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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Shushant/nepaliBERT | 7756f55f1a3baf78954db166fc4a5f72d2dd223f | 2021-12-30T10:50:41.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Shushant | null | Shushant/nepaliBERT | 220 | 1 | transformers | 3,500 | # Masked Language Model for nepali language trained on nepali news scrapped from different nepali news website. The data set contained about 10 million of nepali sentences mainly related to nepali news.
Usage
```
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("S... |
salti/xlm-roberta-large-arabic_qa | 9b67103437243acee1496171e03c470b07003b44 | 2020-08-16T06:11:43.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | salti | null | salti/xlm-roberta-large-arabic_qa | 220 | 1 | transformers | 3,501 | Entry not found |
sentence-transformers/gtr-t5-base | 967b0854e46f8d3a0d42429301397715821a682f | 2022-02-09T12:27:26.000Z | [
"pytorch",
"t5",
"en",
"arxiv:2112.07899",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/gtr-t5-base | 220 | null | sentence-transformers | 3,502 | ---
pipeline_tag: sentence-similarity
language: en
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/gtr-t5-base
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 di... |
okwach/mawaidhaChatbot2 | ec5c5a7df9a91cc0b3b3c3bc8d036bb1c6ccce21 | 2022-05-20T00:32:11.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | okwach | null | okwach/mawaidhaChatbot2 | 220 | null | transformers | 3,503 | ---
tags:
- conversational
---
# mawaidhaChatbot Model |
romainlhardy/t5-small-booksum | 6e3603147c20f9e14818b881b623b287bb13d1b4 | 2022-07-04T08:24:36.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | romainlhardy | null | romainlhardy/t5-small-booksum | 220 | null | transformers | 3,504 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-booksum
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. -->
# t5-small-booksum
... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment | d383f6d3a1fd2aa63c99186b0155ed4258eb512f | 2021-10-17T12:08:30.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment | 219 | 2 | transformers | 3,505 | ---
language:
- ar
license: apache-2.0
widget:
- text: "أنا بخير"
---
# CAMeLBERT MSA SA Model
## Model description
**CAMeLBERT MSA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Modern Standard Arabic (MSA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa/)... |
Plencers/DialoGPT-small-homer | 7b3aff837e30d8f7b917b81f08f25875f96b246f | 2021-08-28T07:37:46.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Plencers | null | Plencers/DialoGPT-small-homer | 219 | null | transformers | 3,506 | ---
tags:
- conversational
---
#Homer DialoGPT Model |
madhurjindal/autonlp-Gibberish-Detector-492513457 | db6c021260b82f42ba81a4e48dc2906ca8ba25c8 | 2022-01-12T10:42:19.000Z | [
"pytorch",
"distilbert",
"text-classification",
"en",
"dataset:madhurjindal/autonlp-data-Gibberish-Detector",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | false | madhurjindal | null | madhurjindal/autonlp-Gibberish-Detector-492513457 | 219 | 1 | transformers | 3,507 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- madhurjindal/autonlp-data-Gibberish-Detector
co2_eq_emissions: 5.527544460835904
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 492513457
- CO2 Emissions (in grams): 5.527544460835904
## Validatio... |
mikabeebee/Peterbot | c24f8b63211f7098bf9761d27bfacbb55783cba8 | 2022-02-26T16:56:05.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | mikabeebee | null | mikabeebee/Peterbot | 219 | null | transformers | 3,508 | ---
tags:
- conversational
---
# Peter from Your Boyfriend Game.
|
ChrisUPM/BioBERT_Re_trained | 8e39448c5a6a226656f3872407286051bcda1307 | 2022-06-15T11:10:39.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | ChrisUPM | null | ChrisUPM/BioBERT_Re_trained | 219 | null | transformers | 3,509 | PyTorch trained model on GAD dataset for relation classification, using BioBert weights. |
laituan245/molt5-small | f3c5e3abbb55561901cadb09f798b70c8eba102e | 2022-05-03T18:07:24.000Z | [
"pytorch",
"t5",
"text2text-generation",
"arxiv:2204.11817",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | laituan245 | null | laituan245/molt5-small | 219 | 1 | transformers | 3,510 | ---
license: apache-2.0
---
## Example Usage
```python
from transformers import AutoTokenizer, T5ForConditionalGeneration
tokenizer = AutoTokenizer.from_pretrained("laituan245/molt5-small", model_max_length=512)
model = T5ForConditionalGeneration.from_pretrained('laituan245/molt5-small')
```
## Paper
For more inform... |
Browbon/DialoGPT-medium-LucaChangretta | 5842d11f7a2b77521cc5867ad973c2a1d8f0b8d3 | 2022-06-15T07:51:32.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Browbon | null | Browbon/DialoGPT-medium-LucaChangretta | 219 | null | transformers | 3,511 | ---
tags:
- conversational
---
# LucaChangretta DialoGPT Model |
crystallyzing/DialoGPT-small-kiryu | 49f8a05c3be7578bdc4cf46456449c19cce81917 | 2022-06-20T23:53:27.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | crystallyzing | null | crystallyzing/DialoGPT-small-kiryu | 219 | null | transformers | 3,512 | ---
tags:
- conversational
---
# Kiryu Chatbot Model |
ZeyadAhmed/AraElectra-Arabic-SQuADv2-QA | 039af903dd4c78cfe36b87fc4115d4dfdfcc971a | 2022-07-04T15:34:40.000Z | [
"pytorch",
"electra",
"question-answering",
"ar",
"dataset:ZeyadAhmed/Arabic-SQuADv2.0",
"transformers",
"autotrain_compatible"
] | question-answering | false | ZeyadAhmed | null | ZeyadAhmed/AraElectra-Arabic-SQuADv2-QA | 219 | null | transformers | 3,513 | ---
datasets:
- ZeyadAhmed/Arabic-SQuADv2.0
language:
- ar
metrics:
-
name: exact_match
type: exact_match
value: 65.12
-
name: F1
type: f1
value: 71.49
---
# AraElectra for Question Answering on Arabic-SQuADv2
This is the [AraElectra](https://huggingface.co/aubmindlab/araelectra-... |
cardiffnlp/twitter-roberta-base-jun2022 | 93359ad9421cd11b46684cd5c72ef496613db1d5 | 2022-07-19T17:08:36.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.03829",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cardiffnlp | null | cardiffnlp/twitter-roberta-base-jun2022 | 219 | 1 | transformers | 3,514 | # Twitter June 2022 (RoBERTa-base, 132M)
This is a RoBERTa-base model trained on 132.26M tweets until the end of June 2022.
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 interface. For a... |
Kyleiwaniec/COS_TAPT_n_RoBERTa | 1ea115a0af6be092bfc37aef97b0227d67089794 | 2022-07-20T05:48:38.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"license:cc",
"autotrain_compatible"
] | fill-mask | false | Kyleiwaniec | null | Kyleiwaniec/COS_TAPT_n_RoBERTa | 219 | null | transformers | 3,515 | ---
license: cc
---
|
Newtral/xlm-r-finetuned-toxic-political-tweets-es | dcb737a20afc37daf8aeef107ee902de1cc2c7ec | 2022-05-09T07:47:22.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"es",
"transformers",
"license:apache-2.0"
] | text-classification | false | Newtral | null | Newtral/xlm-r-finetuned-toxic-political-tweets-es | 218 | 3 | transformers | 3,516 | ---
language: es
license: apache-2.0
---
# xlm-r-finetuned-toxic-political-tweets-es
This model is based on the pre-trained model [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) and was fine-tuned on a dataset of tweets from members of the [Spanish Congress of the Deputies](https://www.congreso.es/) annot... |
fmmolina/bert-base-spanish-wwm-uncased-finetuned-NER-medical | 1003bba70adfafd239b13f805f641532ce007108 | 2022-04-03T13:39:03.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | fmmolina | null | fmmolina/bert-base-spanish-wwm-uncased-finetuned-NER-medical | 218 | null | transformers | 3,517 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-spanish-wwm-uncased-finetuned-NER-medical
results: []
widget:
- text: "El útero o matriz es el lugar donde se desarrolla el bebé cuando una mujer está embarazada."
- text: "El síndrome de dolor regional com... |
yanekyuk/berturk-uncased-keyword-discriminator | 622dcea3aac29e86bc7f4b1e6b9b878667251306 | 2022-06-06T17:09:35.000Z | [
"pytorch",
"bert",
"token-classification",
"tr",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | yanekyuk | null | yanekyuk/berturk-uncased-keyword-discriminator | 218 | null | transformers | 3,518 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
language:
- tr
widget:
- text: "İngiltere'de düzenlenen Avrupa Tekvando ve Para Tekvando Şampiyonası’nda millî tekvandocular 5 altın, 2 gümüş ve 4 bronz olmak üzere 11, millî para tekvandocular ise 4 altın, 3 gümüş ve 1 bronz ... |
IDEA-CCNL/Randeng-T5-784M | 19a36b40eef4631a89929885e6f8af12b5c882f5 | 2022-06-08T13:04:59.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"zh",
"transformers",
"T5",
"chinese",
"sentencepiece",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | IDEA-CCNL | null | IDEA-CCNL/Randeng-T5-784M | 218 | null | transformers | 3,519 | ---
language:
- zh
license: apache-2.0
tags:
- T5
- chinese
- sentencepiece
inference: true
widget:
- text: "北京有悠久的 <extra_id_0>和 <extra_id_1>。"
- type: "text-generation"
---
# Randeng-T5-784M, one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
Based on mt5-large, Randeng-T5-784M only ... |
wvangils/BLOOM-350m-Beatles-Lyrics-finetuned-newlyrics | 99fddd1509379bd6a5a2c93bfdb80273c32e991f | 2022-07-05T09:01:30.000Z | [
"pytorch",
"tensorboard",
"bloom",
"text-generation",
"transformers",
"generated_from_trainer",
"license:bigscience-bloom-rail-1.0",
"model-index"
] | text-generation | false | wvangils | null | wvangils/BLOOM-350m-Beatles-Lyrics-finetuned-newlyrics | 218 | null | transformers | 3,520 | ---
license: bigscience-bloom-rail-1.0
tags:
- generated_from_trainer
model-index:
- name: BLOOM-350m-Beatles-Lyrics-finetuned-newlyrics
results: []
widget:
- text: "Last night I couldn't sleep"
example_title: "Sleep"
- text: "It hasn't rained in weeks"
example_title: "Rain"
---
# BLOOM-350m-Beatles-Lyri... |
thannarot/hug-clip-bid | 6f6b2967f2956fdee5db9c6092ef975f03446fd3 | 2022-07-14T08:07:35.000Z | [
"pytorch",
"clip",
"feature-extraction",
"transformers",
"generated_from_trainer",
"model-index"
] | feature-extraction | false | thannarot | null | thannarot/hug-clip-bid | 218 | null | transformers | 3,521 | ---
tags:
- generated_from_trainer
model-index:
- name: hug-clip-bid
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. -->
# hug-clip-bid
This model is a fine-tuned v... |
EMBEDDIA/finest-bert | c61edda13bbf7eed6207fb1955c78a49f2dbe4c3 | 2021-05-18T18:22:50.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"fi",
"et",
"en",
"multilingual",
"arxiv:2006.07890",
"transformers",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | EMBEDDIA | null | EMBEDDIA/finest-bert | 217 | 2 | transformers | 3,522 | ---
language:
- fi
- et
- en
- multilingual
license: cc-by-4.0
---
# FinEst BERT
FinEst BERT is a trilingual model, using bert-base architecture, trained on Finnish, Estonian, and English corpora. Focusing on three languages, the model performs better than [multilingual BERT](https://huggingface.co/bert-base-multilin... |
SkolkovoInstitute/t5-paraphrase-paws-msrp-opinosis-paranmt | b57298e55f51f97a69e563bc6abfa183d80a5c92 | 2021-11-02T17:58:47.000Z | [
"pytorch",
"t5",
"text2text-generation",
"arxiv:1711.05732",
"arxiv:1911.00536",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | SkolkovoInstitute | null | SkolkovoInstitute/t5-paraphrase-paws-msrp-opinosis-paranmt | 217 | null | transformers | 3,523 | This is a paraphraser based on [ceshine/t5-paraphrase-paws-msrp-opinosis](https://huggingface.co/ceshine/t5-paraphrase-paws-msrp-opinosis)
and additionally fine-tuned on [ParaNMT](https://arxiv.org/abs/1711.05732).
The model was trained for the paper [Text Detoxification using Large Pre-trained Neural Models](https://... |
Tejas3/distillbert_base_uncased_80_equal | ee468b60927a3f86b74d0b696cc1d21e58d99ae7 | 2021-07-15T08:48:42.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | Tejas3 | null | Tejas3/distillbert_base_uncased_80_equal | 217 | null | transformers | 3,524 | Entry not found |
tprincessazula/Dialog-GPT-small-SOKKA-AVATAR | afe1e4694d9eb7d16c0c8f3955d68d86ed1cc816 | 2021-12-12T08:03:47.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | tprincessazula | null | tprincessazula/Dialog-GPT-small-SOKKA-AVATAR | 217 | 1 | transformers | 3,525 | ---
tags:
- conversational
---
#SOKKA DialoGPT Model |
north/demo-deuncaser-base | 568a9c61bdc3a74c9cb4d98e9a1152fe260a69c2 | 2022-05-29T21:33:28.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"no",
"transformers",
"translation",
"license:cc-by-4.0",
"autotrain_compatible"
] | translation | false | north | null | north/demo-deuncaser-base | 217 | null | transformers | 3,526 | ---
language: no
tags:
- translation
widget:
- text: "tirsdag var travel for ukrainas president volodymyr zelenskyj på morgenen tok han imot polens statsminister mateusz morawiecki"
- text: "tirsdagvartravelforukrainaspresidentvolodymyrzelenskyjpåkveldentokhanimotpolensstatsministermateuszmorawiecki"
- text: "deterikke... |
dbmdz/distilbert-base-german-europeana-cased | 1eaca02960b72f719043fbd4a8b026d4543b4dad | 2022-06-09T07:27:27.000Z | [
"pytorch",
"tf",
"distilbert",
"de",
"transformers",
"historic german",
"license:mit"
] | null | false | dbmdz | null | dbmdz/distilbert-base-german-europeana-cased | 216 | 2 | transformers | 3,527 | ---
language: de
license: mit
tags:
- "historic german"
---
# 🤗 + 📚 dbmdz DistilBERT model
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a German Europeana DistilBERT model 🎉
# German Europeana DistilBERT
We use the open source [Europeana newspapers](http://... |
sakares/wav2vec2-large-xlsr-thai-demo | ba9ae764735fbb69671c7c2befb88ef3501683eb | 2021-03-22T07:15:18.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | sakares | null | sakares/wav2vec2-large-xlsr-thai-demo | 216 | 2 | transformers | 3,528 | ---
language: th
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Large Thai by Sakares
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Comm... |
SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask | df97ce5e290c1764e73041a13a65b8729f999d60 | 2021-06-23T06:39:28.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask | 215 | null | transformers | 3,529 | ---
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 large model architecture... |
ionite/DialoGPT-medium-IoniteAI | 2466d0a29b45187b76471501039beac68f4e6bd4 | 2021-11-19T04:10:33.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ionite | null | ionite/DialoGPT-medium-IoniteAI | 215 | null | transformers | 3,530 | ---
tags:
- conversational
---
# IoniteAI DialoGPT Model |
lrakotoson/scitldr-catts-xsum-ao | 44d53024dcfd315d3af7259838399042748e0aac | 2021-07-20T07:51:18.000Z | [
"pytorch",
"tf",
"bart",
"text2text-generation",
"en",
"dataset:xsum",
"dataset:scitldr",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | lrakotoson | null | lrakotoson/scitldr-catts-xsum-ao | 215 | 7 | transformers | 3,531 | ---
language:
- en
datasets:
- xsum
- scitldr
widget:
- text: "We introduce TLDR generation, a new form of extreme summarization, for scientific papers. TLDR generation involves high source compression and requires expert background knowledge and understanding of complex domain-specific language. To facilitate study on... |
sh110495/kor-pegasus | 401672258ab4df7d9201c796f40a3bf7a0542ef2 | 2022-07-19T13:52:32.000Z | [
"pytorch",
"pegasus",
"feature-extraction",
"transformers"
] | feature-extraction | false | sh110495 | null | sh110495/kor-pegasus | 215 | 1 | transformers | 3,532 | Entry not found |
felinecity/DioloGPT-small-KaeyaBot2 | 37a4f9ea84aed5b65548a4f4f02576500df2e589 | 2022-01-15T06:26:04.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | felinecity | null | felinecity/DioloGPT-small-KaeyaBot2 | 214 | null | transformers | 3,533 | ---
tags:
- conversational
---
# DioloGPT KaeyaBot model |
flax-community/t5-base-cnn-dm | 8ee9fb4705b4682c7643eae5c0e0204e5b017200 | 2022-06-29T20:37:14.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"en",
"dataset:cnn_dailymail",
"transformers",
"summarization",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | flax-community | null | flax-community/t5-base-cnn-dm | 214 | 1 | transformers | 3,534 | ---
language: en
tags:
- summarization
license: apache-2.0
datasets:
- cnn_dailymail
model-index:
- name: flax-community/t5-base-cnn-dm
results:
- task:
type: summarization
name: Summarization
dataset:
name: cnn_dailymail
type: cnn_dailymail
config: 3.0.0
split: test
metr... |
lgris/bp500-base10k_voxpopuli | d3f6416e7d2edb18abd5a604cf5c847bc52595c2 | 2022-04-01T20:34:35.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:common_voice",
"dataset:mls",
"dataset:cetuc",
"dataset:lapsbm",
"dataset:voxforge",
"dataset:tedx",
"dataset:sid",
"arxiv:2012.03411",
"transformers",
"audio",
"speech",
"portuguese-speech-corpus",
"PyTorch",
"h... | automatic-speech-recognition | false | lgris | null | lgris/bp500-base10k_voxpopuli | 214 | null | transformers | 3,535 | ---
language: pt
datasets:
- common_voice
- mls
- cetuc
- lapsbm
- voxforge
- tedx
- sid
metrics:
- wer
tags:
- audio
- speech
- wav2vec2
- pt
- portuguese-speech-corpus
- automatic-speech-recognition
- speech
- PyTorch
- hf-asr-leaderboard
model-index:
- name: bp500-base10k_voxpopuli
results:
- task:
name: ... |
munezah/DialoGPT-small-aot | 8f45548e2773ab5ec614e093b8f8792399b739e7 | 2021-09-12T15:59:00.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | munezah | null | munezah/DialoGPT-small-aot | 214 | null | transformers | 3,536 | ---
tags:
- conversational
---
# aot DialoGPT Model
|
Intel/bert-large-uncased-squadv1.1-sparse-80-1x4-block-pruneofa | 64efe51573e91a5882bd5404a64f681add1e03f9 | 2022-03-27T21:44:13.000Z | [
"pytorch",
"onnx",
"bert",
"question-answering",
"en",
"arxiv:2111.05754",
"transformers",
"autotrain_compatible"
] | question-answering | false | Intel | null | Intel/bert-large-uncased-squadv1.1-sparse-80-1x4-block-pruneofa | 214 | null | transformers | 3,537 | ---
language: en
---
# 80% 1x4 Block Sparse BERT-Large (uncased) Fine Tuned on SQuADv1.1
This model is a result of fine-tuning a Prune OFA 80% 1x4 block sparse pre-trained BERT-Large combined with knowledge distillation.
This model yields the following results on SQuADv1.1 development set:<br>
`{"exact_match": 84.673, ... |
dmis-lab/biosyn-biobert-bc2gn | c4e5e1f07dba9f564624a8dae134e3d3c6ea0187 | 2022-02-25T13:34:38.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | dmis-lab | null | dmis-lab/biosyn-biobert-bc2gn | 213 | null | transformers | 3,538 | hello
|
shahrukhx01/gbert-germeval-2021 | a864e82a4abec0bdd00cfae57b44836e21b393f8 | 2022-03-23T18:21:01.000Z | [
"pytorch",
"bert",
"text-classification",
"de",
"transformers",
"hate-speech-classification"
] | text-classification | false | shahrukhx01 | null | shahrukhx01/gbert-germeval-2021 | 213 | null | transformers | 3,539 | ---
language: "de"
tags:
- hate-speech-classification
widget:
- text: "Als jemand, der im real existierenden Sozialismus aufgewachsen ist, kann ich über George Weineberg nur sagen, dass er ein Voll...t ist. Finde es schon gut, dass der eingeladen wurde. Hat gezeigt, dass er viel Meinung hat, aber offensichtlich we... |
csebuetnlp/banglabert_generator | 06dd644b4167462e40bb0354ee62a530b2d2febd | 2022-06-07T12:16:59.000Z | [
"pytorch",
"electra",
"fill-mask",
"bn",
"en",
"arxiv:2101.00204",
"transformers",
"autotrain_compatible"
] | fill-mask | false | csebuetnlp | null | csebuetnlp/banglabert_generator | 213 | 1 | transformers | 3,540 | ---
language:
- bn
- en
licenses:
- cc-by-nc-sa-4.0
---
# BanglishBERT
This repository contains the pretrained generator checkpoint of the model [**BanglaBERT**](). This is an [ELECTRA](https://openreview.net/pdf?id=r1xMH1BtvB) generator model pretrained with the Masked Language Modeling (MLM) objective on large amo... |
xlm-roberta-large-finetuned-conll02-dutch | c0a0c5196da660dc28bc80e9d94edd28b35fc4e5 | 2022-07-22T08:07:08.000Z | [
"pytorch",
"rust",
"xlm-roberta",
"fill-mask",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha",
"he... | fill-mask | false | null | null | xlm-roberta-large-finetuned-conll02-dutch | 212 | null | transformers | 3,541 | ---
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- my
... |
howey/roberta-large-sst2 | 39794fcd4c738aeb975812ff1e03f397725f5ecb | 2021-06-03T11:35:36.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | howey | null | howey/roberta-large-sst2 | 212 | null | transformers | 3,542 | Entry not found |
otto-camp/DialoGPT-small-RickBot | 6003ba0aa0854666ba3aa8a5c3b5cacc692e3a73 | 2021-10-16T14:49:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | otto-camp | null | otto-camp/DialoGPT-small-RickBot | 212 | null | transformers | 3,543 | ---
tags:
- conversational
---
# Rick DialoGPT Model |
K024/mt5-zh-ja-en-trimmed | 6da335241a1792378b455db3e60a86472e50b8e9 | 2022-03-24T14:57:22.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"zh",
"ja",
"en",
"transformers",
"translation",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | translation | false | K024 | null | K024/mt5-zh-ja-en-trimmed | 211 | 5 | transformers | 3,544 | ---
language:
- zh
- ja
- en
tags:
- translation
widget:
- text: "ja2zh: 吾輩は猫である。名前はまだ無い。"
license: cc-by-nc-sa-4.0
---
This model is finetuned from [mt5-base](https://huggingface.co/google/mt5-base).
The model vocabulary is trimmed to ~1/3 by selecting top 85000 tokens in the training data. The c... |
adamlin/comet-atomic_2020_BART | 2123a1f6509dbdfc006a336e3ea0321b155f88a0 | 2021-07-18T12:46:13.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | adamlin | null | adamlin/comet-atomic_2020_BART | 211 | 2 | transformers | 3,545 | Entry not found |
deepmind/optical-flow-perceiver | dd4bf60748100842873f4c74660f409889989faf | 2021-12-11T13:28:43.000Z | [
"pytorch",
"perceiver",
"dataset:autoflow",
"arxiv:2107.14795",
"transformers",
"license:apache-2.0"
] | null | false | deepmind | null | deepmind/optical-flow-perceiver | 211 | 2 | transformers | 3,546 | ---
license: apache-2.0
tags:
datasets:
- autoflow
---
# Perceiver IO for optical flow
Perceiver IO model trained on [AutoFlow](https://autoflow-google.github.io/). It was introduced in the paper [Perceiver IO: A General Architecture for Structured Inputs & Outputs](https://arxiv.org/abs/2107.14795) by Jaegle et al. ... |
icelab/spaceroberta | e66632e6c6ba4d4a60f142694f98a28c4f33a8df | 2021-10-21T08:40:55.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | icelab | null | icelab/spaceroberta | 211 | null | transformers | 3,547 | ### SpaceRoBERTa
This is one of the 3 further pre-trained models from the SpaceTransformers family presented in [SpaceTransformers: Language Modeling for Space Systems](https://ieeexplore.ieee.org/document/9548078). The original Git repo is [strath-ace/smart-nlp](https://github.com/strath-ace/smart-nlp).
The further ... |
textattack/distilbert-base-cased-QQP | 8e5453d3a4d843a638701f7918896fee4d12ec8b | 2020-06-09T16:46:12.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/distilbert-base-cased-QQP | 211 | null | transformers | 3,548 | Entry not found |
tartuNLP/nmt-all-to-liv-base | 16d92cfae3fc7f8083e03b17219ac94c014c1bba | 2022-04-04T06:49:23.000Z | [
"pytorch",
"m2m_100",
"text2text-generation",
"en",
"lt",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | tartuNLP | null | tartuNLP/nmt-all-to-liv-base | 211 | null | transformers | 3,549 | ---
language:
- en
- lt
widget:
- text: "Let us translate some text to Livonian!"
---
# Livonian NMT
This model translates English, Estonian and Latvian into Livonian. It is based on [m2m100_418M](https://huggingface.co/facebook/m2m100_418M), fine-tuned to all-to-Livonian data from the [liv4ever](https://... |
imxly/t5-copy-summary | f986a2f4b5ea47473e830df512c8a5f8f3e9d63c | 2022-05-05T11:05:44.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | imxly | null | imxly/t5-copy-summary | 211 | null | transformers | 3,550 | Entry not found |
StanfordAIMI/stanford-deidentifier-only-radiology-reports-augmented | 9b3bce8b1fef32bba2f32b6c8452396a5580bc3d | 2022-07-18T03:49:15.000Z | [
"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-radiology-reports-augmented | 211 | 2 | transformers | 3,551 | ---
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... |
KBLab/wav2vec2-large-voxrex-swedish | 9f474d0de2343f862a2d3ee4984402814d30b3ca | 2022-05-16T09:43:37.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv",
"dataset:common_voice",
"dataset:NST Swedish ASR Database",
"dataset:P4",
"arxiv:2205.03026",
"transformers",
"audio",
"speech",
"hf-asr-leaderboard",
"license:cc0-1.0",
"model-index"
] | automatic-speech-recognition | false | KBLab | null | KBLab/wav2vec2-large-voxrex-swedish | 210 | 1 | transformers | 3,552 | ---
language: sv
datasets:
- common_voice
- NST Swedish ASR Database
- P4
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- hf-asr-leaderboard
license: cc0-1.0
model-index:
- name: Wav2vec 2.0 large VoxRex Swedish
results:
- task:
name: Speech Recognition
type: automatic-speech-reco... |
ccdv/lsg-bart-base-4096 | b19ad1086f91c4013dc9f0c609d244cf473b51b8 | 2022-07-25T05:36:15.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"arxiv:1910.13461",
"transformers",
"summarization",
"long context",
"fill-mask",
"autotrain_compatible"
] | fill-mask | false | ccdv | null | ccdv/lsg-bart-base-4096 | 210 | null | transformers | 3,553 | ---
tags:
- summarization
- bart
- long context
language:
- en
pipeline_tag: fill-mask
---
# LSG model
**Transformers >= 4.18.0**\
**This model relies on a custom modeling file, you need to add trust_remote_code=True**\
**See [\#13467](https://github.com/huggingface/transformers/pull/13467)**
* [Usage](#usage)
* [Pa... |
mkhalifa/gpt2-biographies | b444af05322fe1159e3a4044cb55f30a4e24a6b2 | 2021-05-23T09:37:00.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | mkhalifa | null | mkhalifa/gpt2-biographies | 210 | 1 | transformers | 3,554 | Entry not found |
mrm8488/distilgpt2-finetuned-wsb-tweets | 915d44dda5da9513770ed91ae43be53492973ef5 | 2021-05-23T10:23:17.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"wsb",
"tweets"
] | text-generation | false | mrm8488 | null | mrm8488/distilgpt2-finetuned-wsb-tweets | 210 | 0 | transformers | 3,555 | ---
language: en
tags:
- wsb
- tweets
widget:
- text: "Come on guys this is"
---
# distilGPT-2 fine-tuned on Kaggle WSB Reddit posts dataset |
w11wo/indonesian-roberta-base-sentiment-classifier | b359aedef1ff88b64a47b2378cb542ef037bfc49 | 2021-07-19T18:17:52.000Z | [
"pytorch",
"tf",
"roberta",
"text-classification",
"id",
"dataset:indonlu",
"arxiv:1907.11692",
"transformers",
"indonesian-roberta-base-sentiment-classifier",
"license:mit"
] | text-classification | false | w11wo | null | w11wo/indonesian-roberta-base-sentiment-classifier | 210 | 1 | transformers | 3,556 | ---
language: id
tags:
- indonesian-roberta-base-sentiment-classifier
license: mit
datasets:
- indonlu
widget:
- text: "Jangan sampai saya telpon bos saya ya!"
---
## Indonesian RoBERTa Base Sentiment Classifier
Indonesian RoBERTa Base Sentiment Classifier is a sentiment-text-classification model based on the [... |
xcjthu/Lawformer | 860b4e23118d5884b44abb060bf2a498d02c5ffc | 2021-05-05T11:57:20.000Z | [
"pytorch",
"longformer",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | xcjthu | null | xcjthu/Lawformer | 210 | 1 | transformers | 3,557 | ## Lawformer
### Introduction
This repository provides the source code and checkpoints of the paper "Lawformer: A Pre-trained Language Model forChinese Legal Long Documents". You can download the checkpoint from the [huggingface model hub](https://huggingface.co/xcjthu/Lawformer) or from [here](https://data.thunlp.org... |
yoshitomo-matsubara/bert-base-uncased-rte | 18e5ebac21791f2672657f0388d42375f21acc29 | 2021-05-29T21:55:13.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:rte",
"transformers",
"rte",
"glue",
"torchdistill",
"license:apache-2.0"
] | text-classification | false | yoshitomo-matsubara | null | yoshitomo-matsubara/bert-base-uncased-rte | 210 | null | transformers | 3,558 | ---
language: en
tags:
- bert
- rte
- glue
- torchdistill
license: apache-2.0
datasets:
- rte
metrics:
- accuracy
---
`bert-base-uncased` fine-tuned on RTE dataset, using [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Colab](https://colab.research.google.com/github/yoshitomo-mats... |
zemi/jakebot | d24f6a4f049e6c29f2c752a42c81cf9de0089b09 | 2021-09-12T10:17:03.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | zemi | null | zemi/jakebot | 210 | null | transformers | 3,559 | ---
tags:
- conversational
---
# Jake Peralta |
etmckinley/BOTHALTEROUT | 8b6271a4385c8775de14947020f57cdbe8229b87 | 2022-06-04T18:26:24.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"license:mit",
"model-index"
] | text-generation | false | etmckinley | null | etmckinley/BOTHALTEROUT | 210 | 2 | transformers | 3,560 | ---
license: mit
tags:
model-index:
- name: BERFALTER
results: []
widget:
- text: "Gregg Berhalter"
- text: "The USMNT won't win the World Cup"
- text: "The Soccer Media in this country"
- text: "Ball don't"
- text: "This lineup"
---
# BOTHALTEROUT
This model is a fine-tuned version of [GPT-2](https://huggingface.... |
HooshvareLab/bert-base-parsbert-peymaner-uncased | 984799b9ec0f4a959c9af22072e40e440853717a | 2021-05-18T20:45:45.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"fa",
"arxiv:2005.12515",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | HooshvareLab | null | HooshvareLab/bert-base-parsbert-peymaner-uncased | 209 | null | transformers | 3,561 | ---
language: fa
license: apache-2.0
---
## ParsBERT: Transformer-based Model for Persian Language Understanding
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: [arXiv:2005.12515](https://arxiv.org/abs/2005.12515)
Al... |
erfan226/persian-t5-paraphraser | c175f241a097a9e4f175e393fc2d012dddf68c7c | 2022-02-11T09:19:12.000Z | [
"pytorch",
"t5",
"text2text-generation",
"fa",
"dataset:tapaco",
"transformers",
"paraphrasing",
"autotrain_compatible"
] | text2text-generation | false | erfan226 | null | erfan226/persian-t5-paraphraser | 209 | null | transformers | 3,562 | ---
language: fa
tags:
- paraphrasing
datasets:
- tapaco
widget:
- text: "این یک مقالهٔ خرد آلمان است. میتوانید با گسترش آن به ویکیپدیا کمک کنید."
- text: "برای خرید یک کتاب باید از فروشگاه اینترنتی استفاده کنید."
---
# Persian-t5-paraphraser
This is a paraphrasing model for the Persian language. It is based on [t... |
facebook/wav2vec2-xls-r-300m-21-to-en | 4df5c4fb8b8fa521c0d84cf5ce8e7a681ff14e3d | 2022-05-26T22:23:06.000Z | [
"pytorch",
"speech-encoder-decoder",
"automatic-speech-recognition",
"multilingual",
"fr",
"de",
"es",
"ca",
"it",
"ru",
"zh",
"pt",
"fa",
"et",
"mn",
"nl",
"tr",
"ar",
"sv",
"lv",
"sl",
"ta",
"ja",
"id",
"cy",
"en",
"dataset:common_voice",
"dataset:multilingual... | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-xls-r-300m-21-to-en | 209 | 3 | transformers | 3,563 | ---
language:
- multilingual
- fr
- de
- es
- ca
- it
- ru
- zh
- pt
- fa
- et
- mn
- nl
- tr
- ar
- sv
- lv
- sl
- ta
- ja
- id
- cy
- en
datasets:
- common_voice
- multilingual_librispeech
- covost2
tags:
- speech
- xls_r
- automatic-speech-recognition
- xls_r_translation
pipeline_tag: automatic-speech-recognition
l... |
ken11/bert-japanese-ner | f5e3a9af91473242297737f91ce6b4ef4a83f032 | 2021-11-13T17:34:01.000Z | [
"pytorch",
"bert",
"token-classification",
"ja",
"transformers",
"ner",
"japanese",
"license:mit",
"autotrain_compatible"
] | token-classification | false | ken11 | null | ken11/bert-japanese-ner | 209 | 1 | transformers | 3,564 | ---
tags:
- ner
- token-classification
- japanese
- bert
language:
- ja
license: mit
---
## bert-japanese-ner
このモデルは日本語の固有表現抽出タスクを目的として、[京都大学 黒橋・褚・村脇研究室が公開しているBERT日本語Pretrainedモデル](https://nlp.ist.i.kyoto-u.ac.jp/?ku_bert_japanese)をベースに[ストックマーク株式会社が公開しているner-wikipedia-dataset](https://github.com/stockmarkteam/ner-wi... |
microsoft/unispeech-sat-base-plus | 74f559583458188867750f1b8cb6710b11f5be41 | 2021-11-05T12:40:37.000Z | [
"pytorch",
"unispeech-sat",
"pretraining",
"en",
"arxiv:1912.07875",
"arxiv:2106.06909",
"arxiv:2101.00390",
"arxiv:2110.05752",
"transformers",
"speech"
] | null | false | microsoft | null | microsoft/unispeech-sat-base-plus | 209 | null | transformers | 3,565 | ---
language:
- en
tags:
- speech
---
# UniSpeech-SAT-Base
[Microsoft's UniSpeech](https://www.microsoft.com/en-us/research/publication/unispeech-unified-speech-representation-learning-with-labeled-and-unlabeled-data/)
The base model pretrained on 16kHz sampled speech audio with utterance and speaker contrastive los... |
mrm8488/deberta-v3-base-goemotions | 0ae8ac01b571596b221dc06891d45f45ed112ffa | 2021-12-28T20:55:50.000Z | [
"pytorch",
"tensorboard",
"deberta-v2",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | mrm8488 | null | mrm8488/deberta-v3-base-goemotions | 209 | 1 | transformers | 3,566 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: deberta-v3-base-goemotions
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. -->
# d... |
tiedeman/opus-mt-he-en | d1f295aeecf3139b988f44cc2df27fb523dda9f9 | 2021-03-04T17:46:12.000Z | [
"pytorch",
"rust",
"marian",
"text2text-generation",
"he",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | tiedeman | null | tiedeman/opus-mt-he-en | 209 | null | transformers | 3,567 | ---
language:
- he
- en
tags:
- translation
license: apache-2.0
---
### he-en
* source group: Hebrew
* target group: English
* OPUS readme: [heb-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/heb-eng/README.md)
* model: transformer
* source language(s): heb
* target language(s): eng
... |
studio-ousia/luke-base-lite | 97bed8f1d69c36c0e66d9fd79118d8053e91ab37 | 2022-04-13T10:28:03.000Z | [
"pytorch",
"luke",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | studio-ousia | null | studio-ousia/luke-base-lite | 209 | null | transformers | 3,568 | Entry not found |
inywer/DialoGPT-medium-shouko01 | df6d41a1a61e93f42d1cd300fd0fd8d685236b23 | 2022-07-10T05:50:04.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | inywer | null | inywer/DialoGPT-medium-shouko01 | 209 | null | transformers | 3,569 | ---
tags:
- conversational
---
# shouko01 DialoGPT Model |
neulab/distilgpt2-finetuned-wikitext103 | cc0607f13717bb7aadc98c4304f4d3b9a96a11ba | 2022-07-14T15:38:33.000Z | [
"pytorch",
"gpt2",
"text-generation",
"arxiv:2201.12431",
"transformers"
] | text-generation | false | neulab | null | neulab/distilgpt2-finetuned-wikitext103 | 209 | null | transformers | 3,570 | This is a `distilgpt2` model, finetuned on the Wikitext-103 dataset.
It achieves a perplexity of **18.25** using a "sliding window" context, using the `run_clm.py` script at [https://github.com/neulab/knn-transformers](https://github.com/neulab/knn-transformers).
| Base LM: | `distilgpt2` | `gpt2` |
| :--- ... |
log/DialoGPT-small-scott | 4d876bab855ea75e8f0e7d043e33ca5f78fee4ed | 2021-11-14T20:34:01.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | log | null | log/DialoGPT-small-scott | 208 | null | transformers | 3,571 | ---
tags:
- conversational
---
# Game of thrones DialoGPT |
monsoon-nlp/hindi-tpu-electra | 62878f6bbd8fef1ecea9b7e2c5a8b8db7bff673c | 2020-08-26T22:19:45.000Z | [
"pytorch",
"tf",
"electra",
"feature-extraction",
"hi",
"transformers"
] | feature-extraction | false | monsoon-nlp | null | monsoon-nlp/hindi-tpu-electra | 208 | 1 | transformers | 3,572 | ---
language: hi
---
# Hindi language model
## Trained with ELECTRA base size settings
<a href="https://colab.research.google.com/drive/1R8TciRSM7BONJRBc9CBZbzOmz39FTLl_">Tokenization and training CoLab</a>
## Example Notebooks
This model outperforms Multilingual BERT on <a href="https://colab.research.google.com/d... |
mrm8488/deberta-v3-base-finetuned-squadv2 | afe43d1ac6f4df735900f0d3ca06808e11c8f677 | 2021-12-09T19:15:29.000Z | [
"pytorch",
"deberta-v2",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | mrm8488 | null | mrm8488/deberta-v3-base-finetuned-squadv2 | 208 | 1 | transformers | 3,573 | Entry not found |
nvidia/segformer-b0-finetuned-cityscapes-512-1024 | dd5010787e3453d0536d48de4c3c8bcf5bce2d6d | 2022-07-20T09:54:11.000Z | [
"pytorch",
"tf",
"segformer",
"dataset:cityscapes",
"arxiv:2105.15203",
"transformers",
"vision",
"image-segmentation",
"license:apache-2.0"
] | image-segmentation | false | nvidia | null | nvidia/segformer-b0-finetuned-cityscapes-512-1024 | 208 | null | transformers | 3,574 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
datasets:
- cityscapes
widget:
- src: https://www.researchgate.net/profile/Anurag-Arnab/publication/315881952/figure/fig5/AS:667673876779033@1536197265755/Sample-results-on-the-Cityscapes-dataset-The-above-images-show-how-our-method-can-handle.jpg
example_ti... |
spockinese/DialoGPT-small-sherlock | 03cbdc6bb55a50e050ce84d97a903163148babc4 | 2021-09-25T10:40:24.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | spockinese | null | spockinese/DialoGPT-small-sherlock | 208 | null | transformers | 3,575 | ---
tags:
- conversational
---
#Sherlock DialoGPT Model |
luxxkat/Peterbot | d9b96c125da7616a1fb1b1efbc8a3fa2ff78cec5 | 2022-03-04T13:52:15.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | luxxkat | null | luxxkat/Peterbot | 208 | null | transformers | 3,576 | ---
tags:
- conversational
---
# Peter from Your Boyfriend Game.
|
Willow/DialoGPT-large-willow | 771c8262430ae6a051f58f29b59f6ab5c6b6066d | 2022-05-07T21:40:52.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Willow | null | Willow/DialoGPT-large-willow | 208 | null | transformers | 3,577 | ---
tags:
- conversational
---
# Willow DialoGPT Model
|
T-Systems-onsite/mt5-small-sum-de-en-v2 | 30be2f4abcd905dd414fa378c48e3c273b188a36 | 2021-09-23T15:59:08.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"de",
"en",
"dataset:cnn_dailymail",
"dataset:xsum",
"dataset:mlsum",
"dataset:swiss_text_2019",
"transformers",
"summarization",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | summarization | false | T-Systems-onsite | null | T-Systems-onsite/mt5-small-sum-de-en-v2 | 207 | 1 | transformers | 3,578 | ---
language:
- de
- en
license: cc-by-nc-sa-4.0
tags:
- summarization
datasets:
- cnn_dailymail
- xsum
- mlsum
- swiss_text_2019
---
# mT5-small-sum-de-en-v2
This is a bilingual summarization model for English and German. It is based on the multilingual T5 model [google/mt5-small](https://huggingface.co/google/m... |
superb/wav2vec2-base-superb-er | 441a7599c3b22107314dcbd9166621c5c83f2cc5 | 2021-11-04T16:03:36.000Z | [
"pytorch",
"wav2vec2",
"audio-classification",
"en",
"dataset:superb",
"arxiv:2105.01051",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | audio-classification | false | superb | null | superb/wav2vec2-base-superb-er | 207 | 1 | transformers | 3,579 | ---
language: en
datasets:
- superb
tags:
- speech
- audio
- wav2vec2
- audio-classification
license: apache-2.0
widget:
- example_title: IEMOCAP clip "happy"
src: https://cdn-media.huggingface.co/speech_samples/IEMOCAP_Ses01F_impro03_F013.wav
- example_title: IEMOCAP clip "neutral"
src: https://cdn-media.huggingfa... |
waboucay/french-camembert-postag-model-finetuned-perceo | f55ac8cabbad15f218b329a62230cf2f7cd37c2e | 2022-03-11T09:37:32.000Z | [
"pytorch",
"camembert",
"token-classification",
"fr",
"transformers",
"pos-tagging",
"autotrain_compatible"
] | token-classification | false | waboucay | null | waboucay/french-camembert-postag-model-finetuned-perceo | 207 | null | transformers | 3,580 | ---
language:
- fr
tags:
- pos-tagging
---
## Eval results
We obtain the following results on ```validation``` and ```test``` sets:
| Set | F1<sub>micro</sub> | F1<sub>macro</sub> |
|------------|--------------------|--------------------|
| validation | 98.2 | 93.2 |
| test | ... |
allenai/unifiedqa-v2-t5-11b-1251000 | 642be0a823e573a22ed41f6272e8f2ed3ce0c4b4 | 2022-02-22T17:41:50.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/unifiedqa-v2-t5-11b-1251000 | 206 | null | transformers | 3,581 | # Further details: https://github.com/allenai/unifiedqa
|
anon-submission-mk/bert-base-macedonian-bulgarian-cased | f5bf50acb2c1c00fbf9939d14a406e236805b652 | 2021-05-18T23:39:42.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | anon-submission-mk | null | anon-submission-mk/bert-base-macedonian-bulgarian-cased | 206 | null | transformers | 3,582 | Entry not found |
beomus/layoutxlm | 749f96ed9384a170642be7d2c2e5675804198529 | 2022-02-02T08:21:14.000Z | [
"pytorch",
"layoutlmv2",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | beomus | null | beomus/layoutxlm | 206 | null | transformers | 3,583 | # LayoutXLM finetuned on XFUN.ja
```python
import torch
import numpy as np
from PIL import Image, ImageDraw, ImageFont
from pathlib import Path
from itertools import chain
from tqdm.notebook import tqdm
from pdf2image import convert_from_path
from transformers import LayoutXLMProcessor, LayoutLMv2ForTokenClassificatio... |
noahjadallah/cause-effect-detection | b69d7b577bf92f74a2ceb77d916160be02af635b | 2021-05-20T02:01:13.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | noahjadallah | null | noahjadallah/cause-effect-detection | 206 | null | transformers | 3,584 | ---
widget:
- text: "If a user signs up, he will receive a confirmation email."
---
# Cause-Effect Detection for Software Requirements Based on Token Classification with BERT
This model uses BERT to detect cause and effect from a single sentence. The focus of this model is the domain of software requirements engineer... |
smaranjitghose/big-cat-classifier | 3148b97c10cb44e7a468cd1a8dc6af8badc969ae | 2021-07-03T08:12:25.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | smaranjitghose | null | smaranjitghose/big-cat-classifier | 206 | null | transformers | 3,585 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: big-cat-classifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0... |
Geotrend/bert-base-bg-cased | 5189f67d1dfe16627a1e939cdc40699a7851958b | 2021-05-18T18:48:47.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"bg",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/bert-base-bg-cased | 205 | null | transformers | 3,586 | ---
language: bg
datasets: wikipedia
license: apache-2.0
---
# bert-base-bg-cased
We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.
Unlike [distilbert-base-multilingual-cased](https://huggingface.co/disti... |
akhooli/xlm-r-large-arabic-sent | 009460bdbefcc7d4dd3d1475a7f78bbb4052578b | 2020-12-11T21:32:16.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ar",
"en",
"transformers",
"license:mit"
] | text-classification | false | akhooli | null | akhooli/xlm-r-large-arabic-sent | 205 | 2 | transformers | 3,587 | ---
language:
- ar
- en
license: mit
---
### xlm-r-large-arabic-sent
Multilingual sentiment classification (Label_0: mixed, Label_1: negative, Label_2: positive) of Arabic reviews by fine-tuning XLM-Roberta-Large.
Zero shot classification of other languages (also works in mixed languages - ex. Arabic & English). Mi... |
ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa | 8a508924465b34346a5ac40a33610219a316f0fe | 2021-12-22T08:52:47.000Z | [
"pytorch",
"bert",
"text-classification",
"id",
"dataset:indonlu",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | ayameRushia | null | ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa | 205 | null | transformers | 3,588 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
model-index:
- name: bert-base-indonesian-1.5G-finetuned-sentiment-analysis-smsa
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: indonlu
type: indonlu
args: s... |
castorini/tct_colbert-v2-msmarco-cqe | 651951a336693452c5369eaf8c7d32fc690d393c | 2021-10-18T23:34:32.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | castorini | null | castorini/tct_colbert-v2-msmarco-cqe | 205 | 1 | transformers | 3,589 | This model is to reproduce Contextualized Query Embeddings for Conversational Search described in the following paper:
> Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. [Contextualized Query Embeddings for Conversational Search.](https://cs.uwaterloo.ca/~jimmylin/publications/Lin_etal_EMNLP2021.pdf) EMNLP, Nov 2021. ... |
jackieliu930/bart-large-cnn-samsum | bc62810f58dd0360768236afb3b20b1828dc67dd | 2022-06-28T03:46:12.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:samsum",
"transformers",
"sagemaker",
"summarization",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | jackieliu930 | null | jackieliu930/bart-large-cnn-samsum | 205 | 1 | transformers | 3,590 |
---
language: en
tags:
- sagemaker
- bart
- summarization
license: apache-2.0
datasets:
- samsum
model-index:
- name: bart-large-cnn-samsum
results:
- task:
name: Abstractive Text Summarization
type: abstractive-text-summarization
dataset:
name: 'SAMSum Corpus: A Human-annotated Dialogue Data... |
transformersbook/distilbert-base-uncased-finetuned-emotion | 8e2ef1893047c2771f4c9bd895d18dccf4723d9a | 2022-05-30T06:13:40.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | transformersbook | null | transformersbook/distilbert-base-uncased-finetuned-emotion | 205 | null | transformers | 3,591 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
facebook/levit-256 | 283f5f3d06de87c7a08f9852184bd86082a924a0 | 2022-06-01T13:21:14.000Z | [
"pytorch",
"levit",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2104.01136",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/levit-256 | 205 | null | transformers | 3,592 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
widget:
- 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... |
Salesforce/mixqg-base | 387b4e5397cb5af4218208638c6ae168b42a20c8 | 2021-10-18T16:12:40.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"arxiv:2110.08175",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Salesforce | null | Salesforce/mixqg-base | 204 | 3 | transformers | 3,593 | ---
language: en
widget:
- text: Robert Boyle \\n In the late 17th century, Robert Boyle proved that air is necessary for combustion.
---
# MixQG (base-sized model)
MixQG is a new question generation model pre-trained on a collection of QA datasets with a mix of answer types. It was introduced in the paper [MixQG: Ne... |
hf-internal-testing/tiny-random-deit | eb36ceed818f4098fe8c1308c9617d11f7c6e5c4 | 2021-09-17T19:22:55.000Z | [
"pytorch",
"deit",
"transformers"
] | null | false | hf-internal-testing | null | hf-internal-testing/tiny-random-deit | 204 | null | transformers | 3,594 | Entry not found |
jonatasgrosman/wav2vec2-large-english | 81ac3bef3309f991c0a65b2d7a0719214d3a1b85 | 2022-07-27T23:34:18.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-large-english | 204 | 1 | transformers | 3,595 | ---
language: en
datasets:
- common_voice
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Wav2Vec2 English by Jonatas Grosman
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
data... |
lschneidpro/distilbert_uncased_imdb | 8ba2d804414aee8d13fea68f193de309e5fff9e7 | 2020-09-07T16:11:36.000Z | [
"pytorch",
"tf",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | lschneidpro | null | lschneidpro/distilbert_uncased_imdb | 204 | null | transformers | 3,596 | Entry not found |
microsoft/unispeech-large-1500h-cv | 4e1a2ace9d4d4ef4bafd208826ef02af0336ad7e | 2021-11-05T12:41:56.000Z | [
"pytorch",
"unispeech",
"pretraining",
"en",
"dataset:common_voice",
"arxiv:2101.07597",
"transformers",
"speech"
] | null | false | microsoft | null | microsoft/unispeech-large-1500h-cv | 204 | null | transformers | 3,597 | ---
language:
- en
datasets:
- common_voice
tags:
- speech
---
# UniSpeech-Large
[Microsoft's UniSpeech](https://www.microsoft.com/en-us/research/publication/unispeech-unified-speech-representation-learning-with-labeled-and-unlabeled-data/)
The large model pretrained on 16kHz sampled speech audio and phonetic labels... |
patrickvonplaten/bert2gpt2-cnn_dailymail-fp16 | a30547834c8e029c92e00ece8402b210ec4aa2a9 | 2021-08-18T14:38:10.000Z | [
"pytorch",
"jax",
"encoder_decoder",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | patrickvonplaten | null | patrickvonplaten/bert2gpt2-cnn_dailymail-fp16 | 204 | 2 | transformers | 3,598 | # Bert2GPT2 Summarization with 🤗 EncoderDecoder Framework
This model is a Bert2Bert model fine-tuned on summarization.
Bert2GPT2 is a `EncoderDecoderModel`, meaning that the encoder is a `bert-base-uncased`
BERT model and the decoder is a `gpt2` GPT2 model. Leveraging the [EncoderDecoderFramework](https://huggingfa... |
yangheng/deberta-v3-large-absa-v1.1 | b63ac5f6e9e16438ec3b7daf8c59365085eafb8f | 2022-03-19T00:42:23.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"dataset:laptop14",
"dataset:restaurant14",
"dataset:restaurant16",
"dataset:ACL-Twitter",
"dataset:MAMS",
"dataset:Television",
"dataset:TShirt",
"dataset:Yelp",
"arxiv:2110.08604",
"transformers",
"aspect-based-sentiment-analysis",
... | text-classification | false | yangheng | null | yangheng/deberta-v3-large-absa-v1.1 | 204 | 2 | transformers | 3,599 |
---
language:
- en
tags:
- aspect-based-sentiment-analysis
- PyABSA
license: mit
datasets:
- laptop14
- restaurant14
- restaurant16
- ACL-Twitter
- MAMS
- Television
- TShirt
- Yelp
metrics:
- accuracy
- macro-f1
widget:
- text: "[CLS] when tables opened up, the manager sat another party befor... |
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