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values | private bool 1
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values | __index_level_0__ int64 0 38.5k | readme stringlengths 0 186k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
aspis/data2vec-text-finetuned-squad2 | 168c261c73222cb3e1988c9f2c8ff0b7f5b2cd1b | 2022-07-05T20:03:52.000Z | [
"pytorch",
"tensorboard",
"data2vec-text",
"question-answering",
"dataset:squad_v2",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | question-answering | false | aspis | null | aspis/data2vec-text-finetuned-squad2 | 22 | null | transformers | 8,100 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: data2vec-text-finetuned-squad2
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 commen... |
akhisreelibra/mt5-small-finetuned-amazon-en-es | c000dd436ace73d04608af84d3d53ff8af1f6e2a | 2022-07-05T16:04:31.000Z | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"transformers",
"summarization",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | akhisreelibra | null | akhisreelibra/mt5-small-finetuned-amazon-en-es | 22 | null | transformers | 8,101 | |
PrimeQA/tapas-based-tableqa-wikisql-lookup | 6fdf82954f7b8ec19079ec525809be1966c0dd70 | 2022-07-09T18:28:41.000Z | [
"pytorch",
"tapas",
"table-question-answering",
"arxiv:2004.02349",
"transformers",
"license:apache-2.0"
] | table-question-answering | false | PrimeQA | null | PrimeQA/tapas-based-tableqa-wikisql-lookup | 22 | null | transformers | 8,102 | ---
license: apache-2.0
---
# Model description
This is an [tapas-base](https://huggingface.co/google/tapas-base) model, trained on the lookup queries of [wikisql](https://huggingface.co/datasets/wikisql) dataset. It was trained to take tables and questions as input to extract answers from the table.
# Overview
*La... |
KevinChoi/dpr-question_encoder-klue-roberta-base | b3ee4d28023018d06a09a9b5106a63f7d46180f0 | 2022-07-06T03:52:47.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | KevinChoi | null | KevinChoi/dpr-question_encoder-klue-roberta-base | 22 | null | transformers | 8,103 | Entry not found |
sgugger/test-dynamic-pipeline | d895845216b0915a68d360931b2b635fa6276f1f | 2022-07-06T22:23:14.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | sgugger | null | sgugger/test-dynamic-pipeline | 22 | null | transformers | 8,104 | Entry not found |
Manishkalra/discourse_classification | 0e4021b553e6c213a6c593baa3732199675bfc9a | 2022-07-20T09:48:11.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Manishkalra | null | Manishkalra/discourse_classification | 22 | null | transformers | 8,105 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: discourse_classification
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 c... |
NAACL2022/spider-nq-ctx-encoder | 421284fcf5d863bfe4408d2bd55bbdc263892ae3 | 2022-07-09T19:20:32.000Z | [
"pytorch",
"dpr",
"arxiv:2112.07708",
"transformers"
] | null | false | NAACL2022 | null | NAACL2022/spider-nq-ctx-encoder | 22 | 4 | transformers | 8,106 | # Spider-NQ: Context Encoder
This is the context encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## Usage
We used weight sharing for the query encoder and passage encoder, ... |
p2o/neuralmind-bert-base-portuguese-squad | d074a6cd5d1cb50e1e84ac887fb0e7181f518a79 | 2022-07-09T20:01:53.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | p2o | null | p2o/neuralmind-bert-base-portuguese-squad | 22 | null | transformers | 8,107 | Entry not found |
sssingh/distilbert-base-uncased-emotion-finetuned | e5ccaeddda7b7983c122f9085cdc7edd4bea05c7 | 2022-07-16T08:15:11.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | sssingh | null | sssingh/distilbert-base-uncased-emotion-finetuned | 22 | null | transformers | 8,108 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- f1
model-index:
- name: distilbert-base-uncased-emotion-finetuned
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metric... |
Hamzaaa/wav2vec2-base-finetuned-trained-3-languages | 715134f2a40b8a6caf06b54f86b5b0d3f8b9204e | 2022-07-11T16:38:37.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"transformers"
] | audio-classification | false | Hamzaaa | null | Hamzaaa/wav2vec2-base-finetuned-trained-3-languages | 22 | null | transformers | 8,109 | Entry not found |
srini98/distilbert_finetuned-clinc | 80bb3493ef2d30af920e6197400f4f965497bc99 | 2022-07-13T15:05:53.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:clinc_oos",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | srini98 | null | srini98/distilbert_finetuned-clinc | 22 | null | transformers | 8,110 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert_finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
... |
jhonparra18/bert-base-uncased-cv-position-classifier | c446350fd81416e2481c4b7c2a8c9e728ebc7647 | 2022-07-13T18:10:30.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | jhonparra18 | null | jhonparra18/bert-base-uncased-cv-position-classifier | 22 | null | transformers | 8,111 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: bert-base-uncased-cv-position-classifier
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and com... |
NimaBoscarino/efficientformer-l1-1000 | 4d215f01f9ec95e56bc7fb8224634f61e41a5873 | 2022-07-18T20:14:47.000Z | [
"pytorch",
"en",
"dataset:imagenet-1k",
"arxiv:2206.01191",
"timm",
"mobile",
"vison",
"image-classification",
"license:apache-2.0"
] | image-classification | false | NimaBoscarino | null | NimaBoscarino/efficientformer-l1-1000 | 22 | null | timm | 8,112 | ---
language:
- en
license: apache-2.0
library_name: timm
tags:
- mobile
- vison
- image-classification
datasets:
- imagenet-1k
metrics:
- accuracy
---
# EfficientFormer-L1
## Table of Contents
- [EfficientFormer-L1](#-model_id--defaultmymodelname-true)
- [Table of Contents](#table-of-contents)
- [Model Details](... |
Team-PIXEL/pixel-base-finetuned-conll2003-en | 3dd353a6df09737aff194d2b36dbec67218a4b3b | 2022-07-15T03:12:42.000Z | [
"pytorch",
"pixel",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Team-PIXEL | null | Team-PIXEL/pixel-base-finetuned-conll2003-en | 22 | null | transformers | 8,113 | Entry not found |
aalbertini1990/autotrain-first-test-html-1136241677 | e19b7e4367b2d20f7ca4525c490a74ff7f6d7aa0 | 2022-07-16T21:16:30.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"en",
"dataset:aalbertini1990/autotrain-data-first-test-html",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | aalbertini1990 | null | aalbertini1990/autotrain-first-test-html-1136241677 | 22 | null | transformers | 8,114 | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- aalbertini1990/autotrain-data-first-test-html
co2_eq_emissions: 19.49742293318862
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1136241677
- CO2 Emissions (in grams): 19.49742293318862
## Validation Met... |
koushikn/segformer-finetuned-Maize-10k-steps-sem | 3bedd986d2e9e3a7d6f4eacf9cacd102e1dbbcf2 | 2022-07-17T12:52:45.000Z | [
"pytorch",
"tensorboard",
"segformer",
"transformers",
"image-segmentation",
"vision",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-segmentation | false | koushikn | null | koushikn/segformer-finetuned-Maize-10k-steps-sem | 22 | null | transformers | 8,115 | ---
license: apache-2.0
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-Maize-10k-steps-sem
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it... |
kabelomalapane/En-Nso_update | 347016caba50c0d083d7ea198605bd9a3d61e348 | 2022-07-19T12:44:05.000Z | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"translation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | translation | false | kabelomalapane | null | kabelomalapane/En-Nso_update | 22 | null | transformers | 8,116 | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: En-Nso_update
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... |
erikanesse/test-trainer-gbb-3 | fd2648e4ae31389a3331bb29a115d1ad71309e31 | 2022-07-19T21:12:49.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"model-index"
] | text-generation | false | erikanesse | null | erikanesse/test-trainer-gbb-3 | 22 | 1 | transformers | 8,117 | ---
tags:
- generated_from_trainer
model-index:
- name: test-trainer-gbb-3
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. -->
# test-trainer-gbb-3
This model is a ... |
benoitb/nkbert | 5037b8c2586e15e58345ae21fb7983597c291de1 | 2022-07-21T03:42:06.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | benoitb | null | benoitb/nkbert | 22 | null | transformers | 8,118 | ---
license: mit
---
## NKBert
A BERT model finetuned from a <a href="https://github.com/SKTBrain/KoBERT">KoBERT</a> base on a dataset of North Korean data.
|
eclat12450/fine-tuned-NSPKCbert-12 | 215c888ee997ce2abccb99ef378de9b57d81186b | 2022-07-27T06:22:04.000Z | [
"pytorch",
"bert",
"next-sentence-prediction",
"transformers"
] | null | false | eclat12450 | null | eclat12450/fine-tuned-NSPKCbert-12 | 22 | null | transformers | 8,119 | Entry not found |
jungjongho/wav2vec2-large-xlsr-korean-demo-colab | 14fb4f4e8ef1ee1b849e9897a3eaf7e5300a41c6 | 2022-07-28T22:43:35.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | jungjongho | null | jungjongho/wav2vec2-large-xlsr-korean-demo-colab | 22 | null | transformers | 8,120 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-korean-demo-colab
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. -->
... |
ParkSaeroyi/distilroberta-base-finetuned-wikitext2 | 60e608ccb626feb9e47ed089be3a387d079749cc | 2022-07-29T08:10:16.000Z | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | ParkSaeroyi | null | ParkSaeroyi/distilroberta-base-finetuned-wikitext2 | 22 | null | transformers | 8,121 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilroberta-base-finetuned-wikitext2
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. -->... |
Anon25/DialoGPT-Medium-BaymaxBot | 7505e67fb3bcb7da4c00043f45d3af5fc8e45db7 | 2022-07-29T14:58:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Anon25 | null | Anon25/DialoGPT-Medium-BaymaxBot | 22 | null | transformers | 8,122 | ---
tags:
- conversational
---
# DialoGPT BaymaxBot |
A-bhimany-u08/bert-base-cased-qqp | b5e8848d0676e40a2b8a2f4b0a3a3073e581d3e6 | 2021-05-23T06:58:51.000Z | [
"pytorch",
"bert",
"text-classification",
"dataset:qqp",
"transformers"
] | text-classification | false | A-bhimany-u08 | null | A-bhimany-u08/bert-base-cased-qqp | 21 | null | transformers | 8,123 |
---
inference: False
datasets:
- qqp
---
bert-base-cased model trained on quora question pair dataset. The task requires to predict whether the two given sentences (or questions) are `not_duplicate` (label 0) or `duplicate` (label 1). The model achieves 89% evaluation accuracy
|
Aleksandar/bert-srb-ner-setimes | a06811745221ba5ede99506829f2b28bcc6eac66 | 2021-09-22T12:19:23.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | token-classification | false | Aleksandar | null | Aleksandar/bert-srb-ner-setimes | 21 | null | transformers | 8,124 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model_index:
- name: bert-srb-ner-setimes
results:
- task:
name: Token Classification
type: token-classification
metric:
name: Accuracy
type: accuracy
value: 0.9645112274185379
---
<!-- This model car... |
CenIA/bert-base-spanish-wwm-uncased-finetuned-pos | 1b3e20ce7cd4507a1b9b52f47dc2f901b8f60536 | 2021-12-18T00:34:15.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | CenIA | null | CenIA/bert-base-spanish-wwm-uncased-finetuned-pos | 21 | null | transformers | 8,125 | Entry not found |
Contrastive-Tension/RoBerta-Large-CT-STSb | 43813afe01041a34f21aff389f44ae7b5a65feec | 2021-05-20T11:41:18.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | Contrastive-Tension | null | Contrastive-Tension/RoBerta-Large-CT-STSb | 21 | null | transformers | 8,126 | Entry not found |
DanL/scientific-challenges-and-directions | d86bd50d2b94e0b592b752b2b1c1674ddea5f65d | 2022-01-19T12:47:22.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:DanL/scientific-challenges-and-directions-dataset",
"arxiv:2108.13751",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | DanL | null | DanL/scientific-challenges-and-directions | 21 | null | transformers | 8,127 | ---
tags:
- generated_from_trainer
- text-classification
language:
- en
datasets:
- DanL/scientific-challenges-and-directions-dataset
widget:
- text: "severe atypical cases of pneumonia emerged and quickly spread worldwide."
example_title: "challenge"
- text: "we speculate that studying IL-6 will be beneficial."
... |
EMBEDDIA/sloberta-tweetsentiment | 2cbfdc5fb6cdd8b5400eb33153c68ac3072ab726 | 2021-07-09T14:27:28.000Z | [
"pytorch",
"camembert",
"text-classification",
"transformers"
] | text-classification | false | EMBEDDIA | null | EMBEDDIA/sloberta-tweetsentiment | 21 | null | transformers | 8,128 | Entry not found |
EasthShin/Klue-CommonSense-model | 4f01be2e2b74f65ba541d9a75839008e6fd98b59 | 2021-07-12T10:01:36.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | EasthShin | null | EasthShin/Klue-CommonSense-model | 21 | null | transformers | 8,129 |
#### Klue-bert base for Common Sense QA
#### Klue-CommonSense-model DEMO: [Ainize DEMO](https://main-klue-common-sense-qa-east-h-shin.endpoint.ainize.ai/)
#### Klue-CommonSense-model API: [Ainize API](https://ainize.ai/EastHShin/Klue-CommonSense_QA?branch=main)
### Overview
**Language model**: klue/bert-base
<br>
... |
GKLMIP/bert-khmer-base-uncased-tokenized | 8654291edec0db4592eb4b0db0eb34b7eccfc3fb | 2021-07-31T03:07:47.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | GKLMIP | null | GKLMIP/bert-khmer-base-uncased-tokenized | 21 | null | transformers | 8,130 | https://github.com/GKLMIP/Pretrained-Models-For-Khmer
If you use our model, please consider citing our paper:
```
@article{,
author="Jiang, Shengyi
and Fu, Sihui
and Lin, Nankai
and Fu, Yingwen",
title="Pre-trained Models and Evaluation Data for the Khmer Language",
year="2021",
publisher="Tsinghua Science and Technol... |
GKLMIP/bert-myanmar-small-uncased | ed42175fd89ee3972cf4b4a706d9f463f23baf35 | 2021-10-11T04:59:22.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | GKLMIP | null | GKLMIP/bert-myanmar-small-uncased | 21 | null | transformers | 8,131 | The Usage of tokenizer for Myanmar is same as Laos in https://github.com/GKLMIP/Pretrained-Models-For-Laos.
If you use our model, please consider citing our paper:
```
@InProceedings{,
author="Jiang, Shengyi
and Huang, Xiuwen
and Cai, Xiaonan
and Lin, Nankai",
title="Pre-trained Models and Evaluation Data for the Myan... |
GPL/msmarco-distilbert-margin-mse | 3fbae3e91e291b2472e58a9fff859a5e564f00a1 | 2021-12-15T04:10:19.000Z | [
"pytorch",
"distilbert",
"feature-extraction",
"arxiv:2112.07577",
"transformers"
] | feature-extraction | false | GPL | null | GPL/msmarco-distilbert-margin-mse | 21 | 1 | transformers | 8,132 | This is the zero-shot baseline model in the paper ["GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval"](https://arxiv.org/abs/2112.07577)
The training setup:
1. Start from `distilbert-base-uncased`;
2. Mine 50 hard negatives for each query on MS MARCO with `sentence-transformers/msm... |
Hate-speech-CNERG/dehatebert-mono-indonesian | 08693d6cc64f7e7b3019b2a3abe3b1a9c8ca74c2 | 2021-05-18T20:33:24.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"arxiv:2004.06465",
"transformers"
] | text-classification | false | Hate-speech-CNERG | null | Hate-speech-CNERG/dehatebert-mono-indonesian | 21 | null | transformers | 8,133 | This model is used detecting **hatespeech** in **Indonesian language**. The mono in the name refers to the monolingual setting, where the model is trained using only Arabic language data. It is finetuned on multilingual bert model.
The model is trained with different learning rates and the best validation score achieve... |
Helsinki-NLP/opus-mt-ceb-fr | 90d773c1774988007f9fd8f44477de8d5ee310b6 | 2021-09-09T21:28:34.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ceb",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ceb-fr | 21 | null | transformers | 8,134 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ceb-fr
* source languages: ceb
* target languages: fr
* OPUS readme: [ceb-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ceb-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-en-ha | 36027da91d68364e34454ce37ce60d0a43671430 | 2021-09-09T21:35:46.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"ha",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-ha | 21 | null | transformers | 8,135 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-ha
* source languages: en
* target languages: ha
* OPUS readme: [en-ha](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-ha/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-en-ig | 32e340a06fdff2e071d306a127d91b5fbb31c359 | 2021-09-09T21:36:12.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"ig",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-ig | 21 | null | transformers | 8,136 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-ig
* source languages: en
* target languages: ig
* OPUS readme: [en-ig](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-ig/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-es-swc | a75200fce67b931b7ec153baa31b9f56755429f5 | 2021-09-09T21:44:57.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"swc",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-es-swc | 21 | null | transformers | 8,137 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-es-swc
* source languages: es
* target languages: swc
* OPUS readme: [es-swc](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/es-swc/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-gil-en | c9d7eff5c31aff094d44707990b24e11358b7dfd | 2021-09-09T21:59:03.000Z | [
"pytorch",
"marian",
"text2text-generation",
"gil",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-gil-en | 21 | null | transformers | 8,138 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-gil-en
* source languages: gil
* target languages: en
* OPUS readme: [gil-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/gil-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-lus-en | f69813f841d2399ba35b514a9377a64aff188fc6 | 2021-09-10T13:56:48.000Z | [
"pytorch",
"marian",
"text2text-generation",
"lus",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-lus-en | 21 | null | transformers | 8,139 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-lus-en
* source languages: lus
* target languages: en
* OPUS readme: [lus-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/lus-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-nyk-en | 635c9eeb90b4d5fb0674da39f756b46981bbc195 | 2021-09-10T13:59:59.000Z | [
"pytorch",
"marian",
"text2text-generation",
"nyk",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-nyk-en | 21 | null | transformers | 8,140 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-nyk-en
* source languages: nyk
* target languages: en
* OPUS readme: [nyk-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/nyk-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-pon-en | f2e18a245014af64478edabce9c590c6ef049919 | 2021-09-10T14:01:30.000Z | [
"pytorch",
"marian",
"text2text-generation",
"pon",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-pon-en | 21 | null | transformers | 8,141 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-pon-en
* source languages: pon
* target languages: en
* OPUS readme: [pon-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/pon-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-sm-en | 75d732a3c9dcc01e3218d965fe0eda4a972775d3 | 2021-09-10T14:03:53.000Z | [
"pytorch",
"marian",
"text2text-generation",
"sm",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sm-en | 21 | null | transformers | 8,142 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-sm-en
* source languages: sm
* target languages: en
* OPUS readme: [sm-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sm-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-tiv-en | 6ec75c7fab0b64d880ab2370c6b672c4208e271d | 2021-09-11T10:48:08.000Z | [
"pytorch",
"marian",
"text2text-generation",
"tiv",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-tiv-en | 21 | null | transformers | 8,143 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-tiv-en
* source languages: tiv
* target languages: en
* OPUS readme: [tiv-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/tiv-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-war-es | 6a6f9fb2b0a5db968aa332d1924f6573889f610d | 2021-09-11T10:51:54.000Z | [
"pytorch",
"marian",
"text2text-generation",
"war",
"es",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-war-es | 21 | null | transformers | 8,144 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-war-es
* source languages: war
* target languages: es
* OPUS readme: [war-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/war-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Jitin/romanized-malayalam | 1ce63a6321b546686dfebfce8f70c01adbd5be0c | 2021-05-20T11:58:42.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Jitin | null | Jitin/romanized-malayalam | 21 | null | transformers | 8,145 | Entry not found |
KoichiYasuoka/roberta-large-japanese-luw-upos | 79973f2afb55e1a6b6ca01a745ba716ba74f4cec | 2022-05-24T06:27:45.000Z | [
"pytorch",
"roberta",
"token-classification",
"ja",
"dataset:universal_dependencies",
"transformers",
"japanese",
"pos",
"dependency-parsing",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/roberta-large-japanese-luw-upos | 21 | null | transformers | 8,146 | ---
language:
- "ja"
tags:
- "japanese"
- "token-classification"
- "pos"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
widget:
- text: "国境の長いトンネルを抜けると雪国であった。"
---
# roberta-large-japanese-luw-upos
## Model Description
This is a RoBERTa model ... |
LanceaKing/spkrec-ecapa-cnceleb | 014d1d63fdbccd155fe30bce8459d33fea81290c | 2022-01-08T09:27:18.000Z | [
"zh",
"dataset:cnceleb",
"arxiv:2106.04624",
"speechbrain",
"embeddings",
"Speaker",
"Verification",
"Identification",
"pytorch",
"ECAPA",
"TDNN",
"license:apache-2.0"
] | null | false | LanceaKing | null | LanceaKing/spkrec-ecapa-cnceleb | 21 | 1 | speechbrain | 8,147 | ---
language: "zh"
thumbnail:
tags:
- speechbrain
- embeddings
- Speaker
- Verification
- Identification
- pytorch
- ECAPA
- TDNN
license: "apache-2.0"
datasets:
- cnceleb
metrics:
- EER
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" framebord... |
LilaBoualili/bert-sim-pair | e03568203cd506372323431ac462711969082076 | 2021-05-18T21:26:27.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | LilaBoualili | null | LilaBoualili/bert-sim-pair | 21 | null | transformers | 8,148 | At its core it uses an BERT-Base model (bert-base-uncased) fine-tuned on the MS MARCO passage classification task using the Sim-Pair marking strategy that highlights exact term matches between the query and the passage via marker tokens (#). It can be loaded using the TF/AutoModelForSequenceClassification classes.
Ref... |
NoLawz/DialoGPT-medium-hagrid | c8b2bdebdc4cc87859abeb56336afbd909720f63 | 2021-08-27T04:32:38.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | NoLawz | null | NoLawz/DialoGPT-medium-hagrid | 21 | null | transformers | 8,149 | ---
tags:
- conversational
---
# Hagrid DialoGPT medium model |
PereLluis13/wav2vec2-large-xlsr-53-greek | 1038521bc2c8994cb6778ff514fec91c388243f8 | 2021-07-05T16:44:41.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"el",
"dataset:common_voice",
"dataset:CSS10",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | PereLluis13 | null | PereLluis13/wav2vec2-large-xlsr-53-greek | 21 | null | transformers | 8,150 | ---
language: el #TODO: replace {lang_id} in your language code here. Make sure the code is one of the *ISO codes* of [this](https://huggingface.co/languages) site.
datasets:
- common_voice #TODO: remove if you did not use the common voice dataset
- CSS10
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- sp... |
Pyjay/gpt2-medium-dutch-finetuned-text-generation | 320d8904c16b550e03a873be6709796643c8c5d2 | 2021-07-23T09:44:31.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer"
] | text-generation | false | Pyjay | null | Pyjay/gpt2-medium-dutch-finetuned-text-generation | 21 | null | transformers | 8,151 | ---
tags:
- generated_from_trainer
model_index:
- name: gpt2-medium-dutch-finetuned-text-generation
results:
- task:
name: Causal Language Modeling
type: text-generation
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably... |
Pyjay/sentence-transformers-multilingual-snli-v2-500k | db1e3450586788d37d6d0df60a0fd5f72d554aa3 | 2021-08-05T21:42:55.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | Pyjay | null | Pyjay/sentence-transformers-multilingual-snli-v2-500k | 21 | 1 | sentence-transformers | 8,152 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# Pyjay/sentence-transformers-multilingual-snli-v2-500k
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense... |
SEBIS/code_trans_t5_large_commit_generation_multitask | 90b07932ba1f058f61a452044f07181d179f3dcc | 2021-06-23T08:09:26.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_large_commit_generation_multitask | 21 | null | transformers | 8,153 | ---
tags:
- summarization
widget:
- text: "new file mode 100644 index 000000000 . . 892fda21b Binary files / dev / null and b / src / plugins / gateway / lib / joscar . jar differ"
---
# CodeTrans model for git commit message generation
Pretrained model on git commit using the t5 large model architecture. It was fir... |
Theivaprakasham/sentence-transformers-paraphrase-MiniLM-L6-v2-twitter_sentiment | 2c704c61b29e85390dd28858371bf95d8af4306e | 2021-12-06T06:18:02.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Theivaprakasham | null | Theivaprakasham/sentence-transformers-paraphrase-MiniLM-L6-v2-twitter_sentiment | 21 | null | transformers | 8,154 | Entry not found |
TuhinColumbia/germanpoetrymany | 339c1b86ce4524cc7d61743ede33ba9c6bca47ee | 2021-09-04T09:37:02.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | TuhinColumbia | null | TuhinColumbia/germanpoetrymany | 21 | null | transformers | 8,155 | Entry not found |
abdelkader/distilbert-base-uncased-finetuned-clinc | 43cb619030ec12a7c61727fb0f1300c011eb2d4c | 2022-01-20T04:59:36.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:clinc_oos",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | abdelkader | null | abdelkader/distilbert-base-uncased-finetuned-clinc | 21 | null | transformers | 8,156 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... |
alexbrandsen/ArcheoBERTje-NER | 7139d3191d64934a64e07b2083c7f00adc80a676 | 2021-05-18T23:21:58.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | alexbrandsen | null | alexbrandsen/ArcheoBERTje-NER | 21 | 1 | transformers | 8,157 | # ArcheoBERTje-NER
A Dutch BERT model for Named Entity Recognition in the Archaeology domain
This is the [ArcheoBERTje](https://huggingface.co/alexbrandsen/ArcheoBERTje) model finetuned for NER, targeting the following entities:
- Time periods
- Places
- Artefacts
- Contexts
- Materials
- Species
|
allenai/dsp_roberta_base_tapt_chemprot_4169 | b8b106a3c5d0b7fd876320ddd4f801c205782f1c | 2021-05-20T13:23:16.000Z | [
"pytorch",
"jax",
"roberta",
"transformers"
] | null | false | allenai | null | allenai/dsp_roberta_base_tapt_chemprot_4169 | 21 | null | transformers | 8,158 | Entry not found |
aodiniz/bert_uncased_L-2_H-512_A-8_cord19-200616_squad2_covid-qna | 629f45e60d677baff78e60affe105a553414c073 | 2021-05-18T23:49:46.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | aodiniz | null | aodiniz/bert_uncased_L-2_H-512_A-8_cord19-200616_squad2_covid-qna | 21 | null | transformers | 8,159 | Entry not found |
aphuongle95/xlnet_effect_partial_new | f2c28acc4a763fb7af0150a2933fbe859e1fdec5 | 2020-09-23T16:40:15.000Z | [
"pytorch",
"xlnet",
"text-generation",
"transformers"
] | text-generation | false | aphuongle95 | null | aphuongle95/xlnet_effect_partial_new | 21 | null | transformers | 8,160 | Entry not found |
benjaminbeilharz/dialoGPT-small-empatheticdialogues-generation | 4a8d404f9b35c1d92a511c5424d9a0243dafaeb1 | 2022-01-27T11:07:49.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"en",
"dataset:empathetic dialogues",
"transformers",
"conversational",
"license:mit"
] | conversational | false | benjaminbeilharz | null | benjaminbeilharz/dialoGPT-small-empatheticdialogues-generation | 21 | null | transformers | 8,161 | ---
language:
- en
datasets:
- empathetic dialogues
tags:
- conversational
- pytorch
- transformers
- gpt2
license: mit
---
Still figuring out to properly write model cards.
WIP. |
bgoel4132/tweet-disaster-classifier | db2a76702f811bfe3c016d1f29c205b842394a33 | 2021-11-02T09:55:27.000Z | [
"pytorch",
"distilbert",
"text-classification",
"en",
"dataset:bgoel4132/autonlp-data-tweet-disaster-classifier",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | false | bgoel4132 | null | bgoel4132/tweet-disaster-classifier | 21 | null | transformers | 8,162 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- bgoel4132/autonlp-data-tweet-disaster-classifier
co2_eq_emissions: 27.22397099134103
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 28716412
- CO2 Emissions (in grams): 27.22397099134103
## Valida... |
castorini/duot5-3b-med-msmarco | 553eafaab45ee8b980baa4c9ca2df4eb044f8235 | 2021-05-28T12:02:55.000Z | [
"pytorch",
"t5",
"feature-extraction",
"arxiv:2101.05667",
"transformers"
] | feature-extraction | false | castorini | null | castorini/duot5-3b-med-msmarco | 21 | null | transformers | 8,163 | This model is a T5-3B reranker pre-finetuned on the MS MARCO passage dataset for 10K steps (or 1 epoch) on the pairwise task and then finetuned on MedMARCO (from [Sledge-Z paper](https://www.aclweb.org/anthology/2020.emnlp-main.341.pdf)) for 1K steps on the pairwise task.
For more details on how to use it, check [pyga... |
danurahul/alex_gpt3_Doctextfull2 | 0a212546424a9936eacf37501e9a3b8698534b8c | 2021-05-21T15:19:06.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | danurahul | null | danurahul/alex_gpt3_Doctextfull2 | 21 | null | transformers | 8,164 | Entry not found |
dbmdz/flair-historic-ner-onb | 99c1e7122a688aae8a1f45f875207a358bb109d0 | 2021-02-26T15:41:21.000Z | [
"pytorch",
"de",
"flair",
"token-classification",
"sequence-tagger-model",
"license:mit"
] | token-classification | false | dbmdz | null | dbmdz/flair-historic-ner-onb | 21 | null | flair | 8,165 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: de
widget:
- text: "April Martin Ansclm, K. Gefangen-Auffehers Georg Sausgruber."
license: mit
---
# Towards Robust Named Entity Recognition for Historic German
Based on [our paper](https://www.aclweb.org/anthology/W19-4312/)
we release a new ... |
dbsamu/electra-small-discriminator-finetuned-ner | 22872a0c99f393a67de341f085453242bad81129 | 2022-01-24T14:27:41.000Z | [
"pytorch",
"tensorboard",
"electra",
"token-classification",
"dataset:wikiann",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | dbsamu | null | dbsamu/electra-small-discriminator-finetuned-ner | 21 | null | transformers | 8,166 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-small-discriminator-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wiki... |
fergusq/finbert-finnsentiment | 132114fa461bd591d0861cf10d0299f9d227f22d | 2021-09-30T20:41:06.000Z | [
"pytorch",
"bert",
"text-classification",
"fi",
"arxiv:2012.02613",
"transformers"
] | text-classification | false | fergusq | null | fergusq/finbert-finnsentiment | 21 | 1 | transformers | 8,167 | ---
language: fi
---
# FinBERT fine-tuned with the FinnSentiment dataset
This is a FinBERT model fine-tuned with the [FinnSentiment dataset](https://arxiv.org/pdf/2012.02613.pdf).
|
fidukm34/biobert_v1.1_pubmed-finetuned-ner | 43583cebe51e3bcb4a135f83cc5e216e415b6d38 | 2021-09-16T17:09:50.000Z | [
"pytorch",
"bert",
"token-classification",
"dataset:ncbi_disease",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | token-classification | false | fidukm34 | null | fidukm34/biobert_v1.1_pubmed-finetuned-ner | 21 | null | transformers | 8,168 | ---
tags:
- generated_from_trainer
datasets:
- ncbi_disease
metrics:
- precision
- recall
- f1
- accuracy
model_index:
- name: biobert_v1.1_pubmed-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ncbi_disease
type: ncbi_disease
arg... |
gabrieljg/wav2vec2-common_voice-es-demo | ba9f8bb7d9ceb676c5939e817e2e3f45533327ac | 2022-01-30T21:38:32.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:common_voice",
"transformers",
"common_voice",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | gabrieljg | null | gabrieljg/wav2vec2-common_voice-es-demo | 21 | null | transformers | 8,169 | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-common_voice-es-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to.... |
gokulkarthik/xlm-roberta-qa-chaii | 02f9edd5440b984f92764c4fadadab75079be001 | 2021-12-06T15:50:08.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"en",
"ta",
"hi",
"dataset:squad",
"dataset:chaii",
"transformers",
"autotrain_compatible"
] | question-answering | false | gokulkarthik | null | gokulkarthik/xlm-roberta-qa-chaii | 21 | null | transformers | 8,170 | ---
language:
- en
- ta
- hi
datasets:
- squad
- chaii
widget:
- text: "அலுமினியத்தின் அணு எண் என்ன?"
context: "அலுமினியம் (ஆங்கிலம்: அலுமினியம்; வட அமெரிக்க ஆங்கிலம்: Aluminum) ஒரு வேதியியல் தனிமம் ஆகும். இதனுடைய அணு எண் 13 ஆகும். இது பூமியில் அதிகம் கிடைக்கும் உலோகங்களுள் ஒன்று. இது மின்சாரத்தையும் வெப்பத்தை... |
google/t5-efficient-base-nl40 | f3d787d3e0e8156d17f6f2b437fb14631c8abbd8 | 2022-02-15T10:53:33.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"arxiv:2109.10686",
"transformers",
"deep-narrow",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-efficient-base-nl40 | 21 | null | transformers | 8,171 | ---
language:
- en
datasets:
- c4
tags:
- deep-narrow
inference: false
license: apache-2.0
---
# T5-Efficient-BASE-NL40 (Deep-Narrow version)
T5-Efficient-BASE-NL40 is a variation of [Google's original T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) following the [T5 model architectur... |
huggingtweets/4by3animetits | 09ba7bd133af922a75414d546b5498ad10218abe | 2021-09-14T06:15:43.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/4by3animetits | 21 | null | transformers | 8,172 | ---
language: en
thumbnail: https://www.huggingtweets.com/4by3animetits/1631600106043/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; ... |
huggingtweets/molleindustria | 52a1a47c3167a2e2b5d4af6428c7e128fb7312e7 | 2021-05-22T15:04:01.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/molleindustria | 21 | null | transformers | 8,173 | ---
language: en
thumbnail: https://www.huggingtweets.com/molleindustria/1607297976960/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
<style>
@media (prefers-color-scheme: dark) {
.prose {... |
huggingtweets/porngum_ebooks | e2db877750ef12891172d68191b803a3050083aa | 2021-05-22T19:07:00.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/porngum_ebooks | 21 | null | transformers | 8,174 | ---
language: en
thumbnail: https://www.huggingtweets.com/porngum_ebooks/1621363486627/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;... |
hyunwoongko/megatron-11B | 587257c53d3f43ca2ec213451f4d4c17a8c3e2ed | 2021-06-22T18:21:05.000Z | [
"pytorch",
"megatron",
"text-generation",
"transformers"
] | text-generation | false | hyunwoongko | null | hyunwoongko/megatron-11B | 21 | 2 | transformers | 8,175 | Entry not found |
idjotherwise/autonlp-reading_prediction-172506 | 6dd4934e8fe44bad70006d590cfb855b7984a23e | 2021-05-20T16:57:07.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"en",
"dataset:idjotherwise/autonlp-data-reading_prediction",
"transformers",
"autonlp"
] | text-classification | false | idjotherwise | null | idjotherwise/autonlp-reading_prediction-172506 | 21 | null | transformers | 8,176 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- idjotherwise/autonlp-data-reading_prediction
---
# Model Trained Using AutoNLP
- Problem type: Single Column Regression
- Model ID: 172506
## Validation Metrics
- Loss: 0.03257797285914421
- MSE: 0.03257797285914421
- MAE: 0.142465323209... |
infinitejoy/wav2vec2-large-xls-r-300m-hindi | 67d68e320645ef250a94d97eea9c620ecc9cdf9e | 2022-03-23T18:34:51.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"hi",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"license:apache-2.0",
"... | automatic-speech-recognition | false | infinitejoy | null | infinitejoy/wav2vec2-large-xls-r-300m-hindi | 21 | null | transformers | 8,177 | ---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- hi
- model_for_talk
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Hindi
results:
- task:
n... |
ismaelardo/BETO_4d | d2114ea296185c262ca9c5c3f305316eb910271a | 2021-12-30T23:53:21.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | ismaelardo | null | ismaelardo/BETO_4d | 21 | null | transformers | 8,178 | Entry not found |
it5/it5-small-headline-generation | f985f0d04fe60572ac4df4aeca2d32133565489e | 2022-03-09T08:00:22.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:gsarti/change_it",
"arxiv:2203.03759",
"transformers",
"italian",
"sequence-to-sequence",
"newspaper",
"ilgiornale",
"repubblica",
"headline-generation",
"license:apache-2.0",
"model-index",
"co2_... | text2text-generation | false | it5 | null | it5/it5-small-headline-generation | 21 | null | transformers | 8,179 | ---
language:
- it
license: apache-2.0
datasets:
- gsarti/change_it
tags:
- italian
- sequence-to-sequence
- newspaper
- ilgiornale
- repubblica
- headline-generation
widget:
- text: "WASHINGTON - La Corea del Nord torna dopo nove anni nella blacklist Usa degli Stati considerati sponsor del terrorismo. Come Iran, Siria... |
jkgrad/xlnet-base-cased-squad-quoref | 1ab9e6595274eda0ab1960db6b0ac95b7fb3cb25 | 2021-01-28T06:54:08.000Z | [
"pytorch",
"xlnet",
"question-answering",
"arxiv:1906.08237",
"transformers",
"autotrain_compatible"
] | question-answering | false | jkgrad | null | jkgrad/xlnet-base-cased-squad-quoref | 21 | null | transformers | 8,180 | # XLNet Fine-tuned on SQuAD / Quoref Dataset
[XLNet](https://arxiv.org/abs/1906.08237) jointly developed by Google and CMU and fine-tuned on [SQuAD / SQuAD 2.0](https://rajpurkar.github.io/SQuAD-explorer/) and [Quoref](https://leaderboard.allenai.org/quoref) for question answering down-stream task.
## Evaluation Resu... |
junnyu/roformer_chinese_char_small | 9bfe6ff7c9e88946e660b3444d25674047409eb3 | 2022-01-04T11:45:10.000Z | [
"pytorch",
"tf",
"jax",
"roformer",
"fill-mask",
"zh",
"arxiv:2104.09864",
"transformers",
"tf2.0",
"autotrain_compatible"
] | fill-mask | false | junnyu | null | junnyu/roformer_chinese_char_small | 21 | null | transformers | 8,181 | ---
language: zh
tags:
- roformer
- pytorch
- tf2.0
widget:
- text: "今天[MASK]很好，我想去公园玩！"
---
## 介绍
### tf版本
https://github.com/ZhuiyiTechnology/roformer
### pytorch版本+tf2.0版本
https://github.com/JunnYu/RoFormer_pytorch
## pytorch使用
```python
import torch
from transformers import RoFormerForMaskedLM, RoFormerTokenizer... |
liam168/gen-gpt2-medium-chinese | efb34b2f0b82adfe57a9c3f11be066a2a6afc620 | 2021-07-07T02:26:55.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"zh",
"transformers"
] | text-generation | false | liam168 | null | liam168/gen-gpt2-medium-chinese | 21 | null | transformers | 8,182 | ---
language: zh
widget:
- text: "晓日千红"
- text: "长街躞蹀"
---
# gen-gpt2-medium-chinese
# Overview
- **Language model**: GPT2-Medium
- **Model size**: 68M
- **Language**: Chinese
# Example
```python
from transformers import TFGPT2LMHeadModel,AutoTokenizer
from transformers import TextGenerationPipeline
mode_name ... |
liam168/qa-roberta-base-chinese-extractive | 4d2f870d15305bbf09588dc42f2dd845157e51e2 | 2021-07-16T05:01:19.000Z | [
"pytorch",
"bert",
"question-answering",
"zh",
"transformers",
"autotrain_compatible"
] | question-answering | false | liam168 | null | liam168/qa-roberta-base-chinese-extractive | 21 | 2 | transformers | 8,183 | ---
language: zh
widget:
- text: "著名诗歌《假如生活欺骗了你》的作者是"
context: "普希金从那里学习人民的语言，吸取了许多有益的养料，这一切对普希金后来的创作产生了很大的影响。这两年里，普希金创作了不少优秀的作品，如《囚徒》、《致大海》、《致凯恩》和《假如生活欺骗了你》等几十首抒情诗，叙事诗《努林伯爵》，历史剧《鲍里斯·戈都诺夫》，以及《叶甫盖尼·奥涅金》前六章。"
---
# Chinese RoBERTa-Base Model for QA
## Model description
用中文预料微调的QA模型.
## Overview
- **Language model*... |
liangtaiwan/t5-v1_1-lm100k-base | ff02d26d22780e2a4e42b96965d2c7f5fa90e9e5 | 2021-10-21T09:30:59.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | liangtaiwan | null | liangtaiwan/t5-v1_1-lm100k-base | 21 | null | transformers | 8,184 | Entry not found |
madlag/bert-base-uncased-squad1.1-block-sparse-0.13-v1 | 9457400a20c3a0bdc0711ed11f3339b30d7b31aa | 2021-05-19T22:32:43.000Z | [
"pytorch",
"tf",
"bert",
"question-answering",
"en",
"dataset:squad",
"arxiv:2005.07683",
"transformers",
"bert-base",
"license:mit",
"autotrain_compatible"
] | question-answering | false | madlag | null | madlag/bert-base-uncased-squad1.1-block-sparse-0.13-v1 | 21 | null | transformers | 8,185 | ---
language: en
thumbnail:
license: mit
tags:
- question-answering
- bert
- bert-base
datasets:
- squad
metrics:
- squad
widget:
- text: "Where is the Eiffel Tower located?"
context: "The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris, France. It is named after the engineer Gustave Eiffe... |
monologg/koelectra-small-finetuned-goemotions | 761a00c48d933899f3d70a71ba131cbcaca5145e | 2020-05-18T21:39:13.000Z | [
"pytorch",
"electra",
"transformers"
] | null | false | monologg | null | monologg/koelectra-small-finetuned-goemotions | 21 | null | transformers | 8,186 | Entry not found |
mrm8488/CodeGPT-small-finetuned-python-token-completion | 06b027cb8ff99bc236e608c7e3a73f855c99ccf6 | 2021-05-23T10:08:40.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers"
] | text-generation | false | mrm8488 | null | mrm8488/CodeGPT-small-finetuned-python-token-completion | 21 | 1 | transformers | 8,187 |
---
language: en
widget:
- text: "<s> def add_number ( a , b ) : <EOL> return a +"
---
# CodeGPT-small-py fine-tuned on CodeXGLUE for code-refinement task |
persiannlp/mt5-large-parsinlu-snli-entailment | 29df81b8dc19909cb5060518d726b0da287caedf | 2021-09-23T16:20:24.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"dataset:snli",
"transformers",
"entailment",
"mt5",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-large-parsinlu-snli-entailment | 21 | null | transformers | 8,188 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- entailment
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- snli
metrics:
- accuracy
---
# Textual Entailment (مدل برای پاسخ به استلزام منطقی)
This is a model for textual entailmen... |
razent/SciFive-large-PMC | 742f5f056b465b331b6efabaf199cf68534296cc | 2022-03-20T17:45:54.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"en",
"dataset:pmc/open_access",
"arxiv:2106.03598",
"transformers",
"token-classification",
"text-classification",
"question-answering",
"text-generation",
"autotrain_compatible"
] | text-classification | false | razent | null | razent/SciFive-large-PMC | 21 | 1 | transformers | 8,189 | ---
language:
- en
tags:
- token-classification
- text-classification
- question-answering
- text2text-generation
- text-generation
datasets:
- pmc/open_access
---
# SciFive PMC Large
## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/abs/2106.03598)
A... |
readerbench/jurBERT-large | af9617d9c39dc5807704062b2f47d3b734d25d98 | 2021-11-19T11:55:47.000Z | [
"pytorch",
"tf",
"bert",
"ro",
"transformers"
] | null | false | readerbench | null | readerbench/jurBERT-large | 21 | null | transformers | 8,190 | Model card for jurBERT-large
---
language:
- ro
---
# jurBERT-large
## Pretrained juridical BERT model for Romanian
BERT Romanian juridical model trained using a masked language modeling (MLM) and next sentence prediction (NSP) objective.
It was introduced in this [paper](https://aclanthology.org/2021.nllp-1.8/... |
remi/bertabs-finetuned-extractive-abstractive-summarization | af86c661fc7f94c8526300104d4f7442cdbd1a80 | 2021-05-20T04:15:22.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | remi | null | remi/bertabs-finetuned-extractive-abstractive-summarization | 21 | null | transformers | 8,191 | Entry not found |
saburbutt/xlnet_large_tweetqa | ed48a14ba0af1780f818c98b14de2100baba899a | 2021-04-13T22:34:59.000Z | [
"pytorch",
"xlnet",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | saburbutt | null | saburbutt/xlnet_large_tweetqa | 21 | null | transformers | 8,192 | |
sap-ai-research/BERT-Large-Contrastive-Self-Supervised-ACL2020 | 68db970e7f9e4d00ec4fafc13df43607e1aed9cd | 2021-05-20T04:50:14.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | sap-ai-research | null | sap-ai-research/BERT-Large-Contrastive-Self-Supervised-ACL2020 | 21 | null | transformers | 8,193 | Entry not found |
sc2qa/msmarco_qa_classifier | 2b4efdfe1e6b089de60c9340eb9175ac6dffae4c | 2022-03-30T18:33:34.000Z | [
"pytorch",
"roberta",
"text-classification",
"arxiv:2109.04689",
"transformers"
] | text-classification | false | sc2qa | null | sc2qa/msmarco_qa_classifier | 21 | null | transformers | 8,194 | For details, please refer to the following links.
Github repo: https://github.com/amazon-research/SC2QA-DRIL
Paper: [Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learning](https://arxiv.org/pdf/2109.04689.pdf) |
shahukareem/wav2vec2-large-xlsr-53-dhivehi-v2 | 21f901058ba6daf20f130cfb4412c2d731f8433f | 2021-08-21T18:31:59.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"dv",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"license:apache-2.0"
] | automatic-speech-recognition | false | shahukareem | null | shahukareem/wav2vec2-large-xlsr-53-dhivehi-v2 | 21 | 3 | transformers | 8,195 | ---
language: dv
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
license: apache-2.0
---
# Wav2Vec2-Large-XLSR-53-Dhivehi
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Dhivehi using the [Common Voice](https://huggin... |
skylord/wav2vec2-large-xlsr-hindi | c3bd6e40aadcdd3e7abf6a1ccfcef7b10447be75 | 2021-04-20T07:24:00.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hi",
"dataset:common_voice",
"dataset:indic tts",
"dataset:iiith",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | skylord | null | skylord/wav2vec2-large-xlsr-hindi | 21 | 1 | transformers | 8,196 | ---
language: hi
datasets:
- common_voice
- indic tts
- iiith
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Hindi XLSR Wav2Vec2 Large 53
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dat... |
sonoisa/t5-base-japanese-article-generation | 1355b9d6a603285ddba4ed9f1171e2eb69f944ab | 2022-02-21T13:37:45.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ja",
"transformers",
"seq2seq",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | sonoisa | null | sonoisa/t5-base-japanese-article-generation | 21 | null | transformers | 8,197 | ---
language: ja
tags:
- t5
- text2text-generation
- seq2seq
license: cc-by-sa-4.0
---
# タイトルから記事本文を生成するモデル
SEE: https://qiita.com/sonoisa/items/a9af64ff641f0bbfed44 |
spencerh/leftcenterpartisan | 69f9ba06e6d0c13a5c9b59e8fd0f85ef5693f988 | 2021-04-23T19:42:54.000Z | [
"pytorch",
"tf",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | spencerh | null | spencerh/leftcenterpartisan | 21 | null | transformers | 8,198 | Entry not found |
ssmadha/gpt2-finetuned-scientific-articles | 7e10f99dbe964b0fd2d222165f50d14d036d8624 | 2021-12-14T20:47:55.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-generation | false | ssmadha | null | ssmadha/gpt2-finetuned-scientific-articles | 21 | 2 | transformers | 8,199 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gpt2-finetuned-scientific-articles
results: []
---
This repository is the submission for the final project for BF510 [Institutional Racism in Health and Science](http://irhs.bu.edu/) for Shariq Madha.
To see Jupyter detailing how this model was pr... |
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