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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
flax-community/gpt2-base-thai | f8388ca939b247158f87ee25cc20ed12a2cb0e21 | 2021-07-17T10:11:12.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"th",
"dataset:oscar",
"transformers",
"gpt2-base-thai",
"license:mit"
] | text-generation | false | flax-community | null | flax-community/gpt2-base-thai | 161 | 2 | transformers | 3,900 | ---
language: th
tags:
- gpt2-base-thai
license: mit
datasets:
- oscar
widget:
- text: "สวัสดีตอนเช้า"
---
## GPT-2 Base Thai
GPT-2 Base Thai is a causal language model based on the [OpenAI GPT-2](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) model. It wa... |
microsoft/beit-large-patch16-224-pt22k | d1b5d428118fa9b220cc1585289fb5a6bc5ceb92 | 2022-01-28T10:20:43.000Z | [
"pytorch",
"jax",
"beit",
"dataset:imagenet",
"dataset:imagenet-21k",
"arxiv:2106.08254",
"transformers",
"image-classification",
"vision",
"license:apache-2.0"
] | image-classification | false | microsoft | null | microsoft/beit-large-patch16-224-pt22k | 161 | null | transformers | 3,901 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
- imagenet-21k
---
# BEiT (large-sized model, pre-trained only)
BEiT model pre-trained in a self-supervised fashion on ImageNet-22k - also called ImageNet-21k (14 million images, 21,841 classes) at resolution 224x224. It was introduce... |
mrm8488/deberta-v3-large-finetuned-mnli | 141a9d86bd10505c60fec17e2b53836d2d7f0cc0 | 2021-12-20T16:57:12.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"dataset:glue",
"arxiv:2006.03654",
"arxiv:2111.09543",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | mrm8488 | null | mrm8488/deberta-v3-large-finetuned-mnli | 161 | 2 | transformers | 3,902 | ---
language:
- en
license: mit
widget:
- text: "She was badly wounded already. Another spear would take her down."
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: deberta-v3-large-mnli-2
results:
- task:
name: Text Classification
type: text-classification
da... |
speechbrain/google_speech_command_xvector | 0e93d6f0644e9014851c622ea8d75a38f2aebc1e | 2021-11-30T00:41:50.000Z | [
"en",
"dataset:google speech commands",
"arxiv:1804.03209",
"arxiv:2106.04624",
"speechbrain",
"embeddings",
"Commands",
"Keywords",
"Keyword Spotting",
"pytorch",
"xvectors",
"TDNN",
"Command Recognition",
"audio-classification",
"license:apache-2.0"
] | audio-classification | false | speechbrain | null | speechbrain/google_speech_command_xvector | 161 | 2 | speechbrain | 3,903 | ---
language: "en"
thumbnail:
tags:
- speechbrain
- embeddings
- Commands
- Keywords
- Keyword Spotting
- pytorch
- xvectors
- TDNN
- Command Recognition
- audio-classification
license: "apache-2.0"
datasets:
- google speech commands
metrics:
- Accuracy
widget:
- example_title: Speech Commands "down"
src: https://cd... |
tdopierre/ProtAugment-LM-BANKING77 | 67583e52c69e82c5df4929c966cee780fcc0308a | 2021-07-01T13:48:46.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | tdopierre | null | tdopierre/ProtAugment-LM-BANKING77 | 161 | null | transformers | 3,904 | Entry not found |
vasilis/wav2vec2-large-xlsr-53-greek | 424132d02ed2597a0288e683572ee325d38c9264 | 2021-03-26T23:51:48.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"el",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | vasilis | null | vasilis/wav2vec2-large-xlsr-53-greek | 161 | null | transformers | 3,905 | ---
language: el
datasets:
- common_voice
- CSS10 Greek: Single Speaker Speech Dataset
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: V XLSR Wav2Vec2 Large 53 - greek
results:
- task:
name: Speech Recognition
t... |
Felix92/doctr-dummy-torch-magc-resnet31 | 3292da2d65e1acd65856524f4bcf30953759997d | 2022-04-14T08:18:52.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-magc-resnet31 | 161 | null | transformers | 3,906 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
Felix92/doctr-dummy-torch-mobilenet-v3-small | dcf2221cfd71298abba03ab536c77272d740764a | 2022-04-14T08:25:21.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-mobilenet-v3-small | 161 | null | transformers | 3,907 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
Felix92/doctr-dummy-torch-mobilenet-v3-large | 1d16bd16e709a267cb44a61b1ba38c9c301214ca | 2022-04-14T08:49:23.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-mobilenet-v3-large | 161 | null | transformers | 3,908 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
Felix92/doctr-dummy-torch-db-resnet50 | 8dbfbdce98b877e5cfd2aba81dfa242faed23a89 | 2022-04-14T08:54:22.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-db-resnet50 | 161 | null | transformers | 3,909 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: detection
https://github.com/mindee/doctr
### Example usag... |
Felix92/doctr-dummy-torch-db-mobilenet-v3-large | 1fda1f7e55b1a6d4c72946aa4d067384d5d661e9 | 2022-04-14T08:57:32.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-db-mobilenet-v3-large | 161 | null | transformers | 3,910 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: detection
https://github.com/mindee/doctr
### Example usag... |
crodri/roberta-ca-v2-qa-squac-ca-catalanqa | d3455bc6020e81dfb68d92e4bcae39a2773ec501 | 2022-07-01T10:36:17.000Z | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | question-answering | false | crodri | null | crodri/roberta-ca-v2-qa-squac-ca-catalanqa | 161 | null | transformers | 3,911 | ---
license: cc-by-sa-4.0
---
|
PlanTL-GOB-ES/roberta-base-bne-capitel-ner | 998bcf449b882707aec171a0c0ab7c4eaa361d87 | 2022-04-06T14:43:10.000Z | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | PlanTL-GOB-ES | null | PlanTL-GOB-ES/roberta-base-bne-capitel-ner | 160 | null | transformers | 3,912 | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
- "capitel"
- "ner"
datasets:
- "bne"
- "capitel"
metrics:
- "f1"
inference:
parameters:
aggregation_strategy: "first"
---
# Spanish RoBERTa-base trained on BNE finetuned for CAPITEL Named Entity Recognition (NER) d... |
TajMahaladeen/pokemon_gptj | 2e7ab98f5b9dc0d661e471393d4ff60015b52c8f | 2022-01-31T06:12:31.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers",
"license:apache-2.0"
] | text-generation | false | TajMahaladeen | null | TajMahaladeen/pokemon_gptj | 160 | null | transformers | 3,913 | ---
license: apache-2.0
---
|
asafaya/albert-base-arabic | ee582a9951cda838764c4f612b23d0cfd07e41ef | 2022-02-11T13:45:48.000Z | [
"pytorch",
"tf",
"albert",
"fill-mask",
"ar",
"dataset:oscar",
"dataset:wikipedia",
"transformers",
"masked-lm",
"autotrain_compatible"
] | fill-mask | false | asafaya | null | asafaya/albert-base-arabic | 160 | null | transformers | 3,914 | ---
language: ar
datasets:
- oscar
- wikipedia
tags:
- ar
- masked-lm
---
# Arabic-ALBERT Base
Arabic edition of ALBERT Base pretrained language model
_If you use any of these models in your work, please cite this work as:_
```
@software{ali_safaya_2020_4718724,
author = {Ali Safaya},
title = {Ara... |
jonatasgrosman/wav2vec2-xls-r-1b-polish | 2130508d8112999fe5ad30be7ddca1b49aea7cc1 | 2022-07-27T23:38:59.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pl",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-xls-r-1b-polish | 160 | 1 | transformers | 3,915 | ---
language:
- pl
license: apache-2.0
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- pl
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R Wav2Vec2 Polish by Jonatas Grosman
results:
- task:
name: Automatic Speec... |
keshan/SinhalaBERTo | 07773c644cf82601e37ee414f7062b7b909e78fd | 2021-07-11T13:14:51.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"fill-mask",
"si",
"dataset:oscar",
"arxiv:1907.11692",
"transformers",
"SinhalaBERTo",
"Sinhala",
"autotrain_compatible"
] | fill-mask | false | keshan | null | keshan/SinhalaBERTo | 160 | null | transformers | 3,916 | ---
language: si
tags:
- SinhalaBERTo
- Sinhala
- roberta
datasets:
- oscar
---
### Overview
This is a slightly smaller model trained on [OSCAR](https://oscar-corpus.com/) Sinhala dedup dataset. As Sinhala is one of those low resource languages, there are only a handful of models been trained. So, this would be a grea... |
asahi417/lmqg-mt5-base-jaquad | a29a11aad1d290c3623f226cef5fa76465bffa7d | 2022-06-09T10:54:10.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"ja",
"dataset:asahi417/qg_jaquad",
"transformers",
"question generation",
"license:cc-by-4.0",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-mt5-base-jaquad | 160 | null | transformers | 3,917 | ---
language: ja
tags:
- question generation
license: cc-by-4.0
datasets:
- asahi417/qg_jaquad
metrics:
- bleu
- meteor
- rouge
- bertscore
widget:
- text: "ゾフィーは貴族出身ではあったが王族出身ではなく、ハプスブルク家の皇位継承者であるフランツ・フェルディナントとの結婚は貴賤結婚となった。皇帝フランツ・ヨーゼフは、2人の間に生まれた子孫が皇位を継がないことを条件として結婚を承認していた。視察が予定されている<hl>6月28日<hl>は2人の14回目の結婚記念日であった。"
... |
TencentGameMate/chinese-hubert-large | 90cb660492214f687e60f5ca509b20edae6e75bd | 2022-06-24T01:57:26.000Z | [
"pytorch",
"hubert",
"feature-extraction",
"transformers",
"license:mit"
] | feature-extraction | false | TencentGameMate | null | TencentGameMate/chinese-hubert-large | 160 | 4 | transformers | 3,918 | ---
license: mit
---
Pretrained on 10k hours WenetSpeech L subset. More details in [TencentGameMate/chinese_speech_pretrain](https://github.com/TencentGameMate/chinese_speech_pretrain)
This model does not have a tokenizer as it was pretrained on audio alone.
In order to use this model speech recognition, a tokenizer... |
helliun/primary_or_secondary_v3 | cbfda5ecfab8abe05aaeb52df8fe96f5023b040e | 2022-06-10T15:37:44.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | helliun | null | helliun/primary_or_secondary_v3 | 160 | null | transformers | 3,919 | Entry not found |
Helsinki-NLP/opus-tatoeba-es-zh | 66c9fde497d230664c53c4c91c21d2e30f8cab47 | 2021-01-04T16:53:57.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"zh",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-tatoeba-es-zh | 159 | 1 | transformers | 3,920 | ---
language:
- es
- zh
tags:
- translation
license: apache-2.0
---
### es-zh
* source group: Spanish
* target group: Chinese
* OPUS readme: [spa-zho](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-zho/README.md)
* model: transformer
* source language(s): spa
* target language(s): cjy_... |
asahi417/lmqg-bart-base-squad | 7ba631ad84fc0a10025b15f9a7427dfc6ac517b2 | 2022-06-09T18:37:45.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:asahi417/qg_squad",
"transformers",
"question generation",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-bart-base-squad | 159 | null | transformers | 3,921 | ---
language:
- en
tags:
- question generation
license: mit
datasets:
- asahi417/qg_squad
metrics:
- bleu
- meteor
- rouge
- bertscore
- moverscore
widget:
- text: "<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
example_title... |
facebook/wav2vec2-large-xlsr-53-polish | 5a552eaee7b7cb205ceb15d0a6e8ff4b724b382a | 2021-07-06T02:58:29.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:common_voice",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-large-xlsr-53-polish | 159 | null | transformers | 3,922 | ---
language: nl
datasets:
- common_voice
tags:
- speech
- audio
- automatic-speech-recognition
license: apache-2.0
---
## Evaluation on Common Voice PL Test
```python
import torchaudio
from datasets import load_dataset, load_metric
from transformers import (
Wav2Vec2ForCTC,
Wav2Vec2Processor,
)
import torch
... |
ghosh-r/bangla-gpt2 | ecd06078bc3b0d0970af08591944674b4e724240 | 2021-07-20T15:22:47.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"bn",
"transformers"
] | text-generation | false | ghosh-r | null | ghosh-r/bangla-gpt2 | 159 | 2 | transformers | 3,923 | ---
language: bn
tags:
- text-generation
widget:
- text: আজ একটি সুন্দর দিন এবং আমি
---
# Bangla-GPT2
### A GPT-2 Model for the Bengali Language
* Dataset- mc4 Bengali
* Training time- ~40 hours
* Written in- JAX
If you use this model, please cite:
```
@misc{bangla-gpt2,
author = {Ritobrata Ghosh},
year = {2016}... |
Felix92/doctr-dummy-torch-db-resnet34 | 8c720afa96b1dd31a3899bc2094de75c23126a35 | 2022-04-14T08:51:36.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-db-resnet34 | 159 | null | transformers | 3,924 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: detection
https://github.com/mindee/doctr
### Example usag... |
BigSalmon/InformalToFormalLincoln46 | 2be33d452be9aa10f4aff7d7546d80093db698be | 2022-05-23T20:10:14.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | BigSalmon | null | BigSalmon/InformalToFormalLincoln46 | 159 | null | transformers | 3,925 | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln45")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln45")
```
```
How To Make Prompt:
informal english: i am very ready to do that just that.
Tra... |
KM4STfulltext/SSCI-SciBERT-e2 | 94c8bf53e16f6a586c5fa7d105b628898bb2aeab | 2022-06-01T09:25:14.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | KM4STfulltext | null | KM4STfulltext/SSCI-SciBERT-e2 | 159 | 1 | transformers | 3,926 | ---
license: apache-2.0
---
# SSCI-BERT: A pretrained language model for social scientific text
## Introduction
The research for social science texts needs the support natural language processing tools.
The pre-trained language model has greatly improved the accuracy of text mining in general texts. At present, th... |
Yehor/wav2vec2-xls-r-300m-uk-with-small-lm | bbd936400e7566ba44560440aa4abd05b5983c17 | 2022-07-30T08:51:01.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"uk",
"dataset:mozilla-foundation/common_voice_10_0",
"transformers",
"license:apache-2.0"
] | automatic-speech-recognition | false | Yehor | null | Yehor/wav2vec2-xls-r-300m-uk-with-small-lm | 159 | 3 | transformers | 3,927 | ---
language:
- uk
license: "apache-2.0"
datasets:
- mozilla-foundation/common_voice_10_0
---
🇺🇦 Join Ukrainian Speech Recognition Community - https://t.me/speech_recognition_uk
⭐ See other Ukrainian models - https://github.com/egorsmkv/speech-recognition-uk
This model has apostrophes and hyphens.
The language... |
pszemraj/distilgpt2-email-generation | 781faba8ab885a94e2a16efb027ce9b2d8ad8932 | 2022-07-21T09:16:31.000Z | [
"pytorch",
"gpt2",
"text-generation",
"dataset:aeslc",
"transformers",
"generated_from_trainer",
"email generation",
"email",
"license:apache-2.0"
] | text-generation | false | pszemraj | null | pszemraj/distilgpt2-email-generation | 159 | 1 | transformers | 3,928 | ---
license: apache-2.0
tags:
- generated_from_trainer
- email generation
- email
datasets:
- aeslc
widget:
- text: "Hey <NAME>,\n\nThank you for signing up for my weekly newsletter. Before we get started, you'll have to confirm your email address."
example_title: "newsletter"
- text: "Hi <NAME>,\n\nI hope this ema... |
Finnish-NLP/gpt2-finnish | 2150ab891ba64ee43caa054221e3a47cbcac95a8 | 2022-06-13T16:13:42.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"transformers",
"finnish",
"license:apache-2.0"
] | text-generation | false | Finnish-NLP | null | Finnish-NLP/gpt2-finnish | 158 | null | transformers | 3,929 | ---
language:
- fi
license: apache-2.0
tags:
- finnish
- gpt2
datasets:
- Finnish-NLP/mc4_fi_cleaned
- wikipedia
widget:
- text: "Tekstiä tuottava tekoäly on"
---
# GPT-2 for Finnish
Pretrained GPT-2 model on Finnish language using a causal language modeling (CLM) objective. GPT-2 was introduced in
[this paper](http... |
GermanT5/t5-efficient-oscar-german-small-el32 | 6958eca520ad7e815a550c274ba30cdee0ece68f | 2022-02-20T18:23:10.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | GermanT5 | null | GermanT5/t5-efficient-oscar-german-small-el32 | 158 | 1 | transformers | 3,930 | Entry not found |
cambridgeltl/trans-encoder-bi-simcse-roberta-base | 6771443bb2feaddc2b053721352d51f8f1ea7312 | 2021-10-18T13:29:56.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"arxiv:2109.13059",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/trans-encoder-bi-simcse-roberta-base | 158 | null | transformers | 3,931 | ---
language: en
tags:
- sentence-embeddings
- sentence-similarity
- dual-encoder
### cambridgeltl/trans-encoder-bi-simcse-roberta-base
An unsupervised sentence encoder (bi-encoder) proposed by [Liu et al. (2021)](https://arxiv.org/pdf/2109.13059.pdf). The model is trained with unlabelled sentence pairs sampled from ... |
gayanin/bart-mlm-pubmed | 7fff9ce2b136cc41641bbe6696af37c44c359ffe | 2021-11-08T12:50:54.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | gayanin | null | gayanin/bart-mlm-pubmed | 158 | 1 | transformers | 3,932 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bart-mlm-pubmed
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. -->
# bart-mlm-pubmed
Th... |
sentence-transformers/nli-roberta-base | ba3a8b8db1132e2e02a6ae688552009b5b59825a | 2022-06-15T22:33:33.000Z | [
"pytorch",
"tf",
"roberta",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/nli-roberta-base | 158 | 1 | sentence-transformers | 3,933 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
**⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: [SBERT.net... |
2gud/DialogGPT-small-Koopsbot | ef66957b3a7baa70ba9652c76c7c49edb18975e9 | 2022-02-25T19:50:25.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | 2gud | null | 2gud/DialogGPT-small-Koopsbot | 158 | null | transformers | 3,934 | ---
tags:
- conversational
---
#Stinky doo doo |
microsoft/tapex-large | 6315ea450000e987c235f173a5c35a1b8d22208a | 2022-05-17T08:26:50.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"arxiv:2107.07653",
"transformers",
"tapex",
"table-question-answering",
"license:mit",
"autotrain_compatible"
] | table-question-answering | false | microsoft | null | microsoft/tapex-large | 158 | null | transformers | 3,935 | ---
language: en
tags:
- tapex
- table-question-answering
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, Jian-Guang Lou. The or... |
clearspandex/face-parsing | 1d02cdc745a2277e3738bef3bbd9328b4bee8b30 | 2022-07-06T04:17:33.000Z | [
"pytorch",
"segformer",
"en",
"dataset:celebamaskhq",
"transformers",
"vision",
"image-segmentation",
"nvidia/mit-b5",
"license:cc0-1.0"
] | image-segmentation | false | clearspandex | null | clearspandex/face-parsing | 158 | 1 | transformers | 3,936 | ---
language: en
license: cc0-1.0
library_name: transformers
tags:
- vision
- image-segmentation
- nvidia/mit-b5
datasets:
- celebamaskhq
---
## Face Parsing |
Akashpb13/Central_kurdish_xlsr | f56917ace1e434a0daaebd363259775ef29ce1d6 | 2022-03-24T11:52:44.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ckb",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Akashpb13 | null | Akashpb13/Central_kurdish_xlsr | 157 | 2 | transformers | 3,937 | ---
language:
- ckb
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- ckb
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: Akashpb13/Central_kurdish_xlsr
results:
-... |
Geotrend/bert-base-es-cased | 3277130ede0919265f4975daa5b414de13b82faa | 2021-05-18T19:55:05.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"es",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/bert-base-es-cased | 157 | 1 | transformers | 3,938 | ---
language: es
datasets: wikipedia
license: apache-2.0
---
# bert-base-es-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... |
Ninja5000/DialoGPT-medium-TWEWYJoshua | 32f77a12b5d30cbb809e62c16a090eabcf2da2ec | 2022-02-23T10:47:52.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Ninja5000 | null | Ninja5000/DialoGPT-medium-TWEWYJoshua | 157 | 1 | transformers | 3,939 | ---
tags:
- conversational
---
# DialoGPT-medium-TWEWYJoshua
Another not-so-good AI chatbot. Joshua from the game TWEWY(The World Ends With You).
* Credits to Lynn's Devlab who made the amazing tutorial. |
alon-albalak/bert-base-multilingual-xquad | 7fc22c05cdaf03aa12a38008017a61641e4b21de | 2021-11-05T20:25:43.000Z | [
"pytorch",
"bert",
"question-answering",
"dataset:xquad",
"transformers",
"multilingual",
"autotrain_compatible"
] | question-answering | false | alon-albalak | null | alon-albalak/bert-base-multilingual-xquad | 157 | null | transformers | 3,940 | ---
tags:
- multilingual
datasets:
- xquad
---
# bert-base-multilingual-uncased for multilingual QA
# Overview
**Language Model**: bert-base-multilingual-uncased \
**Downstream task**: Extractive QA \
**Training data**: [XQuAD](https://github.com/deepmind/xquad) \
**Testing Data**: [XQuAD](https://github.com/deepmind... |
qanastek/XLMRoberta-Alexa-Intents-Classification | 2996b73c03bafabf219d727d2967188cd9c38981 | 2022-05-05T00:52:15.000Z | [
"pytorch",
"dataset:qanastek/MASSIVE",
"Transformers",
"text-classification",
"intent-classification",
"multi-class-classification",
"natural-language-understanding",
"license:cc-by-4.0"
] | text-classification | false | qanastek | null | qanastek/XLMRoberta-Alexa-Intents-Classification | 157 | 1 | null | 3,941 | ---
tags:
- Transformers
- text-classification
- intent-classification
- multi-class-classification
- natural-language-understanding
languages:
- af-ZA
- am-ET
- ar-SA
- az-AZ
- bn-BD
- cy-GB
- da-DK
- de-DE
- el-GR
- en-US
- es-ES
- fa-IR
- fi-FI
- fr-FR
- he-IL
- hi-IN
- hu-HU
- hy-AM
- id-ID
- is-IS
- it-IT
- ja-JP
... |
anas-awadalla/opt-125m-squad | 19bbcf710cb5f0b4db6430d8a537321e3bf5cc9e | 2022-06-25T23:56:38.000Z | [
"pytorch",
"opt",
"text-generation",
"transformers"
] | text-generation | false | anas-awadalla | null | anas-awadalla/opt-125m-squad | 157 | null | transformers | 3,942 | A facebook/opt-125m model trained on SQUAD for extractive question answering.
To use the model format input in the following manner:
"(Context Text)\nQuestion:(Question Text)\nAnswer:"
|
BukaByaka/opus-mt-ru-en-finetuned-ru-to-en | c9f616769dd988a6951dd6bb1c8939bf82574a7c | 2022-06-27T14:05:53.000Z | [
"pytorch",
"marian",
"text2text-generation",
"dataset:wmt16",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | BukaByaka | null | BukaByaka/opus-mt-ru-en-finetuned-ru-to-en | 157 | null | transformers | 3,943 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wmt16
metrics:
- bleu
model-index:
- name: opus-mt-ru-en-finetuned-ru-to-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wmt16
type: wmt16
args: ru-en
m... |
m-salman-a/wav2vec2-xlsr-53-common-voice-indonesian | 4ce6a399d7b599ea4623ba4c6ca21c1c86f8b89b | 2022-07-05T16:37:46.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"id",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers"
] | automatic-speech-recognition | false | m-salman-a | null | m-salman-a/wav2vec2-xlsr-53-common-voice-indonesian | 157 | 1 | transformers | 3,944 | ---
language: id
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
---
# wav2vec 2.0 XLSR-53 Model
This is the [wav2vec 2.0 XLSR-53 model](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) fine-tuned on the [Common Voice 8.0 datasets](https://huggingface.co/datasets/mozilla-foundation/common_voice... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-did-madar-twitter5 | 4d6fbcde0baa8982501145858cfb1b3ea1dbf86e | 2021-10-17T13:35:38.000Z | [
"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-did-madar-twitter5 | 156 | null | transformers | 3,945 | ---
language:
- ar
license: apache-2.0
widget:
- text: "عامل ايه ؟"
---
# CAMeLBERT-MSA DID MADAR Twitter-5 Model
## Model description
**CAMeLBERT-MSA DID MADAR Twitter-5 Model** is a dialect identification (DID) model that was built by fine-tuning the [CAMeLBERT-MSA](https://huggingface.co/CAMeL-Lab/bert-base-arabic... |
Helsinki-NLP/opus-mt-zh-vi | 1f087ae316710c9fb781049f0bb16d91dc054b9d | 2020-08-21T14:42:52.000Z | [
"pytorch",
"marian",
"text2text-generation",
"zh",
"vi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-zh-vi | 156 | null | transformers | 3,946 | ---
language:
- zh
- vi
tags:
- translation
license: apache-2.0
---
### zho-vie
* source group: Chinese
* target group: Vietnamese
* OPUS readme: [zho-vie](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-vie/README.md)
* model: transformer-align
* source language(s): cmn_Hani cmn_Latn... |
Shahm/bart-german | d22d8abba8b2635c5c46ffe048e7bc166b0ea574 | 2021-12-27T09:19:35.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"dataset:mlsum",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | Shahm | null | Shahm/bart-german | 156 | null | transformers | 3,947 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mlsum
metrics:
- rouge
model-index:
- name: mode-bart-deutsch
results:
- task:
name: Summarization
type: summarization
dataset:
name: mlsum de
type: mlsum
args: de
metrics:
- name: Rouge1
type: rouge
... |
tner/xlm-roberta-base-uncased-mit-restaurant | 1a0155a856b5d6ebfac771e757fe9c093ec2c1fb | 2021-02-12T23:47:38.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tner | null | tner/xlm-roberta-base-uncased-mit-restaurant | 156 | null | transformers | 3,948 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-base-uncased-mit-restaurant")
... |
cambridgeltl/simctg_wikitext103 | 16525d5b754781f592a17b9be43bc44ae7eb0318 | 2022-06-25T19:22:06.000Z | [
"pytorch",
"gpt2",
"text-generation",
"arxiv:1609.07843",
"arxiv:2202.06417",
"transformers"
] | text-generation | false | cambridgeltl | null | cambridgeltl/simctg_wikitext103 | 156 | 1 | transformers | 3,949 | This model provides a GPT-2 language model trained with SimCTG on the Wikitext-103 benchmark [(Merity et al., 2016)](https://arxiv.org/abs/1609.07843) based on our paper [_A Contrastive Framework for Neural Text Generation_](https://arxiv.org/abs/2202.06417).
We provide a detailed tutorial on how to apply SimCTG and C... |
huggingtweets/gordonramsay | 37186569732e438f379c947461b759e5447b5f89 | 2021-05-22T05:57:14.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/gordonramsay | 156 | null | transformers | 3,950 | ---
language: en
thumbnail: https://www.huggingtweets.com/gordonramsay/1614174227495/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/134975515031... |
persiannlp/mt5-large-parsinlu-qqp-query-paraphrasing | 65fc3eace893cbef0f81b11fdf8512633b4c7023 | 2021-09-23T16:20:19.000Z | [
"pytorch",
"t5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"dataset:qqp",
"transformers",
"query-paraphrasing",
"mt5",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-large-parsinlu-qqp-query-paraphrasing | 156 | null | transformers | 3,951 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- query-paraphrasing
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- qqp
metrics:
- accuracy
---
# Detection of Paraphrased Queries (تشخصیص سوالات هممعنی)
This is a model for detec... |
pile-of-law/legalbert-large-1.7M-2 | af1320d25bbc8a578cb04f2e5434f3762e5fcb93 | 2022-07-04T07:28:01.000Z | [
"pytorch",
"bert",
"en",
"dataset:pile-of-law/pile-of-law",
"arxiv:1907.11692",
"arxiv:1810.04805",
"arxiv:2110.00976",
"arxiv:2207.00220",
"transformers",
"fill-mask"
] | fill-mask | false | pile-of-law | null | pile-of-law/legalbert-large-1.7M-2 | 156 | 2 | transformers | 3,952 | ---
language:
- en
datasets:
- pile-of-law/pile-of-law
pipeline_tag: fill-mask
---
# Pile of Law BERT large model 2 (uncased)
Pretrained model on English language legal and administrative text using the [RoBERTa](https://arxiv.org/abs/1907.11692) pretraining objective. This model was trained with the same setup a... |
T-Systems-onsite/bert-german-dbmdz-uncased-sentence-stsb | 8870fda4e0c2ba2c2fe5fd1ea908e2cfa5857946 | 2021-05-18T22:43:16.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"de",
"transformers",
"license:mit"
] | feature-extraction | false | T-Systems-onsite | null | T-Systems-onsite/bert-german-dbmdz-uncased-sentence-stsb | 155 | null | transformers | 3,953 | ---
language: de
license: mit
---
# bert-german-dbmdz-uncased-sentence-stsb
**This model is outdated!**
The new [T-Systems-onsite/cross-en-de-roberta-sentence-transformer](https://huggingface.co/T-Systems-onsite/cross-en-de-roberta-sentence-transformer) model is better for German language. It is also the current best... |
allenai/unifiedqa-t5-11b | 01c8ac8c0922513fdcb0e0bd87f02b7dfcc77600 | 2020-11-13T12:10:29.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/unifiedqa-t5-11b | 155 | 1 | transformers | 3,954 | Entry not found |
cambridgeltl/trans-encoder-bi-simcse-bert-base | 1052e6c3873470db4eeddbe26dfba56a86fb1c09 | 2021-11-26T18:26:34.000Z | [
"pytorch",
"bert",
"feature-extraction",
"arxiv:2109.13059",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/trans-encoder-bi-simcse-bert-base | 155 | null | transformers | 3,955 | ---
language: en
tags:
- sentence-embeddings
- sentence-similarity
- dual-encoder
### cambridgeltl/trans-encoder-bi-simcse-bert-base
An unsupervised sentence encoder (bi-encoder) proposed by [Liu et al. (2021)](https://arxiv.org/pdf/2109.13059.pdf). The model is trained with unlabelled sentence pairs sampled from STS... |
castorini/monobert-large-msmarco-finetune-only | 7012b9bf7aa900a5d74615ff0824f8ceed09e723 | 2021-05-19T14:00:06.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | castorini | null | castorini/monobert-large-msmarco-finetune-only | 155 | null | transformers | 3,956 | # Model Description
This checkpoint is a direct conversion of [BERT_Large_trained_on_MSMARCO.zip](https://drive.google.com/open?id=1crlASTMlsihALlkabAQP6JTYIZwC1Wm8) from the original [repo](https://github.com/nyu-dl/dl4marco-bert/).
The corresponding model class is BertForSequenceClassification, and its purpose is for... |
tals/albert-base-vitaminc-mnli | df116a3f65bf21483c75787bcf822560ad86a6e7 | 2022-06-24T01:34:37.000Z | [
"pytorch",
"albert",
"text-classification",
"python",
"dataset:fever",
"dataset:glue",
"dataset:multi_nli",
"dataset:tals/vitaminc",
"transformers"
] | text-classification | false | tals | null | tals/albert-base-vitaminc-mnli | 155 | null | transformers | 3,957 | ---
language: python
datasets:
- fever
- glue
- multi_nli
- tals/vitaminc
---
# Details
Model used in [Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://aclanthology.org/2021.naacl-main.52/) (Schuster et al., NAACL 21`).
For more details see: https://github.com/TalSchuster/VitaminC
When ... |
toloka/t5-large-for-text-aggregation | ec2d49a52c11940f11347be79ebf45cde1de20f3 | 2021-09-23T16:40:58.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:toloka/CrowdSpeech",
"arxiv:1910.10683",
"arxiv:2107.01091",
"transformers",
"text aggregation",
"summarization",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | toloka | null | toloka/t5-large-for-text-aggregation | 155 | 3 | transformers | 3,958 | ---
language:
- en
tags:
- text aggregation
- summarization
license: apache-2.0
datasets:
- toloka/CrowdSpeech
metrics:
- wer
---
# T5 Large for Text Aggregation
## Model description
This is a T5 Large fine-tuned for crowdsourced text aggregation tasks. The model takes multiple performers' responses and yields a sin... |
aihijo/transformers4ime-pinyingpt-concat | 76dd20dc92d8236a350fb732e99dde6fa15e2263 | 2022-03-28T03:57:51.000Z | [
"pytorch",
"gpt2",
"text-generation",
"arxiv:2203.00249",
"transformers",
"license:cc-by-nc-sa-4.0"
] | text-generation | false | aihijo | null | aihijo/transformers4ime-pinyingpt-concat | 155 | null | transformers | 3,959 | ---
license: cc-by-nc-sa-4.0
---
# Transformers4IME
Transformers4IME is repo for exploring and adapting transformer-based models to IME.
## PinyinGPT
PinyinGPT is a model from [Exploring and Adapt... |
leonadase/bert-base-chinese-finetuned-ner-v1 | 55a98392aa20c4f6760345d3fb42df0c3f8c164f | 2022-04-08T17:49:01.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:fdner",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | leonadase | null | leonadase/bert-base-chinese-finetuned-ner-v1 | 155 | null | transformers | 3,960 | ---
tags:
- generated_from_trainer
datasets:
- fdner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-chinese-finetuned-ner-v1
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: fdner
type: fdner
args: fdner
metrics... |
ml6team/keyphrase-generation-t5-small-inspec | cc0e6da67749c6d83b096d197b464abd7d2ae2db | 2022-06-16T18:03:09.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:midas/inspec",
"transformers",
"keyphrase-generation",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | ml6team | null | ml6team/keyphrase-generation-t5-small-inspec | 155 | null | transformers | 3,961 | ---
language: en
license: mit
tags:
- keyphrase-generation
datasets:
- midas/inspec
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 and easily without re... |
gchhablani/bert-base-cased-finetuned-mnli | 4e171ccb1a7e226a59480575d71328752b15d5aa | 2021-09-20T09:07:21.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"en",
"dataset:glue",
"arxiv:2105.03824",
"transformers",
"generated_from_trainer",
"fnet-bert-base-comparison",
"license:apache-2.0",
"model-index"
] | text-classification | false | gchhablani | null | gchhablani/bert-base-cased-finetuned-mnli | 154 | 1 | transformers | 3,962 | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-cased-finetuned-mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: g... |
icelab/spacebert | 5fd7c3381c22a5da3a14ccaaf48e4a50d8976061 | 2021-10-21T08:40:44.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | icelab | null | icelab/spacebert | 154 | null | transformers | 3,963 | ### SpaceBERT
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 pre... |
persiannlp/mt5-small-parsinlu-opus-translation_fa_en | c7aec9eab234f76d9125f709e3bb444ce840ba5b | 2021-09-23T16:20:36.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"transformers",
"machine-translation",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-small-parsinlu-opus-translation_fa_en | 154 | null | transformers | 3,964 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- machine-translation
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- sacrebleu
---
# Machine Translation (ترجمهی ماشینی)
This is an mT5-based model for machine translatio... |
trueto/medbert-kd-chinese | 8a9aee70779f4069f8e7396d15a9f00ee1266843 | 2021-05-20T08:10:57.000Z | [
"pytorch",
"jax",
"bert",
"pretraining",
"transformers"
] | null | false | trueto | null | trueto/medbert-kd-chinese | 154 | null | transformers | 3,965 | # [medbert](https://github.com/trueto/medbert)
本项目开源硕士毕业论文“BERT模型在中文临床自然语言处理中的应用探索与研究”相关模型
## 评估基准
构建了中文电子病历命名实体识别数据集（CEMRNER）、中文医学文本命名实体识别数据集（CMTNER）、
中文医学问句-问句识别数据集（CMedQQ）和中文临床文本分类数据集（CCTC）。
| **数据集** | **训练集** | **验证集** | **测试集** | **任务类型** | **语料来源** |
| ---- | ---- | ---- |---- |---- |:----:|
| CE... |
tscholak/2e826ioa | e95227d8997db5ad1912900a6c71aa17ee08ee2b | 2022-01-10T21:50:39.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:cosql",
"dataset:spider",
"arxiv:2109.05093",
"transformers",
"text2sql",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | tscholak | null | tscholak/2e826ioa | 154 | null | transformers | 3,966 | ---
language:
- en
thumbnail: "https://repository-images.githubusercontent.com/401779782/c2f46be5-b74b-4620-ad64-57487be3b1ab"
tags:
- text2sql
widget:
- "And the concert named Auditions? | concert_singer | stadium : stadium_id, location, name, capacity, highest, lowest, average | singer : sing er_id, name, co... |
north/t5_small_NCC_lm | fe0d4f76efcfd84e1f52b5dabd051ca9e2c752d2 | 2022-06-01T19:40:02.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"no",
"nn",
"sv",
"dk",
"is",
"en",
"dataset:nbailab/NCC",
"dataset:mc4",
"dataset:wikipedia",
"arxiv:2104.09617",
"arxiv:1910.10683",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | north | null | north/t5_small_NCC_lm | 154 | null | transformers | 3,967 | ---
language:
- no
- nn
- sv
- dk
- is
- en
datasets:
- nbailab/NCC
- mc4
- wikipedia
widget:
- text: <extra_id_0> hver uke samles Regjeringens medlemmer til Statsråd på <extra_id_1>. Dette organet er øverste <extra_id_2> i Norge. For at møtet skal være <extra_id_3>, må over halvparten av regjeringens <extra_id_4> ... |
mismayil/comet-gpt2-ai2 | 62ca4053db6a4a40251ab4b0dcd3151d707b4587 | 2022-05-23T13:23:49.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"license:afl-3.0"
] | text-generation | false | mismayil | null | mismayil/comet-gpt2-ai2 | 154 | 1 | transformers | 3,968 | ---
license: afl-3.0
---
This model has been trained by the original authors of the paper [(Comet-) Atomic 2020: On Symbolic and Neural Commonsense Knowledge Graphs.](https://www.semanticscholar.org/paper/COMET-ATOMIC-2020%3A-On-Symbolic-and-Neural-Knowledge-Hwang-Bhagavatula/e39503e01ebb108c6773948a24ca798cd444eb62) a... |
Lvxue/finetuned-mt5-small-10epoch | f89604e482704ffa7360a52470f6a8d2348953a2 | 2022-07-04T03:16:07.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"en",
"ro",
"dataset:wmt16",
"transformers",
"translation",
"wmt16",
"Lvxue",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Lvxue | null | Lvxue/finetuned-mt5-small-10epoch | 154 | null | transformers | 3,969 | ---
language:
- en # Example: fr
- ro # Example: en
license: apache-2.0 # Example: apache-2.0 or any license from https://hf.co/docs/hub/repositories-licenses
tags:
- translation
- wmt16
- Lvxue
datasets:
- wmt16 # Example: common_voice. Use dataset id from https://hf.co/datasets
metrics:
- sacrebleu
- bleu # Exam... |
anablasi/qa_financial_v2 | 1ce37207a25102cdb3b50b08f749500d14333158 | 2022-07-05T10:40:55.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | anablasi | null | anablasi/qa_financial_v2 | 154 | 1 | transformers | 3,970 | Entry not found |
sledz08/finetuned-bert-piqa | 7bcb5fff57e509ccd4d5e0ea8e44a971f5bc34c6 | 2022-07-11T15:54:20.000Z | [
"pytorch",
"tensorboard",
"bert",
"multiple-choice",
"dataset:piqa",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | multiple-choice | false | sledz08 | null | sledz08/finetuned-bert-piqa | 154 | null | transformers | 3,971 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- piqa
metrics:
- accuracy
model-index:
- name: finetuned-bert-piqa
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... |
bloom-testing/test-bloomd-350m-support-backend-dtypes | e17bd335f592786111644fbdb9647651bd40adf4 | 2022-07-28T15:16:24.000Z | [
"pytorch",
"bloom",
"feature-extraction",
"transformers"
] | feature-extraction | false | bloom-testing | null | bloom-testing/test-bloomd-350m-support-backend-dtypes | 154 | null | transformers | 3,972 | Entry not found |
ARTeLab/mbart-summarization-mlsum | 37d5072d7d8d6ae414af8ab86b91c0514fe8b5a5 | 2022-05-03T06:05:43.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"it",
"dataset:ARTeLab/mlsum-it",
"transformers",
"summarization",
"model-index",
"autotrain_compatible"
] | summarization | false | ARTeLab | null | ARTeLab/mbart-summarization-mlsum | 153 | 1 | transformers | 3,973 | ---
tags:
- summarization
language:
- it
metrics:
- rouge
model-index:
- name: summarization_mbart_mlsum
results: []
datasets:
- ARTeLab/mlsum-it
---
# mbart_summarization_mlsum
This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on mlsum-it for Abstra... |
Helsinki-NLP/opus-mt-en-ca | 81d80b5921b66885e45c3b27615752da4b511b40 | 2021-09-09T21:34:27.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"ca",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-ca | 153 | 1 | transformers | 3,974 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-ca
* source languages: en
* target languages: ca
* OPUS readme: [en-ca](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-ca/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
WinKawaks/vit-small-patch16-224 | 4ed2f21a5d8dc3da907ef738c6ab669c33b7ba1e | 2022-01-30T18:04:13.000Z | [
"pytorch",
"vit",
"image-classification",
"dataset:imagenet",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | WinKawaks | null | WinKawaks/vit-small-patch16-224 | 153 | 0 | transformers | 3,975 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet
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
- s... |
anton-l/wav2vec2-large-xlsr-53-tatar | 2e94f8523c498d5d5f1fc05cda4b090a4c1482aa | 2021-07-05T20:40:41.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"tt",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | anton-l | null | anton-l/wav2vec2-large-xlsr-53-tatar | 153 | null | transformers | 3,976 | ---
language: tt
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Tatar XLSR Wav2Vec2 Large 53 by Anton Lozhkov
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
asafaya/bert-medium-arabic | 5bc83756c92b989470415372dcd9ac9376ef2fb1 | 2021-05-19T11:47:42.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"dataset:oscar",
"dataset:wikipedia",
"transformers",
"autotrain_compatible"
] | fill-mask | false | asafaya | null | asafaya/bert-medium-arabic | 153 | null | transformers | 3,977 | ---
language: ar
datasets:
- oscar
- wikipedia
---
# Arabic BERT Medium Model
Pretrained BERT Medium language model for Arabic
_If you use this model in your work, please cite this paper:_
```
@inproceedings{safaya-etal-2020-kuisail,
title = "{KUISAIL} at {S}em{E}val-2020 Task 12: {BERT}-{CNN} for Offensive Spe... |
gsarti/it5-base | 062a1f12d4d0d7da6059b6d26073eaeee327dec8 | 2022-03-09T11:57:08.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:gsarti/clean_mc4_it",
"arxiv:2203.03759",
"transformers",
"seq2seq",
"lm-head",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | gsarti | null | gsarti/it5-base | 153 | 9 | transformers | 3,978 | ---
language:
- it
datasets:
- gsarti/clean_mc4_it
tags:
- seq2seq
- lm-head
license: apache-2.0
inference: false
thumbnail: https://gsarti.com/publication/it5/featured.png
---
# Italian T5 Base 🇮🇹
The [IT5](https://huggingface.co/models?search=it5) model family represents the first effort in pretraining large-sc... |
imthanhlv/vigpt2medium | f63d11e2deb0f92bef16ee5dc1f2559109fbb4ce | 2022-06-17T02:41:16.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | imthanhlv | null | imthanhlv/vigpt2medium | 153 | null | transformers | 3,979 | Entry not found |
tr3cks/2LabelsSentimentAnalysisSpanish | 6ce31c4de6117f9b2af7c8a9df31ae52ce1763f8 | 2021-05-20T08:01:29.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | tr3cks | null | tr3cks/2LabelsSentimentAnalysisSpanish | 153 | null | transformers | 3,980 | Entry not found |
huggingtweets/joejoinerr | c5644fa3b4eae0d99d8f35d4a109b567522659b2 | 2022-06-18T12:02:03.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/joejoinerr | 153 | null | transformers | 3,981 | ---
language: en
thumbnail: http://www.huggingtweets.com/joejoinerr/1655553718810/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; widt... |
Helsinki-NLP/opus-mt-es-ca | 608d4b0c3866482f9d32b0ea71e0acd45061f086 | 2021-01-18T08:22:32.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"ca",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-es-ca | 152 | 1 | transformers | 3,982 | ---
language:
- es
- ca
tags:
- translation
license: apache-2.0
---
### spa-cat
* source group: Spanish
* target group: Catalan
* OPUS readme: [spa-cat](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-cat/README.md)
* model: transformer-align
* source language(s): spa
* target languag... |
justin871030/bert-base-uncased-goemotions-ekman-finetuned | efc4e84814566c560b14716e55cff79a024aac8c | 2022-01-12T12:44:49.000Z | [
"pytorch",
"bert",
"en",
"dataset:go_emotions",
"transformers",
"go-emotion",
"text-classification",
"license:mit"
] | text-classification | false | justin871030 | null | justin871030/bert-base-uncased-goemotions-ekman-finetuned | 152 | null | transformers | 3,983 | ---
language: en
tags:
- go-emotion
- text-classification
- pytorch
datasets:
- go_emotions
metrics:
- f1
widget:
- text: "Thanks for giving advice to the people who need it! 👌🙏"
license: mit
---
## Model Description
1. Based on the uncased BERT pretrained model with a linear output layer.
2. Added several commonly-... |
lassl/bert-ko-small | fac17c6d4e20387bbd8132ab2f6675d0ff2912bb | 2022-02-19T09:49:53.000Z | [
"pytorch",
"bert",
"pretraining",
"ko",
"transformers",
"fill-mask",
"korean",
"lassl",
"license:apache-2.0"
] | fill-mask | false | lassl | null | lassl/bert-ko-small | 152 | null | transformers | 3,984 | ---
license: apache-2.0
language: ko
tags:
- fill-mask
- korean
- lassl
mask_token: "[MASK]"
widget:
- text: 대한민국의 수도는 [MASK] 입니다.
---
# LASSL bert-ko-small
## How to use
```python
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("lassl/bert-ko-small")
tokenizer = AutoTokeniz... |
laxya007/gpt2_TS_DM_AS_CC_TM_HCU_DBS | 3037af4d9331688b1348d9e881ea5e1be7567cc3 | 2022-01-26T12:47:34.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | laxya007 | null | laxya007/gpt2_TS_DM_AS_CC_TM_HCU_DBS | 152 | null | transformers | 3,985 | Entry not found |
m3hrdadfi/albert-fa-base-v2 | f180b9ec44dbb8260cf7b6c5abd41e5b96bfd412 | 2020-12-26T08:26:26.000Z | [
"pytorch",
"albert",
"fill-mask",
"fa",
"transformers",
"albert-persian",
"persian-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | m3hrdadfi | null | m3hrdadfi/albert-fa-base-v2 | 152 | null | transformers | 3,986 | ---
language: fa
tags:
- albert-persian
- persian-lm
license: apache-2.0
---
# ALBERT-Persian
A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
> میتونی بهش بگی برت_کوچولو
## Introduction
ALBERT-Persian trained on a massive amount of public corpora ([Persian Wikidumps](ht... |
superb/wav2vec2-base-superb-ic | f80d68b3d5c0440b43174998ceffb1e83a10affe | 2021-09-02T22:03:59.000Z | [
"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-ic | 152 | null | transformers | 3,987 | ---
language: en
datasets:
- superb
tags:
- speech
- audio
- wav2vec2
license: apache-2.0
---
# Wav2Vec2-Base for Intent Classification
## Model description
This is a ported version of [S3PRL's Wav2Vec2 for the SUPERB Intent Classification task](https://github.com/s3prl/s3prl/tree/master/s3prl/downstream/fluent_comm... |
bertin-project/bertin-gpt-j-6B | f3115efa9e00c50e696c13f3c0293bfc25beb7eb | 2022-07-22T14:30:30.000Z | [
"pytorch",
"gptj",
"text-generation",
"es",
"dataset:bertin-project/mc4-es-sampled",
"arxiv:2104.09864",
"arxiv:2101.00027",
"transformers",
"causal-lm",
"license:apache-2.0"
] | text-generation | false | bertin-project | null | bertin-project/bertin-gpt-j-6B | 152 | 7 | transformers | 3,988 | ---
language:
- es
tags:
- pytorch
- causal-lm
license: apache-2.0
datasets:
- bertin-project/mc4-es-sampled
---
- [Version v1beta3](https://huggingface.co/bertin-project/bertin-gpt-j-6B/tree/v1beta3): July 22nd, 2022 (*[full](https://huggingface.co/bertin-project/bertin-gpt-j-6B/tree/v1beta3) and [half-precision wei... |
ckiplab/bert-tiny-chinese | ca5496ebfd1b6f7c95740b0a06ecbc43f3135a3b | 2022-05-10T03:28:12.000Z | [
"pytorch",
"bert",
"fill-mask",
"zh",
"transformers",
"lm-head",
"license:gpl-3.0",
"autotrain_compatible"
] | fill-mask | false | ckiplab | null | ckiplab/bert-tiny-chinese | 152 | null | transformers | 3,989 | ---
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- lm-head
- bert
- zh
license: gpl-3.0
---
# CKIP BERT Tiny Chinese
This project provides traditional Chinese transformers models (including ALBERT, BERT, GPT2) and NLP tools (including word segmentation, part-o... |
g8a9/bert-base-cased_ami18 | 8341662327fe4c4f77f7ed4b32c2ffcd1ff053d4 | 2022-05-30T12:46:33.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | g8a9 | null | g8a9/bert-base-cased_ami18 | 152 | null | transformers | 3,990 | Entry not found |
jamie613/mt5_correct_puntuation | d7c1e9ce081b3e779d5526b0e4d574b4bf25fedc | 2022-07-20T10:00:44.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | jamie613 | null | jamie613/mt5_correct_puntuation | 152 | null | transformers | 3,991 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: mt5_correct_puntuation_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. -->
# mt5_corre... |
bloom-testing/test-bloomd-350m-efficient-forward-backward | ec106fb608d6160354cf98e494c17dc8aed6734f | 2022-07-23T11:07:21.000Z | [
"pytorch",
"bloom",
"feature-extraction",
"transformers"
] | feature-extraction | false | bloom-testing | null | bloom-testing/test-bloomd-350m-efficient-forward-backward | 152 | null | transformers | 3,992 | Entry not found |
camembert/camembert-base-wikipedia-4gb | e766d74f3ac73805575b1ae2a0e72f374274dc75 | 2020-12-11T21:35:21.000Z | [
"pytorch",
"camembert",
"fr",
"arxiv:1911.03894",
"transformers"
] | null | false | camembert | null | camembert/camembert-base-wikipedia-4gb | 151 | null | transformers | 3,993 | ---
language: fr
---
# CamemBERT: a Tasty French Language Model
## Introduction
[CamemBERT](https://arxiv.org/abs/1911.03894) is a state-of-the-art language model for French based on the RoBERTa model.
It is now available on Hugging Face in 6 different versions with varying number of parameters, amount of pretrain... |
funnel-transformer/medium-base | 9a54dc2185d6ca52bd3d951b259d113cf193eacf | 2020-12-11T21:40:34.000Z | [
"pytorch",
"tf",
"funnel",
"feature-extraction",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"dataset:gigaword",
"arxiv:2006.03236",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | funnel-transformer | null | funnel-transformer/medium-base | 151 | null | transformers | 3,994 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
- gigaword
---
# Funnel Transformer medium model (B6-3x2-3x2 without decoder)
Pretrained model on English language using a similar objective objective as [ELECTRA](https://huggingface.co/transformers/model_doc/electra.html). It was introduced in
... |
hfl/rbt4 | a62c22ddef442fb4ea9c25fd26e26467e7bc5da0 | 2021-05-19T19:21:20.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"arxiv:1906.08101",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | hfl | null | hfl/rbt4 | 151 | 2 | transformers | 3,995 | ---
language:
- zh
tags:
- bert
license: "apache-2.0"
---
# This is a re-trained 4-layer RoBERTa-wwm-ext model.
## Chinese BERT with Whole Word Masking
For further accelerating Chinese natural language processing, we provide **Chinese pre-trained BERT with Whole Word Masking**.
**[Pre-Training with Whole Word Maski... |
khalidalt/DeBERTa-v3-large-mnli | 918cffe0594a2dd41924d5e0dcccb8058ebb79a4 | 2021-11-22T08:38:23.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"arxiv:2006.03654",
"transformers",
"zero-shot-classification"
] | text-classification | false | khalidalt | null | khalidalt/DeBERTa-v3-large-mnli | 151 | 1 | transformers | 3,996 | ---
language:
- en
tags:
- text-classification
- zero-shot-classification
metrics:
- accuracy
widget:
- text: "The Movie have been criticized for the story. However, I think it is a great movie. [SEP] I liked the movie."
---
# DeBERTa-v3-large-mnli
## Model description
This model was trained on the Multi-... |
mrm8488/spanbert-large-finetuned-squadv1 | c8429f15e6c6881a5aa5b1eafbbee42a57e2e9df | 2021-05-20T00:58:31.000Z | [
"pytorch",
"jax",
"bert",
"en",
"arxiv:1907.10529",
"transformers"
] | null | false | mrm8488 | null | mrm8488/spanbert-large-finetuned-squadv1 | 151 | null | transformers | 3,997 | ---
language: en
thumbnail:
---
# SpanBERT large fine-tuned on SQuAD v1
[SpanBERT](https://github.com/facebookresearch/SpanBERT) created by [Facebook Research](https://github.com/facebookresearch) and fine-tuned on [SQuAD 1.1](https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/) for **Q&A** downstream task ([... |
lirondos/anglicisms-spanish-flair-cs | ce0e1a1e7ea5ffc10e34925d6ddfbefb341fb009 | 2022-05-16T14:02:15.000Z | [
"pytorch",
"es",
"dataset:coalas",
"flair",
"anglicisms",
"loanwords",
"borrowing",
"codeswitching",
"token-classification",
"sequence-tagger-model",
"arxiv:2203.16169",
"license:cc-by-4.0"
] | token-classification | false | lirondos | null | lirondos/anglicisms-spanish-flair-cs | 151 | null | flair | 3,998 | ---
language:
- es
license: cc-by-4.0
tags:
- anglicisms # Example: audio
- loanwords # Example: automatic-speech-recognition
- borrowing # Example: speech
- codeswitching # Example to specify a library: allennlp
- flair
- token-classification
- sequence-tagger-model
- arxiv:2203.16169
datasets:
- coalas # Example... |
Souvikcmsa/BERT_sentiment_analysis | 1d2f8b455cc8f74f001bf9680f682dd5a6d0827b | 2022-04-21T17:17:04.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:Souvikcmsa/autotrain-data-sentiment_analysis",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | Souvikcmsa | null | Souvikcmsa/BERT_sentiment_analysis | 151 | null | transformers | 3,999 | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
- Output: "Positive"
datasets:
- Souvikcmsa/autotrain-data-sentiment_analysis
co2_eq_emissions: 0.029363397844935534
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification (3-class Sentiment Classification)
## Validation M... |
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