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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
tner/xlm-roberta-base-panx-dataset-ru | e70931cf283091559ff1606d640c91326730986c | 2021-02-13T00:08:30.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tner | null | tner/xlm-roberta-base-panx-dataset-ru | 0 | null | transformers | 33,600 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-base-panx-dataset-ru")
mode... |
tner/xlm-roberta-base-uncased-bc5cdr | a94f829854c121c128531f628b068547b7528a63 | 2021-02-13T00:08:23.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tner | null | tner/xlm-roberta-base-uncased-bc5cdr | 0 | null | transformers | 33,601 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-base-uncased-bc5cdr")
model... |
tner/xlm-roberta-large-panx-dataset-en | 5a9a00b3df08682bd91282e17af7e7ffd8875529 | 2021-02-13T00:11:22.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tner | null | tner/xlm-roberta-large-panx-dataset-en | 0 | null | transformers | 33,602 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-large-panx-dataset-en")
mod... |
tner/xlm-roberta-large-panx-dataset-ru | c928186c245847850aa748400bddd6893995eeec | 2021-02-13T00:11:34.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tner | null | tner/xlm-roberta-large-panx-dataset-ru | 0 | null | transformers | 33,603 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-large-panx-dataset-ru")
mod... |
tner/xlm-roberta-large-uncased-bc5cdr | 973e4f0fac04e6e73374ec5023a3a2505406fd13 | 2021-02-13T00:11:43.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tner | null | tner/xlm-roberta-large-uncased-bc5cdr | 0 | null | transformers | 33,604 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-large-uncased-bc5cdr")
mode... |
tner/xlm-roberta-large-uncased-fin | 92eb88f13a760c1524fe6c6faacc95e7a30aead0 | 2021-02-13T00:05:55.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tner | null | tner/xlm-roberta-large-uncased-fin | 0 | null | transformers | 33,605 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-large-uncased-fin")
model =... |
bgfruna/double-bart-ensemble-squad2 | 1bb9a0f44dd99ec7c27738cd70112647badc8716 | 2021-07-21T22:47:12.000Z | [
"pytorch",
"en",
"dataset:squad_v2",
"dataset:squad2",
"question-answering",
"license:cc-by-4.0"
] | question-answering | false | bgfruna | null | bgfruna/double-bart-ensemble-squad2 | 0 | null | null | 33,606 | ---
language: en
tags:
- pytorch
- question-answering
datasets:
- squad_v2
- squad2
license: cc-by-4.0
metrics:
- squad_v2
- exact
- f1
widget:
- text: "By what main attribute are computational problems classified utilizing computational complexity theory?"
context: "Computational complexity theory is a branch of the... |
bluebalam/paper-rec | 8ed91678a65abd9e178f930150cfb2c7136b8f5f | 2022-02-04T21:37:35.000Z | [
"en",
"arxiv:2109.03955",
"arxiv:1908.10084",
"recsys",
"pytorch",
"sentence_transformers",
"license:mit"
] | null | false | bluebalam | null | bluebalam/paper-rec | 0 | 3 | null | 33,607 | ---
language:
- en
license: mit
tags:
- recsys
- pytorch
- sentence_transformers
#datasets:
#- {dataset_0} # Example: common_voice. Use dataset id from https://hf.co/datasets
#metrics:
#- {metric_0} # Example: wer. Use metric id from https://hf.co/metrics
---
# `paper-rec` Model Card
Last updated:... |
cross/words | d2097c5faa2c8db9d4e905059369c9bc5edf30e8 | 2021-03-19T12:05:58.000Z | [
"pytorch"
] | null | false | cross | null | cross/words | 0 | null | null | 33,608 | Entry not found |
cyou/bert-base-jp1 | b2b0a3e484cc3ffc3a3c533aa8fe66312b61299d | 2021-11-01T21:15:25.000Z | [
"pytorch"
] | null | false | cyou | null | cyou/bert-base-jp1 | 0 | null | null | 33,609 | |
drcod/DagaareBERTa | 552f8cae48ba2ea1ebdaed209b58b40aa5cabd56 | 2021-08-24T22:23:45.000Z | [
"pytorch",
"tf",
"dataset:Bible",
"arxiv:1907.11692"
] | null | false | drcod | null | drcod/DagaareBERTa | 0 | null | null | 33,610 | ---
datasets:
- Bible
---
Pretrained model on Dagaare language using a masked language modeling (MLM) objective first introduced in
[this paper](https://arxiv.org/abs/1907.11692) and first released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/roberta)\
|
facebook/wav2vec2-base-10k-voxpopuli-ft-de | 1cbaf198475e1af97cc479ca081ce4ddd2d6b5cf | 2021-07-06T01:48:44.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"arxiv:2101.00390",
"transformers",
"audio",
"voxpopuli",
"license:cc-by-nc-4.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-base-10k-voxpopuli-ft-de | 0 | 1 | transformers | 33,611 | ---
language: de
tags:
- audio
- automatic-speech-recognition
- voxpopuli
license: cc-by-nc-4.0
---
# Wav2Vec2-Base-VoxPopuli-Finetuned
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) base model pretrained on the 10K unlabeled subset of [VoxPopuli corpus... |
facebook/wav2vec2-base-10k-voxpopuli-ft-hu | fd70fe41f6e7b7dc71bc952a9cd4b4e23ed7e17f | 2021-07-06T01:50:56.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hu",
"arxiv:2101.00390",
"transformers",
"audio",
"voxpopuli",
"license:cc-by-nc-4.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-base-10k-voxpopuli-ft-hu | 0 | null | transformers | 33,612 | ---
language: hu
tags:
- audio
- automatic-speech-recognition
- voxpopuli
license: cc-by-nc-4.0
---
# Wav2Vec2-Base-VoxPopuli-Finetuned
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) base model pretrained on the 10K unlabeled subset of [VoxPopuli corpus... |
facebook/wav2vec2-base-10k-voxpopuli-ft-it | 653b3c789c7d83134924bda6fabe0c6bb84f579c | 2021-07-06T01:51:18.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"arxiv:2101.00390",
"transformers",
"audio",
"voxpopuli",
"license:cc-by-nc-4.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-base-10k-voxpopuli-ft-it | 0 | null | transformers | 33,613 | ---
language: it
tags:
- audio
- automatic-speech-recognition
- voxpopuli
license: cc-by-nc-4.0
---
# Wav2Vec2-Base-VoxPopuli-Finetuned
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) base model pretrained on the 10K unlabeled subset of [VoxPopuli corpus... |
facebook/wav2vec2-xlsr-53-phon-cv-babel-ft | 2598051121aed794d856e0edac36df88613724ba | 2021-11-10T12:02:20.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-xlsr-53-phon-cv-babel-ft | 0 | null | transformers | 33,614 | Entry not found |
fadhilarkan/t5_paw_global | de340fecbdad839e4cb967aad569361929509139 | 2021-08-23T15:42:54.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | fadhilarkan | null | fadhilarkan/t5_paw_global | 0 | null | transformers | 33,615 | Entry not found |
fadhilarkan/tmpvqruuuz0 | 6477d617cef8553baa2eb1a4088c427cc16fc2f5 | 2021-08-23T17:06:39.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | fadhilarkan | null | fadhilarkan/tmpvqruuuz0 | 0 | null | transformers | 33,616 | Entry not found |
faketermz/DialoGPT | 5c1c9ab8d18265c98d4ea73cc6b4f84a5bc5790c | 2021-12-05T13:02:46.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | faketermz | null | faketermz/DialoGPT | 0 | null | transformers | 33,617 | ---
tags:
- conversational
---
# test DialoGPT Model |
famodde/optimizer-ner-fineTune-lst2021 | b7c5561849ab201f82e58b0442e954e82484ab71 | 2022-02-18T05:01:27.000Z | [
"pytorch",
"camembert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | famodde | null | famodde/optimizer-ner-fineTune-lst2021 | 0 | null | transformers | 33,618 | Entry not found |
famodde/optimizer-ner-fineTune | 9711ce205f254d30f581a73fb57c7053b811ab1d | 2022-02-16T18:41:51.000Z | [
"pytorch",
"camembert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | famodde | null | famodde/optimizer-ner-fineTune | 0 | null | transformers | 33,619 | Entry not found |
famodde/wangchanberta-ner-fineTune | 748a4cc18ff673826965a3b409d38de1fc0a4cf1 | 2022-02-16T08:08:19.000Z | [
"pytorch",
"camembert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | famodde | null | famodde/wangchanberta-ner-fineTune | 0 | null | transformers | 33,620 | Entry not found |
fatemaMeem98/DialoGPT-medium-HermioneGrangerBot | ae7a18a3e2bdf2b41f27661d2cea38143e526ad7 | 2021-12-20T05:35:09.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | fatemaMeem98 | null | fatemaMeem98/DialoGPT-medium-HermioneGrangerBot | 0 | null | transformers | 33,621 | ---
tags:
- conversational
---
# Hermione Granger DialoGPT Model |
fav-kky/FERNET-News_sk | 81e1bf2f8ad90f7f38a171a924f839276bae1217 | 2021-09-09T14:02:40.000Z | [
"pytorch",
"tf",
"roberta",
"fill-mask",
"sk",
"arxiv:2107.10042",
"transformers",
"Slovak",
"KKY",
"FAV",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | fav-kky | null | fav-kky/FERNET-News_sk | 0 | null | transformers | 33,622 | ---
language: "sk"
tags:
- Slovak
- KKY
- FAV
license: "cc-by-nc-sa-4.0"
---
# FERNET-News_sk
FERNET-News_sk is a monolingual Slovak RoBERTa-base model pre-trained from 4.5GB of thoroughly cleaned Slovak news corpus.
It is a Slovak version of our Czech [FERNET-News](https://huggingface.co/fav-kky/FERNET-News) model.
... |
felixai/distilmbart-9-3 | a4499e41be9451ef8c471f44ab5c51875acefe25 | 2021-07-16T14:41:20.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | felixai | null | felixai/distilmbart-9-3 | 0 | null | transformers | 33,623 | # mbart for 9-3
|
ffrmns/t5-small_XSum-finetuned | 9f783d62ef4b9eafd0a82deae62cbef11da85cee | 2021-04-20T00:59:58.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | ffrmns | null | ffrmns/t5-small_XSum-finetuned | 0 | null | transformers | 33,624 | Entry not found |
ffsouza/tiny-mbart-length-96-learning_rate-2e-05-weight_decay-0.005-finetuned-en-to-ro | 119229529e68cec6e0bd457227c9d1d64fca142a | 2021-11-30T19:57:36.000Z | [
"pytorch",
"tensorboard",
"mbart",
"text2text-generation",
"dataset:wmt16_en_ro_pre_processed",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | ffsouza | null | ffsouza/tiny-mbart-length-96-learning_rate-2e-05-weight_decay-0.005-finetuned-en-to-ro | 0 | null | transformers | 33,625 | ---
tags:
- generated_from_trainer
datasets:
- wmt16_en_ro_pre_processed
metrics:
- bleu
model-index:
- name: tiny-mbart-length-96-learning_rate-2e-05-weight_decay-0.005-finetuned-en-to-ro
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: w... |
ffsouza/tiny-mbart-length-96-learning_rate-2e-05-weight_decay-0.02-finetuned-en-to-ro | 6da962a68f0deab4ea27c59dbbaaefd973af78fb | 2021-11-30T20:10:38.000Z | [
"pytorch",
"tensorboard",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | ffsouza | null | ffsouza/tiny-mbart-length-96-learning_rate-2e-05-weight_decay-0.02-finetuned-en-to-ro | 0 | null | transformers | 33,626 | Entry not found |
fgaim/t5-small-squad-v2 | dcbbdbea810d304e270c8a6ab12c475bc0b1f151 | 2022-01-30T21:35:54.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"dataset:squad",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | fgaim | null | fgaim/t5-small-squad-v2 | 0 | null | transformers | 33,627 | ---
language:
- en
datasets:
- c4
- squad
tags:
- text2text-generation
widget:
- text: "question: What is the atomic number for oxygen? context: Oxygen is a chemical element with symbol O and atomic number 8."
- text: "question: What is the chemical symbol of Oxygen? context: Oxygen is a chemical element with symbol O... |
fgua/bert-base-uncased-wikitext2 | 95764d9cfa4dc9ae7291451ddd4e690de53b3b22 | 2022-04-26T15:04:36.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | fgua | null | fgua/bert-base-uncased-wikitext2 | 0 | null | transformers | 33,628 | Entry not found |
fibruh/DialoGPT-small-harrypotter | 46acbb31b70e79dc53b646daee1714fb41bcdc3f | 2021-12-15T04:18:11.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | fibruh | null | fibruh/DialoGPT-small-harrypotter | 0 | null | transformers | 33,629 | ---
tags:
- conversational
---
# Fibruh Bot Model |
finiteautomata/bert-non-contextualized-hate-category-es | 09ecb41256785c2c7cfe8706431c77c54598959b | 2021-05-19T16:51:52.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | finiteautomata | null | finiteautomata/bert-non-contextualized-hate-category-es | 0 | null | transformers | 33,630 | Entry not found |
finiteautomata/beto-fine-grained-hatespeech-news | f4a730bd8173344c79513e47a92ac20cc3cc9d6d | 2021-06-24T14:54:12.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | finiteautomata | null | finiteautomata/beto-fine-grained-hatespeech-news | 0 | null | transformers | 33,631 | ## Fine Grained Hate Speech in News
### WARNING: Work in progress
Model trained on news comments. |
finiteautomata/betonews-bodycontext | efccfffb07da8ad1143d183e8062b37bc39c6cdb | 2021-10-08T14:53:18.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | finiteautomata | null | finiteautomata/betonews-bodycontext | 0 | null | transformers | 33,632 | Entry not found |
finiteautomata/betonews-nonecontext | 444990c470e160583943cabe30d304ddcee642f4 | 2021-10-01T21:32:37.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | finiteautomata | null | finiteautomata/betonews-nonecontext | 0 | null | transformers | 33,633 | Entry not found |
fkHug/modelFromWav2vec | d778372ac925e17981e14547b93dc47b313c3075 | 2021-12-03T17:35:19.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | fkHug | null | fkHug/modelFromWav2vec | 0 | null | transformers | 33,634 | this is my model card
|
flairbook/flairmodel | 5966905c3b083679ba6d327261d1ce73074e6341 | 2022-01-08T18:06:53.000Z | [
"pytorch",
"flair",
"token-classification"
] | token-classification | false | flairbook | null | flairbook/flairmodel | 0 | null | flair | 33,635 | ---
tags:
- flair
- token-classification
widget:
- text: "does this work"
---
## Test model README
Some test README description |
flakje/DialoGPT-small-Marty | 2e8d61849608dda317dc7f069914b2b4ef30a599 | 2021-11-20T18:34:54.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | flakje | null | flakje/DialoGPT-small-Marty | 0 | null | transformers | 33,636 | ---
tags:
- conversational
---
# Marty DialoGPT Model |
flavio-nakasato/deeppolicytracker_500k | aa3c41c375fe846894cd19ffd4088876788b3c5b | 2021-08-14T22:14:07.000Z | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | flavio-nakasato | null | flavio-nakasato/deeppolicytracker_500k | 0 | null | transformers | 33,637 | RoBERTa model pretrained on the Brazilian Federal Official Gazette (500k instances).
|
flax-community/gpt-code-clippy-125M-bs2048-raw | 39fa8caa315e1524b9302e094262888e342b9188 | 2021-07-16T10:29:45.000Z | [
"pytorch",
"jax",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | flax-community | null | flax-community/gpt-code-clippy-125M-bs2048-raw | 0 | null | transformers | 33,638 | Entry not found |
flax-community/gpt-neo-1.3B-resized-embed | b75d14484ef2e569ef6ef10dd60f6a4e8829b674 | 2021-07-16T11:25:41.000Z | [
"pytorch",
"jax",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | flax-community | null | flax-community/gpt-neo-1.3B-resized-embed | 0 | null | transformers | 33,639 | Entry not found |
flax-sentence-embeddings/all_datasets_v4_MiniLM-L12 | 70c1ce7853189f5b4cb094ff364dc1f0869c11be | 2021-07-23T16:01:01.000Z | [
"pytorch",
"bert",
"en",
"arxiv:2104.08727",
"arxiv:1810.09305",
"arxiv:2102.07033",
"arxiv:1904.06472",
"sentence-transformers",
"feature-extraction",
"sentence-similarity"
] | sentence-similarity | false | flax-sentence-embeddings | null | flax-sentence-embeddings/all_datasets_v4_MiniLM-L12 | 0 | 2 | sentence-transformers | 33,640 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language: en
---
# Model description
The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised
contrastive learning objective. We used the pretrained ... |
flboehm/reddit-bert-text2 | e65bd2cef8e20a463711d1ae957444761012de89 | 2021-12-07T14:45:38.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | flboehm | null | flboehm/reddit-bert-text2 | 0 | null | transformers | 33,641 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: reddit-bert-text2
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. -->
# reddit-bert-text2... |
flboehm/reddit-bert-text3 | ad988e5ed57aa5368c34d6c5202aeddf458b7e78 | 2021-12-08T15:32:43.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | flboehm | null | flboehm/reddit-bert-text3 | 0 | null | transformers | 33,642 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: reddit-bert-text3
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. -->
# reddit-bert-text3... |
flboehm/reddit-bert-text4 | 51b7eff9331ea63931d73c1b68120bf5269403c3 | 2021-12-15T08:41:48.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | flboehm | null | flboehm/reddit-bert-text4 | 0 | null | transformers | 33,643 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: reddit-bert-text4
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. -->
# reddit-bert-text4... |
flymushroom/model1 | 3e012e3c0682fd818e16f8b9255fac04851d9539 | 2021-11-02T05:07:30.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | flymushroom | null | flymushroom/model1 | 0 | null | transformers | 33,644 | Entry not found |
formermagic/codet5-small | 770eff8c18ee77115cfade8021030072dfe495ab | 2021-09-21T23:20:48.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | formermagic | null | formermagic/codet5-small | 0 | 1 | transformers | 33,645 | Entry not found |
formermagic/codet5x-small | 921f2c65cd0919588882387818dc57e9073659f9 | 2021-10-08T02:51:31.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | formermagic | null | formermagic/codet5x-small | 0 | null | transformers | 33,646 | Entry not found |
francoMG/sara-qa | 2baf25628af770dc41eeca1c0dbd252aa5faf954 | 2021-10-08T02:45:39.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | francoMG | null | francoMG/sara-qa | 0 | null | transformers | 33,647 | Entry not found |
fznmhmmd/gpt2-wikitext2 | 848acc2279df64fd4d77f0b21cc88727b0312d66 | 2022-02-09T15:44:05.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-generation | false | fznmhmmd | null | fznmhmmd/gpt2-wikitext2 | 0 | null | transformers | 33,648 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gpt2-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. -->
# gpt2-wikitext2
This model ... |
gabtan99/dialogpt-tagalog-medium-10 | 62ec78049ea2dcc6442ed4e487c3b9e872f85c45 | 2021-07-26T10:19:09.000Z | [
"pytorch",
"gpt2",
"text-generation",
"tl",
"transformers",
"conversational",
"tagalog",
"filipino"
] | conversational | false | gabtan99 | null | gabtan99/dialogpt-tagalog-medium-10 | 0 | null | transformers | 33,649 | ---
tags:
- conversational
- tagalog
- filipino
language:
- tl
---
# Tagalog DialoGPT
This is an extension of the base Tagalog DialoGPT model (https://huggingface.co/gabtan99/dialogpt-tagalog-medium).
This model is trained on 52K original conversations and 52K synthetic conversations, where 10% of tokens in each... |
gabtan99/dialogpt-tagalog-medium-20 | 1c1c4a011e106f4b37d3811a8be49d7c064bbcfa | 2021-08-18T03:04:51.000Z | [
"pytorch",
"gpt2",
"text-generation",
"tl",
"transformers",
"conversational",
"tagalog",
"filipino"
] | conversational | false | gabtan99 | null | gabtan99/dialogpt-tagalog-medium-20 | 0 | null | transformers | 33,650 | ---
tags:
- conversational
- tagalog
- filipino
inference: false
language:
- tl
---
# Tagalog DialoGPT
This is an extension of the base Tagalog DialoGPT model (https://huggingface.co/gabtan99/dialogpt-tagalog-medium).
This model is trained on 52K original conversations and 52K synthetic conversations, where 20... |
gabtan99/dialogpt-tagalog-medium-30 | a40da3ce9ff019535b8ae2da4e97c24644b28f28 | 2021-08-18T03:05:00.000Z | [
"pytorch",
"gpt2",
"text-generation",
"tl",
"transformers",
"conversational",
"tagalog",
"filipino"
] | conversational | false | gabtan99 | null | gabtan99/dialogpt-tagalog-medium-30 | 0 | null | transformers | 33,651 | ---
tags:
- conversational
- tagalog
- filipino
inference: false
language:
- tl
---
# Tagalog DialoGPT
This is an extension of the base Tagalog DialoGPT model (https://huggingface.co/gabtan99/dialogpt-tagalog-medium).
This model is trained on 52K original conversations and 52K synthetic conversations, where 30% ... |
gagan3012/wav2vec2-xlsr-chuvash | d08849c6cfdee971e326ced6e4d35ad52369f8ee | 2021-07-06T03:45:55.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"cv",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | gagan3012 | null | gagan3012/wav2vec2-xlsr-chuvash | 0 | null | transformers | 33,652 | ---
language: cv
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: wav2vec2-xlsr-chuvash by Gagan Bhatia
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset... |
gagan3012/wav2vec2-xlsr-punjabi | d37bc866ee1867595d13bbb20b4031cda0adf98a | 2021-07-06T04:21:10.000Z | [
"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 | gagan3012 | null | gagan3012/wav2vec2-xlsr-punjabi | 0 | null | transformers | 33,653 | ---
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: wav2vec2-xlsr-punjabi
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name:... |
gagan3012/xls-r-300m-pa | cf684782f31901700be698d8649c8b26608251e0 | 2022-01-31T15:27:47.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pa-IN",
"dataset:common_voice",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | gagan3012 | null | gagan3012/xls-r-300m-pa | 0 | null | transformers | 33,654 | ---
language:
- pa-IN
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: xls-r-300m-pa
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had ... |
gaotianyu1350/unsup-simcse-bert-large-uncased | c4294b4e7c593ed61814accee7e4837045ea7474 | 2021-05-19T17:11:09.000Z | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | gaotianyu1350 | null | gaotianyu1350/unsup-simcse-bert-large-uncased | 0 | null | transformers | 33,655 | Entry not found |
gaotianyu1350/unsup-simcse-roberta-large | c0abe3578e9554542f25b4a0da9ed19188ec7a51 | 2021-05-20T16:29:43.000Z | [
"pytorch",
"jax",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | gaotianyu1350 | null | gaotianyu1350/unsup-simcse-roberta-large | 0 | null | transformers | 33,656 | Entry not found |
gaussfer/test_simcse_new | d44790f8bce80e98087ce050bcfcf5d84f5791b1 | 2022-01-05T09:03:36.000Z | [
"pytorch",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | gaussfer | null | gaussfer/test_simcse_new | 0 | null | sentence-transformers | 33,657 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# gaussfer/test_simcse_new
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks ... |
gayanin/bart-mlm-pubmed-15 | f8380e42baed492b6960f730b5d9b88f1030e8d1 | 2021-11-22T20:33:06.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | gayanin | null | gayanin/bart-mlm-pubmed-15 | 0 | null | transformers | 33,658 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bart-mlm-pubmed-15
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bart-mlm-pubmed-... |
gayanin/bart-mlm-pubmed-35 | 429403835be043886f4d3c8bf2afc4ead6191f96 | 2021-11-22T21:16:10.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | gayanin | null | gayanin/bart-mlm-pubmed-35 | 0 | null | transformers | 33,659 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bart-mlm-pubmed-35
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bart-mlm-pubmed-... |
gayanin/bart-mlm-pubmed-45 | 92b87fe381d769a93361abedaaedf33e4cdfdea5 | 2021-11-22T21:54:14.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | gayanin | null | gayanin/bart-mlm-pubmed-45 | 0 | null | transformers | 33,660 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bart-mlm-pubmed-45
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bart-mlm-pubmed-... |
gayanin/t5-small-finetuned-pubmed | 7d519c1f7334e135a9b7877b02322b6d9dccb294 | 2021-11-04T03:22:48.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | gayanin | null | gayanin/t5-small-finetuned-pubmed | 0 | null | transformers | 33,661 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-finetuned-pubmed
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-... |
gayanin/t5-small-mlm-pubmed-15 | f070f21ba96b8e9012919dc3d6ac42ca61777939 | 2021-11-22T21:10:30.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | gayanin | null | gayanin/t5-small-mlm-pubmed-15 | 0 | null | transformers | 33,662 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-mlm-pubmed-15
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-mlm... |
gayanin/t5-small-mlm-pubmed-35 | 65b895e8e4aee48cc576ca045ff4f6be27029654 | 2021-11-22T22:24:30.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | gayanin | null | gayanin/t5-small-mlm-pubmed-35 | 0 | null | transformers | 33,663 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-mlm-pubmed-35
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-mlm... |
gchhablani/wav2vec2-large-xlsr-or | bdeb0c534df834da1ba679b1dbacef9a1bc6042c | 2021-07-06T05:17:20.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"or",
"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-or | 0 | null | transformers | 33,664 | ---
language: or
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Large 53 Odia by Gunjan Chhablani
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
gchhablani/wav2vec2-large-xlsr-rm-sursilv | 5a7ae7b5e63a5c837829a986345481e225591929 | 2021-07-06T05:27:40.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"rm-sursilv",
"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-rm-sursilv | 0 | null | transformers | 33,665 | ---
language: rm-sursilv
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 Romansh Sursilvan by Gunjan Chhablani
results:
- task:
name: Speech Recognition
type: automatic-speec... |
gfdream/dialogpt-small-familyguy | a39cb4a7dd8581c0e61a64c3d376c88251be86ea | 2021-09-14T23:33:22.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | gfdream | null | gfdream/dialogpt-small-familyguy | 0 | null | transformers | 33,666 | ---
tags:
- conversational
---
# Family Guy (Peter) DialoGPT Model |
ggosline/t5-small-herblabels | 3101a2ebbeb2ea824a7d70c9151074311354bb3d | 2021-12-08T00:16:57.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | ggosline | null | ggosline/t5-small-herblabels | 0 | null | transformers | 33,667 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-herblabels
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. -->
... |
ghadeermobasher/BC5CDR-Chemical_Modified_BioM-ELECTRA-Base-Discriminator | 7b9cd74e3b0ba39ce6adf12024f57805d29b2be3 | 2022-01-22T23:47:01.000Z | [
"pytorch",
"electra",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC5CDR-Chemical_Modified_BioM-ELECTRA-Base-Discriminator | 0 | null | transformers | 33,668 | Entry not found |
ghadeermobasher/CRAFT-Chem_ImbalancedBioM-ELECTRA-Base-Discriminator | c8ed19fd0bef8890cf8f49a6cc19d44fe2a728b5 | 2022-01-23T01:55:20.000Z | [
"pytorch",
"electra",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/CRAFT-Chem_ImbalancedBioM-ELECTRA-Base-Discriminator | 0 | null | transformers | 33,669 | Entry not found |
ghazikhanihamed/TCDB-BERT | 36cf782d1496a5b40aaa4113fcf89af0d615679b | 2022-02-19T16:20:12.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | ghazikhanihamed | null | ghazikhanihamed/TCDB-BERT | 0 | null | transformers | 33,670 | Entry not found |
ghazikhanihamed/TransportersBERT | 84488b26da5828cd5d9a94154e8d3419bc471a01 | 2022-02-18T11:39:32.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | ghazikhanihamed | null | ghazikhanihamed/TransportersBERT | 0 | null | transformers | 33,671 | This repository belongs to TransportersBERT from ActTrans publication.
Taju, Semmy Wellem, Syed Muazzam Ali Shah, and Yu-Yen Ou. “ActTRANS: Functional Classification in Active Transport Proteins Based on Transfer Learning and Contextual Representations.” Computational Biology and Chemistry 93 (August 1, 2021): 107537.... |
ghhostboy/DialoGPT-medium-connorDBH3-21 | 5ba7b65a620fd29bb50f65d8fbef67f26cb2841e | 2021-11-27T04:29:16.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ghhostboy | null | ghhostboy/DialoGPT-medium-connorDBH3-21 | 0 | null | transformers | 33,672 | ---
tags:
- conversational
---
# Connor |
giacomomiolo/electramed_base_scivocab_750 | aac2aa9460031bb894b52caa39d6529de28bdcf8 | 2020-09-30T11:47:57.000Z | [
"pytorch",
"tf",
"electra",
"pretraining",
"transformers"
] | null | false | giacomomiolo | null | giacomomiolo/electramed_base_scivocab_750 | 0 | null | transformers | 33,673 | Entry not found |
gizmo-dev/DialoGPT-small-jake | b3885bdae8312001dcd5da5b40576656d7b7c8d7 | 2021-08-28T10:16:41.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | gizmo-dev | null | gizmo-dev/DialoGPT-small-jake | 0 | null | transformers | 33,674 | ---
tags:
- conversational
---
# Jake Peralta DialoGPT model |
glasses/deit_base_patch16_224 | 8c4d6fb2a2506f481d7273e69d8f6e43dc5efdab | 2021-04-22T18:44:42.000Z | [
"pytorch",
"arxiv:2010.11929",
"transformers"
] | null | false | glasses | null | glasses/deit_base_patch16_224 | 0 | null | transformers | 33,675 | # deit_base_patch16_224
Implementation of DeiT proposed in [Training data-efficient image
transformers & distillation through
attention](https://arxiv.org/pdf/2010.11929.pdf)
An attention based distillation is proposed where a new token is added
to the model, the [dist]{.title-ref} token.
![image](https://githu... |
glasses/deit_base_patch16_384 | a160baa533a2c7b7b87d14f6ea97f4626da8639c | 2021-04-22T18:44:58.000Z | [
"pytorch",
"arxiv:2010.11929",
"transformers"
] | null | false | glasses | null | glasses/deit_base_patch16_384 | 0 | null | transformers | 33,676 | # deit_base_patch16_384
Implementation of DeiT proposed in [Training data-efficient image
transformers & distillation through
attention](https://arxiv.org/pdf/2010.11929.pdf)
An attention based distillation is proposed where a new token is added
to the model, the [dist]{.title-ref} token.
![image](https://githu... |
glasses/deit_small_patch16_224 | a2b6964107f0eb4afaee873969f7fe0f1ee79ea4 | 2021-04-22T18:44:25.000Z | [
"pytorch",
"arxiv:2010.11929",
"transformers"
] | null | false | glasses | null | glasses/deit_small_patch16_224 | 0 | null | transformers | 33,677 | # deit_small_patch16_224
Implementation of DeiT proposed in [Training data-efficient image
transformers & distillation through
attention](https://arxiv.org/pdf/2010.11929.pdf)
An attention based distillation is proposed where a new token is added
to the model, the [dist]{.title-ref} token.
![image](https://gith... |
glasses/eca_resnet50d | 13bd25b5877737d0f1695d112cdd9d4c98893bae | 2021-11-30T20:23:56.000Z | [
"pytorch",
"transformers"
] | null | false | glasses | null | glasses/eca_resnet50d | 0 | null | transformers | 33,678 | Entry not found |
glasses/regnetx_016 | cf66d97a7ad317998015fbb985143e1546832d53 | 2021-11-30T20:26:57.000Z | [
"pytorch",
"arxiv:2003.13678",
"transformers"
] | null | false | glasses | null | glasses/regnetx_016 | 0 | null | transformers | 33,679 | # regnetx_016
Implementation of RegNet proposed in [Designing Network Design
Spaces](https://arxiv.org/abs/2003.13678)
The main idea is to start with a high dimensional search space and
iteratively reduce the search space by empirically apply constrains
based on the best performing models sampled by the current sea... |
glasses/regnety_006 | 0a70fe056933af6649c2a22731b5aaf43012b896 | 2021-12-01T07:46:05.000Z | [
"pytorch",
"arxiv:2003.13678",
"transformers"
] | null | false | glasses | null | glasses/regnety_006 | 0 | null | transformers | 33,680 | # regnety_006
Implementation of RegNet proposed in [Designing Network Design
Spaces](https://arxiv.org/abs/2003.13678)
The main idea is to start with a high dimensional search space and
iteratively reduce the search space by empirically apply constrains
based on the best performing models sampled by the current sea... |
glasses/resnext101_32x8d | 72729573dbbeaf1bd692695ac1d1f4102de02ad1 | 2021-11-30T20:15:04.000Z | [
"pytorch",
"arxiv:1611.05431",
"transformers"
] | null | false | glasses | null | glasses/resnext101_32x8d | 0 | null | transformers | 33,681 | # resnext101_32x8d
Implementation of ResNetXt proposed in [\"Aggregated Residual
Transformation for Deep Neural
Networks\"](https://arxiv.org/pdf/1611.05431.pdf)
Create a default model
``` python
ResNetXt.resnext50_32x4d()
ResNetXt.resnext101_32x8d()
# create a resnetxt18_32x4d
ResNetXt.resnet18(block=ResNetXtB... |
glasses/vgg13_bn | e09a0a7152c3925e6fafbabfaeb3839019a3be0b | 2021-12-01T08:02:05.000Z | [
"pytorch",
"transformers"
] | null | false | glasses | null | glasses/vgg13_bn | 0 | null | transformers | 33,682 | # vgg13_bn
Implementation of VGG proposed in [Very Deep Convolutional Networks For
Large-Scale Image Recognition](https://arxiv.org/pdf/1409.1556.pdf)
``` python
VGG.vgg11()
VGG.vgg13()
VGG.vgg16()
VGG.vgg19()
VGG.vgg11_bn()
VGG.vgg13_bn()
VGG.vgg16_bn()
VGG.vgg19_bn()
```
Please be aware that the [bn]{.ti... |
glasses/vit_base_patch16_384 | eed350bba31b52e44b7d19bc64d546ec824a823a | 2021-12-01T08:26:46.000Z | [
"pytorch",
"arxiv:2010.11929",
"transformers"
] | null | false | glasses | null | glasses/vit_base_patch16_384 | 0 | null | transformers | 33,683 | # vit_base_patch16_384
Implementation of Vision Transformer (ViT) proposed in [An Image Is
Worth 16x16 Words: Transformers For Image Recognition At
Scale](https://arxiv.org/pdf/2010.11929.pdf)
The following image from the authors shows the architecture.
![image](https://github.com/FrancescoSaverioZuppichini/glas... |
glasses/vit_large_patch16_224 | a975743fb7b441be565d7532b9fd2fda8635e4bd | 2021-04-22T18:42:35.000Z | [
"pytorch",
"arxiv:2010.11929",
"transformers"
] | null | false | glasses | null | glasses/vit_large_patch16_224 | 0 | null | transformers | 33,684 | # vit_large_patch16_224
Implementation of Vision Transformer (ViT) proposed in [An Image Is
Worth 16x16 Words: Transformers For Image Recognition At
Scale](https://arxiv.org/pdf/2010.11929.pdf)
The following image from the authors shows the architecture.
![image](https://github.com/FrancescoSaverioZuppichini/gla... |
glasses/vit_large_patch16_384 | 193c63a7c3aeff06b8a47495faad33a83ad1e364 | 2021-04-22T18:43:25.000Z | [
"pytorch",
"arxiv:2010.11929",
"transformers"
] | null | false | glasses | null | glasses/vit_large_patch16_384 | 0 | null | transformers | 33,685 | # vit_large_patch16_384
Implementation of Vision Transformer (ViT) proposed in [An Image Is
Worth 16x16 Words: Transformers For Image Recognition At
Scale](https://arxiv.org/pdf/2010.11929.pdf)
The following image from the authors shows the architecture.
![image](https://github.com/FrancescoSaverioZuppichini/gla... |
glob-asr/test-asr-sp-model | 06a12ac26c85f73aaf1e2e8e93ef0ee25604aed5 | 2022-01-28T20:46:59.000Z | [
"pytorch",
"wav2vec2",
"feature-extraction",
"transformers"
] | feature-extraction | false | glob-asr | null | glob-asr/test-asr-sp-model | 0 | null | transformers | 33,686 | Entry not found |
gngpostalsrvc/BERiTmodel2 | 4b0d0418776894a2483ba5b7534322a10b3da95b | 2021-12-22T17:25:25.000Z | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | fill-mask | false | gngpostalsrvc | null | gngpostalsrvc/BERiTmodel2 | 0 | null | transformers | 33,687 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: BERiTmodel2
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. -->
# BERiTmodel2
This model is a f... |
gokulkarthik/distilbert-base-uncased-finetuned-squad | 8de82646b339fc7f3a67bc032ff0c1467e145dc0 | 2021-09-29T15:13:52.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"dataset:squad",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | gokulkarthik | null | gokulkarthik/distilbert-base-uncased-finetuned-squad | 0 | null | transformers | 33,688 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
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 remov... |
goodjw/klue-bert-mlm | 451afde04a32165ed465df79fdbed0f5c75473c9 | 2021-10-02T05:18:01.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | goodjw | null | goodjw/klue-bert-mlm | 0 | 1 | transformers | 33,689 | Entry not found |
goodjw/klue-roberta-large-tapt | 4311c1c3cd555818ec2b84a4a30fe3ec7cb3ca45 | 2021-10-06T06:22:40.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | goodjw | null | goodjw/klue-roberta-large-tapt | 0 | null | transformers | 33,690 | Entry not found |
goodjw/klue-roberta-mlm | af64935da25fab9997064cdd9b4f18e9baa60400 | 2021-10-05T04:17:02.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | goodjw | null | goodjw/klue-roberta-mlm | 0 | 1 | transformers | 33,691 | Entry not found |
goodjw/koelectra-mlm | 1668a75be7d81a60f132293f5d1764be51cdd9f6 | 2021-10-06T01:17:58.000Z | [
"pytorch",
"electra",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | goodjw | null | goodjw/koelectra-mlm | 0 | null | transformers | 33,692 | Entry not found |
google/multiberts-seed_0-step_120k | 0cf4a460cb80f7054f426a34f1e430a9de19a9cc | 2021-11-05T23:47:25.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_0",
"multiberts-seed_0-step_120k",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_0-step_120k | 0 | null | transformers | 33,693 | ---
language: en
tags:
- multiberts
- multiberts-seed_0
- multiberts-seed_0-step_120k
license: apache-2.0
---
# MultiBERTs, Intermediate Checkpoint - Seed 0, Step 120k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained w... |
google/multiberts-seed_0-step_140k | e6f8f170bf6295091ff2cfce1723b3b3329b9fec | 2021-11-05T23:49:02.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_0",
"multiberts-seed_0-step_140k",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_0-step_140k | 0 | null | transformers | 33,694 | ---
language: en
tags:
- multiberts
- multiberts-seed_0
- multiberts-seed_0-step_140k
license: apache-2.0
---
# MultiBERTs, Intermediate Checkpoint - Seed 0, Step 140k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained w... |
google/multiberts-seed_0-step_1500k | 1aac894fd46ed128076db103a331475420a04767 | 2021-11-06T00:16:49.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_0",
"multiberts-seed_0-step_1500k",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_0-step_1500k | 0 | null | transformers | 33,695 | ---
language: en
tags:
- multiberts
- multiberts-seed_0
- multiberts-seed_0-step_1500k
license: apache-2.0
---
# MultiBERTs, Intermediate Checkpoint - Seed 0, Step 1500k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained... |
google/multiberts-seed_0-step_300k | ba194e26ef19c2ac7a22c2c1142ed8c2b2f271c5 | 2021-11-05T23:56:05.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_0",
"multiberts-seed_0-step_300k",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_0-step_300k | 0 | null | transformers | 33,696 | ---
language: en
tags:
- multiberts
- multiberts-seed_0
- multiberts-seed_0-step_300k
license: apache-2.0
---
# MultiBERTs, Intermediate Checkpoint - Seed 0, Step 300k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained w... |
google/multiberts-seed_0-step_400k | 5e9c41a7458165ad3230c44bb53efdfc79796c29 | 2021-11-05T23:57:51.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_0",
"multiberts-seed_0-step_400k",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_0-step_400k | 0 | null | transformers | 33,697 | ---
language: en
tags:
- multiberts
- multiberts-seed_0
- multiberts-seed_0-step_400k
license: apache-2.0
---
# MultiBERTs, Intermediate Checkpoint - Seed 0, Step 400k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained w... |
google/multiberts-seed_1-step_1100k | 4c6ea4453f497729d2308ff565d41dd64e2276c2 | 2021-11-06T01:05:05.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_1",
"multiberts-seed_1-step_1100k",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_1-step_1100k | 0 | null | transformers | 33,698 | ---
language: en
tags:
- multiberts
- multiberts-seed_1
- multiberts-seed_1-step_1100k
license: apache-2.0
---
# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 1100k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained... |
google/multiberts-seed_1-step_120k | 7a41b87e6d9246dcd586b59f83cd151f06552b77 | 2021-11-06T00:43:27.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_1",
"multiberts-seed_1-step_120k",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_1-step_120k | 0 | null | transformers | 33,699 | ---
language: en
tags:
- multiberts
- multiberts-seed_1
- multiberts-seed_1-step_120k
license: apache-2.0
---
# MultiBERTs, Intermediate Checkpoint - Seed 1, Step 120k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained w... |
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