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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Rohan-Kurdekar/Arabic_Bert_Model | d274ea8aef70da81277d31187703518d23b7805c | 2021-05-20T12:21:38.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Rohan-Kurdekar | null | Rohan-Kurdekar/Arabic_Bert_Model | 11 | null | transformers | 11,000 | Entry not found |
SEBIS/code_trans_t5_large_api_generation_transfer_learning_finetune | 4792abf3e80fb276e50806249fbb97c6c3512dc4 | 2021-06-23T05:50:50.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_large_api_generation_transfer_learning_finetune | 11 | null | transformers | 11,001 | ---
tags:
- summarization
widget:
- text: "parse the uses licence node of this package , if any , and returns the license definition if theres"
---
# CodeTrans model for api recommendation generation
Pretrained model for api recommendation generation using the t5 large model architecture. It was first released in
[t... |
SEBIS/code_trans_t5_small_commit_generation | e12a8bd060251516b9c12b9ff4c942f83e1a9e2f | 2021-06-23T10:14:01.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_small_commit_generation | 11 | null | transformers | 11,002 | ---
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 small model architecture. It was fir... |
SEBIS/legal_t5_small_multitask_en_it | 5c41bebe0405e0d3c866d8a6c4978715f5cb427e | 2021-06-23T11:00:22.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"English Italian",
"dataset:dcep europarl jrc-acquis",
"transformers",
"translation English Italian model",
"autotrain_compatible"
] | text2text-generation | false | SEBIS | null | SEBIS/legal_t5_small_multitask_en_it | 11 | null | transformers | 11,003 |
---
language: English Italian
tags:
- translation English Italian model
datasets:
- dcep europarl jrc-acquis
widget:
- text: "WRITTEN QUESTION E-1184/07"
---
# legal_t5_small_multitask_en_it model
Model on translating legal text from English to Italian. It was first released in
[this repository](https://github.c... |
SergeiGKS/camembert-base-wikipedia-4gb-finetuned-job-ner | ae4a2506da4e4d146e97d9b1c480932b24fba41d | 2021-12-14T13:24:57.000Z | [
"pytorch",
"tensorboard",
"camembert",
"token-classification",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | SergeiGKS | null | SergeiGKS/camembert-base-wikipedia-4gb-finetuned-job-ner | 11 | null | transformers | 11,004 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: camembert-base-wikipedia-4gb-finetuned-job-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... |
Shushant/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-ContaminationQAmodel_PubmedBERT | 71a293ac3a207ce25c3b1add8cbf32ecbc216082 | 2022-01-16T15:54:15.000Z | [
"pytorch",
"tensorboard",
"bert",
"question-answering",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | question-answering | false | Shushant | null | Shushant/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-ContaminationQAmodel_PubmedBERT | 11 | null | transformers | 11,005 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-ContaminationQAmodel_PubmedBERT
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comp... |
Sindhu/muril-large-squad2 | 1d998e51bc18d19cb55d7b6c54535caa7ec98089 | 2021-11-20T09:43:56.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | Sindhu | null | Sindhu/muril-large-squad2 | 11 | null | transformers | 11,006 | # Muril Large Squad2
This model is finetuned for QA task on Squad2 from [Muril Large checkpoint](https://huggingface.co/google/muril-large-cased).
## Hyperparameters
```
Batch Size: 4
Grad Accumulation Steps = 8
Total epochs = 3
MLM Checkpoint = google/muril-large-cased
max_seq_len = 256
learning_rate = 1e-5
lr_schedu... |
StivenLancheros/spanberta-base-cased-ner-conll02-finetuned-ner | a66639a2cd9307ffc8f046c038d62ec275025cc9 | 2021-11-07T11:32:21.000Z | [
"pytorch",
"tensorboard",
"roberta",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | StivenLancheros | null | StivenLancheros/spanberta-base-cased-ner-conll02-finetuned-ner | 11 | null | transformers | 11,007 | ---
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spanberta-base-cased-ner-conll02-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
... |
TehranNLP/bert-base-cased-mnli | 31df249aed67164640da2676afbdd73dc39f5d37 | 2021-06-03T09:18:49.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | TehranNLP | null | TehranNLP/bert-base-cased-mnli | 11 | null | transformers | 11,008 | Entry not found |
Vivek/GPT2_GSM8k | 204965a60b16ed3518b77a64216bd8a58713f613 | 2021-11-29T15:27:55.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | Vivek | null | Vivek/GPT2_GSM8k | 11 | null | transformers | 11,009 | Entry not found |
Wikidepia/albert-bahasa-uncased-squad | 73eceff56a054d24b0e68cfe603e0cc95934a0b7 | 2021-01-11T01:39:05.000Z | [
"pytorch",
"albert",
"question-answering",
"id",
"transformers",
"autotrain_compatible"
] | question-answering | false | Wikidepia | null | Wikidepia/albert-bahasa-uncased-squad | 11 | null | transformers | 11,010 | ---
language: id
inference: false
---
# SQuAD IndoBERT-Lite Base Model
Fine-tuned IndoBERT-Lite from IndoBenchmark using Translated SQuAD datasets.
## How to use
### Using pipeline
```python
from transformers import BertTokenizerFast, pipeline
tokenizer = BertTokenizerFast.from_pretrained(
'Wikidepia/albert-bah... |
aadelucia/GPT2_medium_narrative_finetuned_medium | 13f6bed7e075f31e10ec2c3105829bf486ebe588 | 2021-12-10T17:44:57.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | aadelucia | null | aadelucia/GPT2_medium_narrative_finetuned_medium | 11 | null | transformers | 11,011 | Please visit the repo for training details. https://github.com/AADeLucia/gpt2-narrative-decoding |
aditeyabaral/additionalpretrained-bert-hinglish-small | adf89296ea3c84bd2a3012d85bda8e5f20063a07 | 2021-10-20T18:26:17.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | aditeyabaral | null | aditeyabaral/additionalpretrained-bert-hinglish-small | 11 | null | transformers | 11,012 | Entry not found |
adityavithaldas/distilbert-base-uncased-finetuned-ner | 17e3fefebe62c7f30f8b8c4206985d3cc4814e8f | 2021-09-22T19:33:37.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | adityavithaldas | null | adityavithaldas/distilbert-base-uncased-finetuned-ner | 11 | 1 | transformers | 11,013 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
model-index:
- name: distilbert-base-uncased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conll2003
---
<!-- This mod... |
adresgezgini/Turkish-GPT-2-Finetuned_digital_ads | 3974533f30de8a228353e783f3b8959ca37a5a17 | 2021-05-21T11:52:06.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | adresgezgini | null | adresgezgini/Turkish-GPT-2-Finetuned_digital_ads | 11 | null | transformers | 11,014 | Entry not found |
airKlizz/distilbart-3-3-multi-combine-wiki-news | c364b739fc4e901eb85ee087c804f07fc4c073cb | 2020-08-21T12:24:19.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | airKlizz | null | airKlizz/distilbart-3-3-multi-combine-wiki-news | 11 | null | transformers | 11,015 | Entry not found |
airKlizz/mt5-base-germeval21-toxic-with-task-specific-pretraining-and-data-augmentation | 7a68d94637e5e7878a120f44bdfb6ff3b66698fe | 2021-07-12T16:04:43.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | airKlizz | null | airKlizz/mt5-base-germeval21-toxic-with-task-specific-pretraining-and-data-augmentation | 11 | null | transformers | 11,016 | Entry not found |
airKlizz/mt5-base-wikinewssum-portuguese | e3fc8ed890f93f8cf6ab2ed1dea305308ef101c9 | 2021-12-26T08:03:49.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"summarization",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | airKlizz | null | airKlizz/mt5-base-wikinewssum-portuguese | 11 | null | transformers | 11,017 | ---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-base-wikinewssum-portuguese
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, the... |
airKlizz/xlm-roberta-base-germeval21-toxic-with-task-specific-pretraining-and-data-augmentation | be93cd64989d3b0c9d4dd6516dd477f4156aef23 | 2021-07-12T15:01:58.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | false | airKlizz | null | airKlizz/xlm-roberta-base-germeval21-toxic-with-task-specific-pretraining-and-data-augmentation | 11 | null | transformers | 11,018 | Entry not found |
allenai/dsp_roberta_base_tapt_rct_500 | def5439c85ce5f29981f5868a21c452b31956c92 | 2021-05-20T13:32:43.000Z | [
"pytorch",
"jax",
"roberta",
"transformers"
] | null | false | allenai | null | allenai/dsp_roberta_base_tapt_rct_500 | 11 | null | transformers | 11,019 | Entry not found |
allenai/longformer-large-4096-extra.pos.embd.only | 3d7ed69023d5e6e9df4454011950d1a199666ef0 | 2021-03-10T02:32:43.000Z | [
"pytorch",
"tf",
"longformer",
"transformers"
] | null | false | allenai | null | allenai/longformer-large-4096-extra.pos.embd.only | 11 | null | transformers | 11,020 | Entry not found |
anirudh21/bert-base-uncased-finetuned-qnli | ebb68e464834a6340176695880c746b19d057ff7 | 2022-01-27T08:21:03.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | anirudh21 | null | anirudh21/bert-base-uncased-finetuned-qnli | 11 | null | transformers | 11,021 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: qnli
metrics:
- name: ... |
annafavaro/bert-base-uncased-finetuned-addresso | 86e360532bd486d2f54a5ea7e577751e6580ad3a | 2021-12-03T23:48:50.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | annafavaro | null | annafavaro/bert-base-uncased-finetuned-addresso | 11 | null | transformers | 11,022 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-finetuned-addresso
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. -->
... |
anthonymirand/haha_2019_adaptation_task | b2aeba7ee0ad1724511327d98f673c3b485a56ee | 2021-05-30T21:16:48.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | anthonymirand | null | anthonymirand/haha_2019_adaptation_task | 11 | null | transformers | 11,023 | Entry not found |
anton-l/sew-mid-100k-ft-keyword-spotting | 68e0aa1aa0e2b91f33be1472a8d9a641b927e49d | 2022-01-26T14:43:39.000Z | [
"pytorch",
"tensorboard",
"sew",
"audio-classification",
"dataset:superb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | audio-classification | false | anton-l | null | anton-l/sew-mid-100k-ft-keyword-spotting | 11 | null | transformers | 11,024 | ---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: sew-mid-100k-ft-keyword-spotting
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably ... |
anton-l/wav2vec2-base-keyword-spotting | b1943623613298087ca1cc4a0fe68dd4ee5277ec | 2021-09-29T16:28:27.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"dataset:superb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | audio-classification | false | anton-l | null | anton-l/wav2vec2-base-keyword-spotting | 11 | null | transformers | 11,025 | ---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: wav2vec2-base-keyword-spotting
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably pr... |
aravind-812/roberta-train-json | a2d3b345e2a51cf7d089425ffde55ff24c9c3981 | 2021-05-20T14:12:53.000Z | [
"pytorch",
"jax",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | aravind-812 | null | aravind-812/roberta-train-json | 11 | null | transformers | 11,026 | ---
datasets:
- squad
widget:
- text: "Which name is also used to describe the Amazon rainforest in English?"
context: "The Amazon rainforest (Portuguese: Floresta Amazônica or Amazônia; Spanish: Selva Amazónica, Amazonía or usually Amazonia; French: Forêt amazonienne; Dutch: Amazoneregenwoud), also known in English ... |
arnolfokam/bert-base-uncased-kin | 156043cdfa14ecf2bbdd99f68e2b43e04b805476 | 2021-11-24T11:07:08.000Z | [
"pytorch",
"bert",
"token-classification",
"kin",
"dataset:masakhaner",
"transformers",
"NER",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | arnolfokam | null | arnolfokam/bert-base-uncased-kin | 11 | null | transformers | 11,027 | ---
language:
- kin
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
license: apache-2.0
widget:
- text: "Ambasaderi Bellomo yavuze ko bishimira ubufatanye burambye hagati ya EU n’u Rwanda, bushingiye nanone ku bufatanye hagati y’imigabane ya Afurika n’u Burayi."
---
# Model description
**bert-ba... |
ayameRushia/indobert-base-uncased-finetuned-indonlu-smsa | 0b25a99d2d40c3fa900e0d5c487752c045ae1bf7 | 2021-12-22T16:23:37.000Z | [
"pytorch",
"bert",
"text-classification",
"dataset:indonlu",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | ayameRushia | null | ayameRushia/indobert-base-uncased-finetuned-indonlu-smsa | 11 | null | transformers | 11,028 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-base-uncased-finetuned-indonlu-smsa
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: indonlu
type: indonlu
... |
baffo32/gpt2-ptmap | e1509c6a886f78039ee944060e2a04ef4b86e7f9 | 2021-12-24T13:45:44.000Z | [
"pytorch",
"tf",
"jax",
"tflite",
"rust",
"gpt2",
"text-generation",
"en",
"transformers",
"exbert",
"license:mit"
] | text-generation | false | baffo32 | null | baffo32/gpt2-ptmap | 11 | null | transformers | 11,029 | ---
language: en
tags:
- exbert
license: mit
---
# GPT-2
Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large
Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
[this paper](https://d4mucfpksywv.cloudfront.net/better... |
baykenney/bert-base-gpt2detector-topp96 | b1f7c7588100e58f2a68ce02d1da24e2724c4e2b | 2021-05-19T12:12:07.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | baykenney | null | baykenney/bert-base-gpt2detector-topp96 | 11 | null | transformers | 11,030 | Entry not found |
bhavikardeshna/xlm-roberta-base-hindi | 414a7949deb43cf5e3c828359b26c44b2dca3467 | 2021-12-21T11:40:15.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"arxiv:2112.09866",
"transformers",
"autotrain_compatible"
] | question-answering | false | bhavikardeshna | null | bhavikardeshna/xlm-roberta-base-hindi | 11 | null | transformers | 11,031 | # BibTeX entry and citation info
```
@misc{pandya2021cascading,
title={Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages},
author={Hariom A. Pandya and Bhavik Ardeshna and Dr. Brijesh S. Bhatt},
year={2021},
eprint={2112.09866},... |
bhavikardeshna/xlm-roberta-base-spanish | 25912d55fd381e4b2d199dcdae3bd9422e898f88 | 2021-12-21T11:39:52.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"arxiv:2112.09866",
"transformers",
"autotrain_compatible"
] | question-answering | false | bhavikardeshna | null | bhavikardeshna/xlm-roberta-base-spanish | 11 | null | transformers | 11,032 | # BibTeX entry and citation info
```
@misc{pandya2021cascading,
title={Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages},
author={Hariom A. Pandya and Bhavik Ardeshna and Dr. Brijesh S. Bhatt},
year={2021},
eprint={2112.09866},... |
bhavikardeshna/xlm-roberta-base-vietnamese | 98a34fe48206b64acaac2e419ef3273cbc7a3d3e | 2021-12-21T11:39:18.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"arxiv:2112.09866",
"transformers",
"autotrain_compatible"
] | question-answering | false | bhavikardeshna | null | bhavikardeshna/xlm-roberta-base-vietnamese | 11 | null | transformers | 11,033 | # BibTeX entry and citation info
```
@misc{pandya2021cascading,
title={Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages},
author={Hariom A. Pandya and Bhavik Ardeshna and Dr. Brijesh S. Bhatt},
year={2021},
eprint={2112.09866},... |
bhuvaneswari/t5-small-text_summarization | 4fc3afa436f85dd36a0c557ca4fd92d0742852f7 | 2021-11-15T04:29:51.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | bhuvaneswari | null | bhuvaneswari/t5-small-text_summarization | 11 | null | transformers | 11,034 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-text_summarization
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
args: default
metric... |
boychaboy/MNLI_roberta-base | 75af53aa738071d3d96276741961022fe43b9078 | 2021-05-20T14:31:05.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | boychaboy | null | boychaboy/MNLI_roberta-base | 11 | null | transformers | 11,035 | Entry not found |
brunodorneles/biobertpt-all-finetuned-ner | 455b762a4b98b7250b04fd1ad9252f62b0474bcf | 2021-11-03T14:40:02.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | brunodorneles | null | brunodorneles/biobertpt-all-finetuned-ner | 11 | null | transformers | 11,036 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biobertpt-all-finetuned-ner
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 th... |
cahya/bert2bert-indonesian-summarization | 2be9212d2b3fb688c461406853bebf54715d635f | 2021-01-29T11:39:42.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"id",
"dataset:id_liputan6",
"transformers",
"pipeline:summarization",
"summarization",
"bert2bert",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | cahya | null | cahya/bert2bert-indonesian-summarization | 11 | 1 | transformers | 11,037 | ---
language: id
tags:
- pipeline:summarization
- summarization
- bert2bert
datasets:
- id_liputan6
license: apache-2.0
---
# Indonesian BERT2BERT Summarization Model
Finetuned BERT-base summarization model for Indonesian.
## Finetuning Corpus
`bert2bert-indonesian-summarization` model is based on `cahya/bert-base-... |
cahya/gpt2-medium-indonesian-story | 21366a4240e1903ff85b8a6cd936b4c6288bfc7e | 2021-09-03T17:46:01.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | cahya | null | cahya/gpt2-medium-indonesian-story | 11 | 1 | transformers | 11,038 | Entry not found |
cahya/wav2vec2-large-xlsr-basque | 7cb9afa381bfe89d8e221126cbd59dfd17bcbf79 | 2021-07-05T23:41:21.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"eu",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | cahya | null | cahya/wav2vec2-large-xlsr-basque | 11 | null | transformers | 11,039 | ---
language: eu
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Basque by Cahya
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
... |
cahya/wav2vec2-large-xlsr-turkish | fca7ef60a379c49399cee2a18fa7f67f1e47f2ed | 2021-07-06T00:06:48.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | cahya | null | cahya/wav2vec2-large-xlsr-turkish | 11 | null | transformers | 11,040 | ---
language: tr
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Turkish by Cahya
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
... |
caixin1998/chinese-poetry-gpt2-pretrain | 3893b84e24410e9ca26db68ca772a6b2de2398b4 | 2021-05-21T14:42:36.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | caixin1998 | null | caixin1998/chinese-poetry-gpt2-pretrain | 11 | null | transformers | 11,041 | Entry not found |
cartyparty/DialoGPT-small-nerdherd | 2702a93c623602354261223661a84abebdf081c1 | 2021-09-01T00:42:04.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | cartyparty | null | cartyparty/DialoGPT-small-nerdherd | 11 | null | transformers | 11,042 | ---
tags:
- conversational
---
# inspired by greentext |
ccdv/lsg-camembert-base-4096 | 9808534d305a0f46101928c6be6b72410a3e051c | 2022-07-27T04:49:56.000Z | [
"pytorch",
"camembert",
"fill-mask",
"fr",
"transformers",
"long context",
"autotrain_compatible"
] | fill-mask | false | ccdv | null | ccdv/lsg-camembert-base-4096 | 11 | 1 | transformers | 11,043 | ---
language: fr
tags:
- long context
pipeline_tag: fill-mask
---
# LSG model
**Transformers >= 4.18.0**\
**This model relies on a custom modeling file, you need to add trust_remote_code=True**\
**See [\#13467](https://github.com/huggingface/transformers/pull/13467)**
* [Usage](#usage)
* [Parameters](#parameters)
* ... |
ceshine/TinyBERT_L-4_H-312_v2-distill-AllNLI | 578833747fd2988f4704d157eb14e202aa0607e6 | 2021-05-19T14:01:36.000Z | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | ceshine | null | ceshine/TinyBERT_L-4_H-312_v2-distill-AllNLI | 11 | null | transformers | 11,044 | # TinyBERT_L-4_H-312_v2 English Sentence Encoder
This is distilled from the `bert-base-nli-stsb-mean-tokens` pre-trained model from [Sentence-Transformers](https://sbert.net/).
The embedding vector is obtained by mean/average pooling of the last layer's hidden states.
Update 20210325: Added the attention matrices im... |
chitra/finetuned-adversarial-paraphrasing-detector | fd268865a7cb28643d83dc767f6f40a1ee5ad7bc | 2022-01-18T12:55:23.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | chitra | null | chitra/finetuned-adversarial-paraphrasing-detector | 11 | null | transformers | 11,045 | Entry not found |
clulab/roberta-timex-semeval | 3b980ef837347209d299deb9c1ce8ca34957a487 | 2021-05-20T15:34:00.000Z | [
"pytorch",
"jax",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | clulab | null | clulab/roberta-timex-semeval | 11 | null | transformers | 11,046 | Entry not found |
crang/wav2vec2-large-xlsr-53-tatar | d9030cc292a84ed19d7fa2db7fc47451d071aefa | 2021-07-06T00:58:16.000Z | [
"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 | crang | null | crang/wav2vec2-large-xlsr-53-tatar | 11 | null | transformers | 11,047 | ---
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
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
na... |
damlab/HIV_BERT | 38e5bb9ec8a7574d08b5bd9b402973f92fdbc093 | 2022-02-24T18:59:51.000Z | [
"pytorch",
"bert",
"fill-mask",
"dataset:damlab/HIV_FLT",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | damlab | null | damlab/HIV_BERT | 11 | null | transformers | 11,048 | ---
license: mit
datasets:
- damlab/HIV_FLT
metrics:
- accuracy
widget:
- text: 'C T R P N N N T R K S I R I Q R G P G R A F V T I G K I G N M R Q A H C'
example_title: 'V3'
- text: 'M E P V D P R L E P W K H P G S Q P K T A C T N C Y C K K C C F H C Q V C F I T K A L G I S Y G R K K R R Q R R R A... |
danasone/rubert-tiny-essay | 343329ca91cb7f519a8a3abf6b1719f297f42b61 | 2022-02-08T22:08:38.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | danasone | null | danasone/rubert-tiny-essay | 11 | null | transformers | 11,049 | Entry not found |
danielbubiola/bangla_asr | 55177dc9a92571793d3fa57ad9fd62338c65184c | 2022-01-26T07:42:22.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"model-index"
] | automatic-speech-recognition | false | danielbubiola | null | danielbubiola/bangla_asr | 11 | null | transformers | 11,050 | ---
tags:
- generated_from_trainer
model-index:
- name: bangla_asr
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. -->
# bangla_asr
This model is a fine-tuned versi... |
danurahul/wav2vec2-large-xlsr-pa-IN | 7e4299aaa0b440cb94ebe719781de820c6569f66 | 2021-07-06T01:28:14.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"pa-IN",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | danurahul | null | danurahul/wav2vec2-large-xlsr-pa-IN | 11 | null | transformers | 11,051 | ---
language: pa-IN
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: danurahul/wav2vec2-large-xlsr-pa-IN
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
datase... |
dbernsohn/algebra_linear_1d | f46dfa8313633510eed5f631d0c7ef2e1afc69c1 | 2021-02-03T07:09:42.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:algebra_linear_1d",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | dbernsohn | null | dbernsohn/algebra_linear_1d | 11 | null | transformers | 11,052 | # algebra_linear_1d
---
language: en
datasets:
- algebra_linear_1d
---
This is a [t5-small](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) fine-tuned version on the [math_dataset/algebra_linear_1d](https://www.tensorflow.org/datasets/catalog/math_dataset#mathdatasetalgebra_linear_1d_defaul... |
deepset/bert-base-german-cased-oldvocab | 7e2765ba36d00041e567517642ffafb4cb2d06fb | 2021-10-21T12:16:47.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"de",
"transformers",
"exbert",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | deepset | null | deepset/bert-base-german-cased-oldvocab | 11 | 3 | transformers | 11,053 | ---
language: de
license: mit
thumbnail: https://static.tildacdn.com/tild6438-3730-4164-b266-613634323466/german_bert.png
tags:
- exbert
---
<a href="https://huggingface.co/exbert/?model=bert-base-german-cased">
\t<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
</a>
# German BERT with old... |
dexhrestha/Nepali-DistilBERT | 976530f2fdf06166c52eab9258c1f97287d24bcc | 2021-10-30T08:31:53.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | dexhrestha | null | dexhrestha/Nepali-DistilBERT | 11 | null | transformers | 11,054 | DistilBERT model trained on OSCAR nepali corpus from huggingface datasets.
We trained the DitilBERT language model on OSCAR nepali corpus and then for downstream sentiment analysis task. The dataset we used for sentiment analysis was first extracted from twitter filtering for devenagari text then labelled it as posti... |
dhlpricing/MyGPT2TG-cased-v1 | 97219ebf67662dcb8ff456b5dd8964dbc9372df9 | 2021-11-19T16:43:44.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | dhlpricing | null | dhlpricing/MyGPT2TG-cased-v1 | 11 | null | transformers | 11,055 | Entry not found |
diegozs97/finetuned-chemprot-seed-1-2000k | e799ecc511e9a847f843e6b6d93f0e7fbb95307f | 2021-12-07T05:26:40.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | diegozs97 | null | diegozs97/finetuned-chemprot-seed-1-2000k | 11 | null | transformers | 11,056 | Entry not found |
dshvadskiy/bert-finetuned-ner-accelerate | 49384111a27f7ccc28f45a4ef1a7a383d8508ec3 | 2022-01-17T18:04:23.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | dshvadskiy | null | dshvadskiy/bert-finetuned-ner-accelerate | 11 | null | transformers | 11,057 | Entry not found |
dsksd/collector_multiwoz | 25afbfcb20c2ab3506ed1e924511560b78cf8aaf | 2021-07-16T07:13:03.000Z | [
"pytorch",
"bart",
"feature-extraction",
"transformers"
] | feature-extraction | false | dsksd | null | dsksd/collector_multiwoz | 11 | null | transformers | 11,058 | Entry not found |
elgeish/wav2vec2-base-timit-asr | 039d878c5ab8656771a6d0254c0c0621ca515f34 | 2021-07-06T01:37:40.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:timit_asr",
"transformers",
"audio",
"speech",
"license:apache-2.0"
] | automatic-speech-recognition | false | elgeish | null | elgeish/wav2vec2-base-timit-asr | 11 | null | transformers | 11,059 | ---
language: en
datasets:
- timit_asr
tags:
- audio
- automatic-speech-recognition
- speech
license: apache-2.0
---
# Wav2Vec2-Base-TIMIT
Fine-tuned [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base)
on the [timit_asr dataset](https://huggingface.co/datasets/timit_asr).
When using this model, ma... |
eliza-dukim/bert-base-finetuned-sts | d77333cf8d6a14fbf5fd3801f51108518a918cb9 | 2021-09-22T11:01:03.000Z | [
"pytorch",
"bert",
"text-classification",
"dataset:klue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | eliza-dukim | null | eliza-dukim/bert-base-finetuned-sts | 11 | null | transformers | 11,060 | ---
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- pearsonr
- f1
model-index:
- name: bert-base-finetuned-sts
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: klue
type: klue
args: sts
metrics:
- name: Pearsonr
type: pear... |
emre/wav2vec2-xls-r-300m-gl-CV8 | 6fabd3e77199283645e47941427e53cdcf366c37 | 2022-03-23T18:34:43.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"gl",
"dataset:common_voice",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | emre | null | emre/wav2vec2-xls-r-300m-gl-CV8 | 11 | null | transformers | 11,061 | ---
license: apache-2.0
language: gl
tags:
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-300m-gl-CV8
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice gl
... |
emrecan/distilbert-base-turkish-cased-allnli_tr | f4efcd8d8c47418033041fad95ff351ebb62ff01 | 2021-12-02T14:57:35.000Z | [
"pytorch",
"distilbert",
"text-classification",
"tr",
"dataset:nli_tr",
"transformers",
"zero-shot-classification",
"nli",
"license:apache-2.0"
] | zero-shot-classification | false | emrecan | null | emrecan/distilbert-base-turkish-cased-allnli_tr | 11 | null | transformers | 11,062 | ---
language:
- tr
tags:
- zero-shot-classification
- nli
- pytorch
pipeline_tag: zero-shot-classification
license: apache-2.0
datasets:
- nli_tr
metrics:
- accuracy
widget:
- text: "Dolar yükselmeye devam ediyor."
candidate_labels: "ekonomi, siyaset, spor"
- text: "Senaryo çok saçmaydı, beğendim diyemem."
candidat... |
espejelomar/BETO_Clasificar_Tweets_Mexicano | 76b10cdd268c03b4882f4ce6a65b5b2bbb77c1c8 | 2022-02-15T17:42:05.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | espejelomar | null | espejelomar/BETO_Clasificar_Tweets_Mexicano | 11 | null | transformers | 11,063 | Entry not found |
ewriji/heil-A.412C-classification | da2c8b313ddb15219b1420eb80f5b591c2efa67d | 2021-12-17T01:11:33.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | ewriji | null | ewriji/heil-A.412C-classification | 11 | null | transformers | 11,064 | Entry not found |
fabriceyhc/bert-base-uncased-dbpedia_14 | 1fbfc3deaa280fcf16372746ca21363313357376 | 2021-09-21T00:56:12.000Z | [
"pytorch",
"bert",
"text-classification",
"dataset:dbpedia_14",
"transformers",
"generated_from_trainer",
"sibyl",
"license:apache-2.0",
"model-index"
] | text-classification | false | fabriceyhc | null | fabriceyhc/bert-base-uncased-dbpedia_14 | 11 | null | transformers | 11,065 | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- dbpedia_14
metrics:
- accuracy
model-index:
- name: bert-base-uncased-dbpedia_14
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: dbpedia_14
type: dbpedia_14
args: dbpedia_... |
facebook/wav2vec2-base-es-voxpopuli | 2fdabe011433c833551e92bda35594df0a18a2ee | 2021-07-06T01:53:59.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"es",
"arxiv:2101.00390",
"transformers",
"audio",
"automatic-speech-recognition",
"voxpopuli",
"license:cc-by-nc-4.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-base-es-voxpopuli | 11 | null | transformers | 11,066 | ---
language: es
tags:
- audio
- automatic-speech-recognition
- voxpopuli
license: cc-by-nc-4.0
---
# Wav2Vec2-Base-VoxPopuli
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) base model pretrained on the es unlabeled subset of [VoxPopuli corpus](https://a... |
facebook/wav2vec2-base-it-voxpopuli | 593e75291702d2ca8d404d63b2b47e6f028f8f39 | 2021-07-06T01:54:46.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"it",
"arxiv:2101.00390",
"transformers",
"audio",
"automatic-speech-recognition",
"voxpopuli",
"license:cc-by-nc-4.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-base-it-voxpopuli | 11 | null | transformers | 11,067 | ---
language: it
tags:
- audio
- automatic-speech-recognition
- voxpopuli
license: cc-by-nc-4.0
---
# Wav2Vec2-Base-VoxPopuli
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) base model pretrained on the it unlabeled subset of [VoxPopuli corpus](https://a... |
flax-community/arabic-t5-small | 887b7a5f66bc2121495ed99d662449048b3c71f1 | 2021-07-29T23:37:03.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"ar",
"dataset:mc4",
"dataset:oscar",
"dataset:arabic_billion_words",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | flax-community | null | flax-community/arabic-t5-small | 11 | 1 | transformers | 11,068 | ---
language:
- ar
datasets:
- mc4
- oscar
- arabic_billion_words
---
# arabic-t5-small
This is a T5v1.1 (small) trained on the concatenation of the Arabic Billion Words corpus and the Arabic subsets of the mC4 and Oscar datasets.
The model could only be trained for about `10%` of the whole dataset due to ti... |
gagan3012/k2t-tiny | 423c0d1dee6ef6b300cd6f1abac11a7d845dd4a8 | 2021-09-22T08:27:33.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:WebNLG",
"dataset:Dart",
"transformers",
"keytotext",
"k2t-tiny",
"Keywords to Sentences",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | gagan3012 | null | gagan3012/k2t-tiny | 11 | null | transformers | 11,069 | ---
language: en
thumbnail: Keywords to Sentences
tags:
- keytotext
- k2t-tiny
- Keywords to Sentences
license: mit
datasets:
- WebNLG
- Dart
metrics:
- NLG
---
# keytotext
Idea is to build a model... |
gagan3012/pickuplines | 3078b63c12a4c9f6cb5c262348b56873e2e3e83f | 2021-10-18T19:53:36.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-generation | false | gagan3012 | null | gagan3012/pickuplines | 11 | null | transformers | 11,070 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: pickuplines
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. -->
# pickuplines
This model is a f... |
gbade786/distilbert-base-uncased-finetuned-emotion | 9f725e4da377629d30bea790a34946abe54d9ff9 | 2022-01-14T14:44:33.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | gbade786 | null | gbade786/distilbert-base-uncased-finetuned-emotion | 11 | null | transformers | 11,071 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
gchhablani/wav2vec2-large-xlsr-pt | e32f8fda6733db09e876e3a8059fc7b441197cf1 | 2021-07-06T05:23:19.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | gchhablani | null | gchhablani/wav2vec2-large-xlsr-pt | 11 | null | transformers | 11,072 | ---
language: pt
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Wav2Vec2 Large 53 Portugese by Gunjan Chhablani
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
ghadeermobasher/bc4chemd-imbalanced-biobert-base-casesd-v1.1 | 5cbf6f489b82f0dd35cbc1433d2445c63cdd7930 | 2022-02-04T07:42:48.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/bc4chemd-imbalanced-biobert-base-casesd-v1.1 | 11 | null | transformers | 11,073 | Entry not found |
google/t5-xxl-ssm-wq | e9f808d09b78ef1bb19e1186a7884ef42234d65d | 2020-12-07T12:35:31.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"dataset:wikipedia",
"dataset:web_questions",
"arxiv:2002.08909",
"arxiv:1910.10683",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-xxl-ssm-wq | 11 | 1 | transformers | 11,074 | ---
language: en
datasets:
- c4
- wikipedia
- web_questions
license: apache-2.0
---
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) for **Closed Book Question Answering**.
The model was pre-trained using T5's denoising objective on [C4](https://huggingface.co/datasets/c4), s... |
google/tapas-mini-finetuned-tabfact | 2ee10173c30cf3adb08636740d75def8a6737987 | 2021-11-29T13:06:50.000Z | [
"pytorch",
"tf",
"tapas",
"text-classification",
"en",
"dataset:tab_fact",
"arxiv:2010.00571",
"arxiv:2004.02349",
"transformers",
"sequence-classification",
"license:apache-2.0"
] | text-classification | false | google | null | google/tapas-mini-finetuned-tabfact | 11 | null | transformers | 11,075 | ---
language: en
tags:
- tapas
- sequence-classification
license: apache-2.0
datasets:
- tab_fact
---
# TAPAS mini model fine-tuned on Tabular Fact Checking (TabFact)
This model has 2 versions which can be used. The latest version, which is the default one, corresponds to the `tapas_tabfact_inter_masklm_mini_reset`... |
hadxu/distilbert-base-uncased-finetuned-emotion | ab5baf280dd140d18a2cd43b5f1fc2d02bb93804 | 2022-02-10T11:20:33.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | hadxu | null | hadxu/distilbert-base-uncased-finetuned-emotion | 11 | null | transformers | 11,076 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
howey/electra-large-qqp | 1fda2eeefe4a766ebf81e9e6f62250f722a25a9b | 2021-07-26T02:47:52.000Z | [
"pytorch",
"electra",
"text-classification",
"transformers"
] | text-classification | false | howey | null | howey/electra-large-qqp | 11 | 1 | transformers | 11,077 | Entry not found |
huawei-noah/TernaryBERT_MNLI | 338819666c7bb32e6f5b39136e253fc918833143 | 2020-10-16T03:07:54.000Z | [
"pytorch",
"transformers"
] | null | false | huawei-noah | null | huawei-noah/TernaryBERT_MNLI | 11 | null | transformers | 11,078 | Entry not found |
huggingartists/arctic-monkeys | ffd5168fb1837f5ad628e00c49c1158f71e4a676 | 2021-10-26T17:28:49.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:huggingartists/arctic-monkeys",
"transformers",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm"
] | text-generation | false | huggingartists | null | huggingartists/arctic-monkeys | 11 | null | transformers | 11,079 | ---
language: en
datasets:
- huggingartists/arctic-monkeys
tags:
- huggingartists
- lyrics
- lm-head
- causal-lm
widget:
- text: "I am"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; h... |
huggingartists/miyagi | 1caa528be4d25fbf1a5ff48e3c359b89d2f6a174 | 2022-07-04T16:58:30.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:huggingartists/miyagi",
"transformers",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm"
] | text-generation | false | huggingartists | null | huggingartists/miyagi | 11 | null | transformers | 11,080 | ---
language: en
datasets:
- huggingartists/miyagi
tags:
- huggingartists
- lyrics
- lm-head
- causal-lm
widget:
- text: "I am"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92... |
huggingtweets/aoc | f3b343ed21a095e9fbe1e4926129be99211a6ba7 | 2022-07-22T22:26:57.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/aoc | 11 | null | transformers | 11,081 | ---
language: en
thumbnail: http://www.huggingtweets.com/aoc/1658528812949/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; width: 92px... |
huggingtweets/bichebuni | 454afafb61458fed65cafb9e08f767c9653e9371 | 2021-05-21T20:37:06.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/bichebuni | 11 | null | transformers | 11,082 | ---
language: en
thumbnail: https://www.huggingtweets.com/bichebuni/1614096170963/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/135641447714351... |
huggingtweets/sigittanew | 0a4b9c3f6c78a2a1a0e315070edb6d0db03ec845 | 2021-05-22T22:54:41.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/sigittanew | 11 | null | transformers | 11,083 | ---
language: en
thumbnail: https://www.huggingtweets.com/sigittanew/1617902420104/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/13153070029990... |
hyunwoongko/brainbert-base-ko-kornli | 2bceaf8392c8c1427653f924da8a146bb315a993 | 2022-01-07T06:35:58.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | hyunwoongko | null | hyunwoongko/brainbert-base-ko-kornli | 11 | null | transformers | 11,084 | Entry not found |
iarfmoose/wav2vec2-large-xlsr-sorbian | ad782fe1576f3a1103e4b6d419ba8d6a9eb9f772 | 2021-07-06T06:01:40.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"hsb",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | iarfmoose | null | iarfmoose/wav2vec2-large-xlsr-sorbian | 11 | null | transformers | 11,085 | ---
language: hsb
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Sorbian by Adam Montgomerie
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
nam... |
ikevin98/bert-base-uncased-finetuned-sst2-sst2-membership | b3ca0fa795d032cadc71cbdf6ea978501549a0eb | 2021-09-04T20:10:24.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | false | ikevin98 | null | ikevin98/bert-base-uncased-finetuned-sst2-sst2-membership | 11 | null | transformers | 11,086 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model_index:
name: bert-base-uncased-finetuned-sst2-sst2-membership
---
<!-- 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 t... |
it5/mt5-small-informal-to-formal | 71f9ee387b8f0b1b863de70377866c4f265ffea6 | 2022-03-09T07:49:29.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"mt5",
"text2text-generation",
"it",
"dataset:yahoo/xformal_it",
"arxiv:2203.03759",
"transformers",
"italian",
"sequence-to-sequence",
"style-transfer",
"formality-style-transfer",
"license:apache-2.0",
"model-index",
"co2_eq_emissions",
"aut... | text2text-generation | false | it5 | null | it5/mt5-small-informal-to-formal | 11 | null | transformers | 11,087 | ---
language:
- it
license: apache-2.0
tags:
- italian
- sequence-to-sequence
- style-transfer
- formality-style-transfer
datasets:
- yahoo/xformal_it
widget:
- text: "maronn qualcuno mi spieg' CHECCOSA SUCCEDE?!?!"
- text: "wellaaaaaaa, ma fraté sei proprio troppo simpatiko, grazieeee!!"
- text: "nn capisco xke tt i r... |
jcblaise/electra-tagalog-small-cased-discriminator | 79952fd321b77d1292385822eeaea2e7bd4342da | 2021-11-12T03:23:59.000Z | [
"pytorch",
"electra",
"pretraining",
"tl",
"transformers",
"tagalog",
"filipino",
"license:gpl-3.0"
] | null | false | jcblaise | null | jcblaise/electra-tagalog-small-cased-discriminator | 11 | null | transformers | 11,088 | ---
language: tl
tags:
- electra
- tagalog
- filipino
license: gpl-3.0
inference: false
---
**Deprecation Notice**
This model is deprecated. New Filipino Transformer models trained with a much larger corpora are available.
Use [`jcblaise/roberta-tagalog-base`](https://huggingface.co/jcblaise/roberta-tagalog-base) ... |
joonhan/roberta-roa | df85c06271eaa6bc4ea2a601d7b0301575b21109 | 2021-10-08T02:05:28.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | joonhan | null | joonhan/roberta-roa | 11 | null | transformers | 11,089 | * Fine-tunning "KLUE/roberta-large" model For CER(Company Entity Recognition) With Custom Dataset
* Custom Datasets are composed of news data
```python
label_list = ['O',"B-PER","I-PER","B-ORG","I-ORG","B-COM","I-COM","B-LOC","I-LOC","B-DAT","I-DAT","B-TIM","I-TIM","B-QNT","I-QNT"]
refer_list = ['0','1','2','3','4... |
joaoalvarenga/model-sid-voxforge-cetuc-2 | 3131f140dd5427fc06cbb81e69ce5e8472e7c328 | 2021-07-06T08:45:23.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | joaoalvarenga | null | joaoalvarenga/model-sid-voxforge-cetuc-2 | 11 | null | transformers | 11,090 | Entry not found |
joaoalvarenga/wav2vec2-cetuc-sid-voxforge-mls-0-new | cba5734fc9160b720e910be953aa58cb93f776e1 | 2021-07-12T12:26:36.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | joaoalvarenga | null | joaoalvarenga/wav2vec2-cetuc-sid-voxforge-mls-0-new | 11 | null | transformers | 11,091 | Entry not found |
jsgao/bart-eli5c | 8a480cb69f41b15e80bd839208f10f6843e9ae27 | 2021-12-14T21:09:14.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:eli5_category",
"transformers",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | jsgao | null | jsgao/bart-eli5c | 11 | null | transformers | 11,092 | ---
language: en
license: MIT
datasets:
- eli5_category
---
Answer generator model of [ELI5-Category Dataset](https://celeritasml.netlify.app/posts/2021-12-01-eli5c/) |
juliusco/biobert-base-cased-v1.1-squad-finetuned-covdrobert | 4a76b5e23ecc89d08691bf22355009dc29190d57 | 2021-12-14T10:28:15.000Z | [
"pytorch",
"bert",
"question-answering",
"dataset:covid_qa_deepset",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | juliusco | null | juliusco/biobert-base-cased-v1.1-squad-finetuned-covdrobert | 11 | null | transformers | 11,093 | ---
tags:
- generated_from_trainer
datasets:
- covid_qa_deepset
model-index:
- name: biobert-base-cased-v1.1-squad-finetuned-covdrobert
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 rem... |
jwa018/norwegian_parliament | fe3b549b8f5b35fec785ffb785f6d904971f9850 | 2021-10-24T21:58:51.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | jwa018 | null | jwa018/norwegian_parliament | 11 | null | transformers | 11,094 | Entry not found |
k-partha/decision_style_bert_bio | 49717e1acd15bd62878039b99d9e4709e860c102 | 2022-01-29T03:36:37.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:2109.06402",
"transformers"
] | text-classification | false | k-partha | null | k-partha/decision_style_bert_bio | 11 | null | transformers | 11,095 | Rates Twitter biographies on decision-making preference: Judging (focused, goal-oriented decision strategy) or Prospecting (open-ended, explorative strategy). Roughly corresponds to [conscientiousness](https://en.wikipedia.org/wiki/Conscientiousness)
Go to your Twitter profile, copy your biography and paste in the inf... |
k-partha/extrabert_bio | 36d571d7fd0d01e2684f5272789c98d8521b99f1 | 2022-01-29T03:36:11.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:2109.06402",
"transformers"
] | text-classification | false | k-partha | null | k-partha/extrabert_bio | 11 | null | transformers | 11,096 | Classifies Twitter biographies as either introverts or extroverts.
Go to your Twitter profile, copy your biography and paste in the inference widget, remove any URLs and press hit!
Trained on self-described personality labels. Interpret as a continuous score, not as a discrete label. Have fun!
Barack Obama: Extrove... |
kbhugging/autonlp-text2sql-18413376 | 5650cb482cdec04eadaf364997f22b5d9dad2dea | 2021-10-15T02:36:42.000Z | [
"pytorch",
"t5",
"text2text-generation",
"unk",
"dataset:kbhugging/autonlp-data-text2sql",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | kbhugging | null | kbhugging/autonlp-text2sql-18413376 | 11 | null | transformers | 11,097 | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- kbhugging/autonlp-data-text2sql
co2_eq_emissions: 1.4091714704861447
---
# Model Trained Using AutoNLP
- Problem type: Summarization
- Model ID: 18413376
- CO2 Emissions (in grams): 1.4091714704861447
## Validation Metrics
- Loss: 0.266... |
kingabzpro/wav2vec2-60-urdu | 128cf5bef2519dfb55b1316bc91afe6ec8ab842a | 2022-03-23T18:27:20.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"ur",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | kingabzpro | null | kingabzpro/wav2vec2-60-urdu | 11 | 1 | transformers | 11,098 | ---
language:
- ur
license: apache-2.0
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-60-urdu
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
... |
kingabzpro/wav2vec2-large-xls-r-1b-Indonesian | 8536e2edf49b1347b4503d12b63b506770117f87 | 2022-03-23T18:29:16.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"id",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | kingabzpro | null | kingabzpro/wav2vec2-large-xls-r-1b-Indonesian | 11 | 1 | transformers | 11,099 | ---
language:
- id
license: apache-2.0
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-large-xls-r-1b-Indonesian
results:
- task:
type: automatic-speech-recognition
name: Sp... |
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