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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
IIC/marimari-r2r-mlsum | 6230c21c7210c1ab68f32fa56dc1c1f9d3cc27b6 | 2022-04-13T16:49:56.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"es",
"dataset:mlsum",
"arxiv:1907.12461",
"transformers",
"summarization",
"seq2seq",
"model-index",
"autotrain_compatible"
] | summarization | false | IIC | null | IIC/marimari-r2r-mlsum | 66 | 2 | transformers | 5,500 | ---
language:
- es
tags:
- summarization # Example: audio
- seq2seq # Example: automatic-speech-recognition
datasets:
- mlsum
metrics:
- rouge2
- rouge1
- rougel
- rougelsum
# Optional. Add this if you want to encode your eval results in a structured way.
model-index:
- name: marimari-r2r-mlsum
results:
- task: ... |
questgen/all-mpnet-base-v2-feature-extraction-pipeline | f88ec83121852d920f89e717d4adedf760a94b57 | 2022-05-15T06:29:59.000Z | [
"pytorch",
"mpnet",
"fill-mask",
"en",
"arxiv:1904.06472",
"arxiv:2102.07033",
"arxiv:2104.08727",
"arxiv:1704.05179",
"arxiv:1810.09305",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"license:apache-2.0"
] | feature-extraction | false | questgen | null | questgen/all-mpnet-base-v2-feature-extraction-pipeline | 66 | null | sentence-transformers | 5,501 | ---
pipeline_tag: feature-extraction
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language: en
license: apache-2.0
---
# all-mpnet-base-v2
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 ... |
zhifei/autotrain-chinese-title-summarization-1060936832 | e3884592b3c6f4f8b619888e41dad01dc14f9970 | 2022-06-30T12:23:58.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"unk",
"dataset:zhifei/autotrain-data-chinese-title-summarization",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | zhifei | null | zhifei/autotrain-chinese-title-summarization-1060936832 | 66 | null | transformers | 5,502 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- zhifei/autotrain-data-chinese-title-summarization
co2_eq_emissions: 3.841483701875158
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1060936832
- CO2 Emissions (in grams): 3.841483701875158
## Validatio... |
gaunernst/bert-small-uncased | 10b42d998a29a4ac8b43c866cc1184cb4880cdd4 | 2022-07-02T07:20:15.000Z | [
"pytorch",
"bert",
"transformers",
"license:apache-2.0"
] | null | false | gaunernst | null | gaunernst/bert-small-uncased | 66 | null | transformers | 5,503 | ---
license: apache-2.0
---
|
yazinga/DialoGPT-medium-scout | 81a1b77c99e99f78cde1d2271d5f1c0f9decc015 | 2022-07-21T20:19:50.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | yazinga | null | yazinga/DialoGPT-medium-scout | 66 | null | transformers | 5,504 | ---
tags:
- conversational
---
# Scout DialoGPT Model |
HooshvareLab/gpt2-fa-comment | a11c3401aa46429b13184a6c94088bd43728c7fd | 2021-05-21T10:47:25.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"fa",
"transformers",
"license:apache-2.0"
] | text-generation | false | HooshvareLab | null | HooshvareLab/gpt2-fa-comment | 65 | null | transformers | 5,505 | ---
language: fa
license: apache-2.0
widget:
- text: "<s>نمونه دیدگاه هم خوب هم بد به طور کلی <sep>"
- text: "<s>نمونه دیدگاه خیلی منفی از نظر کیفیت و طعم <sep>"
- text: "<s>نمونه دیدگاه خوب از نظر بازی و کارگردانی <sep>"
- text: "<s>نمونه دیدگاه خیلی خوب از نظر بازی و صحنه و داستان <sep>"
- text: "<s>نمونه دیدگاه... |
KoichiYasuoka/roberta-classical-chinese-base-sentence-segmentation | c8a9275fdc413f4f8e113cc924861f1994b04d5a | 2021-12-10T00:34:26.000Z | [
"pytorch",
"roberta",
"token-classification",
"lzh",
"transformers",
"classical chinese",
"literary chinese",
"ancient chinese",
"sentence segmentation",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/roberta-classical-chinese-base-sentence-segmentation | 65 | 1 | transformers | 5,506 | ---
language:
- "lzh"
tags:
- "classical chinese"
- "literary chinese"
- "ancient chinese"
- "sentence segmentation"
- "token-classification"
license: "apache-2.0"
pipeline_tag: "token-classification"
widget:
- text: "子曰學而時習之不亦説乎有朋自遠方來不亦樂乎人不知而不慍不亦君子乎"
---
# roberta-classical-chinese-base-sentence-segmentation
## Mode... |
addy88/perceiver_image_classifier | d13564b81f342b5223ac5001a216ef89cfe2c8a4 | 2022-01-02T13:05:37.000Z | [
"pytorch",
"perceiver",
"image-classification",
"transformers"
] | image-classification | false | addy88 | null | addy88/perceiver_image_classifier | 65 | null | transformers | 5,507 | ### How to use
Here is how to use this model in PyTorch:
```python
from transformers import PerceiverFeatureExtractor, PerceiverForImageClassificationLearned
import requests
from PIL import Image
feature_extractor = PerceiverFeatureExtractor.from_pretrained("addy88/perceiver_image_classifier")
model = PerceiverForImage... |
amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061 | 7e66c09a995a61e7f37d29d72e064383ff7ca13e | 2021-10-17T00:32:35.000Z | [
"pytorch",
"distilbert",
"text-classification",
"en",
"dataset:amansolanki/autonlp-data-Tweet-Sentiment-Extraction",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | false | amansolanki | null | amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061 | 65 | null | transformers | 5,508 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- amansolanki/autonlp-data-Tweet-Sentiment-Extraction
co2_eq_emissions: 3.651199395353127
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 20114061
- CO2 Emissions (in grams): 3.651199395353127
## Val... |
ddobokki/electra-small-nli-sts | 3246a95b1b7fba01723b63e394543900f9deaeb5 | 2022-03-28T07:49:33.000Z | [
"pytorch",
"electra",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers",
"ko"
] | sentence-similarity | false | ddobokki | null | ddobokki/electra-small-nli-sts | 65 | 1 | sentence-transformers | 5,509 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- ko
---
# ddobokki/electra-small-nli-sts
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 256 dimensional dense vector space and can be used... |
huggingtweets/jesusisathembo | df9d11183402edc0c16c9fa7357808e68220719e | 2021-05-22T09:38:03.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/jesusisathembo | 65 | null | transformers | 5,510 | ---
language: en
thumbnail: https://www.huggingtweets.com/jesusisathembo/1614096400764/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1331300707... |
LACAI/DialoGPT-small-SGD | 577683f7fd450f9167ea72c5e398bf2046490ade | 2022-01-02T04:08:07.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | LACAI | null | LACAI/DialoGPT-small-SGD | 65 | 1 | transformers | 5,511 | Base model: [microsoft/DialoGPT-small](https://huggingface.co/microsoft/DialoGPT-small)
Fine tuned for dialogue response generation on the [Schema Guided Dialogue Dataset](https://github.com/google-research-datasets/dstc8-schema-guided-dialogue) (Rastogi et al., 2019)
Three additional special tokens were added during... |
raynardj/ner-gene-dna-rna-jnlpba-pubmed | 231b91cf27c49cb398a112e24e439dc407a884f3 | 2021-11-05T07:32:32.000Z | [
"pytorch",
"roberta",
"token-classification",
"en",
"dataset:jnlpba",
"transformers",
"ner",
"gene",
"protein",
"rna",
"bioinfomatics",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | raynardj | null | raynardj/ner-gene-dna-rna-jnlpba-pubmed | 65 | 1 | transformers | 5,512 | ---
language:
- en
tags:
- ner
- gene
- protein
- rna
- bioinfomatics
license: apache-2.0
datasets:
- jnlpba
widget:
- text: "It consists of 25 exons encoding a 1,278-amino acid glycoprotein that is composed of 13 transmembrane domains"
---
# NER to find Gene & Gene products
> The model was trained on jnlpba dataset, ... |
razent/spbert-mlm-base | e98ed8adec9e4cd04a2743cf3f5a10ccabe8a4db | 2022-03-15T03:25:56.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"code",
"arxiv:2106.09997",
"transformers",
"question-answering",
"knowledge-graph",
"autotrain_compatible"
] | question-answering | false | razent | null | razent/spbert-mlm-base | 65 | null | transformers | 5,513 | ---
language:
- code
tags:
- question-answering
- knowledge-graph
---
# SPBERT MLM (Initialized)
## Introduction
Paper: [SPBERT: An Efficient Pre-training BERT on SPARQL Queries for Question Answering over Knowledge Graphs](https://arxiv.org/abs/2106.09997)
Authors: _Hieu Tran, Long Phan, James Anibal, Binh T. Ngu... |
kazandaev/opus-mt-en-ru-finetuned-v3 | 37eb193690cff71e2e0c82e2a09523e0a99becce | 2022-03-08T10:50:47.000Z | [
"pytorch",
"tensorboard",
"rust",
"marian",
"text2text-generation",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | kazandaev | null | kazandaev/opus-mt-en-ru-finetuned-v3 | 65 | null | transformers | 5,514 | ---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-en-ru-finetuned-v3
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. -->
# opus-mt-en-r... |
clapika2010/adult_finetuned | 87bb8dcfb670a100d351462b78c17a1a568d849e | 2022-03-13T00:53:24.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | clapika2010 | null | clapika2010/adult_finetuned | 65 | null | transformers | 5,515 | Entry not found |
fabiochiu/t5-small-medium-title-generation | 512b08cb241e724542ff9791bd01937294593dd2 | 2022-05-17T08:46:22.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"transformers",
"generated_from_keras_callback",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | fabiochiu | null | fabiochiu/t5-small-medium-title-generation | 65 | null | transformers | 5,516 | ---
tags:
- generated_from_keras_callback
model-index:
- name: t5-small-medium-title-generation
results: []
widget:
- text: "summarize: Many financial institutions started building conversational AI, prior to the Covid19 pandemic, as part of a digital transformation initiative. These initial solutions were high profi... |
khanhld/wav2vec2-base-vietnamese-160h | 0c8ad9977189dc089a5c5f55c7b6dbaa79d8c5fd | 2022-05-13T14:13:49.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"vi",
"dataset:vivos",
"dataset:common_voice",
"dataset:FOSD",
"dataset:VLSP",
"transformers",
"audio",
"speech",
"Transformer",
"vietnamese",
"license:cc-by-nc-4.0",
"model-index"
] | automatic-speech-recognition | false | khanhld | null | khanhld/wav2vec2-base-vietnamese-160h | 65 | 1 | transformers | 5,517 | ---
language: vi
datasets:
- vivos
- common_voice
- FOSD
- VLSP
metrics:
- wer
pipeline_tag: automatic-speech-recognition
tags:
- audio
- speech
- Transformer
- wav2vec2
- automatic-speech-recognition
- vietnamese
license: cc-by-nc-4.0
widget:
- example_title: common_voice_vi_30519758.mp3
src: https://huggingface.co/... |
tolmanneo/convo-gpt-j-6b | 1f275b63604eaa09629e494fb83ba796c1993133 | 2022-06-09T16:08:57.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers",
"conversational"
] | conversational | false | tolmanneo | null | tolmanneo/convo-gpt-j-6b | 65 | null | transformers | 5,518 | ---
tags: conversational
--- |
tolmanneo/convo-gpt-j-6b-10x | c5a51f30a7ac057fc844f1115c897471c8ebad86 | 2022-06-09T15:44:39.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers",
"conversational"
] | conversational | false | tolmanneo | null | tolmanneo/convo-gpt-j-6b-10x | 65 | null | transformers | 5,519 | ---
tags:
- conversational
---
|
ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_all_TEST_null__second_train_set_NULL_False | 33f750518ad0ba3a89ab96dd58c9ae2299cd114f | 2022-06-16T09:29:42.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | ali2066 | null | ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_all_TEST_null__second_train_set_NULL_False | 65 | null | transformers | 5,520 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-uncased_token_itr0_0.0001_TRAIN_all_TEST_null__second_train_set_NULL_False
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer... |
luoyixin/marian-finetuned-kde4-en-to-zh | 575d97dab284cba5ff1cc0202ac4a9a4f9a99ab6 | 2022-06-20T10:13:41.000Z | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"dataset:kde4",
"transformers",
"translation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | translation | false | luoyixin | null | luoyixin/marian-finetuned-kde4-en-to-zh | 65 | null | transformers | 5,521 | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
datasets:
- kde4
metrics:
- bleu
model-index:
- name: marian-finetuned-kde4-en-to-zh
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: kde4
type: kde4
args: en... |
Yehor/wav2vec2-xls-r-base-uk-with-small-lm | b958c7f8aecb6ad9de8702c2ec63462a3d02b62c | 2022-07-30T07:00:59.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"uk",
"transformers",
"license:cc-by-nc-sa-4.0"
] | automatic-speech-recognition | false | Yehor | null | Yehor/wav2vec2-xls-r-base-uk-with-small-lm | 65 | null | transformers | 5,522 | ---
language:
- uk
license: "cc-by-nc-sa-4.0"
---
**NOTE**: Look on a better model https://huggingface.co/Yehor/wav2vec2-xls-r-base-uk-with-cv-lm
🇺🇦 Join Ukrainian Speech Recognition Community - https://t.me/speech_recognition_uk
⭐ See other Ukrainian models - https://github.com/egorsmkv/speech-recognition-uk
... |
WindowsRegedit/zuowen | b35bd2ea0489d52b0af56cbcfd84a198d8c55df6 | 2022-06-23T12:47:18.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | WindowsRegedit | null | WindowsRegedit/zuowen | 65 | null | transformers | 5,523 | ### 作文模型
使用方法，请参考[Python 自动写作文库](https://github.com/WindowsRegedit/zuowen)
|
tner/bert-base-tweetner-2020 | cccef3955fffead783edbbb495b5444db567bea5 | 2022-07-08T11:18:19.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tner | null | tner/bert-base-tweetner-2020 | 65 | null | transformers | 5,524 | Entry not found |
Evelyn18/BECASV4.1 | d02d756d758240bbf1bbab8f3f9810d36ce863b6 | 2022-07-19T03:34:08.000Z | [
"pytorch",
"roberta",
"question-answering",
"dataset:becasv2",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | Evelyn18 | null | Evelyn18/BECASV4.1 | 65 | null | transformers | 5,525 | ---
tags:
- generated_from_trainer
datasets:
- becasv2
model-index:
- name: roberta-base-spanish-squades-modelo-robertav1
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 comme... |
Amrrs/wav2vec2-large-xlsr-53-tamil | 017e2f0cf4b196d1656e310c87403fe446e39581 | 2021-07-05T14:14:42.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ta",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Amrrs | null | Amrrs/wav2vec2-large-xlsr-53-tamil | 64 | 1 | transformers | 5,526 | ---
language: ta
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Tamil by Amrrs
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voic... |
Helsinki-NLP/opus-mt-pap-en | 38a0afea7e9b1b124d2ec116e42d8a55a0bfc884 | 2021-09-10T14:00:36.000Z | [
"pytorch",
"marian",
"text2text-generation",
"pap",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-pap-en | 64 | null | transformers | 5,527 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-pap-en
* source languages: pap
* target languages: en
* OPUS readme: [pap-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/pap-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
HooshvareLab/gpt2-fa-poetry | 35d19a3dba707d9d1ca075e35340f0477c8d9e0b | 2021-05-21T10:50:14.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"fa",
"transformers",
"license:apache-2.0"
] | text-generation | false | HooshvareLab | null | HooshvareLab/gpt2-fa-poetry | 64 | null | transformers | 5,528 | ---
language: fa
license: apache-2.0
widget:
- text: "<s>رودکی<|startoftext|>"
- text: "<s>فردوسی<|startoftext|>"
- text: "<s>خیام<|startoftext|>"
- text: "<s>عطار<|startoftext|>"
- text: "<s>نظامی<|startoftext|>"
---
# Persian Poet GPT2
## Poets
The model can generate poetry based on your favorite poet, and yo... |
Irina/fantasy_GPT3Medium | e88c9457179f14b78966559711a4f6039bb31b11 | 2021-11-26T05:29:14.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | Irina | null | Irina/fantasy_GPT3Medium | 64 | null | transformers | 5,529 | Entry not found |
alireza7/PEGASUS-persian-base-voa-title | 314282bf0721fcebe6260a8a6f6da340c15750ac | 2021-09-29T19:26:07.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | alireza7 | null | alireza7/PEGASUS-persian-base-voa-title | 64 | null | transformers | 5,530 | More information about models is available [here](https://github.com/alirezasalemi7/ARMAN). |
banjtheman/distilbert-base-uncased-helpful-amazon | 53364fd30e3bfa78a706b9701cc31ba218c7ff60 | 2022-02-04T21:22:32.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"license:apache-2.0"
] | text-classification | false | banjtheman | null | banjtheman/distilbert-base-uncased-helpful-amazon | 64 | null | transformers | 5,531 | ---
license: apache-2.0
---
## Overview
This model was trained with data from https://registry.opendata.aws/helpful-sentences-from-reviews/ to predict how "helpful" a review is.
The model was fine-tuned from the `distilbert-base-uncased` model
### Labels
LABEL_0 - Not helpful
LABEL_1 - Helpful
##... |
castorini/monobert-large-msmarco | 0a97706f3827389da43b83348d5d18c9d53876fa | 2020-05-29T03:41:44.000Z | [
"pytorch",
"transformers"
] | null | false | castorini | null | castorini/monobert-large-msmarco | 64 | null | transformers | 5,532 | Entry not found |
ensamblador/gpt2-twitter-politico | 768a296746bf63b6f6bd9960c50a0e696622f74b | 2021-05-21T15:54:38.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | ensamblador | null | ensamblador/gpt2-twitter-politico | 64 | null | transformers | 5,533 | Entry not found |
gagan3012/wav2vec2-xlsr-khmer | 2b626a577ac629a05d1ab01ac5ba3ad14740de54 | 2021-07-06T03:58:05.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"km",
"dataset:OpenSLR",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | gagan3012 | null | gagan3012/wav2vec2-xlsr-khmer | 64 | null | transformers | 5,534 | ---
language: km
datasets:
- OpenSLR
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: wav2vec2-xlsr-Khmer by Gagan Bhatia
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
huggingtweets/dogdick420cum | 5d7a5f21ba570ac5f7e530167238886a77aee20e | 2021-05-22T01:55:30.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/dogdick420cum | 64 | null | transformers | 5,535 | ---
language: en
thumbnail: https://www.huggingtweets.com/dogdick420cum/1615429013878/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/13595639914... |
lighteternal/nli-xlm-r-greek | 7fabdac688edc6007f9f5adf212bdb8e2deeb752 | 2021-09-21T16:01:42.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"el",
"en",
"dataset:multi_nli",
"dataset:snli",
"dataset:allnli_greek",
"arxiv:1908.10084",
"transformers",
"xlm-roberta-base",
"license:apache-2.0",
"zero-shot-classification"
] | zero-shot-classification | false | lighteternal | null | lighteternal/nli-xlm-r-greek | 64 | null | transformers | 5,536 | ---
language:
- el
- en
tags:
- xlm-roberta-base
datasets:
- multi_nli
- snli
- allnli_greek
metrics:
- accuracy
pipeline_tag: zero-shot-classification
widget:
- text: "Η Facebook κυκλοφόρησε τα πρώτα «έξυπνα» γυαλιά επαυξημένης πραγματικότητας."
candidate_labels: "τεχνολογία, πολιτική, αθλητισμός... |
lkwate/legal-bigbird-us | a67b19db8f36aa5a8d662aadb739afff12e2405a | 2021-08-21T22:38:29.000Z | [
"pytorch",
"big_bird",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | lkwate | null | lkwate/legal-bigbird-us | 64 | 1 | transformers | 5,537 | Entry not found |
mrm8488/T5-base-finetuned-cuad | b26f9f3466cd0b250a9a813e8da4bd4a393f5ece | 2021-12-28T20:13:19.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:cuad",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/T5-base-finetuned-cuad | 64 | 2 | transformers | 5,538 | ---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- cuad
model-index:
- name: T5-base-cuad-512
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. ... |
mrm8488/t5-base-finetuned-news-titles-classification | e25716f46582a471dacb76058bbc7b7ca67af95c | 2021-06-23T12:52:30.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/t5-base-finetuned-news-titles-classification | 64 | null | transformers | 5,539 | Entry not found |
patrickvonplaten/bert2bert-tiny | ca68b0275d9094f9a582a543519119f6f287239b | 2020-10-18T19:23:27.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | patrickvonplaten | null | patrickvonplaten/bert2bert-tiny | 64 | null | transformers | 5,540 | Entry not found |
tanay/layoutlm-funsd | 0a0442220e4d47fb4373c8d6911542706ec0f2e8 | 2021-06-30T07:21:21.000Z | [
"pytorch",
"layoutlm",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tanay | null | tanay/layoutlm-funsd | 64 | null | transformers | 5,541 | Entry not found |
turing-usp/FinBertPTBR | 109ec9242690581dad9458abd9fef57a71d77d38 | 2021-12-03T01:30:42.000Z | [
"pytorch",
"bert",
"text-classification",
"pt",
"transformers",
"license:apache-2.0"
] | text-classification | false | turing-usp | null | turing-usp/FinBertPTBR | 64 | 2 | transformers | 5,542 | ---
language: pt
license: apache-2.0
widget:
- text: "O futuro de DI caiu 20 bps nesta manhã"
example_title: "Example 1"
- text: "O Nubank decidiu cortar a faixa de preço da oferta pública inicial (IPO) após revés no humor dos mercados internacionais com as fintechs."
example_title: "Example 2"
- text: "O Ibovespa... |
vasudevgupta/mbart-bhasha-hin-eng | 14aee5dd763df50ed065a1e9bc8d1650fe9ff2db | 2021-05-12T03:36:02.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"dataset:pib",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vasudevgupta | null | vasudevgupta/mbart-bhasha-hin-eng | 64 | null | transformers | 5,543 | ---
datasets: pib
widget:
- text: "नमस्ते! मैं वासुदेव गुप्ता हूं"
---
mBART (a pre-trained model by Facebook) is pre-trained to de-noise multiple languages simultaneously with BART objective.
Checkpoint available in this repository is obtained after fine-tuning `facebook/mbart-large-cc25` on all samples (~260K) fro... |
lighteternal/fact-or-opinion-xlmr-el | bf405d95926471dbf248ab13af8441d8d87b3da7 | 2022-02-27T19:41:57.000Z | [
"pytorch",
"tensorboard",
"xlm-roberta",
"text-classification",
"en",
"el",
"multilingual",
"transformers",
"fact-or-opinion",
"license:apache-2.0"
] | text-classification | false | lighteternal | null | lighteternal/fact-or-opinion-xlmr-el | 64 | null | transformers | 5,544 | ---
language:
- en
- el
- multilingual
tags:
- text-classification
- fact-or-opinion
- transformers
widget:
- text: "Ξεχωρίζει η καθηλωτική ερμηνεία του πρωταγωνιστή."
- text: "Η Ελλάδα είναι χώρα της Ευρώπης."
- text: "Tolkien was an English writer"
- text: "Tolkien is my favorite writer."
pipeline_tag: text-clas... |
grayson124/chatbotwaifu | f5f60f481106748b56ced7af5b696b16249ba5dd | 2022-03-01T02:49:54.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | grayson124 | null | grayson124/chatbotwaifu | 64 | null | transformers | 5,545 | ---
tags:
- conversational
---
#waifu bot |
ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_essays_TEST_test_set_05_03_2022-05_56_32 | 1bee69d0d0d1f4fb6ecc8b62693ca3889d5b4f41 | 2022-03-05T04:58:11.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ali2066 | null | ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_essays_TEST_test_set_05_03_2022-05_56_32 | 64 | null | transformers | 5,546 | Entry not found |
ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_essays_TEST_essays_05_03_2022-06_16_34 | 4d2afbc201073279ce4d2f56c02bb4c71b31f1f2 | 2022-03-05T05:18:59.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ali2066 | null | ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_essays_TEST_essays_05_03_2022-06_16_34 | 64 | null | transformers | 5,547 | Entry not found |
ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_editorials_TEST_editorials_05_03_2022-06_24_13 | d23e9f1ed74b383fc7deb0e5e9eec9b83a913cc4 | 2022-03-05T05:26:43.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ali2066 | null | ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_editorials_TEST_editorials_05_03_2022-06_24_13 | 64 | null | transformers | 5,548 | Entry not found |
ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_editorials_TEST_webDiscourse_05_03_2022-06_29_29 | e34093958db3a32457de4358d97a2f13c4adc513 | 2022-03-05T05:31:06.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ali2066 | null | ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_editorials_TEST_webDiscourse_05_03_2022-06_29_29 | 64 | null | transformers | 5,549 | Entry not found |
meedan/paraphrase-filipino-mpnet-base-v2 | 20d8b8d26840bc2f9d47e06ad9f576fa9ef86af3 | 2022-05-11T09:50:47.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | meedan | null | meedan/paraphrase-filipino-mpnet-base-v2 | 64 | null | sentence-transformers | 5,550 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# paraphrase-filipino-mpnet-base-v2
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 f... |
avichr/Legal-heBERT | dd775034faa5d4668da364d21a396e1c51773ec1 | 2022-07-07T07:31:39.000Z | [
"pytorch",
"bert",
"fill-mask",
"arxiv:1911.03090",
"arxiv:2010.02559",
"transformers",
"autotrain_compatible"
] | fill-mask | false | avichr | null | avichr/Legal-heBERT | 64 | null | transformers | 5,551 | # Legal-HeBERT
Legal-HeBERT is a BERT model for Hebrew legal and legislative domains. It is intended to improve the legal NLP research and tools development in Hebrew. We release two versions of Legal-HeBERT. The first version is a fine-tuned model of [HeBERT](https://github.com/avichaychriqui/HeBERT) applied on legal ... |
ml6team/keyphrase-extraction-kbir-kpcrowd | 04963560cd70e18a161b3f70e3d90eb97e13fcdc | 2022-06-16T14:19:57.000Z | [
"pytorch",
"roberta",
"token-classification",
"en",
"dataset:midas/kpcrowd",
"arxiv:2112.08547",
"transformers",
"keyphrase-extraction",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | ml6team | null | ml6team/keyphrase-extraction-kbir-kpcrowd | 64 | null | transformers | 5,552 | ---
language: en
license: mit
tags:
- keyphrase-extraction
datasets:
- midas/kpcrowd
metrics:
- seqeval
widget:
- text: "Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a document.
Thanks to these keyphrases humans can understand the content of a text very quickly ... |
RonEliav/QA_discourse | b892506b6a932bbfc88437e67391895d1a3ca937 | 2022-07-07T20:14:43.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | RonEliav | null | RonEliav/QA_discourse | 64 | 1 | transformers | 5,553 | ---
license: afl-3.0
---
|
Gunulhona/tbsentmodel_v1 | 03cbb401984398fc6ec2021621e66cefd123ef39 | 2022-06-22T07:13:09.000Z | [
"pytorch",
"bart",
"feature-extraction",
"transformers"
] | feature-extraction | false | Gunulhona | null | Gunulhona/tbsentmodel_v1 | 64 | null | transformers | 5,554 | Entry not found |
cynthiachan/CTI_bert_base_cased | 340feea82746c8b0985c0836359ec9ab0d0afa0e | 2022-07-14T06:57:23.000Z | [
"pytorch",
"bert",
"token-classification",
"dataset:cynthiachan/FeedRef_10pct",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | cynthiachan | null | cynthiachan/CTI_bert_base_cased | 64 | null | transformers | 5,555 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cynthiachan/FeedRef_10pct
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: training
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: cynthiachan/FeedRef_10pct
type: c... |
chizhikchi/Spanish_disease_finder | 5634b0c39174d2f41c29aec1fe28b31e60182e37 | 2022-07-15T11:19:42.000Z | [
"pytorch",
"roberta",
"token-classification",
"es",
"transformers",
"biomedical",
"clinical",
"ner",
"license:cc-by-4.0",
"autotrain_compatible"
] | token-classification | false | chizhikchi | null | chizhikchi/Spanish_disease_finder | 64 | 1 | transformers | 5,556 | ---
license: cc-by-4.0
language:
- es
tags:
- biomedical
- clinical
- ner
metrics:
- f1
widget:
- text: "Se realizó angiotomografía urgente de arterias pulmonares, que mostró tromboembolia pulmonar bilateral con dilatación ventricular derecha, además de opacidades periféricas parcheadas compatibles con neumonía por SAR... |
ZakaryaRouzki/t5-punctuation | 20efe8343037e45c47b4656e2d4f26ef0a771cda | 2022-07-04T09:48:53.000Z | [
"pytorch",
"t5",
"text2text-generation",
"fr",
"dataset:orange_sum",
"dataset:mlsum",
"transformers",
"french",
"punctuation",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | ZakaryaRouzki | null | ZakaryaRouzki/t5-punctuation | 64 | 0 | transformers | 5,557 | ---
language:
- "fr"
tags:
- t5
- french
- punctuation
license: apache-2.0
datasets:
- orange_sum
- mlsum
---
# 🚀 Text Punctuator Based on Transformers model T5.
T5 model fine-tuned for punctuation restoration.
Model currently supports only French Language. More language supports will be added later using mT5.
Tr... |
adamnik/electra-event-detection | c20cddf32a6c2f5fef7f2da87f2f08dce3771e4d | 2022-07-20T01:27:14.000Z | [
"pytorch",
"electra",
"text-classification",
"transformers",
"license:mit"
] | text-classification | false | adamnik | null | adamnik/electra-event-detection | 64 | null | transformers | 5,558 | ---
license: mit
---
|
sudo-s/modeversion1_m7_e4 | eacd70d56ffdc0559d8384e642ed4b1fe0964610 | 2022-07-23T22:44:11.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | sudo-s | null | sudo-s/modeversion1_m7_e4 | 64 | null | transformers | 5,559 | ---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: modeversion1_m7_e4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then r... |
SIMAS-UN/blaming_migrants | 4d36a7b17fe31507d758d6a8d2cc872ebe1a6c88 | 2022-07-24T03:56:22.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | SIMAS-UN | null | SIMAS-UN/blaming_migrants | 64 | null | transformers | 5,560 | Entry not found |
AI-Lab-Makerere/en_lg | d74d872401475fa5fce5768f44aaa8f4bfdf41e0 | 2022-06-28T08:38:46.000Z | [
"pytorch",
"marian",
"text2text-generation",
"unk",
"dataset:Eric Peter/autonlp-data-EN-LUG",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | AI-Lab-Makerere | null | AI-Lab-Makerere/en_lg | 63 | null | transformers | 5,561 | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- Eric Peter/autonlp-data-EN-LUG
co2_eq_emissions: 133.0219882109991
---
# Model Trained Using AutoNLP
- Problem type: Machine Translation
- Model ID: 474612462
- CO2 Emissions (in grams): 133.0219882109991
## Validation Metrics
- Loss: 1... |
Helsinki-NLP/opus-mt-hu-fr | c2885a2c79baeea474b021a129a25b561498e1dd | 2021-09-09T22:10:59.000Z | [
"pytorch",
"marian",
"text2text-generation",
"hu",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-hu-fr | 63 | null | transformers | 5,562 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-hu-fr
* source languages: hu
* target languages: fr
* OPUS readme: [hu-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/hu-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-sl-fi | db1452a4a0ec2dfaa1eee5ed4b9881298f84cd50 | 2021-09-10T14:03:42.000Z | [
"pytorch",
"marian",
"text2text-generation",
"sl",
"fi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sl-fi | 63 | null | transformers | 5,563 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-sl-fi
* source languages: sl
* target languages: fi
* OPUS readme: [sl-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sl-fi/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Kowsher/bangla-bert | f82455bb9aad640c5a1ce8f259e3d0952079fa27 | 2022-03-06T15:42:48.000Z | [
"pytorch",
"bert",
"fill-mask",
"bn",
"dataset:BanglaLM dataset",
"arxiv:1810.04805",
"transformers",
"Bert base Bangla",
"Bengali Bert",
"Bengali lm",
"Bangla Base Bert",
"Bangla Bert language model",
"Bangla Bert",
"autotrain_compatible"
] | fill-mask | false | Kowsher | null | Kowsher/bangla-bert | 63 | 1 | transformers | 5,564 | ---
language: bn
tags:
- Bert base Bangla
- Bengali Bert
- Bengali lm
- Bangla Base Bert
- Bangla Bert language model
- Bangla Bert
datasets:
- BanglaLM dataset
---
# Bangla BERT Base
Here we published a pretrained Bangla bert language model as **bangla-bert**! which is now available in huggingface model hub.
Here we ... |
Maunish/ecomm-sbert | f4fc1e544a76a2bc66970a4dad3b60d6fdc69855 | 2022-02-09T17:47:29.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Maunish | null | Maunish/ecomm-sbert | 63 | null | transformers | 5,565 | ---
license: apache-2.0
---
|
Milos/slovak-gpt-j-162M | 3ebb80b851786d0823af43ca854ce619f62d8aa4 | 2022-02-18T14:02:12.000Z | [
"pytorch",
"gptj",
"text-generation",
"sk",
"arxiv:2104.09864",
"transformers",
"Slovak GPT-J",
"causal-lm",
"license:gpl-3.0"
] | text-generation | false | Milos | null | Milos/slovak-gpt-j-162M | 63 | null | transformers | 5,566 | ---
language:
- sk
tags:
- Slovak GPT-J
- pytorch
- causal-lm
license: gpl-3.0
---
# Slovak GPT-J-162M
Slovak GPT-J-162M is the first model released in Slovak GPT-J series and the very first publicly available transformer trained predominantly on Slovak corpus. Since the initial release two other models were made publ... |
Nicki/gpt3-base | 656bb22aff7fd5afb1f92dfd7a940a9e0592fed0 | 2021-07-29T05:53:53.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | Nicki | null | Nicki/gpt3-base | 63 | null | transformers | 5,567 | Entry not found |
Prompsit/paraphrase-bert-en | 75a238bbb26c0f0dca7ec37b5e16b6381f7cdc56 | 2021-12-23T12:03:17.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"transformers"
] | text-classification | false | Prompsit | null | Prompsit/paraphrase-bert-en | 63 | 2 | transformers | 5,568 | ---
pipeline_tag: text-classification
inference: false
language: en
tags:
- transformers
---
# Prompsit/paraphrase-bert-en
This model allows to evaluate paraphrases for a given phrase.
We have fine-tuned this model from pretrained "bert-base-uncased".
Model built under a TSI-100905-2019-4 project, co-financed by M... |
SkolkovoInstitute/ruT5-base-detox | f986f748295a7e9ba6427ff7e1be6b348649c5a0 | 2021-12-29T09:13:41.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | SkolkovoInstitute | null | SkolkovoInstitute/ruT5-base-detox | 63 | null | transformers | 5,569 | This is the detoxification baseline model trained on the [train](https://github.com/skoltech-nlp/russe_detox_2022/blob/main/data/input/train.tsv) part of "RUSSE 2022: Russian Text Detoxification Based on Parallel Corpora" competition. The source sentences are Russian toxic messages from Odnoklassniki, Pikabu, and Twitt... |
ainize/gpt2-spongebob-script-large | 698090c3da4ad7e39a7d6d0ba71ecc7bd9046729 | 2021-05-21T12:18:42.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | ainize | null | ainize/gpt2-spongebob-script-large | 63 | null | transformers | 5,570 | ### Model information
Fine tuning data: https://www.kaggle.com/mikhailgaerlan/spongebob-squarepants-completed-transcripts
License: CC-BY-SA
Base model: gpt-2 large
Epoch: 50
Train runtime: 14723.0716 secs
Loss: 0.0268
API page: [Ainize](https://ainize.ai/fpem123/GPT2-Spongebob?bra... |
deepset/xlm-roberta-base-squad2-distilled | 350a9ad58048570793a7f0899dd988c69c641a51 | 2022-07-26T09:06:02.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"multilingual",
"dataset:squad_v2",
"transformers",
"exbert",
"license:mit",
"autotrain_compatible"
] | question-answering | false | deepset | null | deepset/xlm-roberta-base-squad2-distilled | 63 | 3 | transformers | 5,571 | ---
language: multilingual
datasets:
- squad_v2
license: mit
thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
tags:
- exbert
---
# deepset/xlm-roberta-base-squad2-distilled
- haystack's distillation feature was used for training. deepset/xlm-roberta-... |
flax-sentence-embeddings/multi-QA_v1-mpnet-asymmetric-Q | f74da44e63bbe972163212b46ce195eca92eb35a | 2021-07-25T21:32:52.000Z | [
"pytorch",
"mpnet",
"fill-mask",
"arxiv:2102.07033",
"arxiv:2104.08727",
"sentence-transformers",
"feature-extraction",
"sentence-similarity"
] | sentence-similarity | false | flax-sentence-embeddings | null | flax-sentence-embeddings/multi-QA_v1-mpnet-asymmetric-Q | 63 | null | sentence-transformers | 5,572 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# multi-QA_v1-mpnet-asymmetric-Q
## Model Description
SentenceTransformers is a set of models and frameworks that enable training and generating sentence embeddings from given data. The generated sentence ... |
jasminejwebb/KeywordIdentifier | ff14521a2d83c63f90b8d9cd7a0c1710a06c46f0 | 2022-02-11T21:48:06.000Z | [
"pytorch",
"xlnet",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | jasminejwebb | null | jasminejwebb/KeywordIdentifier | 63 | 4 | transformers | 5,573 | Entry not found |
jcblaise/roberta-tagalog-large | acb6b204dfb1afdd7476eae5da234cbcf8899846 | 2021-11-12T03:25:48.000Z | [
"pytorch",
"tf",
"roberta",
"fill-mask",
"tl",
"transformers",
"tagalog",
"filipino",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | jcblaise | null | jcblaise/roberta-tagalog-large | 63 | null | transformers | 5,574 | ---
language: tl
tags:
- roberta
- tagalog
- filipino
license: cc-by-sa-4.0
inference: false
---
# RoBERTa Tagalog Large
Tagalog RoBERTa trained as an improvement over our previous Tagalog pretrained Transformers. Trained with TLUnified, a newer, larger, more topically-varied pretraining corpus for Filipino. This mode... |
jshu/gpt2-medium-ontapdoc-gen-2 | bf64adef84bb910d69b9630a9894ff189f254ff3 | 2021-11-19T18:29:36.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | jshu | null | jshu/gpt2-medium-ontapdoc-gen-2 | 63 | null | transformers | 5,575 | Entry not found |
mrm8488/mbart-large-finetuned-opus-it-en-translation | 040c4a41cf5b171be94ffc43d22e174da8eb69a8 | 2021-01-27T13:19:19.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"it",
"en",
"dataset:opus100",
"transformers",
"translation",
"autotrain_compatible"
] | translation | false | mrm8488 | null | mrm8488/mbart-large-finetuned-opus-it-en-translation | 63 | 1 | transformers | 5,576 | ---
tags:
- translation
language:
- it
- en
datasets:
- opus100
---
### mbart-large-it-en
This is mbart-large-cc25, finetuned on opus100 for Italian to English translation.
It scores BLEU **25.82** on test set. |
philippelaban/keep_it_simple | e8fe51874a3c97787bbfe6b2ef115b4b409ccdad | 2022-02-09T22:42:47.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"dataset:cnn_dailymail",
"transformers",
"simplification",
"license:apache-2.0"
] | text-generation | false | philippelaban | null | philippelaban/keep_it_simple | 63 | 1 | transformers | 5,577 | ---
language:
- en
tags:
- simplification
license: apache-2.0
datasets:
- cnn_dailymail
widget:
- text: "A capsule containing asteroid soil samples landed in the Australian Outback. The precision required to carry out the mission thrilled many.<|endoftext|>"
example_title: "Example 1"
---
# Try out in the Hosted inf... |
projecte-aina/roberta-base-ca-cased-sts | 1e644c69274edfbb239eccbf565dd6a38d2cef27 | 2022-06-16T08:04:23.000Z | [
"pytorch",
"roberta",
"text-classification",
"ca",
"dataset:projecte-aina/sts-ca",
"arxiv:1907.11692",
"transformers",
"catalan",
"semantic textual similarity",
"sts-ca",
"CaText",
"Catalan Textual Corpus",
"license:apache-2.0",
"model-index"
] | text-classification | false | projecte-aina | null | projecte-aina/roberta-base-ca-cased-sts | 63 | null | transformers | 5,578 | ---
language:
- ca
pipeline_tag: text-classification
license: apache-2.0
tags:
- "catalan"
- "semantic textual similarity"
- "sts-ca"
- "CaText"
- "Catalan Textual Corpus"
datasets:
- "projecte-aina/sts-ca"
metrics:
- "pearson"
model-index:
- name: roberta-base-ca-cased-sts
results:
- task:
type: text-clas... |
razent/cotext-2-cc | c44d0273e79da8a1ec3273c80b300ade6277a493 | 2022-03-15T03:03:51.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"feature-extraction",
"code",
"dataset:code_search_net",
"transformers"
] | feature-extraction | false | razent | null | razent/cotext-2-cc | 63 | null | transformers | 5,579 | ---
language: code
datasets:
- code_search_net
---
# CoText (2-CC)
## Introduction
Paper: [CoTexT: Multi-task Learning with Code-Text Transformer](https://aclanthology.org/2021.nlp4prog-1.5.pdf)
Authors: _Long Phan, Hieu Tran, Daniel Le, Hieu Nguyen, James Anibal, Alec Peltekian, Yanfang Ye_
## How to use
Support... |
wietsedv/xlm-roberta-base-ft-udpos28-tr | 86a24b17a2c653386b580c843d3e38e3791c0c44 | 2022-02-25T09:59:31.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"tr",
"dataset:universal_dependencies",
"transformers",
"part-of-speech",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | wietsedv | null | wietsedv/xlm-roberta-base-ft-udpos28-tr | 63 | null | transformers | 5,580 |
---
language:
- tr
license: apache-2.0
library_name: transformers
tags:
- part-of-speech
- token-classification
datasets:
- universal_dependencies
metrics:
- accuracy
model-index:
- name: xlm-roberta-base-ft-udpos28-tr
results:
- task:
type: token-classification
name: Part-of-Speech Tagging
datas... |
GermanT5/t5-efficient-gc4-german-base-nl36 | 756f657882367c9929e220d9bfba87641cf4a641 | 2022-07-22T05:27:06.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"de",
"transformers",
"german",
"deutsch",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | GermanT5 | null | GermanT5/t5-efficient-gc4-german-base-nl36 | 63 | 3 | transformers | 5,581 | ---
language: de
license: mit
tags:
- german
- deutsch
---
# Creators
- [Stefan Schweter](https://github.com/stefan-it) ([Bayerische Staatsbibliothek](https://www.digitale-sammlungen.de/) / [Open Source @ DBMDZ](https://github.com/dbmdz))
- [Philip May](https://may.la) ([T-Systems onsite](https://www.t-systems-onsite.... |
microsoft/tapex-large-finetuned-wikisql | aff5c522ffb429d0ad290e900a1863ce63a8325f | 2022-07-14T10:10:52.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:wikisql",
"arxiv:2107.07653",
"transformers",
"tapex",
"table-question-answering",
"license:mit",
"autotrain_compatible"
] | table-question-answering | false | microsoft | null | microsoft/tapex-large-finetuned-wikisql | 63 | 1 | transformers | 5,582 | ---
language: en
tags:
- tapex
- table-question-answering
datasets:
- wikisql
license: mit
---
# TAPEX (large-sized model)
TAPEX was proposed in [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://arxiv.org/abs/2107.07653) by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Ji... |
adnankhawaja/RomanUrdu-RoBERTa-AFT | 71f73fefec1f583a7e23874fbdf3a6ea6a6472f8 | 2022-04-07T06:05:31.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | adnankhawaja | null | adnankhawaja/RomanUrdu-RoBERTa-AFT | 63 | null | transformers | 5,583 | Entry not found |
speechbrain/asr-wav2vec2-librispeech | cab1aa4c274467daba8e395b6832f88da8684576 | 2022-06-08T14:40:42.000Z | [
"wav2vec2",
"feature-extraction",
"en",
"dataset:librispeech",
"arxiv:2106.04624",
"speechbrain",
"automatic-speech-recognition",
"CTC",
"Attention",
"Transformer",
"pytorch",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | speechbrain | null | speechbrain/asr-wav2vec2-librispeech | 63 | null | speechbrain | 5,584 | ---
language:
- en
thumbnail: null
pipeline_tag: automatic-speech-recognition
tags:
- automatic-speech-recognition
- CTC
- Attention
- Transformer
- pytorch
- speechbrain
- hf-asr-leaderboard
license: apache-2.0
datasets:
- librispeech
metrics:
- wer
- cer
model-index:
- name: wav2vec2+CTC by SpeechBrain
results:
-... |
shengnan/visualize-v0-pre10w-preseed1 | 06b5ab7354aeff0486a62b88161e304f36171582 | 2022-07-18T02:36:21.000Z | [
"pytorch",
"t5",
"transformers"
] | null | false | shengnan | null | shengnan/visualize-v0-pre10w-preseed1 | 63 | null | transformers | 5,585 | Entry not found |
SharpAI/mal_tls-bert-base | dd28f9eb446b6506df6ae5caed873ab5d9534df6 | 2022-07-27T20:51:25.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"transformers",
"generated_from_keras_callback",
"model-index"
] | text-classification | false | SharpAI | null | SharpAI/mal_tls-bert-base | 63 | null | transformers | 5,586 | ---
tags:
- generated_from_keras_callback
model-index:
- name: mal_tls-bert-base
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-bert-base
This model is a f... |
Helsinki-NLP/opus-mt-en-grk | aaa456e34dfc48aca1e9e13a8e4b0ee357464e03 | 2021-01-18T08:08:31.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"el",
"grk",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-grk | 62 | null | transformers | 5,587 | ---
language:
- en
- el
- grk
tags:
- translation
license: apache-2.0
---
### eng-grk
* source group: English
* target group: Greek languages
* OPUS readme: [eng-grk](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-grk/README.md)
* model: transformer
* source language(s): eng
* target... |
Helsinki-NLP/opus-mt-ro-fr | a71843f60cb4f44315caf92df79fb079912c4adc | 2021-09-10T14:02:10.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ro",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ro-fr | 62 | null | transformers | 5,588 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ro-fr
* source languages: ro
* target languages: fr
* OPUS readme: [ro-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ro-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
RecordedFuture/Swedish-Sentiment-Fear | 7764733e64267aae40785babd36014a0163b250a | 2021-05-18T22:00:42.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"sv",
"transformers",
"license:mit"
] | text-classification | false | RecordedFuture | null | RecordedFuture/Swedish-Sentiment-Fear | 62 | null | transformers | 5,589 | ---
language: sv
license: mit
---
## Swedish BERT models for sentiment analysis
[Recorded Future](https://www.recordedfuture.com/) together with [AI Sweden](https://www.ai.se/en) releases two language models for sentiment analysis in Swedish. The two models are based on the [KB\/bert-base-swedish-cased](https://huggi... |
TransQuest/monotransquest-da-any_en | 386039f2027514b199054024102504cdb2a4d794 | 2021-06-03T19:01:07.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"multilingual-en",
"transformers",
"Quality Estimation",
"monotransquest",
"DA",
"license:apache-2.0"
] | text-classification | false | TransQuest | null | TransQuest/monotransquest-da-any_en | 62 | null | transformers | 5,590 | ---
language: multilingual-en
tags:
- Quality Estimation
- monotransquest
- DA
license: apache-2.0
---
# TransQuest: Translation Quality Estimation with Cross-lingual Transformers
The goal of quality estimation (QE) is to evaluate the quality of a translation without having access to a reference translation. High-acc... |
TuhinColumbia/russianpoetrymany | 036331d815ebd4bec0c902ef01b0f02c9d15372f | 2021-08-31T15:52:43.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | TuhinColumbia | null | TuhinColumbia/russianpoetrymany | 62 | 1 | transformers | 5,591 | Entry not found |
TurkuNLP/wikibert-base-ja-cased | dcef59fb3e01803fdb4bc28b449f1fb0d5011e0d | 2020-05-24T20:00:52.000Z | [
"pytorch",
"transformers"
] | null | false | TurkuNLP | null | TurkuNLP/wikibert-base-ja-cased | 62 | null | transformers | 5,592 | Entry not found |
VictorSanh/bart-base-finetuned-xsum | f7347d6b497512cb9997f14914ea6b309b8f6b7c | 2020-08-17T15:02:57.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | VictorSanh | null | VictorSanh/bart-base-finetuned-xsum | 62 | null | transformers | 5,593 | Entry not found |
aychang/distilbert-base-cased-trec-coarse | 70316ea77d74b8e1e5c939fbf2499594091cab77 | 2021-01-24T20:14:42.000Z | [
"pytorch",
"distilbert",
"text-classification",
"en",
"dataset:trec",
"transformers",
"license:mit"
] | text-classification | false | aychang | null | aychang/distilbert-base-cased-trec-coarse | 62 | null | transformers | 5,594 | ---
language:
- en
thumbnail:
tags:
- text-classification
license: mit
datasets:
- trec
metrics:
---
# TREC 6-class Task: distilbert-base-cased
## Model description
A simple base distilBERT model trained on the "trec" dataset.
## Intended uses & limitations
#### How to use
##### Transformers
```python
# Load ... |
cardiffnlp/twitter-roberta-base-dec2020 | 54381a7fb92f904744f8417a1904157260f0dafe | 2022-02-09T11:15:03.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.03829",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cardiffnlp | null | cardiffnlp/twitter-roberta-base-dec2020 | 62 | null | transformers | 5,595 | # Twitter December 2020 (RoBERTa-base, 107M)
This is a RoBERTa-base model trained on 107.06M tweets until the end of December 2020.
More details and performance scores are available in the [TimeLMs paper](https://arxiv.org/abs/2202.03829).
Below, we provide some usage examples using the standard Transformers interfac... |
echarlaix/bart-base-cnn-r2-19.4-d35-hybrid | 45d5d5098dcd6a347301af116f393e672f13cc2c | 2021-08-20T09:56:33.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:cnn_dailymail",
"transformers",
"summarization",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | echarlaix | null | echarlaix/bart-base-cnn-r2-19.4-d35-hybrid | 62 | null | transformers | 5,596 | ---
language: en
license: apache-2.0
tags:
- summarization
datasets:
- cnn_dailymail
metrics:
- R1
- R2
- RL
---
## facebook/bart-base model fine-tuned on CNN/DailyMail
This model was created using the [nn_pruning](https://github.com/huggingface/nn_pruning) python library: the linear layers contains **35%** of the or... |
huggingartists/oxxxymiron | ff2682609172f5173182077e563b36a0cc057c69 | 2022-07-06T16:17:56.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:huggingartists/oxxxymiron",
"transformers",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm"
] | text-generation | false | huggingartists | null | huggingartists/oxxxymiron | 62 | null | transformers | 5,597 | ---
language: en
datasets:
- huggingartists/oxxxymiron
tags:
- huggingartists
- lyrics
- lm-head
- causal-lm
widget:
- text: "I am"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; heigh... |
lgris/bp_400h_xlsr2_300M | 0cc8ef01e53c684cf94fdffc4b9933c44b3dd1fa | 2022-04-01T20:32:02.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"transformers",
"mozilla-foundation/common_voice_7_0",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | lgris | null | lgris/bp_400h_xlsr2_300M | 62 | 1 | transformers | 5,598 | ---
language:
- pt
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- pt
- hf-asr-leaderboard
license: apache-2.0
model-index:
- name: bp_400h_xlsr2_300M
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voi... |
lighteternal/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-mnli | fdb646ec000c7ec8076df9db55995839aec61b2d | 2021-10-27T07:47:56.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"en",
"dataset:mnli",
"transformers",
"textual-entailment",
"nli",
"license:mit"
] | text-classification | false | lighteternal | null | lighteternal/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-mnli | 62 | 2 | transformers | 5,599 | ---
language: en
tags:
- textual-entailment
- nli
- pytorch
datasets:
- mnli
license: mit
widget :
- text: "EpCAM is overexpressed in breast cancer. </s></s> EpCAM is downregulated in breast cancer."
---
# BiomedNLP-PubMedBERT finetuned on textual entailment (NLI)
The [microsoft/BiomedNLP-PubMedBERT-base-uncased-abst... |
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