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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
imadd/segformer-b0-finetuned-segments-water-2 | e6efa638af3065dc1e10dc74934aa0855a2dce01 | 2022-07-07T18:05:48.000Z | [
"pytorch",
"segformer",
"transformers",
"vision",
"image-segmentation",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-segmentation | false | imadd | null | imadd/segformer-b0-finetuned-segments-water-2 | 30 | null | transformers | 7,200 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-segments-water-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... |
xyma/PROP-wiki | 0e685864e4a5efd3b000f87e8746c0d60b48f28f | 2022-07-12T13:49:52.000Z | [
"pytorch",
"bert",
"pretraining",
"en",
"dataset:wikipedia",
"arxiv:2010.10137",
"transformers",
"PROP",
"Pretrain4IR",
"fill-mask",
"license:apache-2.0"
] | fill-mask | false | xyma | null | xyma/PROP-wiki | 30 | null | transformers | 7,201 | ---
language: en
tags:
- PROP
- Pretrain4IR
- fill-mask
license: apache-2.0
datasets:
- wikipedia
---
# PROP-wiki
**PROP**, **P**re-training with **R**epresentative w**O**rds **P**rediction, is a new pre-training method tailored for ad-hoc retrieval. PROP is inspired by the classical statistical language model for ... |
gaochang/tbsz-picard | b623151f4828c4be73f13c922e58c0f16b548dca | 2022-07-14T09:36:36.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | gaochang | null | gaochang/tbsz-picard | 30 | null | transformers | 7,202 | Entry not found |
Duplets/distilbert-base-uncased-finetuned-squad | 4747c44a9e4d9ef40951a6875c7bad19792de301 | 2022-07-21T00:02:58.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | Duplets | null | Duplets/distilbert-base-uncased-finetuned-squad | 30 | null | transformers | 7,203 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
results: []
We
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remov... |
erickdp/sentiment-analysisi-distillbert-es | e569ee3f6a396bbf41cf024067d50a902167d38f | 2022-07-21T23:28:50.000Z | [
"pytorch",
"distilbert",
"text-classification",
"unk",
"dataset:erickdp/autotrain-data-sentiment-analysis-distillbert-es",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | erickdp | null | erickdp/sentiment-analysisi-distillbert-es | 30 | null | transformers | 7,204 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- erickdp/autotrain-data-sentiment-analysis-distillbert-es
co2_eq_emissions: 4.070674106910222
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1164342966
- CO2 Emissions (in grams): 4.070674106... |
BoxCrab/DialoGPT-unk-AR | 6044b9496ce7249329c4a1479d75d838365bb10a | 2022-07-23T08:13:46.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | BoxCrab | null | BoxCrab/DialoGPT-unk-AR | 30 | null | transformers | 7,205 | ---
tags:
- conversational
---
#homestuck DialoGPT Model |
Giuliano/vit-lung-cancer | 452db03c5e434110f82cd92cee390f310147251e | 2022-07-26T05:02:06.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers"
] | image-classification | false | Giuliano | null | Giuliano/vit-lung-cancer | 30 | null | transformers | 7,206 | Entry not found |
arminmehrabian/all-MiniLM-L6-v2-all-MiniLM-L6-v2-agu | 0e521a4dec7004de7542daed622d95bd7d18d6e1 | 2022-07-29T07:33:58.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | arminmehrabian | null | arminmehrabian/all-MiniLM-L6-v2-all-MiniLM-L6-v2-agu | 30 | null | transformers | 7,207 | Entry not found |
Elluran/Hate_speech_detector | be14317cb136a9133e6e60e838a7d859656fb7b6 | 2021-05-20T11:49:13.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | Elluran | null | Elluran/Hate_speech_detector | 29 | null | transformers | 7,208 | Entry not found |
Graphcore/bert-large-uncased | a9c367bbc13c994d658ac8f6e82ab27a4a03d2f2 | 2022-05-25T18:30:21.000Z | [
"pytorch",
"bert",
"dataset:Graphcore/wikipedia-bert-128",
"dataset:Graphcore/wikipedia-bert-512",
"arxiv:1904.00962",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | null | false | Graphcore | null | Graphcore/bert-large-uncased | 29 | 4 | transformers | 7,209 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Graphcore/wikipedia-bert-128
- Graphcore/wikipedia-bert-512
model-index:
- name: Graphcore/bert-large-uncased
results: []
---
# Graphcore/bert-large-uncased
Optimum Graphcore is a new open-source library and toolkit that enables developers to access... |
Helsinki-NLP/opus-mt-ee-en | a69e3d990dc8b84d8d727b9502c20511a50233ed | 2021-09-09T21:33:10.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ee",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ee-en | 29 | null | transformers | 7,210 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ee-en
* source languages: ee
* target languages: en
* OPUS readme: [ee-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ee-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-en-sg | d8ca39bde6ae7caa48ac06aaa90045cfdf24f8fd | 2021-09-09T21:39:00.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"sg",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-sg | 29 | null | transformers | 7,211 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-sg
* source languages: en
* target languages: sg
* OPUS readme: [en-sg](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-sg/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-es-af | dbd402381410acd3c00ab076e11402f2b2bb176a | 2021-01-18T08:21:38.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"af",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-es-af | 29 | null | transformers | 7,212 | ---
language:
- es
- af
tags:
- translation
license: apache-2.0
---
### spa-afr
* source group: Spanish
* target group: Afrikaans
* OPUS readme: [spa-afr](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-afr/README.md)
* model: transformer-align
* source language(s): spa
* target langu... |
Helsinki-NLP/opus-mt-es-csn | e98aef098fb92058c3dce5d306020228ad0f4280 | 2021-09-09T21:41:45.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"csn",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-es-csn | 29 | null | transformers | 7,213 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-es-csn
* source languages: es
* target languages: csn
* OPUS readme: [es-csn](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/es-csn/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-itc-itc | 43c984c16f7004fa69db29b2937644c0178c9568 | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"it",
"ca",
"rm",
"es",
"ro",
"gl",
"sc",
"co",
"wa",
"pt",
"oc",
"an",
"id",
"fr",
"ht",
"itc",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-itc-itc | 29 | null | transformers | 7,214 | ---
language:
- it
- ca
- rm
- es
- ro
- gl
- sc
- co
- wa
- pt
- oc
- an
- id
- fr
- ht
- itc
tags:
- translation
license: apache-2.0
---
### itc-itc
* source group: Italic languages
* target group: Italic languages
* OPUS readme: [itc-itc](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/i... |
IlyaGusev/xlm_roberta_large_headline_cause_simple | ea1785ed65ee94eb6feae6695d00a00676d7ea55 | 2022-07-13T15:36:36.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ru",
"en",
"dataset:IlyaGusev/headline_cause",
"arxiv:2108.12626",
"transformers",
"xlm-roberta-large",
"license:apache-2.0"
] | text-classification | false | IlyaGusev | null | IlyaGusev/xlm_roberta_large_headline_cause_simple | 29 | null | transformers | 7,215 | ---
language:
- ru
- en
tags:
- xlm-roberta-large
datasets:
- IlyaGusev/headline_cause
license: apache-2.0
widget:
- text: "Песков опроверг свой перевод на удаленку</s>Дмитрий Песков перешел на удаленку"
---
# XLM-RoBERTa HeadlineCause Simple
## Model description
This model was trained to predict the presence of ca... |
M-FAC/bert-tiny-finetuned-mrpc | 5186a04d859ccd40aef8b32e8b1e065b0b4f187b | 2021-12-13T08:12:51.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:2107.03356",
"transformers"
] | text-classification | false | M-FAC | null | M-FAC/bert-tiny-finetuned-mrpc | 29 | null | transformers | 7,216 | # BERT-tiny model finetuned with M-FAC
This model is finetuned on MRPC dataset with state-of-the-art second-order optimizer M-FAC.
Check NeurIPS 2021 paper for more details on M-FAC: [https://arxiv.org/pdf/2107.03356.pdf](https://arxiv.org/pdf/2107.03356.pdf).
## Finetuning setup
For fair comparison against default ... |
M-FAC/bert-tiny-finetuned-sst2 | 41ad6709ec46b414749b37daf49cf5ca1c7dba7c | 2021-12-13T08:13:48.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:2107.03356",
"transformers"
] | text-classification | false | M-FAC | null | M-FAC/bert-tiny-finetuned-sst2 | 29 | null | transformers | 7,217 | # BERT-tiny model finetuned with M-FAC
This model is finetuned on SST-2 dataset with state-of-the-art second-order optimizer M-FAC.
Check NeurIPS 2021 paper for more details on M-FAC: [https://arxiv.org/pdf/2107.03356.pdf](https://arxiv.org/pdf/2107.03356.pdf).
## Finetuning setup
For fair comparison against default... |
Madhour/gpt2-eli5 | be12ea44e909ad3f4d1894b90b2ca7041d48ec28 | 2022-01-23T12:00:23.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"dataset:eli5",
"transformers",
"ELI5",
"license:gpl-3.0"
] | text-generation | false | Madhour | null | Madhour/gpt2-eli5 | 29 | null | transformers | 7,218 | ---
language: en
tags:
- ELI5
license: gpl-3.0
datasets:
- eli5
Task: Summarization
widget:
- text: "<|BOS|><|SEP|>Consulting,business,Fraud<|SEP|>"
inference:
parameters:
temperature: 0.9
return_full_text: False
repetition_penalty: 1
---
# Conditional ELI5 Generator
Given a few keywords, it ge... |
Malaina/mt5-large-spider | 11ff8f57835c5f238948ec4b811d809c454e4e35 | 2022-02-09T04:33:48.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Malaina | null | Malaina/mt5-large-spider | 29 | null | transformers | 7,219 | Entry not found |
Maltehb/aelaectra-danish-electra-small-uncased | 687bd788e396966d15da24cba4fc1b64fe9c4c07 | 2021-11-23T06:39:20.000Z | [
"pytorch",
"electra",
"pretraining",
"da",
"dataset:DAGW",
"arxiv:2003.10555",
"arxiv:1810.04805",
"arxiv:2005.03521",
"transformers",
"ælæctra",
"danish",
"ELECTRA-Small",
"replaced token detection",
"license:mit",
"co2_eq_emissions"
] | null | false | Maltehb | null | Maltehb/aelaectra-danish-electra-small-uncased | 29 | null | transformers | 7,220 | ---
language: "da"
co2_eq_emissions: 4009.5
tags:
- ælæctra
- pytorch
- danish
- ELECTRA-Small
- replaced token detection
license: "mit"
datasets:
- DAGW
metrics:
- f1
---
# Ælæctra - A Step Towards More Efficient Danish Natural Language Processing
**Ælæctra** is a Danish Transformer-based language model created to en... |
SEBIS/legal_t5_small_summ_de | 42d8cb548a1addc92fd43ad8fca86f23783802ea | 2021-06-23T11:21:22.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"Deustch",
"dataset:jrc-acquis",
"transformers",
"summarization Deustch model",
"autotrain_compatible"
] | text2text-generation | false | SEBIS | null | SEBIS/legal_t5_small_summ_de | 29 | null | transformers | 7,221 |
---
language: Deustch
tags:
- summarization Deustch model
datasets:
- jrc-acquis
widget:
- text: "(90/365/EWG) DER RAT DER EUROPÄISCHEN GEMEINSCHAFTEN - gestützt auf den Vertrag zur Gründung der Europäischen Wirtschaftsgemeinschaft, insbesondere auf Artikel 235, auf Vorschlag der Kommission (1), nach Stellungnahme ... |
ShengdingHu/qnli | 5d11db630227970acb31f2a246d698ce6eefe708 | 2022-02-02T13:22:44.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | ShengdingHu | null | ShengdingHu/qnli | 29 | null | transformers | 7,222 | Entry not found |
addy88/wav2vec2-english-stt | 86095016131ad4fc6bfd7e72f4cbb8615319ee74 | 2021-12-19T15:08:42.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | addy88 | null | addy88/wav2vec2-english-stt | 29 | null | transformers | 7,223 | ## Usage
The model can be used directly (without a language model) as follows:
```python
import soundfile as sf
import torch
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import argparse
def parse_transcription(wav_file):
# load pretrained model
processor = Wav2Vec2Processor.from_pretrained("addy88... |
aliosm/ComVE-gpt2-large | babcc66c5ea72dcb089496c92d6e6b0cd0bce7e7 | 2021-05-21T13:12:02.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:https://github.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation",
"transformers",
"exbert",
"commonsense",
"semeval2020",
"comve",
"license:mit"
] | text-generation | false | aliosm | null | aliosm/ComVE-gpt2-large | 29 | null | transformers | 7,224 | ---
language: "en"
tags:
- gpt2
- exbert
- commonsense
- semeval2020
- comve
license: "mit"
datasets:
- https://github.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation
metrics:
- bleu
widget:
- text: "Chicken can swim in water. <|continue|>"
---
# ComVE-gpt2-large
## Model description
Finetu... |
anirudh21/albert-xxlarge-v2-finetuned-wnli | 102c29f68a2b6379f9544f07371d6ad49972424a | 2022-01-27T13:00:48.000Z | [
"pytorch",
"tensorboard",
"albert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | anirudh21 | null | anirudh21/albert-xxlarge-v2-finetuned-wnli | 29 | null | transformers | 7,225 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: albert-xxlarge-v2-finetuned-wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: wnli
metrics:
- name: ... |
anon-submission-mk/electra-base-macedonian-cased-discriminator | d170c38e6658341ed131e73405a540a4e78d089a | 2020-06-17T21:37:57.000Z | [
"pytorch",
"tf",
"electra",
"pretraining",
"transformers"
] | null | false | anon-submission-mk | null | anon-submission-mk/electra-base-macedonian-cased-discriminator | 29 | null | transformers | 7,226 | Entry not found |
anton-l/wav2vec2-large-xlsr-53-hungarian | 05da1d50259d9b3ad85b363937415419d39b69c4 | 2021-07-05T19:47:18.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"hu",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | anton-l | null | anton-l/wav2vec2-large-xlsr-53-hungarian | 29 | null | transformers | 7,227 | ---
language: hu
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Hungarian XLSR Wav2Vec2 Large 53 by Anton Lozhkov
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
arshyajabbari/wav2vec2-large-persian-demo | 5527845c9e900118cecf1ccbab8537c4fc3d0b46 | 2022-02-09T10:39:49.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | arshyajabbari | null | arshyajabbari/wav2vec2-large-persian-demo | 29 | null | transformers | 7,228 | Entry not found |
ashish-shrivastava/dont-know-response | 700388e0f20ccdc535929b7fb5a622ee9a93f09d | 2021-06-23T11:27:25.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"arxiv:2012.01873",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | ashish-shrivastava | null | ashish-shrivastava/dont-know-response | 29 | 2 | transformers | 7,229 | ## Natural Don't Know Response Model
Fine-tuned on [Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) using a combination of a dependency-rule based data and [Quora Question Pairs(QQP)](https://huggingface.co/nlp/viewer/?dataset=quora) dataset for **Don't Know Response Generation... |
bagdaebhishek/IndianPoliticalTweetsLM | e0f9855b3f7a2e73b45d58bdc8bd2d6e5ea55ef3 | 2021-09-22T07:49:02.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:Twitter",
"dataset:IndianPolitics",
"transformers",
"India",
"politics",
"tweets",
"BJP",
"Congress",
"AAP",
"lm-head",
"license:apache-2.0"
] | text-generation | false | bagdaebhishek | null | bagdaebhishek/IndianPoliticalTweetsLM | 29 | null | transformers | 7,230 | ---
language: en
thumbnail: https://bagdeabhishek.github.io/twitterAnalysis_files/networkfin.jpg
tags:
- India
- politics
- tweets
- BJP
- Congress
- AAP
- pytorch
- gpt2
- lm-head
- text-generation
license: apache-2.0
datasets:
- Twitter
- IndianPolitics
---
# Model name
Indian Political Tweets LM
## Model descripti... |
bioformers/bioformer-cased-v1.0-bc2gm | 3ddfa702a1b534b178c3acb765937582ff6e58a3 | 2021-10-19T07:37:45.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | bioformers | null | bioformers/bioformer-cased-v1.0-bc2gm | 29 | null | transformers | 7,231 | [bioformer-cased-v1.0](https://huggingface.co/bioformers/bioformer-cased-v1.0) fined-tuned on the [BC2GM](https://doi.org/10.1186/gb-2008-9-s2-s2) dataset for 10 epochs. This fine-tuned model can be used for NER for genes/proteins.
|
birgermoell/t5-base-swedish | c9fa23681fba1e8efeb1412dafa13e3e3976fabf | 2021-07-17T07:52:39.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"feature-extraction",
"sv",
"dataset:oscar",
"arxiv:1910.10683",
"transformers",
"summarization",
"translation",
"license:apache-2.0"
] | translation | false | birgermoell | null | birgermoell/t5-base-swedish | 29 | null | transformers | 7,232 | ---
language:
- sv
datasets:
- oscar
tags:
- summarization
- translation
license: apache-2.0
---
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html)
Pretraining Dataset: [C4](https://huggingface.co/datasets/oscar)
Paper: [Exploring the Limits of Transfer Learning with a Unified T... |
biu-nlp/superpal | a0383eaa3520d4fae7780f25d63fb5c84eb0694d | 2022-06-18T22:15:17.000Z | [
"pytorch",
"roberta",
"text-classification",
"arxiv:2009.00590",
"transformers"
] | text-classification | false | biu-nlp | null | biu-nlp/superpal | 29 | null | transformers | 7,233 | ---
widget:
- text: "Prime Minister Hun Sen insisted that talks take place in Cambodia. </s><s> Cambodian leader Hun Sen rejected opposition parties' demands for talks outside the country."
---
# SuperPAL model
Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline
Ori Ernst, Ori Shapira, ... |
btk-mufi/bert-pretrain | 8283f6ab56d53811864ab6a65e17acae00ea6115 | 2021-05-19T13:34:00.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | btk-mufi | null | btk-mufi/bert-pretrain | 29 | null | transformers | 7,234 | Entry not found |
castorini/monot5-large-msmarco-10k | cfbf422f744b443bc461fac220541c4d90be9cbe | 2021-11-24T19:15:14.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | castorini | null | castorini/monot5-large-msmarco-10k | 29 | null | transformers | 7,235 | This model is a T5-large reranker fine-tuned on the MS MARCO passage dataset for 10k steps (or 1 epoch).
This model usually has a better zero-shot performance than `monot5-large-msmarco`, i.e., it performs better on datasets different from MS MARCO.
For more details on how to use it, check the following links:
- [A s... |
chirag2706/gpt2_code_generation_model | fe673bce8bc8ea2ce4d9d3e745ec1eed6aba4ec6 | 2021-05-21T14:54:10.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | chirag2706 | null | chirag2706/gpt2_code_generation_model | 29 | null | transformers | 7,236 | Entry not found |
cook/cicero-similis | 971409a88c7293eb6fd8d497589a95f85dcdd78e | 2022-01-10T06:07:57.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"la",
"dataset:Tesserae",
"dataset:Phi5",
"dataset:Thomas Aquinas",
"dataset:Patrologia Latina",
"transformers",
"language model",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | cook | null | cook/cicero-similis | 29 | null | transformers | 7,237 | ---
language:
- la
tags:
- language model
license: apache-2.0
datasets:
- Tesserae
- Phi5
- Thomas Aquinas
- Patrologia Latina
---
# Cicero-Similis
## Model description
A Latin Language Model, trained on Latin texts, and evaluated using the corpus of Cicero, as described in the paper _What Would Cicero Write? -- Exa... |
crazould/multimodal-emotion-recognition | ef9981c345dbcb41678dff53eab90729e93300aa | 2021-08-19T08:49:33.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | crazould | null | crazould/multimodal-emotion-recognition | 29 | null | transformers | 7,238 | Entry not found |
dbdmg/wav2vec2-xls-r-300m-italian-robust | 2ec7d2093dce5453d02fc5630468bc5f2f2c0b7e | 2022-03-23T18:26:04.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | dbdmg | null | dbdmg/wav2vec2-xls-r-300m-italian-robust | 29 | null | transformers | 7,239 | ---
license: apache-2.0
language: it
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300m - Italian
results:
- task:
name: Automatic Speech Recognition
type: automatic-spee... |
diego-fustes/wav2vec2-large-xlsr-gl | e61a69170595a866e391df843fff6df7a71d46d8 | 2021-07-06T01:30:50.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"gl",
"dataset:OpenSLR 77",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | diego-fustes | null | diego-fustes/wav2vec2-large-xlsr-gl | 29 | null | transformers | 7,240 | # Wav2Vec2-Large-XLSR-53
---
language: gl
datasets:
- OpenSLR 77
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Galician Wav2Vec2-Large-XLSR-53
results:
- task:
name: Speech Recognition
type: automatic-speech-recogn... |
dragonSwing/wav2vec2-base-vietnamese | c66735f7a38f4ab727cd4d31d42c16011d2bd388 | 2021-08-26T05:08:04.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"vi",
"dataset:vlsp",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | dragonSwing | null | dragonSwing/wav2vec2-base-vietnamese | 29 | null | transformers | 7,241 | ---
language: vi
datasets:
- vlsp
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
license: apache-2.0
model-index:
- name: Wav2vec2 Base Vietnamese
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice vi
... |
emre/wav2vec2-large-xls-r-300m-tr | 382a24da1774f6a18f68de3c813d6334457a1ee8 | 2022-03-23T18:25:55.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | emre | null | emre/wav2vec2-large-xls-r-300m-tr | 29 | null | transformers | 7,242 | ---
license: apache-2.0
language: tr
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-large-xls-r-300m-tr
results:
- task:
name: Speech Re... |
enelpi/med-electra-small-discriminator | c04a0627bf9463ae42f380385b61a275fbe1c68f | 2021-06-14T22:49:00.000Z | [
"pytorch",
"electra",
"pretraining",
"transformers"
] | null | false | enelpi | null | enelpi/med-electra-small-discriminator | 29 | null | transformers | 7,243 | Entry not found |
google/tapas-small-finetuned-wikisql-supervised | 64471f58bf6e6817f715e8b8fa08d90193548d1b | 2021-11-29T13:07:06.000Z | [
"pytorch",
"tf",
"tapas",
"table-question-answering",
"en",
"dataset:wikisql",
"arxiv:2004.02349",
"arxiv:2010.00571",
"arxiv:1709.00103",
"transformers",
"license:apache-2.0"
] | table-question-answering | false | google | null | google/tapas-small-finetuned-wikisql-supervised | 29 | 3 | transformers | 7,244 | ---
language: en
tags:
- tapas
license: apache-2.0
datasets:
- wikisql
---
# TAPAS small model fine-tuned on WikiSQL (in a supervised fashion)
his model has 2 versions which can be used. The default version corresponds to the `tapas_wikisql_sqa_inter_masklm_small_reset` checkpoint of the [original Github repository](... |
hfl/chinese-electra-small-ex-discriminator | 999c15e16cfa6d3deac78d3a57f34d242908ecf4 | 2021-03-03T01:39:26.000Z | [
"pytorch",
"tf",
"zh",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0"
] | null | false | hfl | null | hfl/chinese-electra-small-ex-discriminator | 29 | 1 | transformers | 7,245 | ---
language:
- zh
license: "apache-2.0"
---
**Please use `ElectraForPreTraining` for `discriminator` and `ElectraForMaskedLM` for `generator` if you are re-training these models.**
## Chinese ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size ... |
huggingtweets/elmo_oxygen | 3cbe8fc1b59d9304e3748966891befe60bcd3736 | 2021-05-22T02:54:09.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/elmo_oxygen | 29 | null | transformers | 7,246 | ---
language: en
thumbnail: https://www.huggingtweets.com/elmo_oxygen/1617790228158/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1358585705165... |
huggingtweets/insert_name27 | b7803456f2e949c18976ea3d1224bffa8c77e3b3 | 2021-05-22T08:23:40.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/insert_name27 | 29 | null | transformers | 7,247 | ---
language: en
thumbnail: https://www.huggingtweets.com/insert_name27/1617820538616/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/13426540085... |
huggingtweets/xxinnernettexx | 9a8030edee6221ef2a00c4b4138e3bbc77856ec0 | 2022-06-18T22:57:58.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/xxinnernettexx | 29 | null | transformers | 7,248 | ---
language: en
thumbnail: http://www.huggingtweets.com/xxinnernettexx/1655593074247/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; ... |
jkulhanek/augpt-mw-21 | 6940ce051e321ddb4fad4da71c2dc0227cf7cc23 | 2021-05-23T05:58:15.000Z | [
"pytorch",
"gpt2",
"transformers"
] | null | false | jkulhanek | null | jkulhanek/augpt-mw-21 | 29 | null | transformers | 7,249 | Entry not found |
liaad/ud_srl-pt_bertimbau-large | a3a905cc9e2abcb54b11e28e1305e5a0c93875c5 | 2021-09-22T08:56:43.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"multilingual",
"pt",
"dataset:PropBank.Br",
"dataset:CoNLL-2012",
"dataset:Universal Dependencies",
"arxiv:2101.01213",
"transformers",
"bert-large-portuguese-cased",
"semantic role labeling",
"finetuned",
"dependency parsing",
"... | feature-extraction | false | liaad | null | liaad/ud_srl-pt_bertimbau-large | 29 | null | transformers | 7,250 | ---
language:
- multilingual
- pt
tags:
- bert-large-portuguese-cased
- semantic role labeling
- finetuned
- dependency parsing
license: apache-2.0
datasets:
- PropBank.Br
- CoNLL-2012
- Universal Dependencies
metrics:
- F1 Measure
---
# BERTimbau large fine-tune in Portuguese Universal Dependencies and semantic role ... |
lighteternal/stsb-xlm-r-greek-transfer | 28e381a9365abcf8ad2c0808532a8b8cf0d48260 | 2021-10-11T21:16:05.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"en",
"el",
"arxiv:2004.09813",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | lighteternal | null | lighteternal/stsb-xlm-r-greek-transfer | 29 | null | sentence-transformers | 7,251 | ---
language:
- en
- el
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
widget:
- source_sentence: "Το κινητό έπεσε και έσπασε."
sentences: [
"H πτώση κατέστρεψε τη συσκευή.",
"Το αυτοκίνητο έσπασε στα δυο.",
"Ο υπουργός έπεσε και έσπασε το πόδι του."
]
pipe... |
mbartolo/roberta-large-synqa-ext | 2119a9ff627644a132a5f2f6172d2d74cb2cff41 | 2022-07-25T23:35:51.000Z | [
"pytorch",
"roberta",
"question-answering",
"en",
"dataset:adversarial_qa",
"dataset:mbartolo/synQA",
"dataset:squad",
"arxiv:2002.00293",
"arxiv:2104.08678",
"transformers",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | mbartolo | null | mbartolo/roberta-large-synqa-ext | 29 | null | transformers | 7,252 | ---
language:
- en
tags:
- question-answering
license: apache-2.0
datasets:
- adversarial_qa
- mbartolo/synQA
- squad
metrics:
- exact_match
- f1
model-index:
- name: mbartolo/roberta-large-synqa-ext
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: adversarial_... |
monologg/koelectra-base-v2-generator | 2e321e404f956bad94c680e21b050b7f613ca137 | 2021-10-20T16:54:01.000Z | [
"pytorch",
"electra",
"fill-mask",
"ko",
"transformers",
"korean",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | monologg | null | monologg/koelectra-base-v2-generator | 29 | null | transformers | 7,253 | ---
language: ko
license: apache-2.0
tags:
- korean
---
# KoELECTRA v2 (Base Generator)
Pretrained ELECTRA Language Model for Korean (`koelectra-base-v2-generator`)
For more detail, please see [original repository](https://github.com/monologg/KoELECTRA/blob/master/README_EN.md).
## Usage
### Load model and token... |
nguyenthanhasia/VNBertLaw | c24aca1c885d8b50e94108c332bbc46b45f27cbf | 2021-05-20T01:49:05.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"transformers"
] | null | false | nguyenthanhasia | null | nguyenthanhasia/VNBertLaw | 29 | null | transformers | 7,254 | This is Vietnamese Bert Law
|
ravirajoshi/wav2vec2-large-xls-r-300m-marathi | 9fe7c2efa5d649a4f112baae21d8c2cd7d643ac1 | 2022-03-23T18:25:45.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mr",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | ravirajoshi | null | ravirajoshi/wav2vec2-large-xls-r-300m-marathi | 29 | null | transformers | 7,255 | ---
language:
- mr
license: apache-2.0
tags:
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
model-index:
- name: wav2vec2-large-xls-r-300m-marathi
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably pro... |
raynardj/keywords-cangtou-chinese-poetry | 69e4343a3f1a06273f52d6724330e7276be6bc5f | 2022-02-21T08:32:16.000Z | [
"pytorch",
"zh",
"generation",
"poetry"
] | null | false | raynardj | null | raynardj/keywords-cangtou-chinese-poetry | 29 | 3 | null | 7,256 | ---
language:
- zh
tags:
- generation
- poetry
widget:
- text: "疆场-思乡-归家-耕织《丘处机》"
---
# 终于落不了油腻俗套， 来弄这劳什子的藏头诗模型
> This is a model to generated Chinese poetry with leading characters and certain tune of mood.
## 本模型为了达到两个目的 Objectives
* 创作藏头诗 🎸
* 创作时尽量融入关键词的意境🪁 🌼 ❄️ 🌝
## 运作原理 How
这个模型充分利用了[gpt2论文](https://d4mucf... |
raynardj/xlsearch-cross-lang-search-zh-vs-classicical-cn | cb8827bc0699381451f35b3d92578509a7585ef7 | 2021-11-30T01:06:55.000Z | [
"pytorch",
"bert",
"feature-extraction",
"zh",
"transformers",
"search"
] | feature-extraction | false | raynardj | null | raynardj/xlsearch-cross-lang-search-zh-vs-classicical-cn | 29 | 1 | transformers | 7,257 | ---
language:
- zh
tags:
- search
---
# Cross Language Search
## Search cliassical CN with modern ZH
* In some cases, Classical Chinese feels like another language, I even trained 2 translation models ([1](https://huggingface.co/raynardj/wenyanwen-chinese-translate-to-ancient) and [2](https://huggingface.co/raynardj... |
sangrimlee/mt5-small-multitask | 0d53905ad122a560eba31fdd02d54b5787b01779 | 2021-03-30T00:50:38.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sangrimlee | null | sangrimlee/mt5-small-multitask | 29 | 1 | transformers | 7,258 | Entry not found |
tr3cks/3LabelsSentimentAnalysisSpanish | 46595d7d1536cb13ca16d0afcea9ae018528c95e | 2021-05-20T08:02:41.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | tr3cks | null | tr3cks/3LabelsSentimentAnalysisSpanish | 29 | null | transformers | 7,259 | Entry not found |
wangfan/jdt-fin-roberta-wwm-large | 4177b56fa7ed52b1cd990d1de117364834213fd8 | 2021-11-08T07:03:09.000Z | [
"pytorch",
"bert",
"fill-mask",
"zh",
"dataset:finance",
"transformers",
"roberta-wwm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | wangfan | null | wangfan/jdt-fin-roberta-wwm-large | 29 | null | transformers | 7,260 | ---
language: zh
tags:
- roberta-wwm
license: apache-2.0
datasets:
- finance
---
在众多业务中，越来越频繁的使用预训练语言模型（Pre-trained Language Models），为了在金融场景下各任务中取得更好效果，我们发布了jdt-fin-roberta-wwm模型
## 模型
* `base模型`：12-layer, 768-hidden, 12-heads, 110M parameters
| 模型简称 | 语料 | 京盘下载 |
| - | - | - |
| fin-roberta-wwm | 金融语料 | - |
## 快... |
wietsedv/bert-base-multilingual-cased-finetuned-conll2002-ner | c0b95e058842b3d0b8d01401a489fd866a8d8d04 | 2021-05-20T09:13:44.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | wietsedv | null | wietsedv/bert-base-multilingual-cased-finetuned-conll2002-ner | 29 | 1 | transformers | 7,261 | Entry not found |
armageddon/albert-xxlarge-v2-squad2-covid-qa-deepset | 30a4c1a72050b836f37438235b631d30d36d57fd | 2022-03-02T11:01:43.000Z | [
"pytorch",
"tensorboard",
"albert",
"question-answering",
"dataset:covid_qa_deepset",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | armageddon | null | armageddon/albert-xxlarge-v2-squad2-covid-qa-deepset | 29 | null | transformers | 7,262 | ---
tags:
- generated_from_trainer
datasets:
- covid_qa_deepset
model-index:
- name: albert-xxlarge-v2-squad2-covid-qa-deepset
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 ... |
facebook/m2m100-12B-avg-10-ckpt | 497102e8ab6b8a32356aa2c524902a9295d0314d | 2022-05-26T22:25:25.000Z | [
"pytorch",
"m2m_100",
"text2text-generation",
"multilingual",
"af",
"am",
"ar",
"ast",
"az",
"ba",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"ceb",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"ff",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha"... | text2text-generation | false | facebook | null | facebook/m2m100-12B-avg-10-ckpt | 29 | null | transformers | 7,263 | ---
language:
- multilingual
- af
- am
- ar
- ast
- az
- ba
- be
- bg
- bn
- br
- bs
- ca
- ceb
- cs
- cy
- da
- de
- el
- en
- es
- et
- fa
- ff
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- ht
- hu
- hy
- id
- ig
- ilo
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- lb
- lg
- ln
- lo
- lt
- lv
- mg
- mk
- m... |
docto/Docto-Bot | 30b7a6d837618f834f576a9ad7bcaae536d68ee4 | 2022-03-25T04:33:28.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"license:afl-3.0"
] | text-generation | false | docto | null | docto/Docto-Bot | 29 | 1 | transformers | 7,264 | ---
license: afl-3.0
---
# Docto Bot
## Usage (HuggingFace Transformers)
```
pip install -U transformers
```
```python
import random
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("docto/Docto-Bot")
model = AutoModelForCausalLM.from_pretrained("d... |
MyOrg123/tinparadox-job_search | 4ce9a0b91965ac44e75032ca81f6c3f6fb4863bb | 2022-06-13T02:09:29.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | MyOrg123 | null | MyOrg123/tinparadox-job_search | 29 | null | transformers | 7,265 | Entry not found |
ikram54/autotrain-harassement-675420038 | fa34bc1f855b2be8b0cba5f1dac392f50d11b14a | 2022-03-27T18:08:30.000Z | [
"pytorch",
"bert",
"text-classification",
"unk",
"dataset:ikram54/autotrain-data-harassement",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | ikram54 | null | ikram54/autotrain-harassement-675420038 | 29 | null | transformers | 7,266 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- ikram54/autotrain-data-harassement
co2_eq_emissions: 2.6332836871905054
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 675420038
- CO2 Emissions (in grams): 2.6332836871905054
## Validation... |
gooohjy/suicidal-bert | 070651c9e7d85ebc49cb747d88c677702278478b | 2022-03-30T12:17:21.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | gooohjy | null | gooohjy/suicidal-bert | 29 | null | transformers | 7,267 | # Suicidal-BERT
This text classification model predicts whether a sequence of words are suicidal (1) or non-suicidal (0).
## Data
The model was trained on the [Suicide and Depression Dataset](https://www.kaggle.com/nikhileswarkomati/suicide-watch) obtained from Kaggle. The dataset was scraped from Reddit and consi... |
shpotes/codegen-350M-mono | 15acb80fd284e5977aefd7aa5df00fe10e21a493 | 2022-06-22T06:02:10.000Z | [
"pytorch",
"codegen",
"text-generation",
"transformers",
"license:bsd-3-clause"
] | text-generation | false | shpotes | null | shpotes/codegen-350M-mono | 29 | 3 | transformers | 7,268 | ---
license: bsd-3-clause
---
# Overview
The CodeGen model was proposed in by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. From Salesforce Research.
The abstract from the paper is the following:
Program synthesis strives to generate a computer program a... |
edwardjross/xlm-roberta-base-finetuned-recipe-all | 2e510e1cd082577bf2aaba6112dbd1a2657879e0 | 2022-04-09T13:19:55.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"arxiv:2004.12184",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | edwardjross | null | edwardjross/xlm-roberta-base-finetuned-recipe-all | 29 | null | transformers | 7,269 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-recipe-all
results: []
widget:
- text: "1 sheet of frozen puff pastry (thawed)"
- text: "1/2 teaspoon fresh thyme, minced"
- text: "2-3 medium tomatoes"
- text: "1 petit oignon rouge"
---
<!-- This model ca... |
sgugger/sharded-gpt-j-6B | dd565b6c037aec5477f98b47531e70c87f1dc021 | 2022-05-11T20:28:51.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers"
] | text-generation | false | sgugger | null | sgugger/sharded-gpt-j-6B | 29 | null | transformers | 7,270 | Entry not found |
Farshid/distilbert-base-uncased-finetuned-financial_phrasebank | b01edc64edffda7d20c284955844ed42818a520a | 2022-06-26T18:57:33.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:financial_phrasebank",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Farshid | null | Farshid/distilbert-base-uncased-finetuned-financial_phrasebank | 29 | null | transformers | 7,271 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-financial_phrasebank
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
... |
gzomer/claim-spotter | 82f22aed62638f5ce174249dcc626245cbb2bb77 | 2022-04-12T14:09:09.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | gzomer | null | gzomer/claim-spotter | 29 | null | transformers | 7,272 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: claim-spotter
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. -->
# claim-s... |
Voicelab/sbert-large-cased-pl | e2179e369a3f72d9b32bcd5004fd9e0597693f94 | 2022-04-13T13:26:50.000Z | [
"pytorch",
"bert",
"feature-extraction",
"pl",
"dataset:Wikipedia",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"license:cc-by-4.0"
] | sentence-similarity | false | Voicelab | null | Voicelab/sbert-large-cased-pl | 29 | 3 | sentence-transformers | 7,273 | ---
license: cc-by-4.0
language:
- pl
datasets:
- Wikipedia
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
widget:
- source_sentence: "Uczenie maszynowe jest konsekwencją rozwoju idei sztucznej inteligencji i metod jej wdrażania praktycznego."
sentences:
... |
Jeevesh8/feather_berts_44 | fe33588d8b3c6b63041a35464261b6334ac5a1d6 | 2022-04-20T13:31:50.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Jeevesh8 | null | Jeevesh8/feather_berts_44 | 29 | null | transformers | 7,274 | Entry not found |
adityay1221/Xegho.30.4 | a17a5a08e3b8ad1bf772f7aad1223e96767df461 | 2022-04-23T12:07:00.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | adityay1221 | null | adityay1221/Xegho.30.4 | 29 | null | transformers | 7,275 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: Xegho.30.4
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. -->
# Xegho.30... |
brennan-richards/gpt2-finetuned-academic-topics | dea749089cacc33939f9c07acdcd0540ff1449a2 | 2022-05-09T23:09:57.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"transformers",
"generated_from_keras_callback",
"license:mit",
"model-index"
] | text-generation | false | brennan-richards | null | brennan-richards/gpt2-finetuned-academic-topics | 29 | null | transformers | 7,276 | ---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: gpt2-finetuned-academic-topics
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# gpt2-finet... |
laurens88/finetuning-crypto-tweet-sentiment-test | 365858bf06b448cfd5bfe0e1cd4b0dbebe5b586c | 2022-05-20T11:14:25.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | laurens88 | null | laurens88/finetuning-crypto-tweet-sentiment-test | 29 | null | transformers | 7,277 | ---
tags:
- generated_from_trainer
model-index:
- name: finetuning-crypto-tweet-sentiment-test
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. -->
# finetuning-crypt... |
CEBaB/bert-base-uncased.CEBaB.sa.5-class.exclusive.seed_99 | c59922a76a6a1b1037560ba830b488e24810eea2 | 2022-05-11T03:23:53.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.5-class.exclusive.seed_99 | 29 | null | transformers | 7,278 | Entry not found |
anas-awadalla/bert-mini-finetuned-squad | 79be3229ea6b1b42526664e1bca7254d3e974855 | 2022-05-21T08:23:12.000Z | [
"pytorch",
"bert",
"question-answering",
"dataset:squad",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | question-answering | false | anas-awadalla | null | anas-awadalla/bert-mini-finetuned-squad | 29 | null | transformers | 7,279 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: bert-mini-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. -->
... |
KoichiYasuoka/deberta-large-japanese-aozora | 140b9ff05491fa0ccc602ce5c90b4cfd52443566 | 2022-07-23T14:43:55.000Z | [
"pytorch",
"deberta-v2",
"fill-mask",
"ja",
"transformers",
"japanese",
"masked-lm",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | KoichiYasuoka | null | KoichiYasuoka/deberta-large-japanese-aozora | 29 | 3 | transformers | 7,280 | ---
language:
- "ja"
tags:
- "japanese"
- "masked-lm"
license: "cc-by-sa-4.0"
pipeline_tag: "fill-mask"
mask_token: "[MASK]"
widget:
- text: "日本に着いたら[MASK]を訪ねなさい。"
---
# deberta-large-japanese-aozora
## Model Description
This is a DeBERTa(V2) model pre-trained on 青空文庫 texts. You can fine-tune `deberta-large-japanese... |
anchit48/fine-tuned-sentiment-analysis-customer-feedback | 40c7d4585e27a1d8a270b6be7be2ff453e1d5895 | 2022-06-03T07:51:05.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | anchit48 | null | anchit48/fine-tuned-sentiment-analysis-customer-feedback | 29 | null | transformers | 7,281 | Entry not found |
ChainYo/segformer-sidewalk | f178724b7ff7654b99f3a5a2ee4fc3c98981e403 | 2022-06-13T19:08:23.000Z | [
"pytorch",
"segformer",
"dataset:segments/sidewalk-semantic",
"arxiv:2105.15203",
"transformers",
"vision",
"image-segmentation",
"license:apache-2.0"
] | image-segmentation | false | ChainYo | null | ChainYo/segformer-sidewalk | 29 | null | transformers | 7,282 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
datasets:
- segments/sidewalk-semantic
---
# SegFormer (b0-sized) model fine-tuned on sidewalk-semantic dataset
SegFormer model fine-tuned on segments/sidewalk-semantic at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient De... |
eslamxm/mt5-base-finetuned-Spanish | e4146c3b83111a17a44ed6964e7ef048d41776a1 | 2022-06-15T05:13:08.000Z | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"dataset:wiki_lingua",
"transformers",
"summarization",
"es",
"spanish",
"abstractive summarization",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | eslamxm | null | eslamxm/mt5-base-finetuned-Spanish | 29 | null | transformers | 7,283 | ---
license: apache-2.0
tags:
- summarization
- mt5
- es
- spanish
- abstractive summarization
- generated_from_trainer
datasets:
- wiki_lingua
model-index:
- name: mt5-base-finetuned-Spanish
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to.... |
waboucay/camembert-large-finetuned-repnum_wl-rua_wl_3_classes | b1c348d2270b74ce091266a3556be7e69e113b72 | 2022-06-20T07:41:39.000Z | [
"pytorch",
"camembert",
"text-classification",
"fr",
"transformers",
"nli"
] | text-classification | false | waboucay | null | waboucay/camembert-large-finetuned-repnum_wl-rua_wl_3_classes | 29 | null | transformers | 7,284 | ---
language:
- fr
tags:
- nli
metrics:
- f1
---
## Eval results
We obtain the following results on ```validation``` and ```test``` sets:
| Set | F1<sub>micro</sub> | F1<sub>macro</sub> |
|------------|--------------------|--------------------|
| validation | 77.3 | 77.3 |
| test ... |
BellaAndBria/distilbert-base-uncased-finetuned-emotion | b19bf3ffa0e4a3270168163bec9227273521b1f1 | 2022-06-21T06:02:19.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | BellaAndBria | null | BellaAndBria/distilbert-base-uncased-finetuned-emotion | 29 | null | transformers | 7,285 | ---
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... |
oussama/layoutlmv3-finetuned-invoice | 4d631e7e074f1e4530fde21bbd6d2f89012b60bc | 2022-06-24T02:57:27.000Z | [
"pytorch",
"tensorboard",
"layoutlmv3",
"token-classification",
"dataset:sroie",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | oussama | null | oussama/layoutlmv3-finetuned-invoice | 29 | null | transformers | 7,286 | ---
tags:
- generated_from_trainer
datasets:
- sroie
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-invoice
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: sroie
type: sroie
args: sroie
metrics:
... |
suvrobaner/distilbert-base-uncased-finetuned-emotion-en-tweets | 5e11246f8925fdc98b25a3bf82fbda6e3e81107f | 2022-07-13T15:40:37.000Z | [
"pytorch",
"distilbert",
"text-classification",
"en",
"dataset:emotion",
"transformers",
"license:apache-2.0"
] | text-classification | false | suvrobaner | null | suvrobaner/distilbert-base-uncased-finetuned-emotion-en-tweets | 29 | null | transformers | 7,287 | ---
language: en
tags:
- text-classification
- pytorch
license: apache-2.0
datasets:
- emotion
---
```python
from transformers import pipeline
model_id = "suvrobaner/distilbert-base-uncased-finetuned-emotion-en-tweets"
classifier = pipeline("text-classification", model = model_id)
custom_tweet = "I saw a movie toda... |
nvidia/stt_zh_citrinet_1024_gamma_0_25 | 86cb0f87f63bebc66227cf4cf0764e046692d9df | 2022-06-28T05:08:12.000Z | [
"nemo",
"zh",
"dataset:aishell_2",
"arxiv:2104.01721",
"automatic-speech-recognition",
"speech",
"audio",
"CTC",
"Citrinet",
"pytorch",
"NeMo",
"hf-asr-leaderboard",
"Riva",
"license:cc-by-4.0",
"model-index"
] | automatic-speech-recognition | false | nvidia | null | nvidia/stt_zh_citrinet_1024_gamma_0_25 | 29 | 1 | nemo | 7,288 | ---
language:
- zh
library_name: nemo
datasets:
- aishell_2
thumbnail: null
tags:
- automatic-speech-recognition
- speech
- audio
- CTC
- Citrinet
- pytorch
- NeMo
- hf-asr-leaderboard
- Riva
license: cc-by-4.0
model-index:
- name: stt_zh_citrinet_1024_gamma_0_25
results:
- task:
name: Automatic Speech Recogn... |
southmost/ru-gpt-dy | 7700bdac7361e9b5ef4f735706be7c358c9bd47c | 2022-07-02T22:15:20.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"en",
"transformers",
"text",
"nlp",
"generation",
"beginner",
"license:gpl"
] | text-generation | false | southmost | null | southmost/ru-gpt-dy | 29 | null | transformers | 7,289 | ---
language:
- en
thumbnail: "url to a thumbnail used in social sharing"
tags:
- text
- nlp
- generation
- beginner
license: "gpl"
---
# ru-gpt-dy
**This is the first model I fine-tuned.**
It is GPT-NEO fine-tuned on around 36,000 of my tweets. It’s a generation model. Input -> output. It’s just okay, but it’s mi... |
Neha2608/pegasus-samsum | 883b01f337e1cb7219857f3aacd7cff72c7a537e | 2022-07-03T11:47:37.000Z | [
"pytorch",
"tensorboard",
"pegasus",
"text2text-generation",
"dataset:samsum",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | Neha2608 | null | Neha2608/pegasus-samsum | 29 | null | transformers | 7,290 | ---
tags:
- generated_from_trainer
datasets:
- samsum
model-index:
- name: pegasus-samsum
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. -->
# pegasus-samsum
This ... |
f00d/Multilingual-MiniLM-L12-H384-MLM-finetuned-wikipedia_bn | e25afa200bb1430752ebd9b011cdbd872a956f81 | 2022-07-08T11:34:38.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | fill-mask | false | f00d | null | f00d/Multilingual-MiniLM-L12-H384-MLM-finetuned-wikipedia_bn | 29 | null | transformers | 7,291 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: Multilingual-MiniLM-L12-H384-MLM-finetuned-wikipedia_bn
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 co... |
kuttersn/gpt2-finetuned-redditComments | 8bff8fe467fb6a261b365ed99fe7cd5138196005 | 2022-07-14T01:38:25.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-generation | false | kuttersn | null | kuttersn/gpt2-finetuned-redditComments | 29 | null | transformers | 7,292 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: gpt2-finetuned-redditComments
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. -->
# gpt2-... |
nvidia/stt_es_conformer_transducer_large | e62ef7c0d82c1e50513e0db40e751fc328c08f7e | 2022-07-13T17:39:38.000Z | [
"nemo",
"es",
"dataset:Fisher",
"dataset:VoxPopuli",
"dataset:facebook/multilingual_librispeech",
"dataset:mozilla-foundation/common_voice_7_0",
"arxiv:2005.08100",
"automatic-speech-recognition",
"speech",
"audio",
"Transducer",
"Conformer",
"Transformer",
"pytorch",
"NeMo",
"hf-asr-l... | automatic-speech-recognition | false | nvidia | null | nvidia/stt_es_conformer_transducer_large | 29 | null | nemo | 7,293 | ---
language:
- es
library_name: nemo
datasets:
- Fisher
- VoxPopuli
- facebook/multilingual_librispeech
- mozilla-foundation/common_voice_7_0
thumbnail: null
tags:
- automatic-speech-recognition
- speech
- audio
- Transducer
- Conformer
- Transformer
- pytorch
- NeMo
- hf-asr-leaderboard
license: cc-by-4.0
model-inde... |
domenicrosati/t5-paraphrase-paws-msrp-opinosis-finetuned-parasci | afe89949a269ace083eab9c999425806a1331c7b | 2022-07-15T16:24:38.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"paraphrasing",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | domenicrosati | null | domenicrosati/t5-paraphrase-paws-msrp-opinosis-finetuned-parasci | 29 | null | transformers | 7,294 | ---
license: apache-2.0
tags:
- paraphrasing
- generated_from_trainer
model-index:
- name: t5-paraphrase-paws-msrp-opinosis-finetuned-parasci
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, th... |
Team-PIXEL/pixel-base-finetuned-mnli | 77bd58a2f15e48da12d530c5e046c034fce0dc15 | 2022-07-15T02:42:53.000Z | [
"pytorch",
"pixel",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | Team-PIXEL | null | Team-PIXEL/pixel-base-finetuned-mnli | 29 | null | transformers | 7,295 | ---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
model-index:
- name: pixel-base-finetuned-mnli
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
... |
domenicrosati/pegasus-paraphrase-finetuned-parasci | 53567a767682328951d08f37ed6026a3a0e0f851 | 2022-07-17T12:07:15.000Z | [
"pytorch",
"tensorboard",
"pegasus",
"text2text-generation",
"transformers",
"paraphrasing",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | domenicrosati | null | domenicrosati/pegasus-paraphrase-finetuned-parasci | 29 | null | transformers | 7,296 | ---
tags:
- paraphrasing
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-paraphrase-finetuned-parasci
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 co... |
google/ncsnpp-ffhq-256 | 3a2a14b6226883d6ce5458738898d989dcc343eb | 2022-07-21T15:00:00.000Z | [
"diffusers",
"arxiv:2011.13456",
"pytorch",
"unconditional-image-generation",
"license:apache-2.0"
] | unconditional-image-generation | false | google | null | google/ncsnpp-ffhq-256 | 29 | null | diffusers | 7,297 | ---
license: apache-2.0
tags:
- pytorch
- diffusers
- unconditional-image-generation
---
# Score-Based Generative Modeling through Stochastic Differential Equations (SDE)
**Paper**: [Score-Based Generative Modeling through Stochastic Differential Equations](https://arxiv.org/abs/2011.13456)
**Authors**: Yang Song, J... |
adit94/question_roi | 28b2950bcd3368e317a5ad51dccf3d6f6178e896 | 2022-07-24T00:43:37.000Z | [
"pytorch",
"detr",
"object-detection",
"transformers"
] | object-detection | false | adit94 | null | adit94/question_roi | 29 | null | transformers | 7,298 | Entry not found |
adamnik/bert-causality-baseline | fa82699976d8b47f30641e32c781d993cad1b80f | 2022-07-24T15:21:15.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:mit"
] | text-classification | false | adamnik | null | adamnik/bert-causality-baseline | 29 | null | transformers | 7,299 | ---
license: mit
---
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.