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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
softcatala/fullstop-catalan-punctuation-prediction | 4b26218160a6efed8b99f7f5167269f57dcc25aa | 2022-04-06T12:45:54.000Z | [
"pytorch",
"roberta",
"token-classification",
"ca",
"dataset:softcatala/Europarl-catalan",
"transformers",
"punctuation prediction",
"punctuation",
"autotrain_compatible"
] | token-classification | false | softcatala | null | softcatala/fullstop-catalan-punctuation-prediction | 204 | null | transformers | 3,600 | ---
language:
- ca
tags:
- punctuation prediction
- punctuation
datasets: softcatala/Europarl-catalan
widget:
- text: "Els investigadors suggereixen que tot i que es tracta de la cua d'un dinosaure jove la mostra revela un plomatge adult i no pas plomissol"
example_title: "Catalan"
metrics:
- f1
---
This model predi... |
EMBO/BioMegatron345mUncased | ab9ac883b103dbb83e55f3b7a416fffcebff4e1b | 2022-07-26T06:50:35.000Z | [
"pytorch",
"megatron-bert",
"en",
"arxiv:2010.06060",
"transformers",
"language model",
"license:cc-by-4.0"
] | null | false | EMBO | null | EMBO/BioMegatron345mUncased | 204 | 1 | transformers | 3,601 | ---
license: cc-by-4.0
language:
- en
thumbnail:
tags:
- language model
---
!---
# ##############################################################################################
#
# This model has been uploaded to HuggingFace by https://huggingface.co/drAbreu
# The model is based on the NVIDIA checkpoint located at... |
SharpAI/mal_tls | 735a8d55f96d3bbbb035834ed8c82df7c8ba9ae2 | 2022-07-27T18:04:04.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"transformers",
"generated_from_keras_callback",
"model-index"
] | text-classification | false | SharpAI | null | SharpAI/mal_tls | 204 | null | transformers | 3,602 | ---
tags:
- generated_from_keras_callback
model-index:
- name: mal_tls
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. -->
# mal_tls
This model is a fine-tuned version of... |
PlanTL-GOB-ES/roberta-base-bne-capitel-ner-plus | 754e83ed79884f3ce74674711f002d95ae5f065e | 2022-04-06T14:43:21.000Z | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | PlanTL-GOB-ES | null | PlanTL-GOB-ES/roberta-base-bne-capitel-ner-plus | 203 | 4 | transformers | 3,603 | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
- "capitel"
- "ner"
datasets:
- "bne"
- "capitel"
metrics:
- "f1"
inference:
parameters:
aggregation_strategy: "first"
---
# Spanish RoBERTa-base trained on BNE finetuned for CAPITEL Named Entity Recognition (NER) d... |
google/vit-large-patch16-384 | 4b143e77059a54c70b348a76677ab9946f584e13 | 2022-01-28T10:22:26.000Z | [
"pytorch",
"tf",
"jax",
"vit",
"image-classification",
"dataset:imagenet",
"dataset:imagenet-21k",
"arxiv:2010.11929",
"arxiv:2006.03677",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | google | null | google/vit-large-patch16-384 | 203 | 2 | transformers | 3,604 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
- imagenet-21k
---
# Vision Transformer (large-sized model)
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000... |
mrm8488/bert2bert_shared-spanish-finetuned-paus-x-paraphrasing | e5fcd441a0b0e6fc55c87b3c89915623941a9426 | 2021-07-31T05:12:47.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"es",
"dataset:pausx",
"transformers",
"spanish",
"paraphrasing",
"paraphrase",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/bert2bert_shared-spanish-finetuned-paus-x-paraphrasing | 203 | 2 | transformers | 3,605 | ---
language: es
datasets:
- pausx
tags:
- spanish
- paraphrasing
- paraphrase
widget:
- text: "El pionero suizo John Sutter (1803-1880) llegó a Alta California con otros colonos euroamericanos en agosto de 1839."
---
# Spanish Bert2Bert (shared) fine-tuned on PAUS-X es for paraphrasing |
HooshvareLab/bert-fa-base-uncased-sentiment-digikala | 88db8245349b36b47ef1b92e49b8b80428b77d7c | 2021-05-18T20:59:17.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"fa",
"transformers",
"license:apache-2.0"
] | text-classification | false | HooshvareLab | null | HooshvareLab/bert-fa-base-uncased-sentiment-digikala | 202 | null | transformers | 3,606 | ---
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](... |
abhi1nandy2/EManuals_RoBERTa | b6fe473485f493db94fe67b8fa9d62bd3d0a43b9 | 2022-05-04T04:57:53.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"English",
"transformers",
"EManuals",
"customer support",
"QA"
] | feature-extraction | false | abhi1nandy2 | null | abhi1nandy2/EManuals_RoBERTa | 202 | null | transformers | 3,607 | ---
language:
- English
tags:
- EManuals
- customer support
- QA
- roberta
---
Refer to https://aclanthology.org/2021.findings-emnlp.392/ for the paper and https://sites.google.com/view/emanualqa/home for the project website
## Citation
Please cite the work if you would like to use it.
```
@inproceedings{nandy-... |
af-ai-center/bert-base-swedish-uncased | 5c7fb9dbad916c7c9738751e8ee117b186f7da91 | 2021-05-18T23:12:14.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | af-ai-center | null | af-ai-center/bert-base-swedish-uncased | 202 | null | transformers | 3,608 | Entry not found |
suhasjain/DailoGPT-small-harrypotter | 27baccd28f5226a79ac26499d6ed6e8feeaba056 | 2021-09-10T08:47:17.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | suhasjain | null | suhasjain/DailoGPT-small-harrypotter | 202 | null | transformers | 3,609 | ---
tags:
- conversational
---
#Harry Potter DialoGPT Model |
yoshitomo-matsubara/bert-base-uncased-mrpc | 6a95d3c0ae14ab6bf2dccfaaa5bf6ee16b2a5172 | 2021-05-29T21:47:37.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:mrpc",
"transformers",
"mrpc",
"glue",
"torchdistill",
"license:apache-2.0"
] | text-classification | false | yoshitomo-matsubara | null | yoshitomo-matsubara/bert-base-uncased-mrpc | 202 | null | transformers | 3,610 | ---
language: en
tags:
- bert
- mrpc
- glue
- torchdistill
license: apache-2.0
datasets:
- mrpc
metrics:
- f1
- accuracy
---
`bert-base-uncased` fine-tuned on MRPC dataset, using [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Colab](https://colab.research.google.com/github/yoshit... |
deepset/gelectra-base-generator | ba9ac3432c2c9904460f59343f1fb80d4c0a0740 | 2021-10-21T12:18:27.000Z | [
"pytorch",
"tf",
"electra",
"fill-mask",
"de",
"dataset:wikipedia",
"dataset:OPUS",
"dataset:OpenLegalData",
"arxiv:2010.10906",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | deepset | null | deepset/gelectra-base-generator | 201 | 3 | transformers | 3,611 | ---
language: de
license: mit
datasets:
- wikipedia
- OPUS
- OpenLegalData
---
# German ELECTRA base 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 dbmdz BERT (a... |
hakurei/lit-125M | f1e7a551a28ee8ad2e982d5425a07e1d59b4be65 | 2022-02-17T22:52:19.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"en",
"transformers",
"causal-lm",
"license:mit"
] | text-generation | false | hakurei | null | hakurei/lit-125M | 201 | null | transformers | 3,612 | ---
language:
- en
tags:
- pytorch
- causal-lm
license: mit
---
# Lit-125M - A Small Fine-tuned Model For Fictional Storytelling
Lit-125M is a GPT-Neo 125M model fine-tuned on 2GB of a diverse range of light novels, erotica, and annotated literature for the purpose of generating novel-like fictional text.
## Model... |
huggingface/funnel-small | 3829c82f3a863632e1726bfe4ecf950a726689df | 2020-08-31T21:06:56.000Z | [
"pytorch",
"funnel",
"feature-extraction",
"transformers"
] | feature-extraction | false | huggingface | null | huggingface/funnel-small | 201 | null | transformers | 3,613 | Entry not found |
hyunwoongko/blenderbot-9B | 20049263e5130cc21015f3327085fb3adbc39939 | 2021-06-17T01:26:34.000Z | [
"pytorch",
"blenderbot",
"text2text-generation",
"en",
"dataset:blended_skill_talk",
"arxiv:1907.06616",
"transformers",
"convAI",
"conversational",
"facebook",
"license:apache-2.0",
"autotrain_compatible"
] | conversational | false | hyunwoongko | null | hyunwoongko/blenderbot-9B | 201 | 5 | transformers | 3,614 | ---
language:
- en
thumbnail:
tags:
- convAI
- conversational
- facebook
license: apache-2.0
datasets:
- blended_skill_talk
metrics:
- perplexity
---
## Model description
+ Paper: [Recipes for building an open-domain chatbot](https://arxiv.org/abs/1907.06616)
+ [Original PARLAI Code](https://parl.ai/projects/recipes... |
lisaterumi/genia-biobert-ent | 929329e6c4611a8add9409d97e0727ea8cfe9e63 | 2022-07-22T21:40:15.000Z | [
"pytorch",
"bert",
"token-classification",
"en",
"dataset:Genia",
"transformers",
"autotrain_compatible"
] | token-classification | false | lisaterumi | null | lisaterumi/genia-biobert-ent | 201 | null | transformers | 3,615 | ---
language: "en"
widget:
- text: "Point mutation of a GATA-1 site at -230 reduced promoter activity by 37%."
- text: "Electrophoretic mobility shift assays indicated that the -230 GATA-1 site has a relatively low affinity for GATA-1."
- text: "Accordingly, the effects of the constitutively active PKCs were compared t... |
xlm-mlm-17-1280 | ed2e1c862c37217e1b185c33a282ed8f3ebdc3e2 | 2022-07-22T08:09:41.000Z | [
"pytorch",
"tf",
"xlm",
"fill-mask",
"multilingual",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"sv",
"pl",
"ru",
"ar",
"tr",
"zh",
"ja",
"ko",
"hi",
"vi",
"arxiv:1901.07291",
"arxiv:1911.02116",
"arxiv:1910.09700",
"transformers",
"license:cc-by-nc-4.0",
"autotr... | fill-mask | false | null | null | xlm-mlm-17-1280 | 200 | 1 | transformers | 3,616 | ---
language:
- multilingual
- en
- fr
- es
- de
- it
- pt
- nl
- sv
- pl
- ru
- ar
- tr
- zh
- ja
- ko
- hi
- vi
license: cc-by-nc-4.0
---
# xlm-mlm-17-1280
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training](#training... |
Helsinki-NLP/opus-mt-en-bg | f3d8448586d3626a38582ec5ff9e61f7d5940255 | 2021-01-18T08:05:27.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"bg",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-bg | 200 | null | transformers | 3,617 | ---
language:
- en
- bg
tags:
- translation
license: apache-2.0
---
### eng-bul
* source group: English
* target group: Bulgarian
* OPUS readme: [eng-bul](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-bul/README.md)
* model: transformer
* source language(s): eng
* target language(s)... |
Helsinki-NLP/opus-mt-gem-en | a0433c2234bd6b0ee27e493c1d47ba46322312bc | 2021-01-18T08:51:56.000Z | [
"pytorch",
"marian",
"text2text-generation",
"da",
"sv",
"af",
"nn",
"fy",
"fo",
"de",
"nb",
"nl",
"is",
"en",
"lb",
"yi",
"gem",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-gem-en | 200 | 1 | transformers | 3,618 | ---
language:
- da
- sv
- af
- nn
- fy
- fo
- de
- nb
- nl
- is
- en
- lb
- yi
- gem
tags:
- translation
license: apache-2.0
---
### gem-eng
* source group: Germanic languages
* target group: English
* OPUS readme: [gem-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gem-eng/README.md)... |
Helsinki-NLP/opus-mt-pa-en | e501d2bca4de5b63384fcdafc6b6185433efb4a9 | 2021-09-10T14:00:06.000Z | [
"pytorch",
"marian",
"text2text-generation",
"pa",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-pa-en | 200 | null | transformers | 3,619 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-pa-en
* source languages: pa
* target languages: en
* OPUS readme: [pa-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/pa-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
ShannonAI/ChineseBERT-base | aa8b6fa9c3427f77b0911b07ab35f2b1b8bf248b | 2022-06-19T08:14:46.000Z | [
"pytorch",
"arxiv:2106.16038"
] | null | false | ShannonAI | null | ShannonAI/ChineseBERT-base | 200 | 6 | null | 3,620 | # ChineseBERT-base
This repository contains code, model, dataset for **ChineseBERT** at ACL2021.
paper:
**[ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information](https://arxiv.org/abs/2106.16038)**
*Zijun Sun, Xiaoya Li, Xiaofei Sun, Yuxian Meng, Xiang Ao, Qing He, Fei Wu and Jiwei Li*
code: ... |
facebook/wav2vec2-large-xlsr-53-dutch | ced00f8603b017d58cb3bcb3883e8c28f19ccdb4 | 2021-07-06T02:35:35.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:common_voice",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-large-xlsr-53-dutch | 200 | null | transformers | 3,621 | ---
language: nl
datasets:
- common_voice
tags:
- speech
- audio
- automatic-speech-recognition
license: apache-2.0
---
## Evaluation on Common Voice NL Test
```python
import torchaudio
from datasets import load_dataset, load_metric
from transformers import (
Wav2Vec2ForCTC,
Wav2Vec2Processor,
)
import torch
... |
maxidl/wav2vec2-large-xlsr-german | 893c0ff874902327f50822f871ff78e4f584fbf5 | 2021-07-06T12:32:21.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | maxidl | null | maxidl/wav2vec2-large-xlsr-german | 200 | null | transformers | 3,622 | ---
language: de
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: {XLSR Wav2Vec2 Large 53 CV-de}
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
... |
pierrerappolt/cart | e1b8e44a537f4a3355859982f3327d4478eb4797 | 2022-03-27T02:53:44.000Z | [
"pytorch",
"roberta",
"question-answering",
"en",
"dataset:squadv2",
"transformers",
"html",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | false | pierrerappolt | null | pierrerappolt/cart | 200 | null | transformers | 3,623 | ---
language: en
tags:
- html
license: apache-2.0
datasets:
- squadv2
inference:
parameters:
handle_impossible_answer: true
---
Txt |
facebook/deit-tiny-distilled-patch16-224 | 488ad407f8f6bcfc79829ece3507658c46d15563 | 2022-07-13T11:41:55.000Z | [
"pytorch",
"tf",
"deit",
"image-classification",
"dataset:imagenet",
"arxiv:2012.12877",
"arxiv:2006.03677",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/deit-tiny-distilled-patch16-224 | 199 | 1 | transformers | 3,624 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
---
# Distilled Data-efficient Image Transformer (tiny-sized model)
Distilled data-efficient Image Transformer (DeiT) model pre-trained and fine-tuned on ImageNet-1k (1 million images, 1,000 classes) at resolution 224x224. It was firs... |
liaad/srl-en_xlmr-large | 93bf9d8074ab8794d705a1774ec2e7f33e25919c | 2021-09-22T08:56:14.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"multilingual",
"pt",
"en",
"dataset:PropBank.Br",
"dataset:CoNLL-2012",
"arxiv:2101.01213",
"transformers",
"xlm-roberta-large",
"semantic role labeling",
"finetuned",
"license:apache-2.0"
] | feature-extraction | false | liaad | null | liaad/srl-en_xlmr-large | 199 | null | transformers | 3,625 | ---
language:
- multilingual
- pt
- en
tags:
- xlm-roberta-large
- semantic role labeling
- finetuned
license: apache-2.0
datasets:
- PropBank.Br
- CoNLL-2012
metrics:
- F1 Measure
---
# XLM-R large fine-tuned on English semantic role labeling
## Model description
This model is the [`xlm-roberta-large`](https:... |
facebook/regnet-y-320-seer | 1b737c5ac08d98ca903d2c1d87d2c83e95df054e | 2022-06-30T10:21:14.000Z | [
"pytorch",
"tf",
"regnet",
"feature-extraction",
"arxiv:2202.08360",
"transformers",
"vision",
"license:apache-2.0"
] | feature-extraction | false | facebook | null | facebook/regnet-y-320-seer | 199 | null | transformers | 3,626 | ---
license: apache-2.0
tags:
- vision
widgets:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https://huggingface.co/datasets/mishig/sample_im... |
Chemsseddine/bert2gpt2SUMM-finetuned-mlsum | 21c2f20b157fac797f5b45eb23163c1a5f8c4d59 | 2022-06-30T19:54:06.000Z | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"fr",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | Chemsseddine | null | Chemsseddine/bert2gpt2SUMM-finetuned-mlsum | 199 | null | transformers | 3,627 | ---
language: fr
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bert2gpt2_med_ml_orange_summ-finetuned_med_sum_new-finetuned_med_sum_new
results: []
---
<img src="https://huggingface.co/Chemsseddine/bert2gpt2_med_ml_orange_summ-finetuned_med_sum_new-finetuned_med_sum_new/reso... |
justheuristic/test-bloomd-350m | e839f6d8cfb0061ee1100c3ddde71db8a7576f6c | 2022-07-07T01:20:37.000Z | [
"pytorch",
"bloom",
"transformers"
] | null | false | justheuristic | null | justheuristic/test-bloomd-350m | 199 | null | transformers | 3,628 | Entry not found |
Helsinki-NLP/opus-mt-yo-en | 94685c1b0eb549569c394538ccd482b6132321a0 | 2021-09-11T10:52:45.000Z | [
"pytorch",
"marian",
"text2text-generation",
"yo",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-yo-en | 198 | null | transformers | 3,629 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-yo-en
* source languages: yo
* target languages: en
* OPUS readme: [yo-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yo-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
aware-ai/byt5-german-grammar | 8ab29798880b659a170a97a3ec9626a28e46ed3f | 2021-06-23T12:20:22.000Z | [
"pytorch",
"t5",
"text2text-generation",
"de",
"transformers",
"grammar",
"autotrain_compatible"
] | text2text-generation | false | aware-ai | null | aware-ai/byt5-german-grammar | 198 | 1 | transformers | 3,630 | ---
language: de
tags:
- grammar
widget:
- text: "correct german grammar: es ist schön so viele tolle menschen um sich zu haben denn ohne sie wäre es nicht so schön"
---
example outputs:
input: ich liebe das leben --> output: Ich liebe das Leben.
input: es ist schön so viele tolle menschen um sich zu haben denn ohne... |
persiannlp/mt5-large-parsinlu-translation_en_fa | 53fec354caa45718befa6f016a8f515a43ca8cd4 | 2021-09-23T16:20:29.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"transformers",
"machine-translation",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-large-parsinlu-translation_en_fa | 198 | null | transformers | 3,631 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- machine-translation
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- sacrebleu
---
# Machine Translation (ترجمهی ماشینی)
This is an mT5-based model for machine translatio... |
sismetanin/xlm_roberta_base-ru-sentiment-rusentiment | 611b0acab81780953a2477cf1e17ddc4429b396f | 2021-02-25T23:57:49.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ru",
"transformers",
"sentiment analysis",
"Russian"
] | text-classification | false | sismetanin | null | sismetanin/xlm_roberta_base-ru-sentiment-rusentiment | 198 | null | transformers | 3,632 | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## XML-RoBERTa-Base-ru-sentiment-RuSentiment
XML-RoBERTa-Base-ru-sentiment-RuSentiment is a [XML-RoBERTa-Base](https://huggingface.co/xlm-roberta-base) model fine-tuned on [RuSentiment dataset](https://github.com/text-machine-lab/rusentiment) of general-dom... |
nlpaueb/sec-bert-shape | 9829e591d1c801f9dcd887365d97da179a71b53e | 2022-04-28T14:46:51.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2203.06482",
"transformers",
"finance",
"financial",
"license:cc-by-sa-4.0",
"fill-mask"
] | fill-mask | false | nlpaueb | null | nlpaueb/sec-bert-shape | 198 | 6 | transformers | 3,633 | ---
language: en
pipeline_tag: fill-mask
license: cc-by-sa-4.0
thumbnail: https://i.ibb.co/0yz81K9/sec-bert-logo.png
tags:
- finance
- financial
widget:
- text: "Total net sales decreased [MASK]% or $[X.X] billion during [XXXX] compared to [XXXX]"
- text: "Total net sales decreased [X]% or $[MASK] billion dur... |
AIDA-UPM/MSTSb_stsb-xlm-r-multilingual | eea01579b009257faffea3516c0da1f89f2d99ba | 2021-07-21T18:32:31.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | AIDA-UPM | null | AIDA-UPM/MSTSb_stsb-xlm-r-multilingual | 197 | null | sentence-transformers | 3,634 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluster... |
Intel/bert-large-uncased-sparse-90-unstructured-pruneofa | 29c4f2d3eef81d3960cf87b214516a49398c09ed | 2022-01-13T12:13:38.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"dataset:wikipedia",
"dataset:bookcorpus",
"arxiv:2111.05754",
"transformers",
"fill-mask"
] | fill-mask | false | Intel | null | Intel/bert-large-uncased-sparse-90-unstructured-pruneofa | 197 | null | transformers | 3,635 | ---
language: en
tags: fill-mask
datasets:
- wikipedia
- bookcorpus
---
# 90% Sparse BERT-Large (uncased) Prune OFA
This model is a result from our paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754) presented in ENLSP NeurIPS Workshop 2021.
For further details on the mode... |
Norod78/hebrew-gpt_neo-xl | 56f66a33c04fc5b0499b0f143ec08abc7ca436a2 | 2022-07-04T13:09:16.000Z | [
"pytorch",
"jax",
"gpt_neo",
"text-generation",
"he",
"transformers",
"license:mit"
] | text-generation | false | Norod78 | null | Norod78/hebrew-gpt_neo-xl | 197 | 1 | transformers | 3,636 | ---
language: he
thumbnail: https://avatars1.githubusercontent.com/u/3617152?norod.jpg
widget:
- text: "עוד בימי קדם"
- text: "קוראים לי דורון ואני מעוניין ל"
- text: "קוראים לי איציק ואני חושב ש"
- text: "החתול שלך מאוד חמוד ו"
- text: "ובדרך ראינו שהגן"
license: mit
---
# hebrew-gpt_neo-xl
Hebrew text generation ... |
comodoro/wav2vec2-xls-r-300m-cs-250 | 5d17dcbb516fa3532bb9b6ce4dc20d4779993142 | 2022-03-23T18:26:50.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"cs",
"dataset:mozilla-foundation/common_voice_8_0",
"dataset:ovm",
"dataset:pscr",
"dataset:vystadial2016",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
... | automatic-speech-recognition | false | comodoro | null | comodoro/wav2vec2-xls-r-300m-cs-250 | 197 | null | transformers | 3,637 | ---
language:
- cs
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- xlsr-fine-tuning-week
datasets:
- mozilla-foundation/common_voice_8_0
- ovm
- pscr
- vystadial2016
model-index:
- name: Czech comodoro W... |
filco306/gpt2-switchboard-paraphraser | c12a7bd906a6d45768ed4860bc2b08a533c6e5dd | 2021-08-28T23:33:47.000Z | [
"pytorch",
"text-generation",
"arxiv:2010.05700",
"transformers"
] | text-generation | false | filco306 | null | filco306/gpt2-switchboard-paraphraser | 197 | null | transformers | 3,638 | # GPT2 Switchboard style transfer paraphraser
This is the trained Switchboard-model from the paper [Reformulating Unsupervised Style Transfer as Paraphrase Generation](https://arxiv.org/abs/2010.05700) by Krishna K. et al. Note that I (the uploader) am not the author of the paper. Permission to upload to Huggingface w... |
neuropark/sahajBERT | e9159abbb5f8b352cc5ec59bababc66ba5382bb4 | 2021-06-24T16:49:26.000Z | [
"pytorch",
"albert",
"pretraining",
"bn",
"dataset:Wikipedia",
"dataset:Oscar",
"arxiv:1909.11942",
"transformers",
"collaborative",
"bengali",
"bangla",
"license:apache-2.0",
"fill-mask"
] | fill-mask | false | neuropark | null | neuropark/sahajBERT | 197 | 7 | transformers | 3,639 | ---
language: bn
tags:
- collaborative
- bengali
- albert
- bangla
license: apache-2.0
datasets:
- Wikipedia
- Oscar
widget:
- text: "জীবনে সবচেয়ে মূল্যবান জিনিস হচ্ছে [MASK]।"
pipeline_tag: fill-mask
---
# sahajBERT
<iframe width="100%" height="1100" frameborder="0"
src="https://observablehq.com/emb... |
pucpr/clinicalnerpt-medical | 0d889f90b203734b0ba45904781a6779c8eac2b9 | 2021-10-13T09:28:28.000Z | [
"pytorch",
"bert",
"token-classification",
"pt",
"dataset:SemClinBr",
"transformers",
"autotrain_compatible"
] | token-classification | false | pucpr | null | pucpr/clinicalnerpt-medical | 197 | 3 | transformers | 3,640 | ---
language: "pt"
widget:
- text: "Hoje realizou avaliacao de mp-cdi, com eletrodos atrial e ventricular."
- text: "Paciente encaminhado a câmera hiperbárica no período da tarde."
datasets:
- SemClinBr
thumbnail: "https://raw.githubusercontent.com/HAILab-PUCPR/BioBERTpt/master/images/logo-biobertpr1.png"
---
<img ... |
raynardj/wenyanwen-ancient-translate-to-modern | 164ab975150c37dcdf1bd2e782e2edd4b1add10c | 2022-01-08T04:22:30.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"zh",
"transformers",
"translation",
"古文",
"文言文",
"ancient",
"classical",
"autotrain_compatible"
] | translation | false | raynardj | null | raynardj/wenyanwen-ancient-translate-to-modern | 197 | 3 | transformers | 3,641 | ---
language:
- zh
- zh
tags:
- translation
- 古文
- 文言文
- ancient
- classical
widget:
- text: "此诚危急存亡之秋也"
---
# From Classical(ancient) Chinese to Modern Chinese
> This model translate Classical(ancient) Chinese to Modern Chinese, so I guess who's interested in the problemset can speak at least modern Chinese, hence..... |
tals/albert-base-vitaminc_wnei-fever | 01a830a7f0c8cf62df0b5d29b473179cdf21c525 | 2022-06-22T23:56:28.000Z | [
"pytorch",
"albert",
"text-classification",
"python",
"dataset:fever",
"dataset:glue",
"dataset:tals/vitaminc",
"transformers"
] | text-classification | false | tals | null | tals/albert-base-vitaminc_wnei-fever | 197 | null | transformers | 3,642 | ---
language: python
datasets:
- fever
- glue
- tals/vitaminc
---
# Details
Model used in [Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://aclanthology.org/2021.naacl-main.52/) (Schuster et al., NAACL 21`).
For more details see: https://github.com/TalSchuster/VitaminC
When using this m... |
unicamp-dl/ptt5-small-portuguese-vocab | 79a744f213b1f3a1a95f27f2230202440be253d1 | 2021-06-23T14:34:42.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"pt",
"dataset:brWaC",
"transformers",
"tensorflow",
"pt-br",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | unicamp-dl | null | unicamp-dl/ptt5-small-portuguese-vocab | 197 | null | transformers | 3,643 | ---
language: pt
license: mit
tags:
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- brWaC
widget:
- text: "Texto de exemplo em português"
inference: false
---
# Portuguese T5 (aka "PTT5")
## Introduction
PTT5 is a T5 model pretrained in the BrWac corpus, a large collection of web pages in Portuguese, improvi... |
hellonesh/test_fine_tuned_crossencoder | a93a54a1b47b64fafab55a53cc80c7879096541b | 2022-07-20T23:21:23.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | hellonesh | null | hellonesh/test_fine_tuned_crossencoder | 197 | null | transformers | 3,644 | Entry not found |
KoichiYasuoka/roberta-classical-chinese-large-char | 6cb9aed2abae0da5fd17c5751598bdaeeb81cc3d | 2021-10-30T00:38:19.000Z | [
"pytorch",
"roberta",
"fill-mask",
"lzh",
"transformers",
"classical chinese",
"literary chinese",
"ancient chinese",
"masked-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | KoichiYasuoka | null | KoichiYasuoka/roberta-classical-chinese-large-char | 196 | null | transformers | 3,645 | ---
language:
- "lzh"
tags:
- "classical chinese"
- "literary chinese"
- "ancient chinese"
- "masked-lm"
license: "apache-2.0"
pipeline_tag: "fill-mask"
mask_token: "[MASK]"
widget:
- text: "孟子[MASK]梁惠王"
---
# roberta-classical-chinese-large-char
## Model Description
This is a RoBERTa model pre-trained on Classical ... |
asapp/sew-tiny-100k-ft-ls100h | a750ca77c83e5595081eddb05926c9b432684116 | 2022-05-24T12:53:02.000Z | [
"pytorch",
"sew",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"arxiv:2109.06870",
"transformers",
"audio",
"speech",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | asapp | null | asapp/sew-tiny-100k-ft-ls100h | 196 | null | transformers | 3,646 | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- speech
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: https://cdn-media.hug... |
federicopascual/finetuning-sentiment-model-3000-samples | 11f7d327123ebcddd97304c57084c6365628dda5 | 2021-12-30T20:59:20.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | federicopascual | null | federicopascual/finetuning-sentiment-model-3000-samples | 196 | null | transformers | 3,647 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
met... |
flax-community/t5-base-wikisplit | 2aafb7c5b0409872cea248eb548aba7405797d83 | 2021-07-21T08:56:00.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | flax-community | null | flax-community/t5-base-wikisplit | 196 | 1 | transformers | 3,648 | Entry not found |
nandinib1999/quote-generator | 43fed603ac9d6e99afba01ae8924b57630a3142c | 2022-03-06T12:04:44.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:quotes-500K",
"transformers",
"text generation",
"license:cc"
] | text-generation | false | nandinib1999 | null | nandinib1999/quote-generator | 196 | 2 | transformers | 3,649 | ---
language:
- en
thumbnail:
tags:
- text generation
license: cc
datasets:
- quotes-500K
metrics:
- perplexity
---
# Quotes Generator
## Model description
This is a GPT2 model fine-tuned on the Quotes-500K dataset.
## Intended uses & limitations
For a given user prompt, it can generate motivational quotes s... |
qanastek/pos-french | b377b7ff5d5b93286e8b3103104d7e5135d5f5be | 2022-07-06T23:48:25.000Z | [
"pytorch",
"fr",
"dataset:qanastek/ANTILLES",
"flair",
"token-classification",
"sequence-tagger-model"
] | token-classification | false | qanastek | null | qanastek/pos-french | 196 | 1 | flair | 3,650 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: fr
datasets:
- qanastek/ANTILLES
widget:
- text: "George Washington est allé à Washington"
---
# POET: A French Extended Part-of-Speech Tagger
- Corpora: [ANTILLES](https://github.com/qanastek/ANTILLES)
- Embeddings: [FastText](https://fasttex... |
google/ddpm-church-256 | 14e3c702d021d2563e924f2682ac4bd31464f888 | 2022-07-21T15:00:14.000Z | [
"diffusers",
"arxiv:2006.11239",
"pytorch",
"unconditional-image-generation",
"license:apache-2.0"
] | unconditional-image-generation | false | google | null | google/ddpm-church-256 | 196 | null | diffusers | 3,651 | ---
license: apache-2.0
tags:
- pytorch
- diffusers
- unconditional-image-generation
---
# Denoising Diffusion Probabilistic Models (DDPM)
**Paper**: [Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239)
**Authors**: Jonathan Ho, Ajay Jain, Pieter Abbeel
**Abstract**:
*We present high qualit... |
Geotrend/distilbert-base-es-cased | d1a2feac7e5bdd65b5d659d766a80315a1e075a5 | 2021-08-16T13:26:35.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"es",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/distilbert-base-es-cased | 195 | null | transformers | 3,652 | ---
language: es
datasets: wikipedia
license: apache-2.0
---
# distilbert-base-es-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... |
SkolkovoInstitute/xlmr_formality_classifier | b491648728ab0fab087598e4eea3e123be7155e6 | 2022-01-09T17:55:13.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"en",
"fr",
"it",
"pt",
"transformers",
"formal or informal classification"
] | text-classification | false | SkolkovoInstitute | null | SkolkovoInstitute/xlmr_formality_classifier | 195 | 0 | transformers | 3,653 | ---
language:
- en
- fr
- it
- pt
tags:
- formal or informal classification
licenses:
- cc-by-nc-sa
---
XLMRoberta-based classifier trained on XFORMAL.
all
| | precision | recall | f1-score | support |
|--------------|-----------|----------|----------|---------|
| 0 | 0.744912 | 0.92779... |
aubmindlab/araelectra-base-generator | 3783d1be2a43dfede443a934410539f753122c41 | 2022-04-07T11:31:12.000Z | [
"pytorch",
"tf",
"tensorboard",
"electra",
"fill-mask",
"ar",
"dataset:wikipedia",
"dataset:OSIAN",
"dataset:1.5B Arabic Corpus",
"dataset:OSCAR Arabic Unshuffled",
"arxiv:2012.15516",
"transformers",
"autotrain_compatible"
] | fill-mask | false | aubmindlab | null | aubmindlab/araelectra-base-generator | 195 | null | transformers | 3,654 | ---
language: ar
datasets:
- wikipedia
- OSIAN
- 1.5B Arabic Corpus
- OSCAR Arabic Unshuffled
widget:
- text: " عاصمة لبنان هي [MASK] ."
---
# AraELECTRA
<img src="https://raw.githubusercontent.com/aub-mind/arabert/master/AraELECTRA.png" width="100" align="left"/>
**ELECTRA** is a method for self... |
koala/kykim-bert-kor-base-ko | d0944e73af133a5e221634d0063bf9af21eef197 | 2021-12-10T12:31:20.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | koala | null | koala/kykim-bert-kor-base-ko | 195 | null | transformers | 3,655 | Entry not found |
l3cube-pune/MarathiSentiment | 61900f644a268997fcf84e4529cec46986daeaf0 | 2021-05-18T07:35:10.000Z | [
"pytorch",
"tf",
"albert",
"text-classification",
"mr",
"dataset:L3CubeMahaSent",
"arxiv:2103.11408",
"transformers",
"license:cc-by-4.0"
] | text-classification | false | l3cube-pune | null | l3cube-pune/MarathiSentiment | 195 | 2 | transformers | 3,656 | ---
language: mr
tags:
- albert
license: cc-by-4.0
datasets:
- L3CubeMahaSent
widget:
- text: "I like you. </s></s> I love you."
---
## MarathiSentiment
MarathiSentiment is an IndicBERT(ai4bharat/indic-bert) model fine-tuned on L3CubeMahaSent - a Marathi tweet-based sentiment analysis dataset.
[dataset link] (https:... |
monologg/bert-base-cased-goemotions-group | 8db941660d9c02eeca1357aa6e9e98844f73b5e1 | 2021-05-19T23:48:19.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | monologg | null | monologg/bert-base-cased-goemotions-group | 195 | 2 | transformers | 3,657 | Entry not found |
yuchenlin/BART0 | ed9861f2002cc16f79ad3953364d764668d52874 | 2022-05-03T01:31:34.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:bigscience/P3",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | yuchenlin | null | yuchenlin/BART0 | 195 | 2 | transformers | 3,658 | ---
datasets:
- bigscience/P3
language: en
license: apache-2.0
widget:
- text: "A is the son's of B's uncle. What is the family relationship between A and B?"
- text: "Reorder the words in this sentence: justin and name bieber years is my am I 27 old."
- text: "Task: copy but say the opposite.\n
PSG won its match again... |
patrickramosobf/bert-base-japanese-v2-wrime-fine-tune | 060beffbf77befb673463d6c742af900f95d879d | 2022-05-22T16:34:55.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"ja",
"dataset:wrime",
"transformers",
"license:cc-by-sa-3.0"
] | text-classification | false | patrickramosobf | null | patrickramosobf/bert-base-japanese-v2-wrime-fine-tune | 195 | null | transformers | 3,659 | ---
license: cc-by-sa-3.0
language:
- ja
tag:
- emotion-analysis
datasets:
- wrime
widget:
- text: "車のタイヤがパンクしてた。。いたずらの可能性が高いんだって。。"
---
# WRIME-fine-tuned BERT base Japanese
This model is a [Japanese BERT<sub>BASE</sub>](https://huggingface.co/cl-tohoku/bert-base-japanese-v2) fine-tuned on the [WRIME](https://github... |
ckb/en-toki-mt | 546b3df927463696d71dbee5b6028148f46f99b1 | 2022-07-09T09:48:35.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"tok",
"transformers",
"generated_from_trainer",
"translation",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | translation | false | ckb | null | ckb/en-toki-mt | 195 | null | transformers | 3,660 | ---
license: apache-2.0
language:
- en
- tok
tags:
- generated_from_trainer
- translation
model-index:
- name: en-toki-mt
results: []
widget:
- text: "Hello, my name is Tom."
- text: "Can the cat speak English?"
---
# en-toki-mt
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ROMANCE](https://hugging... |
DaNLP/da-bert-ner | 9fe6e2483f6a38b6800b63273e4f9848cf334aeb | 2021-09-17T11:18:07.000Z | [
"pytorch",
"tf",
"bert",
"token-classification",
"da",
"dataset:DaNE",
"transformers",
"ner",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | DaNLP | null | DaNLP/da-bert-ner | 194 | null | transformers | 3,661 | ---
language:
- da
tags:
- ner
- bert
- pytorch
- transformers
license: cc-by-sa-4.0
datasets:
- DaNE
metrics:
- f1
widget:
- text: "Jens Peter Hansen kommer fra Danmark"
---
# BERT fine-tuned for Named Entity Recognition in Danish
The model tags tokens (in Danish sentences) with named entity tags (BIO format) [PER, ... |
ans/vaccinating-covid-tweets | ddb15134bf56cda36aea875c56822ab9074d768d | 2021-06-18T04:12:08.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:tweets",
"transformers",
"license:apache-2.0"
] | text-classification | false | ans | null | ans/vaccinating-covid-tweets | 194 | 1 | transformers | 3,662 | ---
language: en
license: apache-2.0
datasets:
- tweets
widget:
- text: "Vaccines to prevent SARS-CoV-2 infection are considered the most promising approach for curbing the pandemic."
---
# Disclaimer: This page is under maintenance. Please DO NOT refer to the information on this page to make any decision yet.
# Vacc... |
hfl/cino-large-v2 | 39af3c16b2256141ad3306fc2be6841f6cc76aec | 2022-01-24T10:40:50.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"fill-mask",
"zh",
"bo",
"kk",
"ko",
"mn",
"ug",
"yue",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | hfl | null | hfl/cino-large-v2 | 194 | 2 | transformers | 3,663 | ---
language:
- zh
- bo
- kk
- ko
- mn
- ug
- yue
license: "apache-2.0"
---
## CINO: Pre-trained Language Models for Chinese Minority Languages（中国少数民族预训练模型）
Multilingual Pre-trained Language Model, such as mBERT, XLM-R, provide multilingual and cross-lingual ability for language understanding.
We have seen rapid pro... |
jchen/DialoGPT-evan | 161625a480f8188bdd82787fd0d3d43373f2dd44 | 2021-10-23T04:12:00.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | jchen | null | jchen/DialoGPT-evan | 194 | null | transformers | 3,664 | ---
tags:
- conversational
---
# Evan Model |
uer/chinese_roberta_L-12_H-256 | 4aeb03283d2d0ff43cffec9674a1ac4621055f68 | 2022-07-15T08:15:47.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"arxiv:1908.08962",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uer | null | uer/chinese_roberta_L-12_H-256 | 194 | null | transformers | 3,665 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "北京是[MASK]国的首都。"
---
# Chinese RoBERTa Miniatures
## Model description
This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
[Turc e... |
DemangeJeremy/4-sentiments-with-flaubert | 1795c955197e73fe016a4a1b03073eb68d7f8430 | 2021-03-29T00:03:14.000Z | [
"pytorch",
"flaubert",
"text-classification",
"fr",
"transformers",
"sentiments",
"french",
"flaubert-large"
] | text-classification | false | DemangeJeremy | null | DemangeJeremy/4-sentiments-with-flaubert | 193 | null | transformers | 3,666 | ---
language: fr
tags:
- sentiments
- text-classification
- flaubert
- french
- flaubert-large
---
# Modèle de détection de 4 sentiments avec FlauBERT (mixed, negative, objective, positive)
Les travaux sont actuellement en cours. Je modifierai le modèle ces prochains jours.
### Comment l'utiliser ?
```python
fro... |
mbien/recipenlg | b690df9e40f6bf58c7cf8d96e1a91e101134167b | 2021-05-23T08:56:58.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | mbien | null | mbien/recipenlg | 193 | 1 | transformers | 3,667 | # RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation
Model accompanying our INLG 2020 paper: [RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation](https://www.aclweb.org/anthology/2020.inlg-1.4.pdf)
## Where is the dataset?
Please visit the website of our project: [recipenl... |
persiannlp/mt5-base-parsinlu-translation_en_fa | 3a107aa2674d8f097adea1c7e1c0332dfc5236f5 | 2021-09-23T16:20:09.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"transformers",
"machine-translation",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-base-parsinlu-translation_en_fa | 193 | null | transformers | 3,668 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- machine-translation
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- sacrebleu
---
# Machine Translation (ترجمهی ماشینی)
This is an mT5-based model for machine translatio... |
helliun/polhol | 20558877f2958c1c49a6f11440e6594ed59d9d5b | 2022-06-17T20:18:08.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | helliun | null | helliun/polhol | 193 | null | transformers | 3,669 | Entry not found |
DeepPavlov/distilrubert-tiny-cased-conversational-5k | b81d5917df739af393e4aef61b7199fb04c502a7 | 2022-06-28T17:05:02.000Z | [
"pytorch",
"distilbert",
"ru",
"arxiv:2205.02340",
"transformers"
] | null | false | DeepPavlov | null | DeepPavlov/distilrubert-tiny-cased-conversational-5k | 193 | null | transformers | 3,670 | ---
language:
- ru
---
# distilrubert-tiny-cased-conversational-5k
Conversational DistilRuBERT-tiny-5k \(Russian, cased, 3‑layers, 264‑hidden, 12‑heads, 3.6M parameters, 5k vocab\) was trained on OpenSubtitles\[1\], [Dirty](https://d3.ru/), [Pikabu](https://pikabu.ru/), and a Social Media segment of Taiga corpus\[2\] (... |
samroni/model_gpt | 3821d526bd9c83a658314707909ed089293b5220 | 2022-06-28T18:36:24.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | samroni | null | samroni/model_gpt | 193 | null | transformers | 3,671 | Entry not found |
KoboldAI/fairseq-dense-1.3B | 35812b21ae79688d634c285fb617640b4e5a9eda | 2022-02-01T22:50:09.000Z | [
"pytorch",
"xglm",
"text-generation",
"transformers"
] | text-generation | false | KoboldAI | null | KoboldAI/fairseq-dense-1.3B | 192 | 1 | transformers | 3,672 | Entry not found |
congcongwang/gpt2_medium_fine_tuned_coder | 636a8814222562b9b5517bada923fee23b8a73f6 | 2021-05-21T15:06:28.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | congcongwang | null | congcongwang/gpt2_medium_fine_tuned_coder | 192 | 1 | transformers | 3,673 | Entry not found |
facebook/s2t-small-mustc-en-it-st | 90f09c8fb0ba436e3ce1c1d5dbe9fb14a1b4cd7e | 2022-02-07T15:01:15.000Z | [
"pytorch",
"tf",
"speech_to_text",
"automatic-speech-recognition",
"en",
"it",
"dataset:mustc",
"arxiv:2010.05171",
"arxiv:1904.08779",
"transformers",
"audio",
"speech-translation",
"license:mit"
] | automatic-speech-recognition | false | facebook | null | facebook/s2t-small-mustc-en-it-st | 192 | 1 | transformers | 3,674 | ---
language:
- en
- it
datasets:
- mustc
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
sr... |
won/DialoGPT-small-harrypotter | 4701f16a4d0c0c19ad226e4506e01f335c3e2100 | 2022-01-15T11:58:54.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | won | null | won/DialoGPT-small-harrypotter | 192 | null | transformers | 3,675 | ---
tags:
- conversational
---
# Harry Potter DialoGPT Model |
yechen/question-answering-chinese | 46beedecafca28a1aeb696b18408e1eb76262c87 | 2021-05-20T09:25:57.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"question-answering",
"zh",
"transformers",
"autotrain_compatible"
] | question-answering | false | yechen | null | yechen/question-answering-chinese | 192 | null | transformers | 3,676 | ---
language: zh
---
|
projecte-aina/roberta-base-ca-v2-cased-qa | 0ab7044d72b9cd2cd91b869ad9854026189faab1 | 2022-07-25T06:50:23.000Z | [
"pytorch",
"roberta",
"question-answering",
"ca",
"dataset:projecte-aina/catalanqa",
"dataset:projecte-aina/xquad-ca",
"arxiv:1907.11692",
"transformers",
"catalan",
"qa",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | projecte-aina | null | projecte-aina/roberta-base-ca-v2-cased-qa | 192 | null | transformers | 3,677 | ---
language:
- ca
license: apache-2.0
tags:
- "catalan"
- "qa"
datasets:
- "projecte-aina/catalanqa"
- "projecte-aina/xquad-ca"
model-index:
- name: roberta-base-ca-v2-cased-qa
results:
- task:
type: question-answering
dataset:
type: projecte-aina/catalanqa
name: CatalanQA
metr... |
dim/dialogpt-medium-persona-chat | d857cbe74c45efede87b707cd4ffc3e2dd851baa | 2022-07-12T11:39:20.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | dim | null | dim/dialogpt-medium-persona-chat | 192 | null | transformers | 3,678 | Entry not found |
codeparrot/codeparrot-small-code-to-text | 28a105e14da86230e3b92e6c6f55d2d398083208 | 2022-07-19T15:46:25.000Z | [
"pytorch",
"gpt2",
"text-generation",
"code",
"dataset:codeparrot/codeparrot-clean",
"dataset:codeparrot/github-jupyter-code-to-text",
"transformers",
"generation",
"license:apache-2.0"
] | text-generation | false | codeparrot | null | codeparrot/codeparrot-small-code-to-text | 192 | null | transformers | 3,679 | ---
language:
- code
license: apache-2.0
tags:
- code
- gpt2
- generation
datasets:
- "codeparrot/codeparrot-clean"
- "codeparrot/github-jupyter-code-to-text"
---
# CodeParrot 🦜 small for text-t-code generation
This model is [CodeParrot-small](https://huggingface.co/codeparrot/codeparrot-small) (from `branch mega... |
SEBIS/code_trans_t5_base_code_documentation_generation_java_multitask_finetune | f692aced9d13bbf9213a1418bd1177a73480a28f | 2021-06-23T04:24:36.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_base_code_documentation_generation_java_multitask_finetune | 191 | null | transformers | 3,680 | ---
tags:
- summarization
widget:
- text: "public static < T , U > Function < T , U > castFunction ( Class < U > target ) { return new CastToClass < T , U > ( target ) ; }"
---
# CodeTrans model for code documentation generation java
Pretrained model on programming language java using the t5 base model architecture.... |
SkolkovoInstitute/roberta-base-formality-ranker-v1 | 507700d5f40abdcee951bd2f859d48aed67367ba | 2022-07-20T21:29:23.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:GYAFC",
"dataset:Pavlick-Tetreault-2016",
"transformers",
"formality"
] | text-classification | false | SkolkovoInstitute | null | SkolkovoInstitute/roberta-base-formality-ranker-v1 | 191 | null | transformers | 3,681 | ---
language:
- en
tags:
- formality
datasets:
- GYAFC
- Pavlick-Tetreault-2016
---
The model has been trained [here](https://git.mts.ai/ai/ml_lab/skoltech-nlp_lab/skoltech/task_oriented_TST/-/blob/main/transfer/formality_ranker_v1.ipynb) to predict for English sentences, whether they are formal or informal. ... |
readerbench/RoGPT2-large | 5d3292f4fb85e0dd83e1a31399f766b520c9b811 | 2021-07-22T11:23:50.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"ro",
"transformers"
] | text-generation | false | readerbench | null | readerbench/RoGPT2-large | 191 | null | transformers | 3,682 | Model card for RoGPT2-large
---
language:
- ro
---
# RoGPT2: Romanian GPT2 for text generation
All models are available:
* [RoBERT-base](https://huggingface.co/readerbench/RoGPT2-base)
* [RoBERT-medium](https://huggingface.co/readerbench/RoGPT2-medium)
* [RoBERT-large](https://huggingface.co/readerbench/RoGPT2-large... |
StanfordAIMI/stanford-deidentifier-only-i2b2 | 45c5edfa4dd56d2d65a7b23eb2f7e4aee4a44584 | 2022-07-18T03:49:38.000Z | [
"pytorch",
"bert",
"en",
"dataset:radreports",
"transformers",
"token-classification",
"sequence-tagger-model",
"pubmedbert",
"uncased",
"radiology",
"biomedical",
"license:mit"
] | token-classification | false | StanfordAIMI | null | StanfordAIMI/stanford-deidentifier-only-i2b2 | 191 | 1 | transformers | 3,683 | ---
widget:
- text: "PROCEDURE: Chest xray. COMPARISON: last seen on 1/1/2020 and also record dated of March 1st, 2019. FINDINGS: patchy airspace opacities. IMPRESSION: The results of the chest xray of January 1 2020 are the most concerning ones. The patient was transmitted to another service of UH Medical Center under... |
Cameron/BERT-rtgender-opgender-annotations | 30c103f3f0b41b05c9b1814be20f59c87b7fbb42 | 2021-05-18T17:34:57.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Cameron | null | Cameron/BERT-rtgender-opgender-annotations | 190 | null | transformers | 3,684 | Entry not found |
FPTAI/velectra-base-discriminator-cased | f594fee501933d92d8c13285c969495681d0cc00 | 2020-09-30T03:52:16.000Z | [
"pytorch",
"electra",
"pretraining",
"transformers"
] | null | false | FPTAI | null | FPTAI/velectra-base-discriminator-cased | 190 | null | transformers | 3,685 | Entry not found |
Harveenchadha/vakyansh-wav2vec2-indian-english-enm-700 | 6889649cf67fd629a47fbdd9e11560626d22ac64 | 2021-08-02T18:42:21.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | Harveenchadha | null | Harveenchadha/vakyansh-wav2vec2-indian-english-enm-700 | 190 | 3 | transformers | 3,686 | Entry not found |
arampacha/wav2vec2-xls-r-1b-hy | 5a34466c5a07b932732d804e02d2a29ea608bebd | 2022-03-23T18:34:38.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"hy-AM",
"dataset:common_voice",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"hy",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | arampacha | null | arampacha/wav2vec2-xls-r-1b-hy | 190 | 1 | transformers | 3,687 | ---
language:
- hy-AM
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- hy
- mozilla-foundation/common_voice_8_0
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-1b-hy-cv
results:
- task:
type: automatic-speech-recognitio... |
monologg/koelectra-base-v3-goemotions | 9b9385c0190252577bc51bf222426e726fea51d0 | 2021-02-09T14:40:17.000Z | [
"pytorch",
"electra",
"transformers"
] | null | false | monologg | null | monologg/koelectra-base-v3-goemotions | 190 | null | transformers | 3,688 | Entry not found |
mrm8488/roberta-base-1B-1-finetuned-squadv1 | 4a0a7703a4ca3bc57af44753073ccfcb03b45a1f | 2021-05-20T18:26:13.000Z | [
"pytorch",
"jax",
"roberta",
"question-answering",
"en",
"transformers",
"autotrain_compatible"
] | question-answering | false | mrm8488 | null | mrm8488/roberta-base-1B-1-finetuned-squadv1 | 190 | null | transformers | 3,689 | ---
language: en
---
# RoBERTa-base (1B-1) + SQuAD v1 ❓
[roberta-base-1B-1](https://huggingface.co/nyu-mll/roberta-base-1B-1) fine-tuned on [SQUAD v1.1 dataset](https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/) for **Q&A** downstream task.
## Details of the downstream task (Q&A) - Model 🧠
RoBERTa Pretra... |
facebook/data2vec-vision-large-ft1k | 9933efaca13b79863d36579c9a339c84cb0e9eca | 2022-05-03T15:22:49.000Z | [
"pytorch",
"tf",
"data2vec-vision",
"image-classification",
"dataset:imagenet",
"dataset:imagenet-1k",
"arxiv:2202.03555",
"arxiv:2106.08254",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/data2vec-vision-large-ft1k | 190 | 2 | transformers | 3,690 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
- imagenet-1k
---
# Data2Vec-Vision (large-sized model, fine-tuned on ImageNet-1k)
BEiT model pre-trained in a self-supervised fashion and fine-tuned on ImageNet-1k (1,2 million images, 1000 classes) at resolution 224x224. It was intr... |
jorge-henao/gpt2-small-spanish-historias-conflicto-col | 0cd442c9fd4fb23202c25f79718ababf200f8ac6 | 2022-07-10T17:30:28.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-generation | false | jorge-henao | null | jorge-henao/gpt2-small-spanish-historias-conflicto-col | 190 | null | transformers | 3,691 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: gpt2-small-spanish-historias-conflicto-col
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.... |
SajjadAyoubi/distil-bigbird-fa-zwnj | 98fd06440980957e6428dc823e16d56593fb805c | 2021-10-28T13:14:34.000Z | [
"pytorch",
"big_bird",
"fill-mask",
"arxiv:1810.04805",
"arxiv:2005.12515",
"arxiv:2007.14062",
"transformers",
"autotrain_compatible"
] | fill-mask | false | SajjadAyoubi | null | SajjadAyoubi/distil-bigbird-fa-zwnj | 189 | null | transformers | 3,692 | <span align="center">
<a href="https://huggingface.co/SajjadAyoubi/"><img src="https://img.shields.io/static/v1?label=%F0%9F%A4%97%20Hugging%20Face&message=SajjadAyoubi&color=yellow"></a>
<a href="https://colab.research.google.com/github/sajjjadayobi/PersianQA/blob/main/notebooks/Demo.ipynb"><img src="https://i... |
eduardofv/stsb-m-mt-es-distiluse-base-multilingual-cased-v1 | dfd98175cd8ebb4da3ebd46c9409f78d4c7e0b73 | 2021-07-06T18:06:30.000Z | [
"pytorch",
"distilbert",
"feature-extraction",
"es",
"dataset:stsb_multi_mt",
"sentence-transformers",
"sentence-similarity"
] | feature-extraction | false | eduardofv | null | eduardofv/stsb-m-mt-es-distiluse-base-multilingual-cased-v1 | 189 | null | sentence-transformers | 3,693 | ---
language: es
datasets:
- stsb_multi_mt
tags:
- sentence-similarity
- sentence-transformers
---
This is a test model that was fine-tuned using the Spanish datasets from [stsb_multi_mt](https://huggingface.co/datasets/stsb_multi_mt) in order to understand and benchmark STS models.
## Model and training data descri... |
sultan/BioM-ELECTRA-Large-SQuAD2 | 7108315378d3adb4168a79035366e1b9a563f0b3 | 2021-08-06T22:27:10.000Z | [
"pytorch",
"electra",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | sultan | null | sultan/BioM-ELECTRA-Large-SQuAD2 | 189 | 1 | transformers | 3,694 | # BioM-Transformers: Building Large Biomedical Language Models with BERT, ALBERT and ELECTRA
# Abstract
The impact of design choices on the performance
of biomedical language models recently
has been a subject for investigation. In
this paper, we empirically study biomedical
domain adaptation with large transformer ... |
uer/roberta-base-finetuned-jd-binary-chinese | b270d7d29fb2c4596908f2502a48a04cf459eb57 | 2022-02-20T07:57:21.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"zh",
"arxiv:1909.05658",
"arxiv:1708.02657",
"transformers"
] | text-classification | false | uer | null | uer/roberta-base-finetuned-jd-binary-chinese | 189 | 2 | transformers | 3,695 | ---
language: zh
widget:
- text: "这本书真的很不错"
---
# Chinese RoBERTa-Base Models for Text Classification
## Model description
This is the set of 5 Chinese RoBERTa-Base classification models fine-tuned by [UER-py](https://arxiv.org/abs/1909.05658). You can download the 5 Chinese RoBERTa-Base classification models eith... |
d0r1h/LEDBill | 714bfe06554698b4945e72ffb0ef406df0347c11 | 2022-07-12T08:11:45.000Z | [
"pytorch",
"led",
"text2text-generation",
"dataset:billsum",
"arxiv:2004.05150",
"transformers",
"summarization",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | d0r1h | null | d0r1h/LEDBill | 189 | null | transformers | 3,696 | ---
license: apache-2.0
datasets: billsum
tags:
- summarization
widget:
- text: "The people of the State of California do enact as follows: SECTIONHEADER Section 1170.02 is added to the Penal Code, to read: 1170.02. A prisoner is not eligible for resentence or recall pursuant to subdivision (e) of Section 1170 if he or... |
Finnish-NLP/roberta-large-wechsel-finnish | d12d05c3dd60b277728436a5cea6e50262f2d749 | 2022-06-13T16:13:27.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"arxiv:1907.11692",
"arxiv:2112.06598",
"transformers",
"finnish",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Finnish-NLP | null | Finnish-NLP/roberta-large-wechsel-finnish | 188 | 1 | transformers | 3,697 | ---
language:
- fi
license: apache-2.0
tags:
- finnish
- roberta
datasets:
- Finnish-NLP/mc4_fi_cleaned
- wikipedia
widget:
- text: "Moikka olen <mask> kielimalli."
---
# RoBERTa large model trained with WECHSEL method for Finnish
Pretrained RoBERTa model on Finnish language using a masked language modeling (MLM) ob... |
Helsinki-NLP/opus-mt-ha-en | a42c55010565f550c110703534b61b32a37fda8c | 2021-09-09T21:59:59.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ha",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ha-en | 188 | null | transformers | 3,698 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ha-en
* source languages: ha
* target languages: en
* OPUS readme: [ha-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ha-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
pki/t5-small-finetuned_xsum | 65e211b0e8840a485ac8cbfc0f49ba4b8988f6e7 | 2022-03-15T13:42:02.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | pki | null | pki/t5-small-finetuned_xsum | 188 | 1 | transformers | 3,699 | ---
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned_xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
args: default
metrics:
- name: Rouge1
... |
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