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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
facebook/convnext-large-384 | 55a95313fa52934fa7b4d8e646aa0ac574eda4ef | 2022-02-26T12:16:55.000Z | [
"pytorch",
"tf",
"convnext",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2201.03545",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/convnext-large-384 | 85 | null | transformers | 4,900 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https... |
facebook/wav2vec2-xls-r-300m-en-to-15 | eca5ea600a8570ea1744fe5bd13f8b1ce505a656 | 2022-05-26T22:27:20.000Z | [
"pytorch",
"speech-encoder-decoder",
"automatic-speech-recognition",
"multilingual",
"en",
"de",
"tr",
"fa",
"sv",
"mn",
"zh",
"cy",
"ca",
"sl",
"et",
"id",
"ar",
"ta",
"lv",
"ja",
"dataset:common_voice",
"dataset:multilingual_librispeech",
"dataset:covost2",
"arxiv:211... | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-xls-r-300m-en-to-15 | 85 | null | transformers | 4,901 | ---
language:
- multilingual
- en
- de
- tr
- fa
- sv
- mn
- zh
- cy
- ca
- sl
- et
- id
- ar
- ta
- lv
- ja
datasets:
- common_voice
- multilingual_librispeech
- covost2
tags:
- speech
- xls_r
- xls_r_translation
- automatic-speech-recognition
pipeline_tag: automatic-speech-recognition
license: apache-2.0
widget:
- e... |
hfl/chinese-electra-small-discriminator | f59e9653eb2382d76ca1a45b782897158d828f26 | 2021-03-03T01:39:00.000Z | [
"pytorch",
"tf",
"electra",
"zh",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0"
] | null | false | hfl | null | hfl/chinese-electra-small-discriminator | 85 | 1 | transformers | 4,902 | ---
language:
- zh
license: "apache-2.0"
---
**Please use `ElectraForPreTraining` for `discriminator` and `ElectraForMaskedLM` for `generator` if you are re-training these models.**
## Chinese ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size ... |
michaelbenayoun/vit-base-beans | b724a7366b1467f6f5e53b978b44c4c08d6c23cc | 2021-12-17T09:17:23.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"dataset:cifar10",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | michaelbenayoun | null | michaelbenayoun/vit-base-beans | 85 | null | transformers | 4,903 | ---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- cifar10
metrics:
- accuracy
model-index:
- name: vit-base-beans
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: cifar10
type: cifar10
args: plain_text
... |
mrm8488/bert2bert_shared-spanish-finetuned-muchocine-review-summarization | 266f7ece730f283e5f979c18056f53fc4896a31f | 2021-05-07T09:26:36.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"es",
"transformers",
"summarization",
"films",
"cinema",
"autotrain_compatible"
] | summarization | false | mrm8488 | null | mrm8488/bert2bert_shared-spanish-finetuned-muchocine-review-summarization | 85 | null | transformers | 4,904 | ---
tags:
- summarization
- films
- cinema
language: es
widget:
- text: "Es la película que con más ansia he esperado, dado el precedente de las dos anteriores entregas, esta debía ser la joya de la corona, el mejor film jamás realizado… Pero cuando salí del cine estaba decepcionado, me leí el libro antes de ver la pe... |
nates-test-org/convit_base | ec61081b76678a0c3c53d4d6bd64305598a6da09 | 2021-10-29T04:40:37.000Z | [
"pytorch",
"timm",
"image-classification"
] | image-classification | false | nates-test-org | null | nates-test-org/convit_base | 85 | null | timm | 4,905 | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for convit_base |
speechbrain/urbansound8k_ecapa | ac8b73ec8c5fd158447654a33101fe236e048bd9 | 2022-05-30T14:34:29.000Z | [
"en",
"dataset:Urbansound8k",
"arxiv:2106.04624",
"speechbrain",
"embeddings",
"Sound",
"Keywords",
"Keyword Spotting",
"pytorch",
"ECAPA-TDNN",
"TDNN",
"Command Recognition",
"audio-classification",
"license:apache-2.0"
] | audio-classification | false | speechbrain | null | speechbrain/urbansound8k_ecapa | 85 | 3 | speechbrain | 4,906 | ---
language: "en"
thumbnail:
tags:
- speechbrain
- embeddings
- Sound
- Keywords
- Keyword Spotting
- pytorch
- ECAPA-TDNN
- TDNN
- Command Recognition
- audio-classification
license: "apache-2.0"
datasets:
- Urbansound8k
metrics:
- Accuracy
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=s... |
uer/t5-v1_1-small-chinese-cluecorpussmall | 4695f4326f388432eed807b081822a18795ec17d | 2022-07-15T08:22:12.000Z | [
"pytorch",
"tf",
"jax",
"mt5",
"text2text-generation",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | uer | null | uer/t5-v1_1-small-chinese-cluecorpussmall | 85 | null | transformers | 4,907 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "作为电子extra0的平台，京东绝对是领先者。如今的刘强extra1已经是身价过extra2的老板。"
---
# Chinese T5 Version 1.1
## Model description
This is the set of Chinese T5 Version 1.1 models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https:/... |
wietsedv/wav2vec2-large-xlsr-53-frisian | 8c02c12454880a55cb031de9744245649fd0e70f | 2021-03-28T20:09:35.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fy-NL",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | wietsedv | null | wietsedv/wav2vec2-large-xlsr-53-frisian | 85 | null | transformers | 4,908 | ---
language: fy-NL
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Frisian XLSR Wav2Vec2 Large 53 by Wietse de Vries
results:
- task:
name: Speech Recognition
type: automatic-speech-recogniti... |
yuvraj/summarizer-cnndm | 4dfc2c9a7a656985c0b7415509cfdd26550e8306 | 2020-12-11T22:04:58.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | yuvraj | null | yuvraj/summarizer-cnndm | 85 | null | transformers | 4,909 | ---
language: "en"
tags:
- summarization
---
# Summarization
## Model description
BartForConditionalGeneration model fine tuned for summarization on 10000 samples from the cnn-dailymail dataset
## How to use
PyTorch model available
```python
from transformers import AutoTokenizer, AutoModelWithLMHead, pipel... |
zhiheng-huang/bert-base-uncased-embedding-relative-key-query | a3126b4d74e3edf3eea4280d186ac7ad4dbc4753 | 2021-05-20T09:45:59.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | zhiheng-huang | null | zhiheng-huang/bert-base-uncased-embedding-relative-key-query | 85 | null | transformers | 4,910 | Entry not found |
kevinjesse/graphcodebert-MT4TS | ee7bbf8909df6ab4b82e3229dfff0b5b4c9cc8c0 | 2022-03-09T11:39:30.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | kevinjesse | null | kevinjesse/graphcodebert-MT4TS | 85 | null | transformers | 4,911 | Entry not found |
hafidber/rare-puppers | aba4ab1fac86f7f7bb5958dd7e8c12ce14ec051b | 2022-04-06T17:53:06.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | hafidber | null | hafidber/rare-puppers | 85 | null | transformers | 4,912 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9552238583564758
---
# rare-puppers
Autoge... |
malteos/gpt2-wechsel-german-ds-meg | 6961d2febd4a803e925a3acc7034548f32e6bc5c | 2022-05-05T19:41:22.000Z | [
"pytorch",
"gpt2",
"text-generation",
"de",
"transformers",
"license:mit"
] | text-generation | false | malteos | null | malteos/gpt2-wechsel-german-ds-meg | 85 | null | transformers | 4,913 | ---
license: mit
language: de
widget:
- text: "In einer schockierenden Entdeckung fanden Wissenschaftler eine Herde Einhörner, die in einem abgelegenen, zuvor unerforschten Tal in den Anden lebten."
---
# Replication of [gpt2-wechsel-german](https://huggingface.co/benjamin/gpt2-wechsel-german)
- trained with [BigScie... |
ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT | 8ff6b1072af538faea974122ed66e9870d9c1ec2 | 2022-06-14T16:29:31.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | ajtamayoh | null | ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT | 85 | null | transformers | 4,914 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NER_EHR_Spanish_model_Mulitlingual_BERT
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread... |
malmarjeh/mbert2mbert-arabic-text-summarization | d575c9342bd733da408d31286672ec2fbe568b63 | 2022-06-29T12:54:31.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"ar",
"transformers",
"Multilingual BERT",
"BERT2BERT",
"MSA",
"Arabic Text Summarization",
"Arabic News Title Generation",
"Arabic Paraphrasing",
"autotrain_compatible"
] | text2text-generation | false | malmarjeh | null | malmarjeh/mbert2mbert-arabic-text-summarization | 85 | null | transformers | 4,915 | ---
language:
- ar
tags:
- Multilingual BERT
- BERT2BERT
- MSA
- Arabic Text Summarization
- Arabic News Title Generation
- Arabic Paraphrasing
---
# An Arabic abstractive text summarization model
A BERT2BERT-based model whose parameters are initialized with mBERT weights and which has been fine-tuned o... |
gustavhartz/roberta-base-cuad-finetuned | b801aecb08c8e28c07b03e162226d93e804b6661 | 2022-06-27T11:58:31.000Z | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | gustavhartz | null | gustavhartz/roberta-base-cuad-finetuned | 85 | null | transformers | 4,916 | # Finetuned legal contract review QA model based 👩⚖️ 📑
Best model presented in the master thesis [*Exploring CUAD using RoBERTa span-selection QA models for legal contract review*](https://github.com/gustavhartz/transformers-legal-tasks) for QA on the Contract Understanding Atticus Dataset. Full training logic and ... |
alistairmcleay/UBAR-distilgpt2 | f5d4fa573db863e37138ea73cb37e61a294850a9 | 2022-06-26T14:10:29.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"license:wtfpl"
] | text-generation | false | alistairmcleay | null | alistairmcleay/UBAR-distilgpt2 | 85 | null | transformers | 4,917 | ---
license: wtfpl
---
|
ebelenwaf/canbert | f1bcf409d524839b6ab581dcc93f9635e5311e8e | 2022-07-17T03:39:02.000Z | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | ebelenwaf | null | ebelenwaf/canbert | 85 | null | transformers | 4,918 | ---
tags:
- generated_from_trainer
model-index:
- name: canbert
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. -->
# canbert
This model is a fine-tuned version of ... |
tinkoff-ai/ruDialoGPT-small | aaf0936bedf44fcc834ee1ae91372af02f69f280 | 2022-07-19T20:27:35.000Z | [
"pytorch",
"gpt2",
"ru",
"arxiv:2001.09977",
"transformers",
"conversational",
"license:mit",
"text-generation"
] | text-generation | false | tinkoff-ai | null | tinkoff-ai/ruDialoGPT-small | 85 | null | transformers | 4,919 | ---
license: mit
pipeline_tag: text-generation
widget:
- text: "@@ПЕРВЫЙ@@ привет @@ВТОРОЙ@@ привет @@ПЕРВЫЙ@@ как дела? @@ВТОРОЙ@@"
example_title: "how r u"
- text: "@@ПЕРВЫЙ@@ что ты делал на выходных? @@ВТОРОЙ@@"
example_title: "wyd"
language:
- ru
tags:
- conversational
---
This generation model is based on [sb... |
nvidia/stt_ca_conformer_transducer_large | b07d20c46f0610ba8051db55674fcc36d438b7d7 | 2022-07-22T18:34:11.000Z | [
"nemo",
"ca",
"dataset:mozilla-foundation/common_voice_9_0",
"arxiv:2005.08100",
"automatic-speech-recognition",
"speech",
"audio",
"Transducer",
"Conformer",
"Transformer",
"pytorch",
"NeMo",
"hf-asr-leaderboard",
"license:cc-by-4.0",
"model-index"
] | automatic-speech-recognition | false | nvidia | null | nvidia/stt_ca_conformer_transducer_large | 85 | 1 | nemo | 4,920 | ---
language:
- ca
library_name: nemo
datasets:
- mozilla-foundation/common_voice_9_0
thumbnail: null
tags:
- automatic-speech-recognition
- speech
- audio
- Transducer
- Conformer
- Transformer
- pytorch
- NeMo
- hf-asr-leaderboard
license: cc-by-4.0
model-index:
- name: stt_ca_conformer_transducer_large
results:
... |
Akashpb13/Swahili_xlsr | 8aa8e010d6a3f1f049fa8fefd8ecc4de57ef00fe | 2022-03-23T18:28:25.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sw",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Akashpb13 | null | Akashpb13/Swahili_xlsr | 84 | null | transformers | 4,921 | ---
language:
- sw
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- sw
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: Akashpb13/Swahili_xlsr
results:
- task:
... |
Frodnar/bee-likes | 58dd1beead6c58c97840cae6cbd6c1ee298056f0 | 2021-07-02T14:47:21.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | Frodnar | null | Frodnar/bee-likes | 84 | null | transformers | 4,922 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: bee-likes
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8333333134651184
---
# bee-likes
Autogenerate... |
HScomcom/gpt2-MyLittlePony | 30475d509fbf395c2a120673a3886f47bc3e4731 | 2021-05-21T10:09:36.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | HScomcom | null | HScomcom/gpt2-MyLittlePony | 84 | 1 | transformers | 4,923 | The model that generates the My little pony script
Fine tuning data: [Kaggle](https://www.kaggle.com/liury123/my-little-pony-transcript?select=clean_dialog.csv)
API page: [Ainize](https://ainize.ai/fpem123/GPT2-MyLittlePony)
Demo page: [End point](https://master-gpt2-my-little-pony-fpem123.endpoint.ainize.ai/)
### ... |
Helsinki-NLP/opus-mt-ja-nl | c2caa48f4d8dc2123fbab467998cd32fe4d79a17 | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"nl",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-nl | 84 | null | transformers | 4,924 | ---
language:
- ja
- nl
tags:
- translation
license: apache-2.0
---
### jpn-nld
* source group: Japanese
* target group: Dutch
* OPUS readme: [jpn-nld](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/jpn-nld/README.md)
* model: transformer-align
* source language(s): jpn jpn_Hani jpn_Hira... |
Helsinki-NLP/opus-mt-ko-ru | 2050b5c2ba3981c9b135ff58febaca447efc75ad | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ko",
"ru",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ko-ru | 84 | null | transformers | 4,925 | ---
language:
- ko
- ru
tags:
- translation
license: apache-2.0
---
### kor-rus
* source group: Korean
* target group: Russian
* OPUS readme: [kor-rus](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/kor-rus/README.md)
* model: transformer-align
* source language(s): kor_Hang kor_Latn
* t... |
Helsinki-NLP/opus-mt-swc-fr | 831ee59763b34c0bf2ecf27bcf966e74f16b2363 | 2021-09-11T10:47:54.000Z | [
"pytorch",
"marian",
"text2text-generation",
"swc",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-swc-fr | 84 | null | transformers | 4,926 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-swc-fr
* source languages: swc
* target languages: fr
* OPUS readme: [swc-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/swc-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
JuliusAlphonso/distilbert-plutchik | 034821c7b7614e228473d28b35ea937d5e1341e6 | 2021-06-19T22:06:23.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | JuliusAlphonso | null | JuliusAlphonso/distilbert-plutchik | 84 | 1 | transformers | 4,927 | Labels are based on Plutchik's model of emotions and may be combined:
 |
KoichiYasuoka/bert-base-japanese-upos | e9077f5b327b42da14e3c5d60f529331a68f9eed | 2022-05-23T21:50:57.000Z | [
"pytorch",
"bert",
"token-classification",
"ja",
"dataset:universal_dependencies",
"transformers",
"japanese",
"pos",
"wikipedia",
"dependency-parsing",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/bert-base-japanese-upos | 84 | 1 | transformers | 4,928 | ---
language:
- "ja"
tags:
- "japanese"
- "token-classification"
- "pos"
- "wikipedia"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
widget:
- text: "国境の長いトンネルを抜けると雪国であった。"
---
# bert-base-japanese-upos
## Model Description
This is a BERT mod... |
arbml/wav2vec2-large-xlsr-dialect-classification | 7d2493de4078502088aebc858be597c98d2cb31d | 2021-07-05T18:15:15.000Z | [
"pytorch",
"jax",
"wav2vec2",
"transformers"
] | null | false | arbml | null | arbml/wav2vec2-large-xlsr-dialect-classification | 84 | null | transformers | 4,929 | Entry not found |
andrejmiscic/simcls-scorer-cnndm | 87f46dbe5b7337432287c0460b614ee0c8ec21c3 | 2021-10-16T20:39:39.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"en",
"dataset:cnn_dailymail",
"arxiv:2106.01890",
"arxiv:1602.06023",
"transformers",
"simcls"
] | feature-extraction | false | andrejmiscic | null | andrejmiscic/simcls-scorer-cnndm | 84 | null | transformers | 4,930 | ---
language:
- en
tags:
- simcls
datasets:
- cnn_dailymail
---
# SimCLS
SimCLS is a framework for abstractive summarization presented in [SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization](https://arxiv.org/abs/2106.01890).
It is a two-stage approach consisting of a *generator* and ... |
bloomberg/KBIR | 482e240f241d6a78157e5592e77d20e7536d4a81 | 2022-07-27T22:11:56.000Z | [
"pytorch",
"roberta",
"arxiv:2112.08547",
"transformers",
"license:apache-2.0"
] | null | false | bloomberg | null | bloomberg/KBIR | 84 | 1 | transformers | 4,931 | ---
license: apache-2.0
---
# Keyphrase Boundary Infilling with Replacement (KBIR)
The KBIR model as described in Learning Rich Representations of Keyphrases from Text (https://arxiv.org/pdf/2112.08547.pdf) builds on top of the RoBERTa architecture by adding an Infilling head and a Replacement Classification head that ... |
dbernsohn/t5_wikisql_SQL2en | 0807b341e3b442a8564a351b31460df88800d71b | 2021-01-18T14:24:14.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:wikisql",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | dbernsohn | null | dbernsohn/t5_wikisql_SQL2en | 84 | null | transformers | 4,932 | # t5_wikisql_SQL2en
---
language: en
datasets:
- wikisql
---
This is a [t5-small](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) fine-tuned version on the [wikisql dataset](https://huggingface.co/datasets/wikisql) for **SQL** to **English** **translation** text2text mission.
To load the m... |
inywer/DialoGPT-medium-leirbag | 27ba149d0e4dbfd239716323d31c66ad9d4b7229 | 2021-10-06T02:28:28.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | inywer | null | inywer/DialoGPT-medium-leirbag | 84 | null | transformers | 4,933 | ---
tags:
- conversational
---
# leirbag DialoGPT Model |
ismgar01/vit-base-cats-vs-dogs | c1701cbf400293e32966a1f93b39011e095bb198 | 2021-11-08T09:10:58.000Z | [
"pytorch",
"vit",
"image-classification",
"dataset:cats_vs_dogs",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | ismgar01 | null | ismgar01/vit-base-cats-vs-dogs | 84 | null | transformers | 4,934 | ---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- cats_vs_dogs
metrics:
- accuracy
model-index:
- name: vit-base-cats-vs-dogs
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: cats_vs_dogs
type: cats_vs_dogs
... |
maxpe/bertin-roberta-base-spanish_semeval18_emodetection | 9acb474fee50b951bc0c18c439b9c33abf4f6565 | 2021-10-27T15:21:12.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | maxpe | null | maxpe/bertin-roberta-base-spanish_semeval18_emodetection | 84 | null | transformers | 4,935 | # BERTIN-roBERTa-base-Spanish_SemEval18_Emodetection
This is a BERTIN-roBERTa-base-Spanish model trained on ~3500 tweets in Spanish annotated for 11 emotion categories in [SemEval-2018 Task 1: Affect in Tweets: SubTask 5: Emotion Classification](https://competitions.codalab.org/competitions/17751).
Run the classifie... |
nateraw/pasta-pizza-ravioli | 077bc96649cc6b8a35bc1471d2f82dc791cd8abe | 2021-06-30T07:10:53.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | nateraw | null | nateraw/pasta-pizza-ravioli | 84 | null | transformers | 4,936 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: pasta-pizza-ravioli
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9375
---
# pasta-pizza-ravioli
Auto... |
pierreguillou/ner-bert-base-cased-pt-lenerbr | 4ca0a39767b49788a93b59b632b19f614d12e26c | 2021-12-29T19:32:39.000Z | [
"pytorch",
"bert",
"token-classification",
"pt",
"dataset:lener_br",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | pierreguillou | null | pierreguillou/ner-bert-base-cased-pt-lenerbr | 84 | null | transformers | 4,937 | ---
language:
- pt
tags:
- generated_from_trainer
datasets:
- lener_br
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: checkpoints
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: lener_br
type: lener_br
metrics:
- name: F1... |
prajjwal1/albert-base-v1-mnli | 293306660f028a76fd36eb0991565b7843bffa8a | 2021-10-05T17:54:14.000Z | [
"pytorch",
"albert",
"text-classification",
"arxiv:2110.01518",
"transformers"
] | text-classification | false | prajjwal1 | null | prajjwal1/albert-base-v1-mnli | 84 | null | transformers | 4,938 | If you use the model, please consider citing this paper
```
@misc{bhargava2021generalization,
title={Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics},
author={Prajjwal Bhargava and Aleksandr Drozd and Anna Rogers},
year={2021},
eprint={2110.01518},
archivePrefix={arXiv},
... |
pucpr/clinicalnerpt-pharmacologic | e74bbc595ad467d1b3e9658db6f3fd87092900df | 2021-10-13T09:33:40.000Z | [
"pytorch",
"bert",
"token-classification",
"pt",
"dataset:SemClinBr",
"transformers",
"autotrain_compatible"
] | token-classification | false | pucpr | null | pucpr/clinicalnerpt-pharmacologic | 84 | 4 | transformers | 4,939 | ---
language: "pt"
widget:
- text: "COMO ESQUEMA DE MEDICAÇÃO PARA ICC PRESCRITO NO ALTA, RECEBE FUROSEMIDA 40 BID, ISOSSORBIDA 40 TID, DIGOXINA 0,25 /D, CAPTOPRIL 50 TID E ESPIRONOLACTONA 25 /D."
- text: "ESTAVA EM USO DE FUROSEMIDA 40 BID, DIGOXINA 0,25 /D, SINVASTATINA 40 /NOITE, CAPTOPRIL 50 TID, ISOSSORBIDA 20 TI... |
osanseviero/llama-horse-zebra | f133fc1416b4aa73a8ef5bb5869a0dc22f145a1d | 2022-05-12T18:58:48.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"llama-leaderboard",
"model-index"
] | image-classification | false | osanseviero | null | osanseviero/llama-horse-zebra | 84 | null | transformers | 4,940 | ---
tags:
- image-classification
- pytorch
- huggingpics
- llama-leaderboard
inference: false
metrics:
- accuracy
model-index:
- name: llama-horse-zebras
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 1.0... |
ybelkada/japanese-roberta-question-answering | 4306006321c17a1a8d040201db2cd1e4de61e54e | 2022-04-08T11:38:39.000Z | [
"pytorch",
"roberta",
"question-answering",
"ja",
"dataset:SkelterLabsInc/JaQuAD",
"transformers",
"extractive-qa",
"license:cc-by-sa-3.0",
"autotrain_compatible"
] | null | false | ybelkada | null | ybelkada/japanese-roberta-question-answering | 84 | null | transformers | 4,941 | ---
license: cc-by-sa-3.0
language: ja
tags:
- question-answering
- extractive-qa
pipeline_tag:
- None
datasets:
- SkelterLabsInc/JaQuAD
metrics:
- Exact match
- F1 score
---
# RoBERTa base Japanese - JaQuAD
## Description
A Japanese Question Answering model fine-tuned on [JaQuAD](https://huggingface.co/datasets/Skelte... |
Finnish-NLP/wav2vec2-base-fi-voxpopuli-v2-finetuned | 9dca1cc8c6eede5293bcf45bb78f56d49a959a57 | 2022-05-26T12:42:28.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"fi",
"dataset:mozilla-foundation/common_voice_9_0",
"arxiv:2006.11477",
"transformers",
"finnish",
"generated_from_trainer",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Finnish-NLP | null | Finnish-NLP/wav2vec2-base-fi-voxpopuli-v2-finetuned | 84 | 3 | transformers | 4,942 | ---
license: apache-2.0
language: fi
metrics:
- wer
- cer
tags:
- automatic-speech-recognition
- fi
- finnish
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_9_0
model-index:
- name: wav2vec2-base-fi-voxpopuli-v2-finetuned
results:
- task:
name: Automatic Speech Recog... |
Finnish-NLP/wav2vec2-large-uralic-voxpopuli-v2-finnish | 72cda0634358fb4cb11da6c09cea9fad6f0cf073 | 2022-05-26T12:37:37.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"fi",
"dataset:mozilla-foundation/common_voice_9_0",
"arxiv:2006.11477",
"transformers",
"finnish",
"generated_from_trainer",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Finnish-NLP | null | Finnish-NLP/wav2vec2-large-uralic-voxpopuli-v2-finnish | 84 | null | transformers | 4,943 | ---
license: apache-2.0
language: fi
metrics:
- wer
- cer
tags:
- automatic-speech-recognition
- fi
- finnish
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_9_0
model-index:
- name: wav2vec2-large-uralic-voxpopuli-v2-finnish
results:
- task:
name: Automatic Speech Re... |
lgodwangl/sent_chineses | 04493d425c3208347b9bf368f864d8c9a2deda7f | 2022-07-11T22:04:50.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | lgodwangl | null | lgodwangl/sent_chineses | 84 | null | transformers | 4,944 | Entry not found |
czearing/article-title-generator | 511d2f366414670c9d01631dd6484c2f810f5c3e | 2022-06-28T20:08:16.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | czearing | null | czearing/article-title-generator | 84 | 1 | transformers | 4,945 | ---
license: mit
---
## Article Title Generator
The model is based on the T5 language model and trained using a large collection of Medium articles.
## Usage
Example code:
```python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("czearing/article-title-generator")
model =... |
Jeevesh8/goog_bert_ft_cola-5 | 35852e6ca1901ddbb5307dc9aea597c42c241812 | 2022-06-29T17:31:47.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Jeevesh8 | null | Jeevesh8/goog_bert_ft_cola-5 | 84 | null | transformers | 4,946 | Entry not found |
knkarthick/TOPIC-SUMMARY | dd97e38f6bef8952181b7c5e8d4d514af813c1b6 | 2022-07-11T05:49:54.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | knkarthick | null | knkarthick/TOPIC-SUMMARY | 84 | null | transformers | 4,947 | Entry not found |
AhmedSSoliman/MarianCG-NL-to-Code | 6336d7b6b6b03cbc7a9f9135ee687e660a47a69f | 2022-06-29T15:53:49.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | AhmedSSoliman | null | AhmedSSoliman/MarianCG-NL-to-Code | 83 | null | transformers | 4,948 | ---
widget:
- text: "create array containing the maximum value of respective elements of array `[2, 3, 4]` and array `[1, 5, 2]"
- text: "check if all elements in list `mylist` are identical"
- text: "enable debug mode on flask application `app`"
- text: "getting the length of `my_tuple`"
- text: 'find all files in dir... |
Finnish-NLP/roberta-large-finnish | 4efd90ea2c50928d27bd43a20a19b956852288d4 | 2022-06-13T16:13:07.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"arxiv:1907.11692",
"transformers",
"finnish",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Finnish-NLP | null | Finnish-NLP/roberta-large-finnish | 83 | 1 | transformers | 4,949 | ---
language:
- fi
license: apache-2.0
tags:
- finnish
- roberta
datasets:
- Finnish-NLP/mc4_fi_cleaned
- wikipedia
widget:
- text: "Moikka olen <mask> kielimalli."
---
# RoBERTa large model for Finnish
Pretrained RoBERTa model on Finnish language using a masked language modeling (MLM) objective. RoBERTa was introdu... |
HHousen/household-rooms | c80d9567f40da3d988bb01232ee66bc11c2a941f | 2022-02-12T06:21:05.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | HHousen | null | HHousen/household-rooms | 83 | null | transformers | 4,950 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: household-rooms
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8482142686843872
---
# household-rooms
... |
Helsinki-NLP/opus-mt-ko-de | 23a6fdbbed8020e0c787c25c7aeeb9f435963fe6 | 2021-09-10T13:54:01.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ko",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ko-de | 83 | null | transformers | 4,951 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ko-de
* source languages: ko
* target languages: de
* OPUS readme: [ko-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ko-de/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-ru-es | 717eeb22c5017551f217849d8b5e2cf91398e336 | 2021-09-10T14:02:21.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ru",
"es",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ru-es | 83 | null | transformers | 4,952 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ru-es
* source languages: ru
* target languages: es
* OPUS readme: [ru-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ru-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Muennighoff/SGPT-5.8B-weightedmean-nli-bitfit | 1aea373089cef8598efd159039b525a06e7ebbcc | 2022-06-18T20:14:43.000Z | [
"pytorch",
"gptj",
"feature-extraction",
"arxiv:2202.08904",
"sentence-transformers",
"sentence-similarity"
] | sentence-similarity | false | Muennighoff | null | Muennighoff/SGPT-5.8B-weightedmean-nli-bitfit | 83 | 2 | sentence-transformers | 4,953 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# SGPT-5.8B-weightedmean-nli-bitfit
## Usage
For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt
## Evaluation Results
For eval results, refer to the eval folder or our... |
baykenney/bert-base-gpt2detector-topk40 | 07f08704e25e432c02d081f85a94fb92beed3cb3 | 2021-05-19T12:10:12.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | baykenney | null | baykenney/bert-base-gpt2detector-topk40 | 83 | null | transformers | 4,954 | Entry not found |
colorfulscoop/bert-base-ja | bba3cc734a1a068222249c4634ff4ea06bb07605 | 2021-09-23T13:46:05.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"ja",
"dataset:wikipedia",
"transformers",
"license:cc-by-sa-4.0",
"fill-mask"
] | fill-mask | false | colorfulscoop | null | colorfulscoop/bert-base-ja | 83 | null | transformers | 4,955 | ---
language: ja
datasets: wikipedia
pipeline_tag: fill-mask
widget:
- text: 得意な科目は[MASK]です。
license: cc-by-sa-4.0
---
# BERT base Japanese model
This repository contains a BERT base model trained on Japanese Wikipedia dataset.
## Training data
[Japanese Wikipedia](https://ja.wikipedia.org/wiki/Wikipedia:データベースダウンロ... |
danyaljj/gpt2_question_generation_given_paragraph_answer | ee45d524ee2eb7ac062b15a8ad66f1065bf9ad01 | 2021-06-17T18:27:47.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | danyaljj | null | danyaljj/gpt2_question_generation_given_paragraph_answer | 83 | null | transformers | 4,956 | Sample usage:
```python
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained("danyaljj/gpt2_question_generation_given_paragraph_answer")
input_ids = tokenizer.encode("There are two apples on the counter. A: apples Q:", return_tensors="pt")
outputs = model.generate(input_ids)
print... |
ibombonato/vit-age-classifier | bc39c91226024da05693ce11422eb79d6c538443 | 2022-02-10T22:06:51.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | ibombonato | null | ibombonato/vit-age-classifier | 83 | null | transformers | 4,957 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: vit-age-classifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8364999890327454
---
# vit-age-classif... |
juanfiguera/ice_cream | c16725e9d0943dd5ddbb2230569f8dd5b7f59836 | 2021-09-10T02:59:58.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | juanfiguera | null | juanfiguera/ice_cream | 83 | null | transformers | 4,958 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: ice_cream
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.5166666507720947
---
# ice_cream
Autogenerate... |
kiri-ai/distiluse-base-multilingual-cased-et | 4cc7064dcd075214b9417ad6092e5769c1119570 | 2020-12-11T21:48:24.000Z | [
"pytorch",
"distilbert",
"feature-extraction",
"et",
"transformers"
] | feature-extraction | false | kiri-ai | null | kiri-ai/distiluse-base-multilingual-cased-et | 83 | null | transformers | 4,959 | ---
language: et
---
## Model Description
This model is based off **Sentence-Transformer's** `distiluse-base-multilingual-cased` multilingual model that has been extended to understand sentence embeddings in Estonian.
## Sentence-Transformers
This model can be imported directly via the SentenceTransformers package a... |
manueltonneau/clinicalcovid-bert-base-cased | feaed908d09e54f65f098c04b09b51584626c096 | 2020-06-02T11:52:31.000Z | [
"pytorch",
"transformers"
] | null | false | manueltonneau | null | manueltonneau/clinicalcovid-bert-base-cased | 83 | null | transformers | 4,960 | Entry not found |
mariagrandury/roberta-base-finetuned-sms-spam-detection | ed7a6c34f9a6041c3a0881fea29eb27e0838dd27 | 2022-02-22T11:54:07.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"dataset:sms_spam",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | mariagrandury | null | mariagrandury/roberta-base-finetuned-sms-spam-detection | 83 | 1 | transformers | 4,961 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- sms_spam
metrics:
- accuracy
model-index:
- name: roberta-base-finetuned-sms-spam-detection
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: sms_spam
type: sms_spam
args: plain_text
m... |
mrm8488/t5-base-finetuned-wikiSQL-sql-to-en | 88935a5332548e7660ee2f1a9f9f846ef4020800 | 2020-12-11T21:56:17.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:wikisql",
"arxiv:1910.10683",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/t5-base-finetuned-wikiSQL-sql-to-en | 83 | 1 | transformers | 4,962 | ---
language: en
datasets:
- wikisql
---
# T5-base fine-tuned on WikiSQL for SQL to English translation
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) fine-tuned on [WikiSQL](https://github.com/salesforce/WikiSQL) for **SQL** to **English** **translation** task.
## Details ... |
nates-test-org/convit_tiny | 6627075ee4777ed2a2bac509b900c115ef003e25 | 2021-10-29T04:46:42.000Z | [
"pytorch",
"timm",
"image-classification"
] | image-classification | false | nates-test-org | null | nates-test-org/convit_tiny | 83 | null | timm | 4,963 | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for convit_tiny |
persiannlp/mt5-large-parsinlu-sentiment-analysis | 0a6e33f37de3e8ae666e2eb5a9ca1ed33042e248 | 2021-09-23T16:20:21.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"transformers",
"sentiment",
"sentiment-analysis",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-large-parsinlu-sentiment-analysis | 83 | null | transformers | 4,964 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- sentiment
- sentiment-analysis
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Sentiment Analysis (آنالیز احساسات)
This is a mT5 model for sentiment analys... |
persiannlp/parsbert-base-parsinlu-multiple-choice | a97e11816584b3eea9b17eeaff63dc00ec824a47 | 2021-09-23T16:20:53.000Z | [
"pytorch",
"jax",
"bert",
"multiple-choice",
"fa",
"multilingual",
"dataset:parsinlu",
"transformers",
"parsbert",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"text-classification"
] | text-classification | false | persiannlp | null | persiannlp/parsbert-base-parsinlu-multiple-choice | 83 | null | transformers | 4,965 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- parsbert
- persian
- farsi
pipeline_tag: text-classification
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به ... |
sreeramajay/pollution | 6e4c26a68b8195ef8003d249813d79934b149b94 | 2021-07-03T07:05:10.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | sreeramajay | null | sreeramajay/pollution | 83 | 1 | transformers | 4,966 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: pollution
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.7129629850387573
---
# pollution
Autogenerate... |
thak123/goan-fish-fry | f6aac0b124bd6f6f2e2c57cc4920927d35762bb3 | 2021-07-02T10:46:53.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | thak123 | null | thak123/goan-fish-fry | 83 | null | transformers | 4,967 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: goan-fish-fry
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.4583333432674408
---
# goan-fish-fry
Auto... |
vivekRahul/animal_classifier_huggingface | aed061da9fc2e8c7c0fc54061e80d0688fb91d20 | 2021-07-25T06:02:38.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | vivekRahul | null | vivekRahul/animal_classifier_huggingface | 83 | null | transformers | 4,968 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: animal_classifier_huggingface
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9910714030265808
---
# anim... |
hamedkhaledi/persain-flair-pos | 1b18d8db47f93b5efc969cad8718dcd4a6748108 | 2022-03-27T22:26:53.000Z | [
"pytorch",
"fa",
"dataset:UPC-2017",
"flair",
"token-classification",
"sequence-tagger-model"
] | token-classification | false | hamedkhaledi | null | hamedkhaledi/persain-flair-pos | 83 | 1 | flair | 4,969 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: fa
datasets:
- UPC-2017
widget:
- text: "تمام ایران یک تابستان تنوری را تجربه میکند ."
---
## Persian Part-of-Speech Tagging in Flair
This is the part-of-speech tagging model for Persian that ships with [Flair](https://github.com/flairNLP/flai... |
mojians/E2E-QA-Mining | 7f23cc4e5b8ba5ebb90d79fa2c7ab629708fa69d | 2022-04-10T02:34:53.000Z | [
"pytorch",
"t5",
"text2text-generation",
"dataset:squad",
"transformers",
"question-generation",
"question-answer mining",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | mojians | null | mojians/E2E-QA-Mining | 83 | 1 | transformers | 4,970 | ---
datasets:
- squad
tags:
- question-generation
- question-answer mining
widget:
- text: "context: The English name 'Normans' comes from the French words Normans/Normanz, plural of Normant, modern French normand, which is itself borrowed from Old Low Franconian Nortmann 'Northman' or directly from Old Norse Norðmaðr,... |
jaygala24/finetuned-vit-base-patch16-224-upside-down-detector | 6d3e260801fa016711309ddda6a6a0f73a5c0c10 | 2022-04-02T15:24:57.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers",
"accelerator",
"license:apache-2.0",
"model-index"
] | image-classification | false | jaygala24 | null | jaygala24/finetuned-vit-base-patch16-224-upside-down-detector | 83 | null | transformers | 4,971 | ---
license: apache-2.0
tags:
- accelerator
metrics:
- accuracy
model-index:
- name: finetuned-vit-base-patch16-224-upside-down-detector
results: []
widget:
- src: https://huggingface.co/jaygala24/finetuned-vit-base-patch16-224-upside-down-detector/resolve/main/original.jpg
example_title: original
- src: https://hu... |
yangy50/garbage-classification | 9bfbbceba2d807df5c8c6f1546ffa48086eb28b2 | 2022-04-25T22:55:50.000Z | [
"pytorch",
"vit",
"image-classification",
"arxiv:2010.11929",
"transformers"
] | image-classification | false | yangy50 | null | yangy50/garbage-classification | 83 | null | transformers | 4,972 | # Garbage Classification
## Overview
### Backgroud
Garbage classification refers to the separation of several types of different categories in accordance with the environmental impact of the use of the value of the composition of garbage components and the requirements of existing treatment methods.
The significance... |
naver/splade-cocondenser-selfdistil | 0f718e09b0540c68c15c5c2b50de731b6e89090a | 2022-05-11T08:02:55.000Z | [
"pytorch",
"bert",
"fill-mask",
"en",
"dataset:ms_marco",
"arxiv:2205.04733",
"transformers",
"splade",
"query-expansion",
"document-expansion",
"bag-of-words",
"passage-retrieval",
"knowledge-distillation",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | naver | null | naver/splade-cocondenser-selfdistil | 83 | 5 | transformers | 4,973 | ---
license: cc-by-nc-sa-4.0
language: "en"
tags:
- splade
- query-expansion
- document-expansion
- bag-of-words
- passage-retrieval
- knowledge-distillation
datasets:
- ms_marco
---
## SPLADE CoCondenser SelfDistil
SPLADE model for passage retrieval. For additional details, please visit:
* paper: https://arxiv.org/a... |
nateraw/vit-base-food101 | 977c7a15b0a1d5775c412d99325894474f695b74 | 2022-05-10T03:40:35.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers"
] | image-classification | false | nateraw | null | nateraw/vit-base-food101 | 83 | null | transformers | 4,974 | Entry not found |
YSU/aspram | 1d31728083d761274b65cd8e6d0b520eaea453ba | 2022-05-19T12:24:13.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hy",
"hy-AM",
"hye",
"dataset:mozilla-foundation/common_voice_9_0",
"dataset:google/fleurs",
"dataset:mc4",
"transformers",
"mozilla-foundation/common_voice_9_0",
"google/fleurs",
"license:apache-2.0"
] | automatic-speech-recognition | false | YSU | null | YSU/aspram | 83 | 2 | transformers | 4,975 | ---
language:
- hy
- hy-AM
- hye
license: apache-2.0
tags:
- automatic-speech-recognition
- hy
- mozilla-foundation/common_voice_9_0
- google/fleurs
models:
- facebook/wav2vec2-xls-r-2b
datasets:
- mozilla-foundation/common_voice_9_0
- google/fleurs
- mc4
task_categories:
- automatic-speech-recognition
- speech-process... |
drhyrum/bert-tiny-torch-vuln | 753c3cb70db0705e814b400330028ad5335246d3 | 2022-07-07T19:17:08.000Z | [
"pytorch",
"bert",
"en",
"arxiv:1908.08962",
"arxiv:2110.01518",
"transformers",
"BERT",
"MNLI",
"NLI",
"transformer",
"pre-training",
"license:mit"
] | null | false | drhyrum | null | drhyrum/bert-tiny-torch-vuln | 83 | 1 | transformers | 4,976 | ---
language:
- en
license:
- mit
tags:
- BERT
- MNLI
- NLI
- transformer
- pre-training
---
The following model is a Pytorch pre-trained model obtained from converting Tensorflow checkpoint found in the [official Google BERT repository](https://github.com/google-research/bert).
This is one of the smaller ... |
arminmehrabian/distilgpt2-finetuned-wikitext2-agu | 596eefbc2b8f3f223849e9afff5abe16c5b69cc5 | 2022-07-30T04:08:38.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-generation | false | arminmehrabian | null | arminmehrabian/distilgpt2-finetuned-wikitext2-agu | 83 | 1 | transformers | 4,977 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-finetuned-wikitext2-agu
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. -->
# ... |
nielsr/donut-base | 905659914224a88ac7f934281c333befd3fbd649 | 2022-07-26T09:09:36.000Z | [
"pytorch",
"vision-encoder-decoder",
"transformers"
] | null | false | nielsr | null | nielsr/donut-base | 83 | null | transformers | 4,978 | Entry not found |
ckb/c-deobfuscate-mt | 2afcaa6025db3e1fad3d276ec71949eda6b26483 | 2022-07-29T02:49:31.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | ckb | null | ckb/c-deobfuscate-mt | 83 | null | transformers | 4,979 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: c-deobfuscate-mt
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. -->
# c-deobfuscate-mt
... |
Amrrs/south-indian-foods | 757e34748641041c8c7a88c2235fb3cdab6ceacb | 2021-07-20T18:22:24.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | Amrrs | null | Amrrs/south-indian-foods | 82 | null | transformers | 4,980 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: south-indian-foods
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.875
---
# south-indian-foods
Autogen... |
Davlan/bert-base-multilingual-cased-finetuned-amharic | 90283498970edd0fe6af2f094f5f25d61e525ebd | 2021-06-02T12:37:53.000Z | [
"pytorch",
"bert",
"fill-mask",
"am",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Davlan | null | Davlan/bert-base-multilingual-cased-finetuned-amharic | 82 | null | transformers | 4,981 | Hugging Face's logo
---
language: am
datasets:
---
# bert-base-multilingual-cased-finetuned-amharic
## Model description
**bert-base-multilingual-cased-finetuned-amharic** is a **Amharic BERT** model obtained by replacing mBERT vocabulary by amharic vocabulary because the language was not supported, and fine-tuning **... |
Helsinki-NLP/opus-mt-fr-id | 03aa1793243ef305e007d30388744fb59b95051b | 2021-09-09T21:54:31.000Z | [
"pytorch",
"marian",
"text2text-generation",
"fr",
"id",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-fr-id | 82 | null | transformers | 4,982 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-fr-id
* source languages: fr
* target languages: id
* OPUS readme: [fr-id](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fr-id/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-it-ar | 894b5e96a86f86b7ac1594fc14b247df05e0ee1e | 2020-08-21T14:42:46.000Z | [
"pytorch",
"marian",
"text2text-generation",
"it",
"ar",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-it-ar | 82 | null | transformers | 4,983 | ---
language:
- it
- ar
tags:
- translation
license: apache-2.0
---
### ita-ara
* source group: Italian
* target group: Arabic
* OPUS readme: [ita-ara](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ita-ara/README.md)
* model: transformer
* source language(s): ita
* target language(s): a... |
Helsinki-NLP/opus-mt-ja-ru | 46386a5e83ca1df32e809077547aea08198f9317 | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"ru",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-ru | 82 | null | transformers | 4,984 | ---
language:
- ja
- ru
tags:
- translation
license: apache-2.0
---
### jpn-rus
* source group: Japanese
* target group: Russian
* OPUS readme: [jpn-rus](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/jpn-rus/README.md)
* model: transformer-align
* source language(s): jpn jpn_Bopo jpn_Ha... |
Helsinki-NLP/opus-mt-vi-fr | d2d4e2e848ae77f77103428f6fe797bd5f9904e8 | 2020-08-21T14:42:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"vi",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-vi-fr | 82 | null | transformers | 4,985 | ---
language:
- vi
- fr
tags:
- translation
license: apache-2.0
---
### vie-fra
* source group: Vietnamese
* target group: French
* OPUS readme: [vie-fra](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/vie-fra/README.md)
* model: transformer-align
* source language(s): vie
* target langu... |
LeBenchmark/wav2vec2-FR-3K-large | 84bcdf4e561f53723623cd139dc70462380072ae | 2021-11-26T20:35:33.000Z | [
"pytorch",
"jax",
"wav2vec2",
"feature-extraction",
"fr",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | LeBenchmark | null | LeBenchmark/wav2vec2-FR-3K-large | 82 | null | transformers | 4,986 | ---
language: "fr"
thumbnail:
tags:
- wav2vec2
license: "apache-2.0"
---
# LeBenchmark: wav2vec2 large model trained on 3K hours of French speech
LeBenchmark provides an ensemble of pretrained wav2vec2 models on different French dataset containing spontaneous, read and broadcasted speech. For more information on ... |
Narrativa/mbart-large-50-finetuned-opus-en-pt-translation | 6558673ba6383ba816acf621d9cc6be5751460f6 | 2021-06-21T11:07:11.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"en",
"pt",
"dataset:opus100",
"dataset:opusbook",
"arxiv:2008.00401",
"arxiv:2004.11867",
"transformers",
"translation",
"autotrain_compatible"
] | translation | false | Narrativa | null | Narrativa/mbart-large-50-finetuned-opus-en-pt-translation | 82 | 1 | transformers | 4,987 | ---
language:
- en
- pt
datasets:
- opus100
- opusbook
tags:
- translation
metrics:
- bleu
---
# mBART-large-50 fine-tuned onpus100 and opusbook for English to Portuguese translation.
[mBART-50](https://huggingface.co/facebook/mbart-large-50/) large fine-tuned on [opus100](https://huggingface.co/datasets/viewer/?da... |
Narrativa/mbart-large-50-finetuned-opus-pt-en-translation | 764997c29e8d47c7d23c77fb0339a75a0d2fd722 | 2021-06-21T11:16:19.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"pt",
"en",
"dataset:opus100",
"dataset:opusbook",
"arxiv:2008.00401",
"arxiv:2004.11867",
"transformers",
"translation",
"autotrain_compatible"
] | translation | false | Narrativa | null | Narrativa/mbart-large-50-finetuned-opus-pt-en-translation | 82 | null | transformers | 4,988 | ---
language:
- pt
- en
datasets:
- opus100
- opusbook
tags:
- translation
metrics:
- bleu
---
# mBART-large-50 fine-tuned onpus100 and opusbook for Portuguese to English translation.
[mBART-50](https://huggingface.co/facebook/mbart-large-50/) large fine-tuned on [opus100](https://huggingface.co/datasets/viewer/?da... |
SkelterLabsInc/bert-base-japanese-jaquad | 7bd5402cab37743c5c989e0773e92cf8089a8c5a | 2022-02-04T02:39:25.000Z | [
"pytorch",
"bert",
"question-answering",
"ja",
"dataset:SkelterLabsInc/JaQuAD",
"arxiv:2202.01764",
"transformers",
"extractive-qa",
"license:cc-by-sa-3.0",
"autotrain_compatible"
] | null | false | SkelterLabsInc | null | SkelterLabsInc/bert-base-japanese-jaquad | 82 | 1 | transformers | 4,989 | ---
license: cc-by-sa-3.0
language: ja
tags:
- question-answering
- extractive-qa
pipeline_tag:
- None
datasets:
- SkelterLabsInc/JaQuAD
metrics:
- Exact match
- F1 score
---
# BERT base Japanese - JaQuAD
## Description
A Japanese Question Answering model fine-tuned on [JaQuAD](https://huggingface.co/datasets/Skelte... |
SriramSridhar78/sriram-car-classifier | acd0d25f394630bd42d8588bf95cee633f7fdff3 | 2022-01-26T16:04:18.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | SriramSridhar78 | null | SriramSridhar78/sriram-car-classifier | 82 | 1 | transformers | 4,990 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: sriram-car-classifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8271908164024353
---
# sriram-car-c... |
ajrae/bert-base-uncased-finetuned-mrpc | 561654da12001407e33f5118cc2d980143030e07 | 2022-02-21T21:19:06.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | ajrae | null | ajrae/bert-base-uncased-finetuned-mrpc | 82 | null | transformers | 4,991 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metrics:
- n... |
akhooli/mbart-large-cc25-ar-en | 903e7a58186a74ce3aed12f6d1c891e27ade277a | 2020-12-11T21:32:04.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"ar",
"en",
"transformers",
"translation",
"license:mit",
"autotrain_compatible"
] | translation | false | akhooli | null | akhooli/mbart-large-cc25-ar-en | 82 | 1 | transformers | 4,992 | ---
tags:
- translation
language:
- ar
- en
license: mit
---
### mbart-large-ar-en
This is mbart-large-cc25, finetuned on a subset of the OPUS corpus for ar_en.
Usage: see [example notebook](https://colab.research.google.com/drive/1I6RFOWMaTpPBX7saJYjnSTddW0TD6H1t?usp=sharing)
Note: model has limited training se... |
b25mayank3/shirt_identifier | 2b37de74691a740e005ea610f5decfa610c6d13b | 2021-07-21T20:29:09.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | b25mayank3 | null | b25mayank3/shirt_identifier | 82 | null | transformers | 4,993 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: shirt_identifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.6875
---
# shirt_identifier
Autogenera... |
bayartsogt/mongolian-roberta-base | 9e6b882a3b2e208f1e7741407e4f0e350fa3a3cc | 2021-07-07T00:52:33.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | bayartsogt | null | bayartsogt/mongolian-roberta-base | 82 | null | transformers | 4,994 | Entry not found |
birgermoell/roberta-swedish-scandi | 3c3b9c6fee15853aa9fe9f472190ab82a180927d | 2021-09-23T13:42:48.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"feature-extraction",
"sv",
"dataset:mc4",
"transformers",
"translate",
"license:cc-by-4.0"
] | feature-extraction | false | birgermoell | null | birgermoell/roberta-swedish-scandi | 82 | null | transformers | 4,995 | ---
language: sv
license: cc-by-4.0
tags:
- translate
datasets:
- mc4
widget:
- text: Meningen med livet är <mask>
---
# Svensk Roberta
## Description
Swedish Roberta model trained on the MC4 dataset. The model performance needs to be assessed
## Model series
This model is part of a series of models training on TPU w... |
deepset/covid_bert_base | defac006e33937242fe54122c275fbc86794223f | 2021-05-19T15:31:18.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | deepset | null | deepset/covid_bert_base | 82 | 4 | transformers | 4,996 | Entry not found |
frgfm/rexnet1_5x | af5a939881795422fa97771e8a06b33e19f2dcab | 2022-07-20T00:54:55.000Z | [
"pytorch",
"onnx",
"dataset:frgfm/imagenette",
"arxiv:2007.00992",
"transformers",
"image-classification",
"license:apache-2.0"
] | image-classification | false | frgfm | null | frgfm/rexnet1_5x | 82 | null | transformers | 4,997 | ---
license: apache-2.0
tags:
- image-classification
- pytorch
- onnx
datasets:
- frgfm/imagenette
---
# ReXNet-1.5x model
Pretrained on [ImageNette](https://github.com/fastai/imagenette). The ReXNet architecture was introduced in [this paper](https://arxiv.org/pdf/2007.00992.pdf).
## Model description
The core i... |
google/bert_uncased_L-6_H-256_A-4 | 67ada51801f40684c01ca3f20c97a35fa7a67d36 | 2021-05-19T17:33:36.000Z | [
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/bert_uncased_L-6_H-256_A-4 | 82 | null | transformers | 4,998 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... |
gsarti/opus-tatoeba-eng-pol | e7460fa29a5d6e992cfd8a442c6127d4f1c6dda1 | 2021-10-18T13:48:19.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"pl",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | gsarti | null | gsarti/opus-tatoeba-eng-pol | 82 | null | transformers | 4,999 | ---
language:
- en
- pl
tags:
- translation
license: apache-2.0
---
### OPUS Tatoeba English-Polish
*This model was obtained by running the script [convert_marian_to_pytorch.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/marian/convert_marian_to_pytorch.py) with the flag `-m eng... |
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