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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
indonesian-nlp/wav2vec2-indonesian-javanese-sundanese | 9cc3f697a6a33259a3ebe8a8d975c3b3b19ad9bc | 2022-05-07T17:19:01.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"id",
"dataset:mozilla-foundation/common_voice_7_0",
"dataset:openslr",
"dataset:magic_data",
"dataset:titml",
"transformers",
"audio",
"hf-asr-leaderboard",
"jv",
"robust-speech-event",
"speech",
"su",
"license:apache-2.0",
"mod... | automatic-speech-recognition | false | indonesian-nlp | null | indonesian-nlp/wav2vec2-indonesian-javanese-sundanese | 249 | 2 | transformers | 3,300 | ---
language: id
datasets:
- mozilla-foundation/common_voice_7_0
- openslr
- magic_data
- titml
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- id
- jv
- robust-speech-event
- speech
- su
license: apache-2.0
model-index:
- name: Wav2Vec2 Indonesian Javanese and Sundanese by Indonesian... |
nbroad/mt5-base-qgen | 9b215a0483e7933191b85076edb65deb6c2e628c | 2022-07-07T16:47:04.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"mt5",
"text2text-generation",
"en",
"hi",
"de",
"ar",
"bn",
"fi",
"ja",
"zh",
"id",
"sw",
"ta",
"gr",
"ru",
"es",
"th",
"tr",
"vi",
"dataset:squad_v2",
"dataset:tydiqa",
"dataset:mlqa",
"dataset:xquad",
"dataset:germanquad... | text2text-generation | false | nbroad | null | nbroad/mt5-base-qgen | 249 | 1 | transformers | 3,301 | ---
datasets:
- squad_v2
- tydiqa
- mlqa
- xquad
- germanquad
language:
- en
- hi
- de
- ar
- bn
- fi
- ja
- zh
- id
- sw
- ta
- gr
- ru
- es
- th
- tr
- vi
widget:
- text: "Hugging Face has seen rapid growth in its popularity since the get-go. It is definitely doing the right things to attract more and more people to ... |
HooshvareLab/bert-fa-base-uncased-clf-digimag | 64b4c8039a9cf7efc6f1e10ac3770b6646064963 | 2021-05-18T20:48:44.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"fa",
"transformers",
"license:apache-2.0"
] | text-classification | false | HooshvareLab | null | HooshvareLab/bert-fa-base-uncased-clf-digimag | 248 | null | transformers | 3,302 | ---
language: fa
license: apache-2.0
---
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT]... |
Kayvane/distilvert-complaints-subproduct | 316cf6cee7e5116790448d9354c12dfdddf9f99a | 2022-02-02T12:13:48.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | Kayvane | null | Kayvane/distilvert-complaints-subproduct | 248 | null | transformers | 3,303 | Entry not found |
dominiqueblok/roberta-base-finetuned-ner | eeaf0b74f6fb7f04a819a1c342172eb05af2ba42 | 2021-09-20T16:02:48.000Z | [
"pytorch",
"roberta",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | dominiqueblok | null | dominiqueblok/roberta-base-finetuned-ner | 248 | null | transformers | 3,304 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: ... |
m3hrdadfi/bert-fa-base-uncased-wikitriplet-mean-tokens | bab457271c0d16f46da87abf1ac1fba3dcf2e954 | 2021-05-28T06:02:17.000Z | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"fa",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | m3hrdadfi | null | m3hrdadfi/bert-fa-base-uncased-wikitriplet-mean-tokens | 248 | 1 | transformers | 3,305 | ---
language: fa
license: apache-2.0
---
# ParsBERT + Sentence Transformers
Please follow the [Sentence-Transformer](https://github.com/m3hrdadfi/sentence-transformers) repo for the latest information about previous and current models.
```bibtex
@misc{SentenceTransformerWiki,
author = {Mehrdad Farahani},
title =... |
miguelvictor/python-gpt2-large | 02c35a19e4580cb98667e28b83f5562639a9a0ec | 2021-05-23T09:30:59.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | miguelvictor | null | miguelvictor/python-gpt2-large | 248 | null | transformers | 3,306 | Entry not found |
theChanChanMan/DialoGPT-small-chandler | e6c82a45f6fd64a0254f4b9da310e97f3ddb8549 | 2021-09-29T17:39:39.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | theChanChanMan | null | theChanChanMan/DialoGPT-small-chandler | 248 | null | transformers | 3,307 | ---
tags:
- conversational
---
# Chandler Bing DialoGPT Model |
luohy/rgx-qg | fcd842ea9e7e3bb7054f734c557888fb6b60c2e7 | 2022-06-29T13:30:02.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | luohy | null | luohy/rgx-qg | 248 | null | transformers | 3,308 | ---
license: afl-3.0
---
|
EmileAjar/DialoGPT-small-peppapig | f731e4e1c8b812f0d66d6c9c6aa9a457b805f26e | 2021-08-28T13:49:05.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | EmileAjar | null | EmileAjar/DialoGPT-small-peppapig | 247 | null | transformers | 3,309 | ---
tags:
- conversational
---
# Peppa pig DialoGPT Model |
asahi417/tner-xlm-roberta-large-all-english | 0c7cdfb6289482e221ef5a5ed1b6ae1dc16799f9 | 2021-02-12T23:48:50.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | asahi417 | null | asahi417/tner-xlm-roberta-large-all-english | 247 | 1 | transformers | 3,310 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-large-all-english")
model =... |
seyonec/BPE_SELFIES_PubChem_shard00_50k | e0e89545fecf14a0a21ee640057b27ce65783ec3 | 2021-05-20T20:48:07.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | seyonec | null | seyonec/BPE_SELFIES_PubChem_shard00_50k | 247 | null | transformers | 3,311 | Entry not found |
CarlCochet/trajectory-transformer-halfcheetah-medium-v2 | 68647ada7a729fe6da99df361609453f2332e1d2 | 2022-05-10T12:38:16.000Z | [
"pytorch",
"trajectory_transformer",
"feature-extraction",
"transformers",
"license:mit"
] | feature-extraction | false | CarlCochet | null | CarlCochet/trajectory-transformer-halfcheetah-medium-v2 | 247 | null | transformers | 3,312 | ---
license: mit
---
|
Wikidepia/IndoT5-small | c9c1f3ba70abb337484d2f4f498973fa64ef2034 | 2021-07-04T06:17:07.000Z | [
"pytorch",
"t5",
"text2text-generation",
"id",
"dataset:allenai/c4",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Wikidepia | null | Wikidepia/IndoT5-small | 246 | null | transformers | 3,313 | ---
language:
- id
datasets:
- allenai/c4
---
# Indonesian T5 Small
T5 (Text-to-Text Transfer Transformer) model pretrained on Indonesian mC4 with [extra filtering](https://github.com/Wikidepia/indonesian_datasets/tree/master/dump/mc4). This model is pre-trained only and needs to be fine-tuned to be used for specific... |
henryu-lin/t5-large-samsum-deepspeed | 77653b11133142f145ec70f32def0f8397dbcb3c | 2021-07-08T09:13:46.000Z | [
"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-large-samsum-deepspeed | 246 | 1 | transformers | 3,314 |
---
language: en
tags:
- azureml
- t5
- summarization
- deepspeed
license: apache-2.0
datasets:
- samsum
model-index:
- name: t5-large-samsum-deepspeed
results:
- task:
name: Abstractive Text Summarization
type: abstractive-text-summarization
dataset:
name: "SAMSum Corpus: A Human-annotated ... |
liaad/srl-pt_bertimbau-base | 5001a47734731b760ee029d0afa398c3047e8f01 | 2021-09-22T08:56:26.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"multilingual",
"pt",
"dataset:PropBank.Br",
"arxiv:2101.01213",
"transformers",
"bert-base-portuguese-cased",
"semantic role labeling",
"finetuned",
"license:apache-2.0"
] | feature-extraction | false | liaad | null | liaad/srl-pt_bertimbau-base | 246 | null | transformers | 3,315 | ---
language:
- multilingual
- pt
tags:
- bert-base-portuguese-cased
- semantic role labeling
- finetuned
license: apache-2.0
datasets:
- PropBank.Br
metrics:
- F1 Measure
---
# BERTimbau base fine-tuned on Portuguese semantic role labeling
## Model description
This model is the [`neuralmind/bert-base-portuguese-cas... |
nanometeres/DialoGPT-medium-halbot | 1722d57de0815cab05b3c531382de64c771874ff | 2021-09-01T11:55:43.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | nanometeres | null | nanometeres/DialoGPT-medium-halbot | 246 | null | transformers | 3,316 | ---
tags: conversational
---
#LilHalMediumModel |
valurank/pegasus-multi_news-headline | b26a7990e5e76d16e507ee60183a9f61ee79be72 | 2022-06-08T20:14:44.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:other",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | valurank | null | valurank/pegasus-multi_news-headline | 246 | 1 | transformers | 3,317 | ---
tags:
- generated_from_trainer
license: other
metrics:
- rouge
model-index:
- name: pegasus-multi_news-headline
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. -->... |
Danastos/qacombination_bert_el_4 | 8a8376042920436e9de2fa753ae56df0b948eb7e | 2022-06-18T11:56:46.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | Danastos | null | Danastos/qacombination_bert_el_4 | 246 | null | transformers | 3,318 | Entry not found |
Recognai/selectra_medium | 953bd230344c2088d9b15d8ca92970b41c31ab68 | 2021-10-19T15:28:03.000Z | [
"pytorch",
"electra",
"pretraining",
"es",
"dataset:oscar",
"transformers",
"license:apache-2.0"
] | null | false | Recognai | null | Recognai/selectra_medium | 245 | 3 | transformers | 3,319 | ---
language:
- es
thumbnail: "url to a thumbnail used in social sharing"
license: apache-2.0
datasets:
- oscar
---
# SELECTRA: A Spanish ELECTRA
SELECTRA is a Spanish pre-trained language model based on [ELECTRA](https://github.com/google-research/electra).
We release a `small` and `medium` version with the follo... |
deepset/gelectra-large-generator | 9dfd9c7ee492ba7695a6ec259069e371b1689144 | 2021-10-21T12:18:52.000Z | [
"pytorch",
"tf",
"electra",
"fill-mask",
"de",
"dataset:wikipedia",
"dataset:OPUS",
"dataset:OpenLegalData",
"dataset:oscar",
"arxiv:2010.10906",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | deepset | null | deepset/gelectra-large-generator | 245 | 2 | transformers | 3,320 | ---
language: de
license: mit
datasets:
- wikipedia
- OPUS
- OpenLegalData
- oscar
---
# German ELECTRA large generator
Released, Oct 2020, this is the generator component of the German ELECTRA language model trained collaboratively by the makers of the original German BERT (aka "bert-base-german-cased") and the dbmd... |
google/multiberts-seed_16 | 63aaff15780ac66d658b41e57943e8a616aa20d1 | 2021-11-05T22:36:56.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_16",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_16 | 245 | null | transformers | 3,321 | ---
language: en
tags:
- multiberts
- multiberts-seed_16
license: apache-2.0
---
# MultiBERTs - Seed 16
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
google/multiberts-seed_18 | f35562c2b663933185a61a3c39d8f46d9a99a71c | 2021-11-05T22:40:12.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_18",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_18 | 245 | null | transformers | 3,322 | ---
language: en
tags:
- multiberts
- multiberts-seed_18
license: apache-2.0
---
# MultiBERTs - Seed 18
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
google/multiberts-seed_23 | 464c5f8311c3698967c6a576b454d862bf341149 | 2021-11-05T22:49:16.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_23",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_23 | 245 | null | transformers | 3,323 | ---
language: en
tags:
- multiberts
- multiberts-seed_23
license: apache-2.0
---
# MultiBERTs - Seed 23
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
Aniemore/rubert-tiny2-russian-emotion-detection | 16b199f717a58b1fc29e82b52c45fa16dc98e2f8 | 2022-05-27T11:10:42.000Z | [
"pytorch",
"bert",
"text-classification",
"ru",
"dataset:Aniemore/cedr-m7",
"transformers",
"russian",
"classification",
"emotion",
"emotion-detection",
"emotion-recognition",
"multiclass",
"license:gpl-3.0",
"model-index"
] | text-classification | false | Aniemore | null | Aniemore/rubert-tiny2-russian-emotion-detection | 245 | 4 | transformers | 3,324 | ---
license: gpl-3.0
language: ["ru"]
tags:
- russian
- classification
- emotion
- emotion-detection
- emotion-recognition
- multiclass
widget:
- text: "Как дела?"
- text: "Дурак твой дед"
- text: "Только попробуй!!!"
- text: "Не хочу в школу("
- text: "Сейчас ровно час дня"
- text: "А ты уверен, что эти полоски снизу... |
google/multiberts-seed_17 | 7ca808c200b4bf0e62e1df75ff1773f66c216362 | 2021-11-05T22:38:31.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_17",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_17 | 244 | null | transformers | 3,325 | ---
language: en
tags:
- multiberts
- multiberts-seed_17
license: apache-2.0
---
# MultiBERTs - Seed 17
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
google/multiberts-seed_21 | 831764632904bcd34dec982839db6ddce0f52581 | 2021-11-05T22:45:53.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_21",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_21 | 244 | null | transformers | 3,326 | ---
language: en
tags:
- multiberts
- multiberts-seed_21
license: apache-2.0
---
# MultiBERTs - Seed 21
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
google/multiberts-seed_22 | beed912e0085b541a91e1dafdcb3e4dbacd89128 | 2021-11-05T22:47:36.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_22",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_22 | 244 | null | transformers | 3,327 | ---
language: en
tags:
- multiberts
- multiberts-seed_22
license: apache-2.0
---
# MultiBERTs - Seed 22
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
mdc1616/DialoGPT-large-sherlock | 0df2bdc0a8973e2f03da887d5073b6c7e5b8ba2a | 2021-08-27T00:52:33.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | mdc1616 | null | mdc1616/DialoGPT-large-sherlock | 244 | null | transformers | 3,328 | ---
tags:
- conversational
---
#Sherlock DialoGPT Model |
michelleshx/DialoGPT-small-michelle-discord-bot | 06edf8f1adf0b042cc9af5b60ce597cb05a7221e | 2021-12-20T09:10:07.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | michelleshx | null | michelleshx/DialoGPT-small-michelle-discord-bot | 244 | null | transformers | 3,329 | ---
tags:
- conversational
---
# Discord DialoGPT Model |
KoboldAI/fairseq-dense-6.7B-Janeway | 179f84c09eacb61564273d2341bcd2ddef548d84 | 2022-04-07T11:47:40.000Z | [
"pytorch",
"xglm",
"text-generation",
"en",
"transformers",
"license:mit"
] | text-generation | false | KoboldAI | null | KoboldAI/fairseq-dense-6.7B-Janeway | 244 | null | transformers | 3,330 | ---
language: en
license: mit
---
# Fairseq-dense 6.7B - Janeway
## Model Description
Fairseq-dense 6.7B-Janeway is a finetune created using Fairseq's MoE dense model.
## Training data
The training data contains around 2210 ebooks, mostly in the sci-fi and fantasy genres. The dataset is identical as dataset used by GPT... |
allenai/multicite-multilabel-roberta-large | 4ed0c81f083f288375da6b8c86a737fb2aaf941a | 2022-05-10T17:46:12.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"transformers",
"Roberta",
"license:mit"
] | text-classification | false | allenai | null | allenai/multicite-multilabel-roberta-large | 244 | null | transformers | 3,331 | ---
language: en
tags:
- Roberta
license: mit
---
# MultiCite: Multi-label Citation Intent Classification with Roberta-large (NAACL 2022)
This model has been trained on the data available here: https://github.com/allenai/multicite. |
Yale-LILY/brio-cnndm-cased | b43d9597957496357911e66331fb0c3a983836c1 | 2022-05-16T01:09:53.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Yale-LILY | null | Yale-LILY/brio-cnndm-cased | 244 | 1 | transformers | 3,332 | Entry not found |
SerdarHelli/ThyroidTumorClassificationModel | 0f1fd610dd4f9c7ddf2c787ba95f1ac850bc0527 | 2022-06-28T09:52:22.000Z | [
"pytorch",
"convnext",
"image-classification",
"transformers",
"medicalimaging",
"thyroidtumor"
] | image-classification | false | SerdarHelli | null | SerdarHelli/ThyroidTumorClassificationModel | 244 | null | transformers | 3,333 | ---
tags:
- medicalimaging
- thyroidtumor
metrics:
- accuracy
---
Thyroid nodule is one of the most common endocrine carcinomas. Due to its higher reveal ability and ability to distinguish between benign and malignant nodules in pathological features, ultrasonography has become the most widely used modality for fin... |
fabriceyhc/bert-base-uncased-imdb | 7e84f0cce24fe5aa3d0ab5bece0da571055c3d6f | 2021-09-21T00:54:38.000Z | [
"pytorch",
"bert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"sibyl",
"license:apache-2.0",
"model-index"
] | text-classification | false | fabriceyhc | null | fabriceyhc/bert-base-uncased-imdb | 243 | null | transformers | 3,334 | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: bert-base-uncased-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- na... |
google/multiberts-seed_19 | 7a6882fed9f3f3dd56b65e2683cec3509f9e72a1 | 2021-11-05T22:42:17.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_19",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_19 | 243 | null | transformers | 3,335 | ---
language: en
tags:
- multiberts
- multiberts-seed_19
license: apache-2.0
---
# MultiBERTs - Seed 19
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
google/multiberts-seed_20 | 53714946d69651632e8d1d0a47b6090c62e72fde | 2021-11-05T22:43:59.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_20",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_20 | 243 | null | transformers | 3,336 | ---
language: en
tags:
- multiberts
- multiberts-seed_20
license: apache-2.0
---
# MultiBERTs - Seed 20
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
google/multiberts-seed_24 | 84c61c0ec7351dad811ee688f80a9b85e3a0f2b8 | 2021-11-05T22:50:53.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_24",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_24 | 243 | null | transformers | 3,337 | ---
language: en
tags:
- multiberts
- multiberts-seed_24
license: apache-2.0
---
# MultiBERTs - Seed 24
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://... |
microsoft/ssr-base | 295984f807b4d3603d246f1b8f234dfa1463974d | 2021-11-17T05:38:17.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"arxiv:2101.00416",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | microsoft | null | microsoft/ssr-base | 243 | null | transformers | 3,338 | ---
language:
- en
datasets:
- c4
tags:
- summarization
- text2text-generation
---
# SSR-base
SSR-base model as in EMNLP 2021 paper [Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting](https://arxiv.org/abs/2101.00416).
|
rovai/Chat_pytorch1 | c3e32465718afc150b2df9e9adb5da625c2c4d7e | 2021-12-01T01:11:02.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | rovai | null | rovai/Chat_pytorch1 | 243 | null | transformers | 3,339 | ---
tags:
- conversational
---
#chat_pytorch1 |
microsoft/dit-large-finetuned-rvlcdip | a482c23ec1ba3f64142cdb7ffb097fcc6473fda7 | 2022-07-21T12:20:31.000Z | [
"pytorch",
"beit",
"image-classification",
"dataset:rvl_cdip",
"arxiv:2203.02378",
"transformers",
"dit"
] | image-classification | false | microsoft | null | microsoft/dit-large-finetuned-rvlcdip | 243 | 2 | transformers | 3,340 | ---
tags:
- dit
datasets:
- rvl_cdip
inference: false
---
# Document Image Transformer (large-sized model)
Document Image Transformer (DiT) model pre-trained on IIT-CDIP (Lewis et al., 2006), a dataset that includes 42 million document images and fine-tuned on [RVL-CDIP](https://www.cs.cmu.edu/~aharley/rvl-cdip/), a... |
cambridgeltl/sst_mobilebert-uncased | 7db84f6f29a24560feb7f0a2296ea5c14b8edf66 | 2022-03-14T14:37:07.000Z | [
"pytorch",
"mobilebert",
"text-classification",
"transformers"
] | text-classification | false | cambridgeltl | null | cambridgeltl/sst_mobilebert-uncased | 243 | null | transformers | 3,341 | Entry not found |
valurank/MiniLM-L6-Keyword-Extraction | 268a06523de516f25e7a089cff7921ad764f072d | 2022-06-08T20:17:38.000Z | [
"pytorch",
"bert",
"feature-extraction",
"en",
"arxiv:1904.06472",
"arxiv:2102.07033",
"arxiv:2104.08727",
"arxiv:1704.05179",
"arxiv:1810.09305",
"sentence-transformers",
"sentence-similarity",
"license:other"
] | sentence-similarity | false | valurank | null | valurank/MiniLM-L6-Keyword-Extraction | 243 | null | sentence-transformers | 3,342 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language: en
license: other
---
# all-MiniLM-L6-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for t... |
M-CLIP/LABSE-Vit-L-14 | f03054697ff64d4cedef16917a8d075aec9849ae | 2022-06-02T23:26:39.000Z | [
"pytorch",
"tf",
"multilingual"
] | null | false | M-CLIP | null | M-CLIP/LABSE-Vit-L-14 | 243 | null | null | 3,343 | ---
language: multilingual
---
## Multilingual-clip: LABSE-Vit-L-14
Multilingual-CLIP extends OpenAI's English text encoders to multiple other languages. This model *only* contains the multilingual text encoder. The corresponding image model `ViT-L-14` can be retrieved via instructions found on OpenAI's [CLIP reposi... |
RUCAIBox/mvp-data-to-text | 98ed82114e6e0c8c04b4d09057a4adb9f5283c70 | 2022-06-27T02:27:50.000Z | [
"pytorch",
"mvp",
"en",
"arxiv:2206.12131",
"transformers",
"text-generation",
"text2text-generation",
"license:apache-2.0"
] | text2text-generation | false | RUCAIBox | null | RUCAIBox/mvp-data-to-text | 243 | 1 | transformers | 3,344 | ---
license: apache-2.0
language:
- en
tags:
- text-generation
- text2text-generation
pipeline_tag: text2text-generation
widget:
- text: "Describe the following data: Iron Man | instance of | Superhero [SEP] Stan Lee | creator | Iron Man"
example_title: "Example1"
- text: "Describe the following data: First Clearing ... |
datien228/distilbart-cnn-12-6-ftn-multi_news | 0003822f8c64725fabd80ea41e2af35735e9871a | 2022-07-11T11:26:02.000Z | [
"pytorch",
"bart",
"text2text-generation",
"dataset:multi_news",
"transformers",
"summarization",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | datien228 | null | datien228/distilbart-cnn-12-6-ftn-multi_news | 243 | null | transformers | 3,345 | ---
license: apache-2.0
tags:
- summarization
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: distilbart-cnn-12-6-ftn-multi_news
results:
- task:
name: Sequence-to-sequence Language Modeling
type: summarization
dataset:
name: multi_news
type: multi_news
args: default
... |
DongHai/DialoGPT-small-rick | 6f955ce1472c2beeb54d9c9fdcf579c64dc9810e | 2021-09-02T03:49:46.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | DongHai | null | DongHai/DialoGPT-small-rick | 242 | null | transformers | 3,346 | ---
tags:
- conversational
---
# Rick DialoGPT Model |
Huffon/klue-roberta-base-nli | 3778d23ecb30a63babb17f5efb37b1493b08d975 | 2021-06-20T17:32:53.000Z | [
"pytorch",
"roberta",
"text-classification",
"ko",
"dataset:klue",
"transformers",
"nli"
] | text-classification | false | Huffon | null | Huffon/klue-roberta-base-nli | 242 | 3 | transformers | 3,347 | ---
language: ko
tags:
- roberta
- nli
datasets:
- klue
---
|
howey/electra-small-mnli | 9e8a6bd9250be4dc610518aea8fcf8188f2ea637 | 2021-04-16T12:57:26.000Z | [
"pytorch",
"electra",
"text-classification",
"transformers"
] | text-classification | false | howey | null | howey/electra-small-mnli | 242 | null | transformers | 3,348 | Entry not found |
josephmagnayon/DialoGPT-medium-Alfred | f2cdc17ef60ce66ef878654103ca422c4567583c | 2022-01-22T12:47:43.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | josephmagnayon | null | josephmagnayon/DialoGPT-medium-Alfred | 242 | null | transformers | 3,349 | ---
tags:
- conversational
---
# Alfred DialoGPT |
ken11/albert-base-japanese-v1 | 0b768a8c8052c9dddfbd58110c524c2c7d355239 | 2021-12-21T18:04:30.000Z | [
"pytorch",
"tf",
"albert",
"fill-mask",
"ja",
"transformers",
"japanese",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | ken11 | null | ken11/albert-base-japanese-v1 | 242 | null | transformers | 3,350 | ---
tags:
- fill-mask
- japanese
- albert
language:
- ja
license: mit
widget:
- text: "2022年の[MASK]概要"
---
## albert-base-japanese-v1
日本語事前学習済みALBERTモデルです
## How to use
### ファインチューニング
このモデルはPreTrainedモデルです
基本的には各種タスク用にファインチューニングして使用されることを想定しています
### Fill-Mask
このモデルではTokenizerにSentencepieceを利用しています
そのままでは`... |
Merry/AID-Neo-125M | 76b6c0e0e186878c6edf5d91b4cf38c94d191206 | 2022-04-28T22:53:53.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | Merry | null | Merry/AID-Neo-125M | 242 | 0 | transformers | 3,351 | # AID-Neo-125M
## Model description
This model was inspired by -- and finetuned on the same dataset of -- [KoboldAI's GPT-Neo-125M-AID (Mia) model](https://huggingface.co/KoboldAI/GPT-Neo-125M-AID): the AI Dungeon dataset (`text_adventures.txt`). This was to fix a possible oversight in the original model, which was tr... |
birgermoell/swedish-gpt | 1c21a3855f89f8c544db2fa9fcc5499bd8885038 | 2021-07-17T07:45:52.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"sv",
"transformers"
] | text-generation | false | birgermoell | null | birgermoell/swedish-gpt | 241 | 1 | transformers | 3,352 | ---
language: sv
widget:
- text: "Jag är en svensk språkmodell."
---
## Model series
This model is part of a series of models training on TPU with Flax Jax during Huggingface Flax/Jax challenge.
## Gpt models
## Swedish Gpt
https://huggingface.co/birgermoell/swedish-gpt/
## Swedish gpt wiki
https://huggingface.co/f... |
patrickvonplaten/wav2vec2-xlsr-53-es-kenlm | cc167e77d9e2afcf0e1234469769229bbdab1b32 | 2021-12-08T14:00:21.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wav2vec2-xlsr-53-es-kenlm | 241 | null | transformers | 3,353 | ---
language: es
datasets:
- common_voice
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
---
# Wav2Vec2-Large-XLSR-53-Spanish-With-LM
This is a model copy of [Wav2Vec2-Large-XLSR-53-Spanish](https://huggingface.co/jonatasgrosman/wav2vec2-large-xl... |
tdopierre/ProtAugment-LM-HWU64 | e8b98bca77aee8bb840cf8c029e61a7aaa5f5c8d | 2021-07-01T13:52:14.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | tdopierre | null | tdopierre/ProtAugment-LM-HWU64 | 241 | null | transformers | 3,354 | Entry not found |
mesolitica/wav2vec2-xls-r-300m-mixed | 626d64add848693049722e7f2bdbe1d7237f393c | 2022-06-02T04:58:36.000Z | [
"pytorch",
"tf",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_keras_callback",
"model-index"
] | automatic-speech-recognition | false | mesolitica | null | mesolitica/wav2vec2-xls-r-300m-mixed | 241 | null | transformers | 3,355 | ---
tags:
- generated_from_keras_callback
model-index:
- name: wav2vec2-xls-r-300m-mixed
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. -->
# wav2vec2-xls-r-300m-mixed
F... |
asahi417/lmqg-mt5-small-koquad-multitask | 61db0373d2ee4dd9bc9f4ae6285f7dd3bad1c908 | 2022-06-09T11:53:51.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-mt5-small-koquad-multitask | 241 | null | transformers | 3,356 | Entry not found |
ccoreilly/wav2vec2-large-xlsr-catala | a4467e83126071845d754ee648e9ec3b9c5f5268 | 2021-07-06T00:12:57.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ca",
"dataset:common_voice",
"dataset:parlament_parla",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | ccoreilly | null | ccoreilly/wav2vec2-large-xlsr-catala | 240 | null | transformers | 3,357 | ---
language: ca
datasets:
- common_voice
- parlament_parla
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Catalan XLSR Wav2Vec2 Large
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
google/bert_uncased_L-12_H-128_A-2 | 769ccb240a0acd026d94f84a96e8a754e4b8eff1 | 2021-05-19T17:26:01.000Z | [
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/bert_uncased_L-12_H-128_A-2 | 240 | null | transformers | 3,358 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... |
monologg/koelectra-base-finetuned-nsmc | 55c42190841c633ca53f6960dad762d41bf091b5 | 2020-08-18T18:41:06.000Z | [
"pytorch",
"electra",
"text-classification",
"transformers"
] | text-classification | false | monologg | null | monologg/koelectra-base-finetuned-nsmc | 240 | null | transformers | 3,359 | Entry not found |
ravephelps/DialoGPT-small-MichaelSbott | 5ba2c3fd899e1c1693aaf06df22bdb5f1931c54a | 2021-08-28T12:54:58.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ravephelps | null | ravephelps/DialoGPT-small-MichaelSbott | 240 | null | transformers | 3,360 | ---
tags:
- conversational
---
# Michael Scott DialoGPT Model |
usamazaheer/DialoGPT-small-harrypotter | abe0dfc5a5a068668e5aeef17ef9b131578e4f7d | 2022-02-08T20:18:36.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | usamazaheer | null | usamazaheer/DialoGPT-small-harrypotter | 240 | null | transformers | 3,361 | ---
tags:
- conversational
---
#Harry Potter DialoGPT Model |
xfbai/AMRBART-large | d45c7b63a746de710375ed78c4acf111db4ac029 | 2022-04-26T06:14:16.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"arxiv:2203.07836",
"transformers",
"AMRBART",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | xfbai | null | xfbai/AMRBART-large | 240 | 1 | transformers | 3,362 | ---
language: en
tags:
- AMRBART
license: mit
---
## AMRBART (large-sized model)
AMRBART model is continually pre-trained on the English text and AMR Graphs based on the BART model. It was introduced in the paper: [Graph Pre-training for AMR Parsing and Generation](https://arxiv.org/pdf/2203.07836.pdf) by bai et al. ... |
ckiplab/bert-base-han-chinese-pos | 7d182977911b6e6103c3a208ba0e1e4493284e8a | 2022-07-04T08:09:23.000Z | [
"pytorch",
"bert",
"token-classification",
"zh",
"transformers",
"license:gpl-3.0",
"autotrain_compatible"
] | token-classification | false | ckiplab | null | ckiplab/bert-base-han-chinese-pos | 240 | null | transformers | 3,363 | ---
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- token-classification
- bert
- zh
license: gpl-3.0
---
# CKIP BERT Base Han Chinese POS
This model provides part-of-speech (POS) tagging for the ancient Chinese language. Our training dataset covers four eras o... |
Bee-Garbs/DialoGPT-real-cartman-small | 906eddd8e689bc80a2b6ed33c0ef5106950b59ca | 2021-12-07T01:55:25.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Bee-Garbs | null | Bee-Garbs/DialoGPT-real-cartman-small | 239 | null | transformers | 3,364 | ---
tags:
- conversational
---
# Cartman Southpark DialoGPT2 small 18 epochs |
flax-community/gpt-neo-125M-code-clippy | 61cb8c8fbcd541027ddec252ed2e207d0dece23e | 2021-07-26T14:07:46.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"arxiv:2107.03374",
"transformers"
] | text-generation | false | flax-community | null | flax-community/gpt-neo-125M-code-clippy | 239 | 3 | transformers | 3,365 | # GPT-Neo-125M-Code-Clippy
> **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 Description
GPT-Neo-125M-Code-Clippy is a [GPT-Neo-125M model](https://huggingface.co/EleutherAI... |
microsoft/beit-base-patch16-384 | 3f8133fb4ce0cd802b8eab61edd881bc2a624597 | 2022-01-28T10:19:30.000Z | [
"pytorch",
"jax",
"beit",
"image-classification",
"dataset:imagenet",
"dataset:imagenet-21k",
"arxiv:2106.08254",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | microsoft | null | microsoft/beit-base-patch16-384 | 239 | null | transformers | 3,366 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
- imagenet-21k
---
# BEiT (base-sized model, fine-tuned on ImageNet-1k)
BEiT model pre-trained in a self-supervised fashion on ImageNet-21k (14 million images, 21,841 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 ... |
textattack/albert-base-v2-CoLA | 3e02233591f32405d343657a2f056d5afe21e86c | 2020-07-06T16:28:50.000Z | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/albert-base-v2-CoLA | 239 | null | transformers | 3,367 | ## TextAttack Model Cardand the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 32, a learning
rate of 3e-05, and a maximum sequence length of 128.
Since this was a classification task, the model was trained with a cross-entropy loss function.
The best score t... |
asahi417/lmqg-mt5-small-dequad-multitask | 85235e035cbb84aff9c9a1d3147e7ea85b078369 | 2022-06-09T11:26:43.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-mt5-small-dequad-multitask | 239 | null | transformers | 3,368 | Entry not found |
asahi417/lmqg-mt5-small-ruquad-multitask | 4ba9350bfd985f2889ddff293bedb214e76decdf | 2022-06-13T01:33:14.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-mt5-small-ruquad-multitask | 239 | null | transformers | 3,369 | Entry not found |
sijunhe/nezha-large-wwm | 7f1935e1fba27f5ca374439228e8317d1975eee4 | 2022-06-24T03:55:48.000Z | [
"pytorch",
"nezha",
"fill-mask",
"arxiv:1909.00204",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | fill-mask | false | sijunhe | null | sijunhe/nezha-large-wwm | 239 | null | transformers | 3,370 | ---
license: afl-3.0
---
**Please use 'Bert' related tokenizer classes and 'Nezha' related model classes**
[NEZHA: Neural Contextualized Representation for Chinese Language Understanding](https://arxiv.org/abs/1909.00204)
Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jian... |
Ivo/emscad-skill-extraction-conference-token-classification | 1e7c8e8ddf8726ebd8b10d7375b95d123c4c22b8 | 2021-06-15T09:20:03.000Z | [
"pytorch",
"tf",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Ivo | null | Ivo/emscad-skill-extraction-conference-token-classification | 238 | null | transformers | 3,371 | Entry not found |
finiteautomata/beto-headlines-sentiment-analysis | e73e01865fe516e5e9f5bf31eff1606b70b1d741 | 2021-07-06T12:33:57.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | finiteautomata | null | finiteautomata/beto-headlines-sentiment-analysis | 238 | null | transformers | 3,372 | # Targeted Sentiment Analysis in News Headlines
BERT classifier fine-tuned in a news headlines dataset annotated for target polarity.
(details to be published)
## Examples
Input is as follows
`Headline [SEP] Target`
where headline is the news title and target is an entity present in the headline.
Try
`Alberto ... |
tinega/DialoGPT-small-harrypotter | 4dfb8aaddd1f825ba362ea8f43dcbcda06cfba1f | 2022-02-14T11:32:35.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | tinega | null | tinega/DialoGPT-small-harrypotter | 238 | null | transformers | 3,373 | ---
tags:
- conversational
---
# Harry Potter DialoGPT MOdel |
wietsedv/bert-base-dutch-cased-finetuned-udlassy-pos | 769f7d091081bc31f6134ba497fa52e1531b94a8 | 2021-05-20T09:11:56.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | wietsedv | null | wietsedv/bert-base-dutch-cased-finetuned-udlassy-pos | 238 | null | transformers | 3,374 | Entry not found |
IDEA-CCNL/Erlangshen-Longformer-110M | 54d92f1ea27093c63bb48881c8efba3349c7df58 | 2022-07-17T09:21:35.000Z | [
"pytorch",
"longformer",
"zh",
"transformers",
"license:apache-2.0"
] | null | false | IDEA-CCNL | null | IDEA-CCNL/Erlangshen-Longformer-110M | 238 | 1 | transformers | 3,375 | ---
language:
- zh
license: apache-2.0
widget:
- text: "生活的真谛是[MASK]。"
---
# longformer model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
We modify the original position code of longformer to rotational position coding，and on the basis of [chinese_roformer_L-12_H-768_A-12.... |
shibing624/bert4ner-base-chinese | a24a2c4d3c5f2ca37b7bceb1991f1ce573e10530 | 2022-05-07T13:32:36.000Z | [
"pytorch",
"bert",
"token-classification",
"zh",
"transformers",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | shibing624 | null | shibing624/bert4ner-base-chinese | 238 | 1 | transformers | 3,376 | ---
language:
- zh
tags:
- bert
- pytorch
- zh
- ner
license: "apache-2.0"
---
# BERT for Chinese Named Entity Recognition(bert4ner) Model
中文实体识别模型
`bert4ner-base-chinese` evaluate PEOPLE(人民日报) test data：
The overall performance of BERT on people **test**:
| | Accuracy | Recall | F1 |
| ---------... |
asahi417/lmqg-mt5-small-esquad-multitask | 9d383943a66228eda00534e3868198226f78a082 | 2022-06-09T12:16:25.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-mt5-small-esquad-multitask | 238 | null | transformers | 3,377 | Entry not found |
asahi417/lmqg-mt5-small-itquad-multitask | 201d943215034814684f418aeed7fa454eaec867 | 2022-06-13T10:48:19.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-mt5-small-itquad-multitask | 238 | null | transformers | 3,378 | Entry not found |
asahi417/lmqg-mt5-small-frquad-multitask | df829846a77664f656e66fb3dce336c99777dce0 | 2022-06-13T12:23:16.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-mt5-small-frquad-multitask | 238 | null | transformers | 3,379 | Entry not found |
ElKulako/cryptobert | 2e1ec4c73a4608b98d15fa4bb9b17ddd61bc61a4 | 2022-07-10T22:22:24.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:ElKulako/stocktwits-crypto",
"transformers",
"cryptocurrency",
"crypto",
"BERT",
"sentiment classification",
"NLP",
"bitcoin",
"ethereum",
"shib",
"social media",
"sentiment analysis",
"cryptocurrency sentiment analysis"
] | text-classification | false | ElKulako | null | ElKulako/cryptobert | 238 | 1 | transformers | 3,380 | ---
datasets:
- ElKulako/stocktwits-crypto
language:
- en
tags:
- cryptocurrency
- crypto
- BERT
- sentiment classification
- NLP
- bitcoin
- ethereum
- shib
- social media
- sentiment analysis
- cryptocurrency sentiment analysis
---
# CryptoBERT
CryptoBERT is a pre-trained NLP model to analyse the language and sent... |
DaNLP/da-bert-tone-subjective-objective | b0a47450aa6992164d0c990056b1f64c1e1b2d4b | 2021-09-23T13:37:20.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"da",
"dataset:Twitter Sentiment",
"dataset:Europarl Sentiment",
"transformers",
"subjectivity",
"objectivity",
"license:cc-by-sa-4.0"
] | text-classification | false | DaNLP | null | DaNLP/da-bert-tone-subjective-objective | 237 | 1 | transformers | 3,381 | ---
language:
- da
tags:
- bert
- pytorch
- subjectivity
- objectivity
license: cc-by-sa-4.0
datasets:
- Twitter Sentiment
- Europarl Sentiment
widget:
- text: Jeg tror alligvel, det bliver godt
metrics:
- f1
---
# Danish BERT Tone for the detection of subjectivity/objectivity
The BERT Tone model detects whether a te... |
megantosh/flair-arabic-multi-ner | 75348fbb37f7a264dd4baf7ea7cc4062c0de0cb0 | 2022-03-09T22:12:22.000Z | [
"pytorch",
"ar",
"en",
"dataset:AQMAR",
"dataset:ANERcorp",
"flair",
"Text Classification",
"token-classification",
"sequence-tagger-model",
"license:apache-2.0"
] | token-classification | false | megantosh | null | megantosh/flair-arabic-multi-ner | 237 | null | flair | 3,382 | ---
language:
- ar
- en
license: apache-2.0
datasets:
- AQMAR
- ANERcorp
thumbnail: https://www.informatik.hu-berlin.de/en/forschung-en/gebiete/ml-en/resolveuid/a6f82e0d7fa446a59c902cac4cafa9cb/@@images/image/preview
tags:
- flair
- Text Classification
- token-classification
- sequence-tagger-model
metrics:
- f1
widge... |
uyharold86/DialoGPT-small-RickAndMorty | 0e5185b8ff4a4853b5bb450ad056755f47ca4e4b | 2021-09-27T06:23:52.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | uyharold86 | null | uyharold86/DialoGPT-small-RickAndMorty | 237 | null | transformers | 3,383 | ---
tags:
- conversational
---
# Rick and Morty DialoGPT Model (small) |
24adamaliv/DialoGPT-medium-Will | 00b542a84bc1db9725e8a36b40daee60b28abd5f | 2022-07-13T23:00:25.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | 24adamaliv | null | 24adamaliv/DialoGPT-medium-Will | 237 | null | transformers | 3,384 | ---
tags:
- conversational
---
# Will Byers DialoGPT model |
jogp10/DialoGPT-medium-arya | d3ce418ceb2eb2be89d8a92718eb87a62f5e879d | 2021-09-02T01:36:46.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | jogp10 | null | jogp10/DialoGPT-medium-arya | 236 | null | transformers | 3,385 | ---
tags:
- conversational
---
# Arya DialoGPT Model |
microsoft/wavlm-base-plus-sd | 5bd86f0662bd55704109a794c6a1b1790ea0f91a | 2022-03-25T12:06:46.000Z | [
"pytorch",
"wavlm",
"audio-frame-classification",
"en",
"arxiv:1912.07875",
"arxiv:2106.06909",
"arxiv:2101.00390",
"arxiv:2110.13900",
"transformers",
"speech"
] | null | false | microsoft | null | microsoft/wavlm-base-plus-sd | 236 | 2 | transformers | 3,386 | ---
language:
- en
tags:
- speech
---
# WavLM-Base-Plus for Speaker Diarization
[Microsoft's WavLM](https://github.com/microsoft/unilm/tree/master/wavlm)
The model was pretrained on 16kHz sampled speech audio with utterance and speaker contrastive loss. When using the model, make sure that your speech input is also ... |
moussaKam/frugalscore_medium_bert-base_bert-score | 035612750d1c8e1d7a13ec64f7886f0a6e80943e | 2022-02-01T10:50:43.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:2110.08559",
"transformers"
] | text-classification | false | moussaKam | null | moussaKam/frugalscore_medium_bert-base_bert-score | 236 | null | transformers | 3,387 | # FrugalScore
FrugalScore is an approach to learn a fixed, low cost version of any expensive NLG metric, while retaining most of its original performance
Paper: https://arxiv.org/abs/2110.08559?context=cs
Project github: https://github.com/moussaKam/FrugalScore
The pretrained checkpoints presented in the paper :
| ... |
niharikadeokar/DialoGPT-small-Jakebot | d95c68a84f5711c87470c42d7e86959a1c7eb5b0 | 2021-12-03T05:46:22.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | niharikadeokar | null | niharikadeokar/DialoGPT-small-Jakebot | 236 | null | transformers | 3,388 | ---
tags:
- conversational
---
# Jake Peralta DialoGPT Model |
Aquasp34/DialoGPT-small-aqua1 | 976f9aa228c0cc184440eeb701b9285902bf3aa5 | 2022-03-03T20:44:13.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"lm-head",
"casual-lm"
] | conversational | false | Aquasp34 | null | Aquasp34/DialoGPT-small-aqua1 | 236 | null | transformers | 3,389 | ---
tags:
- conversational
- lm-head
- casual-lm
---
# Aqua Model |
burakaytan/roberta-base-turkish-uncased | 4bbeca17433c0b7064d073d7b23b7adce47d577a | 2022-05-18T08:18:20.000Z | [
"pytorch",
"roberta",
"fill-mask",
"tr",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | burakaytan | null | burakaytan/roberta-base-turkish-uncased | 236 | 5 | transformers | 3,390 | ---
language: tr
license: mit
---
🇹🇷 RoBERTaTurk
## Model description
This is a Turkish RoBERTa base model pretrained on Turkish Wikipedia, Turkish OSCAR, and some news websites.
The final training corpus has a size of 38 GB and 329.720.508 sentences.
Thanks to Turkcell we could train the model on Intel(R) Xeon(R)... |
QuoQA-NLP/KE-T5-Ko2En-Base | d520ebe60951bfdec650f9377db53f61a207701c | 2022-07-12T04:55:34.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | QuoQA-NLP | null | QuoQA-NLP/KE-T5-Ko2En-Base | 236 | null | transformers | 3,391 | Entry not found |
bespin-global/klue-sentence-roberta-base-kornlu | e0560226adca8f9a7b291528846f67d7489ee44b | 2022-02-07T07:14:21.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"dataset:kor_nlu",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:cc-by-nc-4.0"
] | sentence-similarity | false | bespin-global | null | bespin-global/klue-sentence-roberta-base-kornlu | 235 | null | sentence-transformers | 3,392 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
datasets:
- kor_nlu
license: cc-by-nc-4.0
---
# bespin-global/klue-sentence-roberta-kornlu
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 7... |
doc2query/S2ORC-t5-base-v1 | 10903c6b1a2ecc8728fff62a4b9725b6b72a242c | 2021-10-27T10:04:09.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:S2ORC",
"arxiv:1904.08375",
"arxiv:2104.08663",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | doc2query | null | doc2query/S2ORC-t5-base-v1 | 235 | 1 | transformers | 3,393 | ---
language: en
datasets:
- S2ORC
widget:
- text: "Python is an interpreted, high-level and general-purpose programming language. Python's design philosophy emphasizes code readability with its notable use of significant whitespace. Its language constructs and object-oriented approach aim to help programmers writ... |
elgeish/gpt2-medium-arabic-poetry | 34f7d39e7e64eafcd76e7040657406b5235a49a1 | 2021-05-21T15:45:14.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"ar",
"dataset:Arabic Poetry Dataset (6th - 21st century)",
"transformers",
"poetry",
"license:apache-2.0",
"model-index"
] | text-generation | false | elgeish | null | elgeish/gpt2-medium-arabic-poetry | 235 | 2 | transformers | 3,394 | ---
language: ar
datasets:
- Arabic Poetry Dataset (6th - 21st century)
metrics:
- perplexity
tags:
- text-generation
- poetry
license: apache-2.0
widget:
- text: "للوهلة الأولى قرأت في عينيه"
model-index:
- name: elgeish Arabic GPT2 Medium
results:
- task:
name: Text Generation
type: text-generation
... |
facebook/detr-resnet-101-dc5 | ad4955b9a3e68e213ec74f1866909630e32e7f7d | 2021-11-03T16:18:45.000Z | [
"pytorch",
"detr",
"object-detection",
"dataset:coco",
"arxiv:2005.12872",
"transformers",
"license:apache-2.0"
] | object-detection | false | facebook | null | facebook/detr-resnet-101-dc5 | 235 | 2 | transformers | 3,395 | ---
license: apache-2.0
tags:
- object-detection
datasets:
- coco
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
example_title: Savanna
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
example_title: Football Match
- src: https... |
ntjrrvarma/DialoGPT-small-RickBot | 8c4af00c08ff5a13f5e786b36cc9daad84830042 | 2021-08-27T17:04:24.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ntjrrvarma | null | ntjrrvarma/DialoGPT-small-RickBot | 235 | null | transformers | 3,396 | ---
tags:
- conversational
---
# Rick DialoGPT Model |
sonoisa/t5-base-japanese-title-generation | 24a55d13c29dad961e761da31fc1febae84e6fda | 2022-02-21T13:38:09.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ja",
"transformers",
"seq2seq",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | sonoisa | null | sonoisa/t5-base-japanese-title-generation | 235 | 1 | transformers | 3,397 | ---
language: ja
tags:
- t5
- text2text-generation
- seq2seq
license: cc-by-sa-4.0
---
# 記事本文からタイトルを生成するモデル
SEE: https://qiita.com/sonoisa/items/a9af64ff641f0bbfed44 |
Cirilaron/DialoGPT-medium-raiden | 335c38f00b609cdf8a7be5541700b3aae04e9e2a | 2022-06-05T10:22:54.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Cirilaron | null | Cirilaron/DialoGPT-medium-raiden | 235 | null | transformers | 3,398 | ---
tags:
- conversational
---
#Raiden from Metal Gear Rising DialoGPT Model |
arem/DialoGPT-medium-rickandmorty | 81abe8ebbb35d8da2ae95026a33cfb9ca154b567 | 2022-06-24T08:48:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | arem | null | arem/DialoGPT-medium-rickandmorty | 235 | null | transformers | 3,399 | ---
tags:
- conversational
---
# Try my rick, it responds. |
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