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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
MilaNLProc/hate-ita | e86867f77ebeae746f68907f76506d8a172e4424 | 2022-07-07T15:32:29.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"it",
"arxiv:2104.12250",
"transformers",
"text classification",
"abusive language",
"hate speech",
"offensive language",
"license:mit"
] | text-classification | false | MilaNLProc | null | MilaNLProc/hate-ita | 56 | 1 | transformers | 5,800 | ---
language: it
license: mit
tags:
- text classification
- abusive language
- hate speech
- offensive language
widget:
- text: "Ci sono dei bellissimi capibara!"
example_title: "Hate Speech Classification 1"
- text: "Sei una testa di cazzo!!"
example_title: "Hate Speech Classification 2"
- text: "Ti odio!"
exam... |
BNZSA/distilbert-base-uncased-country-NER-address | 9f7f7600e4e7e90a28cd5a993842b01cad5f7259 | 2022-06-10T11:02:34.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"license:gpl-3.0"
] | text-classification | false | BNZSA | null | BNZSA/distilbert-base-uncased-country-NER-address | 56 | null | transformers | 5,801 | ---
license: gpl-3.0
---
|
microsoft/swinv2-tiny-patch4-window8-256 | 2b979ac403df19f72443cd151e9e957842eb9645 | 2022-07-07T14:18:14.000Z | [
"pytorch",
"swinv2",
"transformers"
] | null | false | microsoft | null | microsoft/swinv2-tiny-patch4-window8-256 | 56 | null | transformers | 5,802 | Entry not found |
fujiki/t5-efficient-xl-nl6-en2ja | 87dd3369f46ec03661da5a33be63a638f82a6c39 | 2022-07-04T03:48:38.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | fujiki | null | fujiki/t5-efficient-xl-nl6-en2ja | 56 | null | transformers | 5,803 | ---
license: afl-3.0
---
|
tezign/Erlangshen-Sentiment-FineTune | 23b9777a3d2355fdcfb06dea2d7b2a3e965746a4 | 2022-07-14T09:36:39.000Z | [
"pytorch",
"bert",
"text-classification",
"zh",
"transformers",
"sentiment-analysis"
] | text-classification | false | tezign | null | tezign/Erlangshen-Sentiment-FineTune | 56 | null | transformers | 5,804 | ---
language: zh
tags:
- sentiment-analysis
- pytorch
widget:
- text: "房间非常非常小，内窗，特别不透气，因为夜里走廊灯光是亮的，内窗对着走廊，窗帘又不能完全拉死，怎么都会有一道光射进来。"
- text: "尽快有洗衣房就好了。"
- text: "很好，干净整洁，交通方便。"
- text: "干净整洁很好"
---
# Note
BERT based sentiment analysis, finetune based on https://huggingface.co/IDEA-CCNL/Erlangshen-Roberta-330M-Sentimen... |
ai4bharat/indicwav2vec-hindi | e746fa3e8de3f6629b9ded29d9c1c565c566f3db | 2022-07-27T20:31:31.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hi",
"arxiv:2006.11477",
"transformers",
"audio",
"speech",
"asr",
"license:apache-2.0"
] | automatic-speech-recognition | false | ai4bharat | null | ai4bharat/indicwav2vec-hindi | 56 | null | transformers | 5,805 | ---
language: hi
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- wav2vec2
- asr
license: apache-2.0
---
# IndicWav2Vec-Hindi
This is a [Wav2Vec2](https://arxiv.org/abs/2006.11477) style ASR model trained in [fairseq](https://github.com/facebookresearch/fairseq) and ported to Hugging Face.... |
ArBert/albert-base-v2-finetuned-ner | d95acee469161c82720bc85773685f8a8e9c60ac | 2022-02-03T14:26:33.000Z | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | ArBert | null | ArBert/albert-base-v2-finetuned-ner | 55 | 1 | transformers | 5,806 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: albert-base-v2-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
... |
Bagus/wav2vec2-xlsr-greek-speech-emotion-recognition | cbe6ba0246652df652d2ad88baa1cad77f180aa4 | 2021-10-20T05:38:41.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"el",
"dataset:aesdd",
"transformers",
"audio",
"audio-classification",
"speech",
"license:apache-2.0"
] | audio-classification | false | Bagus | null | Bagus/wav2vec2-xlsr-greek-speech-emotion-recognition | 55 | null | transformers | 5,807 | ---
language: el
datasets:
- aesdd
tags:
- audio
- audio-classification
- speech
license: apache-2.0
---
~~~
# requirement packages
!pip install git+https://github.com/huggingface/datasets.git
!pip install git+https://github.com/huggingface/transformers.git
!pip install torchaudio
!pip install librosa
!git clone http... |
Finnish-NLP/electra-base-discriminator-finnish | cea3059be27d2b56aeae92e58e92b8fbbfd62f44 | 2022-06-13T16:14:27.000Z | [
"pytorch",
"tensorboard",
"electra",
"pretraining",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"transformers",
"finnish",
"license:apache-2.0"
] | null | false | Finnish-NLP | null | Finnish-NLP/electra-base-discriminator-finnish | 55 | 1 | transformers | 5,808 | ---
language:
- fi
license: apache-2.0
tags:
- finnish
- electra
datasets:
- Finnish-NLP/mc4_fi_cleaned
- wikipedia
---
# ELECTRA for Finnish
Pretrained ELECTRA model on Finnish language using a replaced token detection (RTD) objective. ELECTRA was introduced in
[this paper](https://openreview.net/pdf?id=r1xMH1BtvB)... |
Helsinki-NLP/opus-mt-en-tw | 1bb6b4f687e20670094c8ac30048119e2a2ce972 | 2021-09-09T21:40:21.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"tw",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-tw | 55 | null | transformers | 5,809 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-tw
* source languages: en
* target languages: tw
* OPUS readme: [en-tw](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-tw/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
KoichiYasuoka/roberta-base-english-upos | d0917602cc2cd705ffd94685e0206c3b3a83966a | 2022-02-16T03:13:03.000Z | [
"pytorch",
"roberta",
"token-classification",
"en",
"dataset:universal_dependencies",
"transformers",
"english",
"pos",
"dependency-parsing",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/roberta-base-english-upos | 55 | null | transformers | 5,810 | ---
language:
- "en"
tags:
- "english"
- "token-classification"
- "pos"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
---
# roberta-base-english-upos
## Model Description
This is a RoBERTa model pre-trained with [UD_English](https://universal... |
amitness/nepbert | 929fb302536e823a8ec7a5c6c65ff01f99845f70 | 2021-09-21T16:00:56.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"ne",
"dataset:cc100",
"transformers",
"nepali-laguage-model",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | amitness | null | amitness/nepbert | 55 | null | transformers | 5,811 | ---
language:
- ne
thumbnail:
tags:
- roberta
- nepali-laguage-model
license: mit
datasets:
- cc100
widget:
- text: तिमीलाई कस्तो <mask>?
---
# nepbert
## Model description
Roberta trained from scratch on the Nepali CC-100 dataset with 12 million sentences.
## Intended uses & limitations
#### How to use
```python... |
google/tapas-large-finetuned-tabfact | fdefc8e307f981aba4b8eb772d0f7a884ed24770 | 2021-11-29T13:21:34.000Z | [
"pytorch",
"tf",
"tapas",
"text-classification",
"en",
"dataset:tab_fact",
"arxiv:2010.00571",
"arxiv:2004.02349",
"transformers",
"sequence-classification",
"license:apache-2.0"
] | text-classification | false | google | null | google/tapas-large-finetuned-tabfact | 55 | null | transformers | 5,812 | ---
language: en
tags:
- tapas
- sequence-classification
license: apache-2.0
datasets:
- tab_fact
---
# TAPAS large model fine-tuned on Tabular Fact Checking (TabFact)
This model has 2 versions which can be used. The latest version, which is the default one, corresponds to the `tapas_tabfact_inter_masklm_large_rese... |
indonesian-nlp/gpt2 | 0995ba6b42b12180954cdc68b7e08fa7bc6daae6 | 2022-02-15T17:31:03.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"id",
"transformers"
] | text-generation | false | indonesian-nlp | null | indonesian-nlp/gpt2 | 55 | 1 | transformers | 5,813 | ---
language: id
widget:
- text: "Sewindu sudah kita tak berjumpa, rinduku padamu sudah tak terkira."
---
# GPT2-small-indonesian
This is a pretrained model on Indonesian language using a causal language modeling (CLM) objective, which was first
introduced in [this paper](https://d4mucfpksywv.cloudfront.net/better-l... |
kornosk/bert-election2020-twitter-stance-biden | d74e980707975d786a5bda3528cce403edddb804 | 2022-05-02T22:59:23.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"en",
"transformers",
"twitter",
"stance-detection",
"election2020",
"politics",
"license:gpl-3.0"
] | text-classification | false | kornosk | null | kornosk/bert-election2020-twitter-stance-biden | 55 | 2 | transformers | 5,814 | ---
language: "en"
tags:
- twitter
- stance-detection
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Election 2020 for Stance Detection towards Joe Biden (f-BERT)
Pre-trained weights for **f-BERT** in [Knowledge Enhance Masked Language Model for Stance Detection](https://www.aclweb.... |
monologg/koelectra-small-finetuned-sentiment | 1dd80335c9f7861d2bdc01c7712301c38a23b6f7 | 2020-05-23T09:19:14.000Z | [
"pytorch",
"tflite",
"electra",
"text-classification",
"transformers"
] | text-classification | false | monologg | null | monologg/koelectra-small-finetuned-sentiment | 55 | null | transformers | 5,815 | Entry not found |
philschmid/distilroberta-base-ner-wikiann-conll2003-3-class | cc95e1ad7cb7ca6f393e1c4bf2b44aab8ab23b4a | 2021-05-26T14:13:00.000Z | [
"pytorch",
"roberta",
"token-classification",
"dataset:wikiann-conll2003",
"transformers",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | philschmid | null | philschmid/distilroberta-base-ner-wikiann-conll2003-3-class | 55 | 2 | transformers | 5,816 | ---
license: apache-2.0
tags:
- token-classification
datasets:
- wikiann-conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilroberta-base-ner-wikiann-conll2003-3-class
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann-... |
mindee/fasterrcnn_mobilenet_v3_large_fpn | 36909b9a601bb45bf3154ca176c1cb63477c54b3 | 2022-03-11T09:33:24.000Z | [
"pytorch",
"dataset:docartefacts",
"arxiv:1506.01497",
"doctr",
"object-detection",
"license:apache-2.0"
] | object-detection | false | mindee | null | mindee/fasterrcnn_mobilenet_v3_large_fpn | 55 | 3 | doctr | 5,817 | ---
license: apache-2.0
tags:
- object-detection
- pytorch
library_name: doctr
datasets:
- docartefacts
---
# Faster-RCNN model
Pretrained on [DocArtefacts](https://mindee.github.io/doctr/datasets.html#doctr.datasets.DocArtefacts). The Faster-RCNN architecture was introduced in [this paper](https://arxi... |
ali2066/bert-base-uncased_token_itr0_2e-05_all_01_03_2022-04_40_10 | cc565eaf6b3a035b0ee9155e6073a36ad9cef388 | 2022-03-01T03:43:42.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | ali2066 | null | ali2066/bert-base-uncased_token_itr0_2e-05_all_01_03_2022-04_40_10 | 55 | null | transformers | 5,818 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-uncased_token_itr0_2e-05_all_01_03_2022-04_40_10
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should... |
ali2066/bert-base-uncased_token_itr0_0.0001_all_01_03_2022-04_48_27 | ac80b1a3ff58c13dc4405237763579c509406dea | 2022-03-01T03:51:48.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | ali2066 | null | ali2066/bert-base-uncased_token_itr0_0.0001_all_01_03_2022-04_48_27 | 55 | null | transformers | 5,819 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-uncased_token_itr0_0.0001_all_01_03_2022-04_48_27
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
shoul... |
Finnish-NLP/wav2vec2-xlsr-1b-finnish-lm-v2 | b40472575e770ed814410816176942aab327c602 | 2022-05-26T12:49:05.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fi",
"dataset:mozilla-foundation/common_voice_7_0",
"arxiv:2111.09296",
"transformers",
"finnish",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Finnish-NLP | null | Finnish-NLP/wav2vec2-xlsr-1b-finnish-lm-v2 | 55 | 1 | transformers | 5,820 | ---
license: apache-2.0
language: fi
metrics:
- wer
- cer
tags:
- automatic-speech-recognition
- fi
- finnish
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: wav2vec2-xlsr-1b-finnish-lm-v2
results:
- task:
name: Automatic... |
hamzab/roberta-fake-news-classification | 331696d6bd2286f88fe0ec364b3e31ef0b7042b3 | 2022-04-07T13:25:28.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:fake-and-real-news-dataset on kaggle",
"transformers",
"classification",
"license:mit"
] | text-classification | false | hamzab | null | hamzab/roberta-fake-news-classification | 55 | null | transformers | 5,821 | ---
license: mit
widget:
- text: "Some ninja attacked the White House."
example_title: "Fake example 1"
language:
- en
tags:
- classification
datasets:
- "fake-and-real-news-dataset on kaggle"
---
## Overview
The model is a `roberta-base` fine-tuned on [fake-and-real-news-dataset](https://www.kaggle.com/datasets/clme... |
NCAI/NCAI-BERT | 889c339b60ab295438ec9c2d6df001c0895f0209 | 2022-04-13T11:27:59.000Z | [
"pytorch",
"lean_albert",
"transformers"
] | null | false | NCAI | null | NCAI/NCAI-BERT | 55 | null | transformers | 5,822 | Entry not found |
prithivida/bert-for-patents-64d | a337ab997cdb5f9cbf9fc18568e5cd254cc2c1c4 | 2022-06-29T07:47:23.000Z | [
"pytorch",
"tf",
"bert",
"feature-extraction",
"en",
"transformers",
"masked-lm",
"license:apache-2.0"
] | feature-extraction | false | prithivida | null | prithivida/bert-for-patents-64d | 55 | 2 | transformers | 5,823 | ---
language:
- en
tags:
- masked-lm
- pytorch
pipeline-tag: "fill-mask"
mask-token: "[MASK]"
widget:
- text: "The present [MASK] provides a torque sensor that is small and highly rigid and for which high production efficiency is possible."
- text: "The present invention relates to [MASK] accessories and pertains pa... |
abd-1999/autotrain-bbc-news-summarization-694821095 | 9e36cfeccfe662df7f11b6dcd932859fab347419 | 2022-04-03T09:25:08.000Z | [
"pytorch",
"t5",
"text2text-generation",
"unk",
"dataset:abd-1999/autotrain-data-bbc-news-summarization",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | abd-1999 | null | abd-1999/autotrain-bbc-news-summarization-694821095 | 55 | 1 | transformers | 5,824 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- abd-1999/autotrain-data-bbc-news-summarization
co2_eq_emissions: 2313.4037079026934
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 694821095
- CO2 Emissions (in grams): 2313.4037079026934
## Validation ... |
AnReu/albert-for-math-ar-base-ft | 2ddcf162ed80099933edeb0f41bf653f1010900a | 2022-05-30T13:27:05.000Z | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | false | AnReu | null | AnReu/albert-for-math-ar-base-ft | 55 | 1 | transformers | 5,825 | # ALBERT for Math AR
This model is further pre-trained on the Mathematics StackExchange questions and answers. It is based on Albert base v2 and uses the same tokenizer. In addition to pre-training the model was finetuned on Math Question Answer Retrieval. The sequence classification head is trained to output a releva... |
Graphcore/deberta-base-squad | f87e807b8a577d2270785935fb4c2285d9492dc3 | 2022-06-29T14:22:22.000Z | [
"pytorch",
"tensorboard",
"deberta",
"question-answering",
"dataset:squad",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | Graphcore | null | Graphcore/deberta-base-squad | 55 | 1 | transformers | 5,826 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: deberta-base-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. -->
... |
Alethea/GPT2-chitchat | b8ad66d37acafef9c52597c96684fd9086ad1125 | 2022-04-07T09:44:34.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"license:apache-2.0"
] | conversational | false | Alethea | null | Alethea/GPT2-chitchat | 55 | null | transformers | 5,827 | ---
tags:
- conversational
license: apache-2.0
---
|
hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021 | a2eaa05e4fd69844d93b257139dba7ff591c0eba | 2022-04-09T11:33:51.000Z | [
"pytorch",
"roberta",
"text-classification",
"dataset:EXIST Dataset",
"transformers",
"license:apache-2.0",
"model-index"
] | text-classification | false | hackathon-pln-es | null | hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021 | 55 | null | transformers | 5,828 | ---
license: apache-2.0
tags:
-
datasets:
- EXIST Dataset
widget:
- text: "manejas muy bien para ser mujer"
- text: "En temas políticos hombres y mujeres son iguales"
- text: "Los ipad son unos equipos electrónicos"
metrics:
- accuracy
model-index:
- name: twitter_sexismo-finetuned-exist2021
results:
- task:
... |
castorini/monot5-small-msmarco-10k | 77f8e3f7b1eb1afe353aa21a7c3a2fc8feca702e | 2022-05-25T15:08:05.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | castorini | null | castorini/monot5-small-msmarco-10k | 55 | null | transformers | 5,829 | This model is a T5-small reranker fine-tuned on the MS MARCO passage dataset for 10k steps (or 1 epoch).
For more details on how to use it, check the following links:
- [A simple reranking example](https://github.com/castorini/pygaggle#a-simple-reranking-example)
- [Rerank MS MARCO passages](https://github.com/castori... |
ClassCat/gpt2-base-japanese-v2 | 52e719968dcd858c9be4b21975bf0778fb8fd828 | 2022-06-25T15:36:22.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ja",
"dataset:wikipedia",
"dataset:cc100",
"transformers",
"license:cc-by-sa-4.0"
] | text-generation | false | ClassCat | null | ClassCat/gpt2-base-japanese-v2 | 55 | 1 | transformers | 5,830 | ---
language: ja
license: cc-by-sa-4.0
datasets:
- wikipedia
- cc100
widget:
- text: 天気予報によれば明日は
- text: 私の今日の昼飯は
- text: サッカー日本代表はベルギーに
- text: 日本人サッカー選手が W 杯で
---
## GPT2 Japanese base model version 2
### Prerequisites
transformers==4.19.2
### Model architecture
This model uses GPT2 base setttings except vocabul... |
saitishmukhametov/ruGTP2-P | 852755dbce62d6346c2a8446e41c31d0f88c0ac5 | 2022-06-09T05:58:52.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | saitishmukhametov | null | saitishmukhametov/ruGTP2-P | 55 | null | transformers | 5,831 | |
nmcahill/mbti-classifier | 546c5da706171619361cb174ad4e34ab4c7aeb33 | 2022-06-29T20:08:34.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"license:afl-3.0"
] | text-classification | false | nmcahill | null | nmcahill/mbti-classifier | 55 | null | transformers | 5,832 | ---
license: afl-3.0
---
|
mvonwyl/distilbert-base-uncased-imdb | e78f2fa182bace5db1195f3672ebd502c9d35157 | 2022-06-25T17:45:40.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | mvonwyl | null | mvonwyl/distilbert-base-uncased-imdb | 55 | null | transformers | 5,833 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- name... |
Jeevesh8/goog_bert_ft_cola-3 | 025545ca908d8ba581dda1f11fc2d7f411301962 | 2022-06-29T17:31:50.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Jeevesh8 | null | Jeevesh8/goog_bert_ft_cola-3 | 55 | null | transformers | 5,834 | Entry not found |
Evelyn18/distilbert-base-uncased-becasv2-2 | d89961c38b2debfb58fb4d1805c438419ed6e399 | 2022-07-07T03:47:53.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"dataset:becasv2",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | Evelyn18 | null | Evelyn18/distilbert-base-uncased-becasv2-2 | 55 | null | transformers | 5,835 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- becasv2
model-index:
- name: distilbert-base-uncased-becasv2-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove th... |
DL4NLP-Group11/xtremedistil-l6-h256-uncased-squad | 451c05e65c7b1bd2de9e1b6523ecd1c34cb795bc | 2022-07-14T20:08:11.000Z | [
"pytorch",
"bert",
"question-answering",
"en",
"dataset:squad",
"transformers",
"autotrain_compatible"
] | question-answering | false | DL4NLP-Group11 | null | DL4NLP-Group11/xtremedistil-l6-h256-uncased-squad | 55 | null | transformers | 5,836 | ---
language: en
datasets:
- squad
metrics:
- squad
widget:
- text: "Who is the best girl in NieR:Automata?"
context: "2B is a fictional character from the game NieR: Automata. She is considered by many to be best girl of the series, perhaps due to her appealing design (wearing quite a provoking outfit) and to the gr... |
semy/hf-model-full-0 | e1511ab321f6d7d30b5fd88a727b72e825208cf6 | 2022-07-22T07:02:08.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | semy | null | semy/hf-model-full-0 | 55 | null | transformers | 5,837 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: hf-model-full-0
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. -... |
Ian-AI/EalAIn | c5e1c0e027735f3136a43be06c63dddefbc1501e | 2022-07-21T16:47:20.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"license:afl-3.0"
] | text-generation | false | Ian-AI | null | Ian-AI/EalAIn | 55 | null | transformers | 5,838 | ---
license: afl-3.0
---
EalAIn is a DialoGPT model loosely based on "Janet" from the TV Series "The Good Place". This particular instance of Janet is responds to the name "Ealain" and has some knowledge about art. It will, at times, promote me as an AI artist. |
FinanceInc/auditor_sentiment_finetuned | 928330ed06b005d85486e392015aab22710b5a40 | 2022-07-22T21:05:05.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:rajistics/autotrain-data-auditor-sentiment",
"dataset:FinanceInc/auditor_sentiment",
"transformers",
"autotrain",
"DEV",
"model-index",
"co2_eq_emissions"
] | text-classification | false | FinanceInc | null | FinanceInc/auditor_sentiment_finetuned | 55 | null | transformers | 5,839 | ---
language: en
tags:
- autotrain
- DEV
widget:
- text: "Operating profit jumped to EUR 47 million from EUR 6.6 million"
datasets:
- rajistics/autotrain-data-auditor-sentiment
- FinanceInc/auditor_sentiment
co2_eq_emissions: 3.165771608457648
model-index:
- name: auditor_sentiment_finetuned
results:
- task:
... |
sguskin/minilmv2-L6-H384-squad1.1 | b66ba827e1e82f5f51df48b3c31be992d21b68ff | 2022-07-28T07:28:50.000Z | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | sguskin | null | sguskin/minilmv2-L6-H384-squad1.1 | 55 | null | transformers | 5,840 | Entry not found |
BenDavis71/GPT-2-Finetuning-AIRaid | 61b9ea3097434a2536b3a9a0feecde55f040295b | 2021-05-21T09:29:22.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | BenDavis71 | null | BenDavis71/GPT-2-Finetuning-AIRaid | 54 | null | transformers | 5,841 | Entry not found |
Contrastive-Tension/BERT-Base-CT-STSb | 0ca67e247c982bf1b070f72a6e1e30705a7204f7 | 2021-05-18T17:48:15.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | Contrastive-Tension | null | Contrastive-Tension/BERT-Base-CT-STSb | 54 | null | transformers | 5,842 | Entry not found |
Geotrend/distilbert-base-fr-cased | 5430ab9a994b5516c5d6021d4972a29bbbd9c31c | 2021-08-16T13:21:13.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"fr",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/distilbert-base-fr-cased | 54 | 1 | transformers | 5,843 | ---
language: fr
datasets: wikipedia
license: apache-2.0
---
# distilbert-base-fr-cased
We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.
Our versions give exactly the same representations pro... |
Helsinki-NLP/opus-mt-afa-en | 90ea9ea3351bd6eb88f7d7fc3289823cdb8a3abe | 2021-01-18T07:46:45.000Z | [
"pytorch",
"marian",
"text2text-generation",
"so",
"ti",
"am",
"he",
"mt",
"ar",
"afa",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-afa-en | 54 | null | transformers | 5,844 | ---
language:
- so
- ti
- am
- he
- mt
- ar
- afa
- en
tags:
- translation
license: apache-2.0
---
### afa-eng
* source group: Afro-Asiatic languages
* target group: English
* OPUS readme: [afa-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afa-eng/README.md)
* model: transformer
* ... |
Helsinki-NLP/opus-mt-en-iir | c7cf41bec850d260be15e942fbb94ff6ae1f7641 | 2021-01-18T08:09:38.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"bn",
"or",
"gu",
"mr",
"ur",
"hi",
"ps",
"os",
"as",
"si",
"iir",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-iir | 54 | null | transformers | 5,845 | ---
language:
- en
- bn
- or
- gu
- mr
- ur
- hi
- ps
- os
- as
- si
- iir
tags:
- translation
license: apache-2.0
---
### eng-iir
* source group: English
* target group: Indo-Iranian languages
* OPUS readme: [eng-iir](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-iir/README.md)
* m... |
Helsinki-NLP/opus-mt-en_el_es_fi-en_el_es_fi | 8d915c98083ed0dc9f8dfdd2e465f18936fff802 | 2021-09-09T21:40:45.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"el",
"es",
"fi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en_el_es_fi-en_el_es_fi | 54 | 1 | transformers | 5,846 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en_el_es_fi-en_el_es_fi
* source languages: en,el,es,fi
* target languages: en,el,es,fi
* OPUS readme: [en+el+es+fi-en+el+es+fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en+el+es+fi-en+el+es+fi/README.md)
* dataset: opus
* model: t... |
Helsinki-NLP/opus-mt-om-en | 08917ded8bae79f2c459b4be133ec12a8f497315 | 2021-09-10T14:00:02.000Z | [
"pytorch",
"marian",
"text2text-generation",
"om",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-om-en | 54 | null | transformers | 5,847 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-om-en
* source languages: om
* target languages: en
* OPUS readme: [om-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/om-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-sem-sem | 3bc83774049409237ecbdc84779c50d7016b1674 | 2020-08-21T14:42:49.000Z | [
"pytorch",
"marian",
"text2text-generation",
"mt",
"ar",
"he",
"ti",
"am",
"sem",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sem-sem | 54 | null | transformers | 5,848 | ---
language:
- mt
- ar
- he
- ti
- am
- sem
tags:
- translation
license: apache-2.0
---
### sem-sem
* source group: Semitic languages
* target group: Semitic languages
* OPUS readme: [sem-sem](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/sem-sem/README.md)
* model: transformer
* sourc... |
NYTK/sentiment-hts2-hubert-hungarian | 7afdc64bc3fd66174b5ebb068e1fc0870b914903 | 2022-01-26T13:20:21.000Z | [
"pytorch",
"bert",
"text-classification",
"hu",
"transformers",
"license:gpl"
] | text-classification | false | NYTK | null | NYTK/sentiment-hts2-hubert-hungarian | 54 | null | transformers | 5,849 | ---
language:
- hu
tags:
- text-classification
license: gpl
metrics:
- accuracy
widget:
- text: "Jó reggelt! majd küldöm az élményhozókat :)."
---
# Hungarian Sentence-level Sentiment Analysis model with huBERT
For further models, scripts and details, see [our repository](https://github.com/nytud/sentiment-analy... |
SetFit/deberta-v3-large__sst2__train-8-2 | 0843471896f06585114d90510408ce32e9064962 | 2022-02-10T08:35:53.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | SetFit | null | SetFit/deberta-v3-large__sst2__train-8-2 | 54 | null | transformers | 5,850 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-8-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comm... |
cankeles/DPTNet_WHAMR_enhsingle_16k | a8366a7337463c149b151a3152cab84bceafb3a6 | 2022-02-17T19:53:06.000Z | [
"pytorch",
"dataset:Libri1Mix",
"dataset:enh_single",
"asteroid",
"audio",
"DPTNet",
"audio-to-audio",
"license:cc-by-sa-4.0"
] | audio-to-audio | false | cankeles | null | cankeles/DPTNet_WHAMR_enhsingle_16k | 54 | 1 | asteroid | 5,851 | ---
tags:
- asteroid
- audio
- DPTNet
- audio-to-audio
datasets:
- Libri1Mix
- enh_single
license: cc-by-sa-4.0
---
## Asteroid model `cankeles/DPTNet_WHAMR_enhsignle_16k`
Description:
This model was trained by M. Can Keleş using the librimix recipe in [Asteroid](https://github.com/asteroid-team/asteroid).
It was tra... |
dbmdz/bert-base-historic-dutch-cased | 0a7074b8d8d9f737286c7e3ab44ced1982f08cd3 | 2021-12-13T16:31:17.000Z | [
"pytorch",
"tf",
"tensorboard",
"bert",
"fill-mask",
"dutch",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | dbmdz | null | dbmdz/bert-base-historic-dutch-cased | 54 | null | transformers | 5,852 | ---
language: dutch
license: mit
widget:
- text: "de [MASK] vau Financien, in hec vorige jaar, da inkomswi"
---
# Language Model for Historic Dutch
In this repository we open source a language model for Historic Dutch, trained on the
[Delpher Corpus](https://www.delpher.nl/over-delpher/delpher-open-krantenarchief/do... |
efederici/text2tags | 5441fe47bfbfea04e556fd043baa988b79b78081 | 2022-05-26T10:51:47.000Z | [
"pytorch",
"t5",
"text2text-generation",
"it",
"transformers",
"summarization",
"tags",
"Italian",
"autotrain_compatible"
] | summarization | false | efederici | null | efederici/text2tags | 54 | null | transformers | 5,853 | ---
language:
- it
tags:
- summarization
- tags
- Italian
inference:
parameters:
do_sample: False
min_length: 0
widget:
- text: "Nel 1924 la scrittrice Virginia Woolf affrontò nel saggio Mr Bennett e Mrs Brown il tema della costruzione e della struttura del romanzo, genere all’epoca considerato in declin... |
flax-community/gpt-neo-125M-apps | 9cf90328fea0748637cb8b1cadc205ff94fb99b5 | 2021-09-22T08:25:34.000Z | [
"pytorch",
"jax",
"gpt_neo",
"text-generation",
"en",
"python",
"dataset:apps",
"arxiv:2107.03374",
"transformers",
"code_synthesis",
"license:mit"
] | text-generation | false | flax-community | null | flax-community/gpt-neo-125M-apps | 54 | null | transformers | 5,854 | ---
language:
- en
- python
license: mit
tags:
- gpt_neo
- code_synthesis
datasets:
- apps
---
# GPT-Neo-125M-APPS
> **Please refer to our new [GitHub Wiki](https://github.com/ncoop57/gpt-code-clippy/wiki) which documents our efforts in detail in creating the open source version of GitHub Copilot**
## Model Descript... |
google/tapas-medium-finetuned-wtq | ab7607cdf73b129a5f14db098fef3a90e280fe92 | 2022-07-14T10:14:59.000Z | [
"pytorch",
"tf",
"tapas",
"table-question-answering",
"en",
"dataset:wikitablequestions",
"arxiv:2004.02349",
"arxiv:2010.00571",
"arxiv:1508.00305",
"transformers",
"license:apache-2.0"
] | table-question-answering | false | google | null | google/tapas-medium-finetuned-wtq | 54 | null | transformers | 5,855 | ---
language: en
tags:
- tapas
- table-question-answering
license: apache-2.0
datasets:
- wikitablequestions
---
# TAPAS medium model fine-tuned on WikiTable Questions (WTQ)
This model has 2 versions which can be used. The default version corresponds to the `tapas_wtq_wikisql_sqa_inter_masklm_medium_reset` checkpoint... |
gpt2-adstext/gpt2-adstext | 78f2295bfb2535a1a94e89aace15f07845d6fb7c | 2021-05-21T16:17:48.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | gpt2-adstext | null | gpt2-adstext/gpt2-adstext | 54 | null | transformers | 5,856 | Entry not found |
henryu-lin/t5-3b-samsum-deepspeed | 7feb6eb6ffb6218e7fb394c0f445bb946c255dc4 | 2021-07-08T06:45:41.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:samsum",
"transformers",
"azureml",
"summarization",
"deepspeed",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | henryu-lin | null | henryu-lin/t5-3b-samsum-deepspeed | 54 | null | transformers | 5,857 | ---
language: en
tags:
- azureml
- t5
- summarization
- deepspeed
license: apache-2.0
datasets:
- samsum
model-index:
- name: t5-3b-samsum-deepspeed
results:
- task:
name: Abstractive Text Summarization
type: abstractive-text-summarization
dataset:
name: "SAMSum Corpus: A Human-annotated Dial... |
inywer/DialoGPT-small-awazimuruk | 9438b947d184d8e46981bf8a7c5e842983e9aabd | 2021-10-05T21:39:04.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | inywer | null | inywer/DialoGPT-small-awazimuruk | 54 | null | transformers | 5,858 | ---
tags:
- conversational
---
# awazimuruk DialoGPT Model |
kornosk/bert-political-election2020-twitter-mlm | 674022950a54308a1cbf9394c80056b59b100aed | 2022-05-10T04:45:45.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"en",
"transformers",
"twitter",
"masked-token-prediction",
"election2020",
"politics",
"license:gpl-3.0",
"autotrain_compatible"
] | fill-mask | false | kornosk | null | kornosk/bert-political-election2020-twitter-mlm | 54 | 2 | transformers | 5,859 | ---
language: "en"
tags:
- twitter
- masked-token-prediction
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Political Election 2020
Pre-trained weights for [Knowledge Enhance Masked Language Model for Stance Detection](https://www.aclweb.org/anthology/2021.naacl-main.376), NAACL 202... |
navteca/tapas-large-finetuned-wtq | cd7feb8b379e08187f8927debec340fa05ca3715 | 2021-08-09T12:46:26.000Z | [
"pytorch",
"tapas",
"table-question-answering",
"en",
"dataset:sqa",
"dataset:wikisql",
"dataset:wtq",
"arxiv:2004.02349",
"transformers",
"license:mit"
] | table-question-answering | false | navteca | null | navteca/tapas-large-finetuned-wtq | 54 | null | transformers | 5,860 | ---
datasets:
- sqa
- wikisql
- wtq
language: en
license: mit
pipeline_tag: table-question-answering
tags:
- tapas
- table-question-answering
---
# TAPAS large model fine-tuned on WikiTable Questions (WTQ)
TAPAS is a BERT-like transformers model pretrained on a large corpus of English data from Wikipedia in a self-su... |
pparasurama/raceBERT-ethnicity | babd5c78b799aaac6346b7d934b510674ae27d63 | 2021-11-09T20:42:29.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | pparasurama | null | pparasurama/raceBERT-ethnicity | 54 | 1 | transformers | 5,861 | Entry not found |
speechbrain/asr-crdnn-commonvoice-it | 5eef440c7208564abdc2a55cabd61ca824a4ea4e | 2021-11-30T00:37:30.000Z | [
"it",
"dataset:common_voice",
"arxiv:2106.04624",
"speechbrain",
"automatic-speech-recognition",
"CTC",
"Attention",
"pytorch",
"license:apache-2.0"
] | automatic-speech-recognition | false | speechbrain | null | speechbrain/asr-crdnn-commonvoice-it | 54 | null | speechbrain | 5,862 | ---
language: "it"
thumbnail:
tags:
- automatic-speech-recognition
- CTC
- Attention
- pytorch
- speechbrain
license: "apache-2.0"
datasets:
- common_voice
metrics:
- wer
- cer
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scro... |
uer/bart-chinese-4-768-cluecorpussmall | 9736dc35093a9815a4c3fdb254b8a0f22b793f73 | 2021-10-08T14:46:07.000Z | [
"pytorch",
"bart",
"text2text-generation",
"Chinese",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | uer | null | uer/bart-chinese-4-768-cluecorpussmall | 54 | 1 | transformers | 5,863 | ---
language: Chinese
datasets: CLUECorpusSmall
widget:
- text: "作为电子[MASK]的平台，京东绝对是领先者。如今的刘强[MASK]已经是身价过[MASK]的老板。"
---
# Chinese BART
## Model description
This model is pre-trained by [UER-py](https://arxiv.org/abs/1909.05658).
## How to use
You can use this model directly with a pipeline for text2text genera... |
w11wo/sundanese-gpt2-base | fe065ade05b3b0a104e7ec5799bc0bf306feaa7d | 2022-02-26T13:15:02.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"su",
"dataset:mc4",
"dataset:cc100",
"dataset:oscar",
"dataset:wikipedia",
"transformers",
"sundanese-gpt2-base",
"license:mit"
] | text-generation | false | w11wo | null | w11wo/sundanese-gpt2-base | 54 | 1 | transformers | 5,864 | ---
language: su
tags:
- sundanese-gpt2-base
license: mit
datasets:
- mc4
- cc100
- oscar
- wikipedia
widget:
- text: "Nami abdi Budi, ti Indonésia"
---
## Sundanese GPT-2 Base
Sundanese GPT-2 Base is a causal language model based on the [OpenAI GPT-2](https://cdn.openai.com/better-language-models/languag... |
wietsedv/bert-base-dutch-cased-finetuned-lassysmall-pos | 3b28296bc7d0f1d5c2099279cff7462b64458117 | 2021-05-20T09:08:08.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | wietsedv | null | wietsedv/bert-base-dutch-cased-finetuned-lassysmall-pos | 54 | null | transformers | 5,865 | Entry not found |
IIC/roberta-base-spanish-sqac | 642575580b06c3e71f56bc520b610451b220ab8c | 2022-04-02T15:11:03.000Z | [
"pytorch",
"roberta",
"question-answering",
"es",
"dataset:PlanTL-GOB-ES/SQAC",
"arxiv:2107.07253",
"transformers",
"model-index",
"autotrain_compatible"
] | question-answering | false | IIC | null | IIC/roberta-base-spanish-sqac | 54 | 1 | transformers | 5,866 | ---
language:
- es
tags:
- question-answering # Example: audio
datasets:
- PlanTL-GOB-ES/SQAC
metrics:
- f1
# Optional. Add this if you want to encode your eval results in a structured way.
model-index:
- name: roberta-base-spanish_sqac
results:
- task:
type: question-answering # Required. Example: automati... |
mary905el/rugpt3large_neuro_chgk | 75a2e2dde695cf432d5933ed485ad7f388e1782a | 2022-04-26T06:34:16.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ru",
"transformers",
"PyTorch",
"Transformers"
] | text-generation | false | mary905el | null | mary905el/rugpt3large_neuro_chgk | 54 | null | transformers | 5,867 | ---
language:
- ru
tags:
- PyTorch
- Transformers
- text-generation
widget:
- text: "Известный человек"
inference:
parameters:
max_length: 60
do_sample: True
temperature: 0.6
no_repeat_ngram_size: 2
---
This is https://huggingface.co/sberbank-ai/rugpt3large_based_on_gpt2 model, fine-tuned on the ques... |
ifrz/wav2vec2-large-xlsr-galician | 0e2118b3fcc822fca186a3a2c2a2253ff7520259 | 2022-07-13T07:15:21.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"gl",
"dataset:OpenSLR 77",
"dataset:mozilla-foundation common_voice_8_0",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | ifrz | null | ifrz/wav2vec2-large-xlsr-galician | 54 | null | transformers | 5,868 | # wav2vec2-large-xlsr-galician
---
language: gl
datasets:
- OpenSLR 77
- mozilla-foundation common_voice_8_0
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Galician wav2vec2-large-xlsr-galician
results:
- task:
name: Speec... |
doc2query/msmarco-portuguese-mt5-base-v1 | c92f7664af7e81c16fccbf45abbf27434e62a1f2 | 2022-04-29T12:08:25.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"pt",
"dataset:unicamp-dl/mmarco",
"arxiv:1904.08375",
"arxiv:2104.08663",
"arxiv:2112.07577",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | doc2query | null | doc2query/msmarco-portuguese-mt5-base-v1 | 54 | 2 | transformers | 5,869 | ---
language: pt
datasets:
- unicamp-dl/mmarco
widget:
- text: "Python é uma linguagem de programação de alto nível, interpretada de script, imperativa, orientada a objetos, funcional, de tipagem dinâmica e forte. Foi lançada por Guido van Rossum em 1991. Atualmente, possui um modelo de desenvolvimento comunitário... |
joaogante/test_audio | d08c0a24b1982bf1f6ee06e87de5f5f178ec7300 | 2022-05-31T11:55:52.000Z | [
"pytorch",
"speech_to_text",
"automatic-speech-recognition",
"fr",
"en",
"dataset:covost2",
"arxiv:2010.05171",
"arxiv:1912.06670",
"arxiv:1904.08779",
"transformers",
"audio",
"speech-translation",
"license:mit"
] | automatic-speech-recognition | false | joaogante | null | joaogante/test_audio | 54 | null | transformers | 5,870 | ---
language:
- fr
- en
datasets:
- covost2
tags:
- audio
- speech-translation
- automatic-speech-recognition
license: mit
pipeline_tag: automatic-speech-recognition
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
... |
north/demo-nynorsk-base | 8954f48e96bc98db66a97d39f87dfa5fca4a6a20 | 2022-05-29T20:09:12.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"no",
"transformers",
"translation",
"license:cc-by-4.0",
"autotrain_compatible"
] | translation | false | north | null | north/demo-nynorsk-base | 54 | null | transformers | 5,871 | ---
language: no
tags:
- translation
widget:
- text: "En av de vanskeligste oppgavene når man oversetter fra bokmål til nynorsk, er å passe på at man bruker riktige pronomen. Man kan for eksempel si at man eier en bil og at den er rød."
- text: "Arbeidsmiljøloven har også som formål å sikre et arbeidsmiljø som gir grun... |
tinkoff-ai/response-toxicity-classifier-base | 9f849fade5bfa7c027ec968cec7afbe4ad652107 | 2022-07-22T05:43:10.000Z | [
"pytorch",
"bert",
"text-classification",
"ru",
"transformers",
"russian",
"pretraining",
"conversational",
"license:mit"
] | text-classification | false | tinkoff-ai | null | tinkoff-ai/response-toxicity-classifier-base | 54 | null | transformers | 5,872 | ---
language: ["ru"]
tags:
- russian
- pretraining
- conversational
license: mit
widget:
- text: "[CLS] привет [SEP] привет! [SEP] как дела? [RESPONSE_TOKEN] норм"
example_title: "Dialog example 1"
- text: "[CLS] привет [SEP] привет! [SEP] как дела? [RESPONSE_TOKEN] ты *****"
example_title: "Dialog example 2"
---
... |
nytimesrd/paraphrase-MiniLM-L6-v2 | 8aa77c41847a7ce070af41af6f0cf838b08d1969 | 2022-06-06T17:21:31.000Z | [
"pytorch",
"bert",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | nytimesrd | null | nytimesrd/paraphrase-MiniLM-L6-v2 | 54 | null | sentence-transformers | 5,873 | ---
pipeline_tag: feature-extraction
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/paraphrase-MiniLM-L6-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense... |
Hamzaaa/wav2vec2-base-finetuned-Tess | 505a1dc87f18d6a21e6461956c08fe4bea579210 | 2022-07-13T16:36:11.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"transformers"
] | audio-classification | false | Hamzaaa | null | Hamzaaa/wav2vec2-base-finetuned-Tess | 54 | null | transformers | 5,874 | Entry not found |
Danish-summarisation/dansum-mt5-base-v1 | 3be4ac3aa9c032fd41c4d272165357635b164d09 | 2022-07-07T12:06:30.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"da",
"arxiv:1804.11283",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | Danish-summarisation | null | Danish-summarisation/dansum-mt5-base-v1 | 54 | null | transformers | 5,875 | ---
language:
- da
tags:
- summarization
widget:
- text: "De strejkende SAS-piloter melder sig nu klar til gøre en undtagelse fra strejken for at hente strandede chartergæster hjem fra flere ferieområder.
Undtagelsen skal gælde nogle uger frem, men piloterne vil under ingen omstændigheder have nye gæster med sig ne... |
sam34738/bert-hinglish | 42532573f07e417493228ed8607c8305d81ee854 | 2022-07-08T00:00:58.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | sam34738 | null | sam34738/bert-hinglish | 54 | null | transformers | 5,876 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-hinglish
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. -->
# bert-hinglish
This m... |
simecek/DNADebertaBPE10k | b8fec7d20681a8860542a645eadd01a28b4c0b31 | 2022-07-15T06:43:43.000Z | [
"pytorch",
"tensorboard",
"deberta",
"fill-mask",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | simecek | null | simecek/DNADebertaBPE10k | 54 | null | transformers | 5,877 | ---
tags:
- generated_from_trainer
model-index:
- name: DNADebertaBPE10k
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. -->
# DNADebertaBPE10k
This model is a fine... |
hassan4830/distil-bert-uncased-finetuned-english | c67f0b49bc66d1e758e35b5449b416c367ae80e5 | 2022-07-21T14:29:38.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"license:afl-3.0"
] | text-classification | false | hassan4830 | null | hassan4830/distil-bert-uncased-finetuned-english | 54 | 1 | transformers | 5,878 | ---
license: afl-3.0
---
distilbert Binary Text Classifier
This distilbert based text classification model trained on imdb dataset performs binary sentiment classification on any given sentence.
The model has been fine tuned for better results in manageable time frames.
LABEL0 - Negative
LABEL1 - Positive |
AlekseyDorkin/xlm-roberta-en-ru-emoji | dc5f644204d24cfde0619a74ce5b729edb014fe4 | 2021-11-15T18:08:03.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"en",
"ru",
"dataset:tweet_eval",
"transformers"
] | text-classification | false | AlekseyDorkin | null | AlekseyDorkin/xlm-roberta-en-ru-emoji | 53 | null | transformers | 5,879 | ---
language:
- en
- ru
datasets:
- tweet_eval
model_index:
- name: xlm-roberta-en-ru-emoji
results:
- task:
name: Sentiment Analysis
type: sentiment-analysis
dataset:
name: Tweet Eval
type: tweet_eval
args: emoji
widget:
- text: "Отлично!"
- text: "Awesome!"
- text: "l... |
CenIA/albert-xxlarge-spanish-finetuned-qa-mlqa | f54896f961e419cb0dcb9e08d9b741448777d79e | 2022-02-14T16:59:14.000Z | [
"pytorch",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | CenIA | null | CenIA/albert-xxlarge-spanish-finetuned-qa-mlqa | 53 | null | transformers | 5,880 | Entry not found |
DTAI-KULeuven/mbert-corona-tweets-belgium-topics | 92031a69cf948386540c9429199162b7c0b4fd98 | 2021-05-18T18:07:37.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"multilingual",
"arxiv:2104.09947",
"transformers",
"Dutch",
"French",
"English",
"Tweets",
"Topic classification"
] | text-classification | false | DTAI-KULeuven | null | DTAI-KULeuven/mbert-corona-tweets-belgium-topics | 53 | null | transformers | 5,881 | ---
language: "multilingual"
tags:
- Dutch
- French
- English
- Tweets
- Topic classification
widget:
- text: "I really can't wait for this lockdown to be over and go back to waking up early."
---
# Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
[Blog post »](https://people... |
Davlan/distilbert-base-multilingual-cased-masakhaner | 319d81df340d7006aeaafd5ff30f0ff1e47abdeb | 2022-06-27T10:57:26.000Z | [
"pytorch",
"tf",
"distilbert",
"token-classification",
"ha",
"ig",
"rw",
"lg",
"luo",
"pcm",
"sw",
"wo",
"yo",
"multilingual",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | false | Davlan | null | Davlan/distilbert-base-multilingual-cased-masakhaner | 53 | 1 | transformers | 5,882 | Hugging Face's logo
---
language:
- ha
- ig
- rw
- lg
- luo
- pcm
- sw
- wo
- yo
- multilingual
datasets:
- masakhaner
---
# bert-base-multilingual-cased-masakhaner
## Model description
**distilbert-base-multilingual-cased-masakhaner** is the first **Named Entity Recognition** model for 9 African languages (Hausa, I... |
JonatanGk/roberta-base-bne-finetuned-cyberbullying-spanish | 39adc1e0e25c86c3912534ad2eba4ec0084779ba | 2021-10-10T09:47:45.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"es",
"transformers",
"spanish"
] | text-classification | false | JonatanGk | null | JonatanGk/roberta-base-bne-finetuned-cyberbullying-spanish | 53 | 3 | transformers | 5,883 | ---
language: es
tags:
- "spanish"
metrics:
- accuracy
widget:
- text: "Eres mas pequeño que un pitufo!"
- text: "Eres muy feo!"
- text: "Odio tu forma de hablar!"
- text: "Eres tan fea que cuando eras pequeña te echaban de comer por debajo de la puerta."
---
# roberta-base-bne-finetuned-ciberbullying-spanish
Th... |
TransQuest/microtransquest-en_de-it-nmt | 61842e882af256b14dde831809b66961947c1753 | 2021-06-04T08:19:43.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"en-de",
"transformers",
"Quality Estimation",
"microtransquest",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | TransQuest | null | TransQuest/microtransquest-en_de-it-nmt | 53 | null | transformers | 5,884 | ---
language: en-de
tags:
- Quality Estimation
- microtransquest
license: apache-2.0
---
# TransQuest: Translation Quality Estimation with Cross-lingual Transformers
The goal of quality estimation (QE) is to evaluate the quality of a translation without having access to a reference translation. High-accuracy QE that ... |
TransQuest/microtransquest-en_zh-wiki | 842323880c2a74f59bdb3cd56efdd22ea1a7e3f4 | 2021-06-04T08:22:58.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"en-zh",
"transformers",
"Quality Estimation",
"microtransquest",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | TransQuest | null | TransQuest/microtransquest-en_zh-wiki | 53 | null | transformers | 5,885 | ---
language: en-zh
tags:
- Quality Estimation
- microtransquest
license: apache-2.0
---
# TransQuest: Translation Quality Estimation with Cross-lingual Transformers
The goal of quality estimation (QE) is to evaluate the quality of a translation without having access to a reference translation. High-accuracy QE that ... |
allenai/macaw-answer-11b | e81db93a1ceda31aebc7664f70a87f728d34b22c | 2021-09-21T15:59:24.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/macaw-answer-11b | 53 | 7 | transformers | 5,886 | ---
language: en
widget:
- text: $answer$ ; $mcoptions$ ; $question$ = What is the color of a cloudy sky?
license: apache-2.0
---
# macaw-answer-11b
## Model description
Macaw (<b>M</b>ulti-<b>a</b>ngle <b>c</b>(q)uestion <b>a</b>ns<b>w</b>ering) is a ready-to-use model capable of
general question answering,
showi... |
baykenney/bert-large-gpt2detector-random | 38c2d1a930bfac6b759459a9d270af6374f90b23 | 2021-05-19T12:14:50.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | baykenney | null | baykenney/bert-large-gpt2detector-random | 53 | null | transformers | 5,887 | Entry not found |
chitra/distilbert-negation | 90697aed80297d8fd77b880dea8596816c03776c | 2022-02-09T06:59:47.000Z | [
"pytorch",
"tf",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | chitra | null | chitra/distilbert-negation | 53 | null | transformers | 5,888 | Entry not found |
facebook/dino-vits16 | bf35519e78e06dbb878dd88eff1e12fc1c3f8576 | 2021-08-25T17:38:44.000Z | [
"pytorch",
"vit",
"feature-extraction",
"dataset:imagenet-1k",
"arxiv:2010.11929",
"arxiv:2104.14294",
"transformers",
"dino",
"license:apache-2.0"
] | feature-extraction | false | facebook | null | facebook/dino-vits16 | 53 | null | transformers | 5,889 | ---
license: apache-2.0
tags:
- dino
datasets:
- imagenet-1k
---
# Vision Transformer (small-sized model, patch size 16) trained using DINO
Vision Transformer (ViT) model trained using the DINO method. It was introduced in the paper [Emerging Properties in Self-Supervised Vision Transformers](https://arxiv.org/abs/2... |
fmikaelian/flaubert-base-uncased-squad | 39a3c87a64ed520c20c6e6eea9e97bb6bdc09c69 | 2020-12-11T21:40:15.000Z | [
"pytorch",
"flaubert",
"question-answering",
"fr",
"transformers",
"autotrain_compatible"
] | question-answering | false | fmikaelian | null | fmikaelian/flaubert-base-uncased-squad | 53 | 1 | transformers | 5,890 | ---
language: fr
---
# flaubert-base-uncased-squad
## Description
A baseline model for question-answering in french ([flaubert](https://github.com/getalp/Flaubert) model fine-tuned on [french-translated SQuAD 1.1 dataset](https://github.com/Alikabbadj/French-SQuAD))
## Training hyperparameters
```shell... |
google/tapas-tiny-finetuned-sqa | 9e62729ba223d47b8812e264d621e719d7fdaaf5 | 2021-11-29T13:08:47.000Z | [
"pytorch",
"tf",
"tapas",
"table-question-answering",
"en",
"dataset:msr_sqa",
"arxiv:2004.02349",
"arxiv:2010.00571",
"transformers",
"license:apache-2.0"
] | table-question-answering | false | google | null | google/tapas-tiny-finetuned-sqa | 53 | null | transformers | 5,891 | ---
language: en
tags:
- tapas
license: apache-2.0
datasets:
- msr_sqa
---
# TAPAS tiny model fine-tuned on Sequential Question Answering (SQA)
This model has 2 versions which can be used. The default version corresponds to the `tapas_sqa_inter_masklm_tiny_reset` checkpoint of the [original Github repository](https:/... |
jcblaise/gpt2-tagalog | a93a67a87de37c526fb3aa414b2c4cae166f4c79 | 2021-11-11T06:12:25.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"tl",
"transformers",
"tagalog",
"filipino",
"license:gpl-3.0"
] | text-generation | false | jcblaise | null | jcblaise/gpt2-tagalog | 53 | null | transformers | 5,892 | ---
language: tl
tags:
- gpt2
- tagalog
- filipino
license: gpl-3.0
inference: false
---
# GPT-2 Tagalog
The Tagalog GPT-2 model used to benchmark our fake news detection system Cruz et al. (2020). We make available an improved version of our GPT-2 model trained with NewsPH in addition to WikiText-TL-39.
## Limitatio... |
m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres | caf978c8328a2cec4229b3eb0b41b162e379caa1 | 2021-07-06T10:26:27.000Z | [
"pytorch",
"wav2vec2",
"transformers",
"audio",
"automatic-speech-recognition",
"audio-classification"
] | automatic-speech-recognition | false | m3hrdadfi | null | m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres | 53 | 4 | transformers | 5,893 | ---
tags:
- audio
- automatic-speech-recognition
- audio-classification
---
# Music Genre Classification using Wav2Vec 2.0
## How to use
### Requirements
```bash
# requirement packages
!pip install git+https://github.com/huggingface/datasets.git
!pip install git+https://github.com/huggingface/transformers.git
!pip... |
mys/electra-base-turkish-cased-ner | d1aeabc657ef56b5ea68268b94ccfc34b36b0fcf | 2020-12-11T21:56:51.000Z | [
"pytorch",
"tf",
"electra",
"token-classification",
"tr",
"transformers",
"autotrain_compatible"
] | token-classification | false | mys | null | mys/electra-base-turkish-cased-ner | 53 | 2 | transformers | 5,894 | ---
language: tr
---
## What is this
A NER model for Turkish with 48 categories trained on the dataset [Shrinked TWNERTC Turkish NER Data](https://www.kaggle.com/behcetsenturk/shrinked-twnertc-turkish-ner-data-by-kuzgunlar) by Behçet Şentürk, which is itself a filtered and cleaned version of the following automatical... |
nickmuchi/distilroberta-finetuned-financial-text-classification | e66b163632379b0f926c8aec99543d48fe83c02a | 2022-04-06T06:05:03.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"en",
"dataset:financial_phrasebank",
"dataset:Kaggle Self label",
"dataset:nickmuchi/financial-classification",
"transformers",
"financial-sentiment-analysis",
"sentiment-analysis",
"sentence_50agree",
"generated_from_trainer",
"... | text-classification | false | nickmuchi | null | nickmuchi/distilroberta-finetuned-financial-text-classification | 53 | null | transformers | 5,895 | ---
license: apache-2.0
language: "en"
tags:
- financial-sentiment-analysis
- sentiment-analysis
- sentence_50agree
- generated_from_trainer
- financial
- stocks
- sentiment
datasets:
- financial_phrasebank
- Kaggle Self label
- nickmuchi/financial-classification
metrics:
- f1
widget:
- text: "The USD rallied by 10% la... |
nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large | 96633c569d2e35adf610f2deead8d8300953f8c7 | 2021-06-20T19:02:55.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | nreimers | null | nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large | 53 | 3 | transformers | 5,896 | # MiniLMv2
This is a MiniLMv2 model from: [https://github.com/microsoft/unilm](https://github.com/microsoft/unilm/tree/master/minilm) |
beomi/kcelectra-v2022-dev | 42204d40600422c885cbecef412ee2aa378316ae | 2022-03-24T05:51:11.000Z | [
"pytorch",
"electra",
"pretraining",
"transformers",
"license:mit"
] | null | false | beomi | null | beomi/kcelectra-v2022-dev | 53 | 1 | transformers | 5,897 | ---
license: mit
---
|
Jeevesh8/feather_berts_95 | 3ddf7cf9cea53386c95d45a820dbcbaad45b27af | 2022-04-20T13:55:22.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Jeevesh8 | null | Jeevesh8/feather_berts_95 | 53 | null | transformers | 5,898 | Entry not found |
imxly/t5-copy | b8511ae016e65773141b478a8da512ef99c69d36 | 2022-05-05T09:08:00.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | imxly | null | imxly/t5-copy | 53 | null | transformers | 5,899 | Entry not found |
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