bằng i-nốc sáng loáng hình bầu dục. Chỗ dài nhất của đế vừa bằng gang tay của em. Chỗ rộng nhất bằng hơn nửa gang tay."
example_title: "Descriptive - Miêu tả"
- text: "Hiệ... |
praf-choub/bart-CaPE-xsum | 5ea01de016ebaa55b238e2e27a1e3b5c94d26acd | 2022-06-14T04:51:24.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:xsum",
"arxiv:2110.07166",
"transformers",
"summarization",
"license:bsd-3-clause",
"autotrain_compatible"
] | summarization | false | praf-choub | null | praf-choub/bart-CaPE-xsum | 12 | null | transformers | 10,742 | ---
language: en
tags:
- summarization
license: bsd-3-clause
datasets:
- xsum
---
Citation
```
@misc{https://doi.org/10.48550/arxiv.2110.07166,
doi = {10.48550/ARXIV.2110.07166},
url = {https://arxiv.org/abs/2110.07166},
author = {Choubey, Prafulla Kumar and Fabbri, Alexander R. and Vig, Jesse and Wu, Chien-Shen... |
Hate-speech-CNERG/marathi-codemixed-abusive-MuRIL | dedc74530ccdf1ca44c4d5d71b649813c578c499 | 2022-05-03T08:45:38.000Z | [
"pytorch",
"bert",
"text-classification",
"mr",
"arxiv:2204.12543",
"transformers",
"license:afl-3.0"
] | text-classification | false | Hate-speech-CNERG | null | Hate-speech-CNERG/marathi-codemixed-abusive-MuRIL | 12 | null | transformers | 10,743 | ---
language: mr
license: afl-3.0
---
This model is used to detect **abusive speech** in **Marathi**. It is finetuned on MuRIL model using Marathi abusive speech dataset.
The model is trained with learning rates of 2e-5. Training code can be found at this [url](https://github.com/hate-alert/IndicAbusive)
LABEL_0 :-> ... |
AlexTaylor/distilbert-base-uncased-finetuned-emotion | 1ff60c79ed3f5dc8b645a988389d05f79d3451b7 | 2022-04-25T13:24:10.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | AlexTaylor | null | AlexTaylor/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,744 | ---
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... |
bdickson/electra-small-discriminator-finetuned-squad | b17c8792162fb86558192851a25757c17af5048b | 2022-04-28T03:39:47.000Z | [
"pytorch",
"tensorboard",
"electra",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | bdickson | null | bdickson/electra-small-discriminator-finetuned-squad | 12 | null | transformers | 10,745 | Entry not found |
vegetable/test | a427e05f8b3a5ad64c943635d1f4b2ff1ef22400 | 2022-04-30T02:48:07.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | vegetable | null | vegetable/test | 12 | null | transformers | 10,746 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: test
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conll2003
m... |
cfilt/HiNER-original-xlm-roberta-large | 94dac1de022fa75c441c2e898e85e6da270daf2a | 2022-05-02T10:19:28.000Z | [
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"dataset:cfilt/HiNER-original",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | cfilt | null | cfilt/HiNER-original-xlm-roberta-large | 12 | null | transformers | 10,747 | ---
tags:
- generated_from_trainer
datasets:
- cfilt/HiNER-original
metrics:
- precision
- recall
- f1
model-index:
- name: HiNER-original-xlm-roberta-large
results:
- task:
name: Token Classification
type: token-classification
dataset:
type: cfilt/HiNER-original
name: HiNER Original
... |
ali2066/DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_NULL_True | 4932fde06e2a5d1694dce821c5a2fd99ba53b3e5 | 2022-05-02T14:07:36.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | ali2066 | null | ali2066/DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_NULL_True | 12 | null | transformers | 10,748 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_NULL_True
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should p... |
atomsspawn/DialoGPT-small-shelbot | 07516eb879bcde2854f589f3d81599cfe48bd660 | 2022-05-17T20:31:47.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | atomsspawn | null | atomsspawn/DialoGPT-small-shelbot | 12 | null | transformers | 10,749 | ---
tags:
- conversational
---
# Sheldon Cooper DialoGPT Model |
ali2066/DistilBERT_FINAL_ctxSentence_TRAIN_essays_TEST_NULL_second_train_set_null_False | 4cc122ab0c7d4943984eff60cd119141ac2943d5 | 2022-05-02T18:23:52.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | ali2066 | null | ali2066/DistilBERT_FINAL_ctxSentence_TRAIN_essays_TEST_NULL_second_train_set_null_False | 12 | null | transformers | 10,750 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DistilBERT_FINAL_ctxSentence_TRAIN_essays_TEST_NULL_second_train_set_null_False
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had ... |
masakhane/m2m100_418M-FR-NEWS | b49b945102620b0a54c8011ef50f1e292a6dcd71 | 2022-05-12T13:43:29.000Z | [
"pytorch",
"m2m_100",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | masakhane | null | masakhane/m2m100_418M-FR-NEWS | 12 | null | transformers | 10,751 | ---
license: afl-3.0
---
|
enimai/opus-mt-en-de-finetuned-en-to-de | d40c5249f29423d19c94f3bbcc5cc33ce63ea7f9 | 2022-05-03T15:57:16.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | enimai | null | enimai/opus-mt-en-de-finetuned-en-to-de | 12 | null | transformers | 10,752 | ---
license: apache-2.0
---
|
enimai/opus-mt-en-hi-finetuned-en-to-hi | f32133f8d0a0d90eafb60e45073ed843841a67ae | 2022-05-03T16:29:04.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | enimai | null | enimai/opus-mt-en-hi-finetuned-en-to-hi | 12 | null | transformers | 10,753 | ---
license: apache-2.0
---
|
ml4pubmed/biobert-v1.1_pub_section | 445f0a103a0817cc174f0681c8af9db0fd0c4792 | 2022-05-04T00:02:48.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:pubmed",
"transformers"
] | text-classification | false | ml4pubmed | null | ml4pubmed/biobert-v1.1_pub_section | 12 | null | transformers | 10,754 | ---
language:
- en
datasets:
- pubmed
metrics:
- f1
pipeline_tag: text-classification
widget:
- text: "Many pathogenic processes and diseases are the result of an erroneous activation of the complement cascade and a number of inhibitors of complement have thus been examined for anti-inflammatory actions."
example_tit... |
ml4pubmed/scibert-scivocab-uncased_pub_section | ba7656f774cdddca4bb441f903f7873afe25e9d6 | 2022-06-22T10:59:11.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:pubmed",
"transformers",
"document sections",
"sentence classification",
"document classification",
"medical",
"health",
"biomedical"
] | text-classification | false | ml4pubmed | null | ml4pubmed/scibert-scivocab-uncased_pub_section | 12 | null | transformers | 10,755 | ---
language:
- en
datasets:
- pubmed
metrics:
- f1
pipeline_tag: text-classification
tags:
- text-classification
- document sections
- sentence classification
- document classification
- medical
- health
- biomedical
widget:
- text: "many pathogenic processes and diseases are the result of an erroneous activation of t... |
dkasti/distilbert-base-uncased-finetuned-emotion | 0f8b949ad83d90ff8cafb22a40a7fc79e458a763 | 2022-05-04T05:03:46.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | dkasti | null | dkasti/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,756 | ---
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... |
cwkeam/mctct-large | c0fab5422e4bb621097c18bf96a1cd2bbc7048e0 | 2022-05-05T11:02:00.000Z | [
"pytorch",
"mctct",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"dataset:common_voice",
"arxiv:2111.00161",
"transformers",
"speech",
"license:apache-2.0"
] | automatic-speech-recognition | false | cwkeam | null | cwkeam/mctct-large | 12 | null | transformers | 10,757 | ---
language: en
datasets:
- librispeech_asr
- common_voice
tags:
- speech
license: apache-2.0
---
# M-CTC-T
Massively multilingual speech recognizer from Meta AI. The model is a 1B-param transformer encoder, with a CTC head over 8065 character labels and a language identification head over 60 language ID labels. I... |
brjezierski/bert-finetuned-ner | 7f01546dbdc3df17a7febc2f69a89a3083aa5cc8 | 2022-05-06T21:10:12.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | brjezierski | null | brjezierski/bert-finetuned-ner | 12 | null | transformers | 10,758 | ---
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... |
ChainYo/t5-base-sede-txt2sql | bf06838fc7182603f0a8609fe63abd60a9d478e6 | 2022-05-07T18:50:12.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"dataset:sede",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | ChainYo | null | ChainYo/t5-base-sede-txt2sql | 12 | null | transformers | 10,759 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- sede
model-index:
- name: t5-base-sede-txt2sql
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. -->
... |
Jeevesh8/bert_ft_qqp-0 | 17645bf0b6f171d517ac3e9a13f50eb1908b5b4d | 2022-05-07T12:10:57.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Jeevesh8 | null | Jeevesh8/bert_ft_qqp-0 | 12 | null | transformers | 10,760 | Entry not found |
theojolliffe/distilbart-cnn-arxiv-pubmed | ee16b09c909770f31a2a53f0eb5e150d839db3e4 | 2022-05-07T19:16:46.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"dataset:scientific_papers",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | theojolliffe | null | theojolliffe/distilbart-cnn-arxiv-pubmed | 12 | null | transformers | 10,761 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: distilbart-cnn-12-6-finetuned-arxiv-pubmed
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
... |
shibing624/bert4ner-base-uncased | a0011f0880da6a53d90fa1380b7ab45a7ee6944d | 2022-05-09T09:05:56.000Z | [
"pytorch",
"bert",
"token-classification",
"en",
"transformers",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | shibing624 | null | shibing624/bert4ner-base-uncased | 12 | 1 | transformers | 10,762 | ---
language:
- en
tags:
- bert
- pytorch
- en
- ner
license: "apache-2.0"
---
# BERT for English Named Entity Recognition(bert4ner) Model
英文实体识别模型
`bert4ner-base-uncased` evaluate CoNLL-2003 test data：
The overall performance of BERT on CoNLL-2003 **test**:
| | Accuracy | Recall | F1 |
| -------... |
allermat/distilbert-base-uncased-finetuned-emotion | eec3d837edc52d4b2b7baeab3e3992df013286f4 | 2022-07-13T15:20:51.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | allermat | null | allermat/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,763 | ---
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/roberta-base-bne-finetuned-amazon_reviews_multi | 1a8e16e597c1b152bc8236ee10b420207ea21f26 | 2022-05-10T08:40:55.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"dataset:amazon_reviews_multi",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | JoanTirant | null | JoanTirant/roberta-base-bne-finetuned-amazon_reviews_multi | 12 | null | transformers | 10,764 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
model-index:
- name: roberta-base-bne-finetuned-amazon_reviews_multi
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
type: ... |
CEBaB/bert-base-uncased.CEBaB.sa.3-class.exclusive.seed_42 | 70ce805d2148f60f46aaa6fa6dc93146905741a2 | 2022-05-10T23:38:33.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.3-class.exclusive.seed_42 | 12 | null | transformers | 10,765 | Entry not found |
CEBaB/gpt2.CEBaB.sa.5-class.exclusive.seed_42 | 9bb2e23db865006ea01e4e840de07e8c3f0e7bb4 | 2022-05-11T00:07:04.000Z | [
"pytorch",
"gpt2",
"transformers"
] | null | false | CEBaB | null | CEBaB/gpt2.CEBaB.sa.5-class.exclusive.seed_42 | 12 | null | transformers | 10,766 | Entry not found |
CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_66 | 6e3451c4e138d40221f290988582cf397eb3ab92 | 2022-05-11T00:13:38.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_66 | 12 | null | transformers | 10,767 | Entry not found |
CEBaB/gpt2.CEBaB.sa.5-class.exclusive.seed_66 | d7f6b0eedff1e03a9f7f3b52652ef63f6c5d9d27 | 2022-05-11T00:58:51.000Z | [
"pytorch",
"gpt2",
"transformers"
] | null | false | CEBaB | null | CEBaB/gpt2.CEBaB.sa.5-class.exclusive.seed_66 | 12 | null | transformers | 10,768 | Entry not found |
CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_77 | 46655e6b2d35a744f50f618f191edfbe66cd6f5b | 2022-05-11T01:05:26.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_77 | 12 | null | transformers | 10,769 | Entry not found |
CEBaB/gpt2.CEBaB.sa.5-class.exclusive.seed_77 | 2321dbbc4e4e8090ead9957138d46991da9299a9 | 2022-05-11T01:51:08.000Z | [
"pytorch",
"gpt2",
"transformers"
] | null | false | CEBaB | null | CEBaB/gpt2.CEBaB.sa.5-class.exclusive.seed_77 | 12 | null | transformers | 10,770 | Entry not found |
CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_88 | 00c99284efde48e92111b40026b7f51278f76323 | 2022-05-11T01:57:55.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_88 | 12 | null | transformers | 10,771 | Entry not found |
CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_99 | 960e21617611136cb71cc76ac148043ac82bff04 | 2022-05-11T02:49:21.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_99 | 12 | null | transformers | 10,772 | Entry not found |
SalamaThanks/SalamaThanksTransformer_en2fil_v2 | 99452bf272a6ea72f0787db5a373984376419175 | 2022-05-11T05:58:25.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | SalamaThanks | null | SalamaThanks/SalamaThanksTransformer_en2fil_v2 | 12 | null | transformers | 10,773 | ---
license: afl-3.0
---
SalamaThanks Transformer for English-to-Filipino Text Translation version 2.
A finetuned transformer model based on the Helsinki-NLP/opus-mt-en-tl transformer model. |
idsedykh/model1 | 1f2906fb6270afa48fb73afb00e1202def80040f | 2022-05-11T19:03:10.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | idsedykh | null | idsedykh/model1 | 12 | null | transformers | 10,774 | Entry not found |
eslamxm/mt5-base-finetuned-english-finetuned-english-arabic | c3a3fb4f6afac0be24667ddf4100e01b7294f5f0 | 2022-05-13T19:39:26.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"dataset:xlsum",
"transformers",
"summarization",
"arabic",
"ar",
"en",
"Abstractive Summarization",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | eslamxm | null | eslamxm/mt5-base-finetuned-english-finetuned-english-arabic | 12 | null | transformers | 10,775 | ---
license: apache-2.0
tags:
- summarization
- arabic
- ar
- en
- mt5
- Abstractive Summarization
- generated_from_trainer
datasets:
- xlsum
model-index:
- name: mt5-base-finetuned-english-finetuned-english-arabic
results: []
---
<!-- This model card has been generated automatically according to the information the... |
Leizhang/distilbert-base-uncased-finetuned-emotion | 3ed7f1d85960ea53ccfb1ea904c9e21f34630690 | 2022-05-14T20:55:21.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Leizhang | null | Leizhang/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,776 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
model-index:
- name: distilbert-base-uncased-finetuned-emotion
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 r... |
importsmart/bert-to-distilbert-NER | 6c03e95e50b1ebc826685e8b6b949ae641d8755c | 2022-05-16T18:02:27.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | importsmart | null | importsmart/bert-to-distilbert-NER | 12 | null | transformers | 10,777 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-to-distilbert-NER
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conl... |
huggingtweets/cryptanime | 02fdbdeffcf7bb1c1b501111f13c8cac2360b86a | 2022-05-17T06:54:30.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/cryptanime | 12 | null | transformers | 10,778 | ---
language: en
thumbnail: http://www.huggingtweets.com/cryptanime/1652770465803/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; widt... |
CEBaB/bert-base-uncased.CEBaB.absa.exclusive.seed_88 | c79f59439e487f91d658df8885f5acf662292048 | 2022-05-17T18:57:57.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.absa.exclusive.seed_88 | 12 | null | transformers | 10,779 | Entry not found |
CEBaB/bert-base-uncased.CEBaB.absa.exclusive.seed_99 | 64b6fb17e67b411cff4fceea3276b71aa68f5cbd | 2022-05-17T19:02:40.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.absa.exclusive.seed_99 | 12 | null | transformers | 10,780 | Entry not found |
NFflow/healthcare_27.03.2021-27.03.2022_redditflow | e3bafb55f51bc5e44eb63b548524d83244f803d4 | 2022-05-21T06:41:02.000Z | [
"pytorch",
"distilbert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | NFflow | null | NFflow/healthcare_27.03.2021-27.03.2022_redditflow | 12 | null | sentence-transformers | 10,781 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
inference: false
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for t... |
huggingtweets/vgdunkey | a9998cf6d149d16c71bc5d7947868b467f79c2e3 | 2022-07-23T05:14:07.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/vgdunkey | 12 | null | transformers | 10,782 | ---
language: en
thumbnail: http://www.huggingtweets.com/vgdunkey/1658553242358/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width:... |
ericklerouge123/distilbert-base-uncased-finetuned-emotion | f451c519a6c91b43ac7977bec79013c614e18eeb | 2022-05-20T20:35:39.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | ericklerouge123 | null | ericklerouge123/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,783 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
model-index:
- name: distilbert-base-uncased-finetuned-emotion
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 r... |
stplgg/distilbert-base-uncased-finetuned-emotion | 8cc0bf41d29423710a59428c18cf27089850dbdf | 2022-05-20T15:12:48.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | stplgg | null | stplgg/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,784 | ---
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... |
connectivity/bert_ft_qqp-22 | 1392e2961a6df2515d11065880ef420f163f48ae | 2022-05-21T16:32:43.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | connectivity | null | connectivity/bert_ft_qqp-22 | 12 | null | transformers | 10,785 | Entry not found |
connectivity/bert_ft_qqp-98 | c77f676310d9736076867ba6c4472055be9224ef | 2022-05-21T16:38:29.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | connectivity | null | connectivity/bert_ft_qqp-98 | 12 | null | transformers | 10,786 | Entry not found |
RaphaelReinauer/mbart50-finetuned-multi30-en-to-de | 8f79a72f046575790c31ce33c2bd00070fccc4b1 | 2022-05-23T22:42:15.000Z | [
"pytorch",
"tensorboard",
"mbart",
"text2text-generation",
"transformers",
"translation",
"model-index",
"autotrain_compatible"
] | translation | false | RaphaelReinauer | null | RaphaelReinauer/mbart50-finetuned-multi30-en-to-de | 12 | null | transformers | 10,787 | ---
tags:
- translation
metrics:
- bleu
model-index:
- name: mbart50-finetuned-multi30-en-to-de
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. -->
# mbart50-finetun... |
krotima1/mbart-ht2a-cs | 8b761742bd3b2346e5198e444e3665f2fd5c6c66 | 2022-05-26T12:59:01.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"cs",
"dataset:private Czech News Center dataset news-based",
"dataset:SumeCzech dataset news-based",
"transformers",
"Summarization",
"abstractive summarization",
"mbart-cc25",
"Czech",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | krotima1 | null | krotima1/mbart-ht2a-cs | 12 | null | transformers | 10,788 | ---
language:
- cs
- cs
tags:
- Summarization
- abstractive summarization
- mbart-cc25
- Czech
license: apache-2.0
datasets:
- private Czech News Center dataset news-based
- SumeCzech dataset news-based
metrics:
- rouge
- rougeraw
---
# mBART fine-tuned model for Czech abstractive summarization (HT2A-CS)
This model is... |
fabraz/distilbert-base-uncased-finetunned-emotion | 84b2dd3b38d87acf34730acefe4999985021c7ec | 2022-05-23T18:39:31.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | fabraz | null | fabraz/distilbert-base-uncased-finetunned-emotion | 12 | null | transformers | 10,789 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetunned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: defaul... |
Rgl73/distilbert-base-uncased-finetuned-emotion | 423b86c06f6c5ea1b3e4055219aae26b49eca19a | 2022-06-05T10:40:49.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Rgl73 | null | Rgl73/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,790 | ---
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... |
sexomq/DialoGPT-medium-TeoBot | e4e710e758eadf51f6eeb62f8f5777195ba28efe | 2022-05-23T20:26:34.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | sexomq | null | sexomq/DialoGPT-medium-TeoBot | 12 | 1 | transformers | 10,791 | ---
tags:
- conversational
--- |
pkumc/distilbert-base-uncased-finetuned-cola | 7ccea95d005eeb78d71d2c95c54927e5e5d97925 | 2022-05-24T11:43:04.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | pkumc | null | pkumc/distilbert-base-uncased-finetuned-cola | 12 | null | transformers | 10,792 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
model-index:
- name: distilbert-base-uncased-finetuned-cola
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 ... |
joaobarroca/distilbert-base-uncased-finetuned-massive-intent-detection-english | 3b68440a34957a9ccdef5aa07f9f9becb6485b20 | 2022-05-24T17:12:14.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:massive",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | joaobarroca | null | joaobarroca/distilbert-base-uncased-finetuned-massive-intent-detection-english | 12 | null | transformers | 10,793 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-massive-intent-detection-english
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: massive
type: massive... |
usama98/arabic_poem_gen | 5de15a71dc14fd4436aafaedf74953c4617b030d | 2022-05-31T16:55:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ar",
"dataset:Arabic Poem Comprehensive Dataset (APCD)",
"transformers",
"license:apache-2.0"
] | text-generation | false | usama98 | null | usama98/arabic_poem_gen | 12 | null | transformers | 10,794 |
---
language:
- ar
tags:
- text-generation
license: apache-2.0
datasets:
- Arabic Poem Comprehensive Dataset (APCD)
widget:
- text: "عمرو بنِ قُمَيئَة: خَليلَيَّ لا تَستَعجِلا أَن"
---
# GPTPoet: Pre-training GPT2 for Arabic Poetry Language Understanding
<img src="https://huggingface.co/usama98/arabic_poem_gen/res... |
arcAman07/distilbert-base-uncased-finetuned-emotion | 9f262d260a97df09580f1a20425a410e1510c1ab | 2022-05-25T17:08:01.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | arcAman07 | null | arcAman07/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,795 | ---
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... |
tbosse/bert-base-german-cased-finetuned-subj_v6_7Epoch_v2 | 2c3bc64c72fe2d0f98cc3a7c910cdde0bae5a68b | 2022-05-25T17:48:28.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | tbosse | null | tbosse/bert-base-german-cased-finetuned-subj_v6_7Epoch_v2 | 12 | null | transformers | 10,796 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-german-cased-finetuned-subj_v6_7Epoch_v2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proof... |
tbosse/bert-base-german-cased-finetuned-subj_v6_7Epoch_v3 | 73b1febd1e8d1c7b1cabd6a445e8100c0553daaf | 2022-05-25T19:01:02.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | tbosse | null | tbosse/bert-base-german-cased-finetuned-subj_v6_7Epoch_v3 | 12 | null | transformers | 10,797 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-german-cased-finetuned-subj_v6_7Epoch_v3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proof... |
sayanmandal/t5-small_6_3-hi_en-to-en | 75cb22e308720d322134d6e89959a45a56220262 | 2022-05-26T11:32:32.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"dataset:cmu_hinglish_dog",
"transformers",
"translation",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | translation | false | sayanmandal | null | sayanmandal/t5-small_6_3-hi_en-to-en | 12 | 0 | transformers | 10,798 | ---
tags:
- translation
- generated_from_trainer
datasets:
- cmu_hinglish_dog
metrics:
- bleu
model-index:
- name: t5-small_6_3-hi_en-to-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: cmu_hinglish_dog
type: cmu_hinglish_dog
... |
Yah216/Poem_Qafiyah_Detection | 0a6f758cf92894b97c86af3e7cce2e9ec747aaab | 2022-05-28T07:56:56.000Z | [
"pytorch",
"bert",
"text-classification",
"ar",
"dataset:Yah216/Poem_Rawiy_detection",
"transformers",
"co2_eq_emissions"
] | text-classification | false | Yah216 | null | Yah216/Poem_Qafiyah_Detection | 12 | null | transformers | 10,799 | ---
language: ar
datasets:
- Yah216/Poem_Rawiy_detection
co2_eq_emissions: 1.8046766441629636
widget:
- "سَلو قَلبي غَداةَ سَلا وَثابا لَعَلَّ عَلى الجَمالِ لَهُ عِتاب"
---
# Model
- Problem type: Multi-class Classification
- CO2 Emissions (in grams): 1.8046766441629636
## Dataset
We used the APCD dataset cited he... |
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