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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ScyKindness/Hatsune_Miku | d1b6c8860d16dbb2acd842a1402567c8ea59aeff | 2022-04-19T13:27:18.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"arxiv:1911.00536",
"transformers",
"conversational",
"license:mit"
] | conversational | false | ScyKindness | null | ScyKindness/Hatsune_Miku | 31 | null | transformers | 7,100 | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
tags:
- conversational
license: mit
---
## A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)
DialoGPT is a SOTA large-scale pretrained dialogue response generation model for multiturn conversations.
The [human evaluation... |
shishirAI/wav2vec2-xlsr-nepali | dc4e991478b645ddf7be14bbc2819926adb058cf | 2022-04-18T16:35:18.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | shishirAI | null | shishirAI/wav2vec2-xlsr-nepali | 31 | null | transformers | 7,101 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-nepali
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. -->
# wav2vec2... |
Intel/electra-small-discriminator-mrpc-int8-static | cd77fc803a357eb6d0e96cb232553ebb3cafc546 | 2022-06-10T02:42:51.000Z | [
"pytorch",
"electra",
"text-classification",
"en",
"dataset:glue",
"transformers",
"text-classfication",
"int8",
"Intel® Neural Compressor",
"PostTrainingStatic",
"license:mit",
"model-index"
] | text-classification | false | Intel | null | Intel/electra-small-discriminator-mrpc-int8-static | 31 | null | transformers | 7,102 | ---
language:
- en
license: mit
tags:
- text-classfication
- int8
- Intel® Neural Compressor
- PostTrainingStatic
datasets:
- glue
metrics:
- f1
model-index:
- name: electra-small-discriminator-mrpc-int8-static
results:
- task:
name: Text Classification
type: text-classification
dataset:
name:... |
maximedb/reviews-generator | 5e2d6eb7650eb4bdba82ee8a5c4874ab14dc6847 | 2022-04-25T19:15:12.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"dataset:amazon_reviews_multi",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | maximedb | null | maximedb/reviews-generator | 31 | null | transformers | 7,103 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
model-index:
- name: reviews-generator
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 ... |
anton-l/xtreme_s_xlsr_300m_voxpopuli_en | ee39996874355b2efbd63b2f8b32744de9e310af | 2022-05-03T09:55:15.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:google/xtreme_s",
"transformers",
"voxpopuli",
"google/xtreme_s",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | anton-l | null | anton-l/xtreme_s_xlsr_300m_voxpopuli_en | 31 | null | transformers | 7,104 | ---
language:
- en
license: apache-2.0
tags:
- voxpopuli
- google/xtreme_s
- generated_from_trainer
datasets:
- google/xtreme_s
model-index:
- name: xtreme_s_xlsr_300m_voxpopuli_en
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should... |
avichr/Legal-heBERT_ft | 0f00d4cc4098e5fcb800af91beeb7473c7c5686f | 2022-07-07T07:31:58.000Z | [
"pytorch",
"bert",
"fill-mask",
"arxiv:1911.03090",
"arxiv:2010.02559",
"transformers",
"autotrain_compatible"
] | fill-mask | false | avichr | null | avichr/Legal-heBERT_ft | 31 | 1 | transformers | 7,105 | # Legal-HeBERT
Legal-HeBERT is a BERT model for Hebrew legal and legislative domains. It is intended to improve the legal NLP research and tools development in Hebrew. We release two versions of Legal-HeBERT. The first version is a fine-tuned model of [HeBERT](https://github.com/avichaychriqui/HeBERT) applied on legal ... |
kabelomalapane/En-Tn | 58250ed6164cc2202c45764b846fb916a3f56e52 | 2022-06-02T07:03:01.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"translation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | translation | false | kabelomalapane | null | kabelomalapane/En-Tn | 31 | null | transformers | 7,106 | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: En-Tn
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. -->
#... |
ziq/depression_tweet | 242c1526e6b6c3d2be7314281b511bcf4f7d968e | 2022-06-06T09:09:04.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | ziq | null | ziq/depression_tweet | 31 | null | transformers | 7,107 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: depression_tweet
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. -->
# depre... |
jboomc/rotten_tomatoes_finetuned | 74ee8d0e562bf0992f6a7d98cc75ec977095e2d5 | 2022-06-08T16:16:03.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | jboomc | null | jboomc/rotten_tomatoes_finetuned | 31 | null | transformers | 7,108 | Entry not found |
ml6team/keyphrase-extraction-kbir-kptimes | baceaac4c0e2eba23d6307d3a2dce69fbbdfd2b9 | 2022-06-16T18:22:00.000Z | [
"pytorch",
"roberta",
"token-classification",
"en",
"dataset:midas/kptimes",
"arxiv:2112.08547",
"arxiv:1911.12559",
"transformers",
"keyphrase-extraction",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | ml6team | null | ml6team/keyphrase-extraction-kbir-kptimes | 31 | null | transformers | 7,109 | ---
language: en
license: mit
tags:
- keyphrase-extraction
datasets:
- midas/kptimes
metrics:
- seqeval
widget:
- text: "Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a document.
Thanks to these keyphrases humans can understand the content of a text very quickly ... |
nickmuchi/yolos-base-finetuned-masks | 5b99479dde3098c15b2e09463a046a05e4fe5985 | 2022-06-20T00:01:11.000Z | [
"pytorch",
"yolos",
"object-detection",
"transformers"
] | object-detection | false | nickmuchi | null | nickmuchi/yolos-base-finetuned-masks | 31 | null | transformers | 7,110 | Entry not found |
wiselinjayajos/t5-end2end-questions-generation-squadV2 | f14d9ae2fb2b7a679e97900d7a813f1d3e1a8b07 | 2022-07-06T02:27:13.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | wiselinjayajos | null | wiselinjayajos/t5-end2end-questions-generation-squadV2 | 31 | null | transformers | 7,111 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-end2end-questions-generation-squadV2
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. --... |
oussama/Layoutlm_Form_information_extraction | e9521ba8dda211ce890cb755e77a23a55e111714 | 2022-06-24T08:33:16.000Z | [
"pytorch",
"layoutlm",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | oussama | null | oussama/Layoutlm_Form_information_extraction | 31 | null | transformers | 7,112 | Entry not found |
Matthijs/mobilenet_v2_1.0_224 | ad6885df81ee0cd4a75e867a1dca518f21cfd516 | 2022-06-28T12:51:25.000Z | [
"pytorch",
"coreml",
"mobilenet_v2",
"dataset:imagenet-1k",
"arxiv:1801.04381",
"transformers",
"vision",
"image-classification",
"license:other"
] | image-classification | false | Matthijs | null | Matthijs/mobilenet_v2_1.0_224 | 31 | null | transformers | 7,113 | ---
license: other
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://hu... |
nvidia/stt_fr_conformer_ctc_large | d4e37487087ab8e199eea40aaf0200ac40ab94d5 | 2022-06-30T20:01:15.000Z | [
"nemo",
"fr",
"dataset:multilingual_librispeech",
"dataset:mozilla-foundation/common_voice_7_0",
"dataset:VoxPopuli",
"arxiv:2005.08100",
"automatic-speech-recognition",
"speech",
"audio",
"CTC",
"Conformer",
"Transformer",
"pytorch",
"NeMo",
"hf-asr-leaderboard",
"Riva",
"license:cc... | automatic-speech-recognition | false | nvidia | null | nvidia/stt_fr_conformer_ctc_large | 31 | 2 | nemo | 7,114 | ---
language: fr
library_name: nemo
datasets:
- multilingual_librispeech
- mozilla-foundation/common_voice_7_0
- VoxPopuli
thumbnail: null
tags:
- automatic-speech-recognition
- speech
- audio
- CTC
- Conformer
- Transformer
- pytorch
- NeMo
- hf-asr-leaderboard
- Riva
license: cc-by-4.0
model-index:
- name: stt_fr_con... |
Matthijs/deeplabv3_mobilenet_v2_1.0_513 | c4897d738a13a29458817fc8f8936fb6a7b3ffcc | 2022-06-28T13:39:52.000Z | [
"pytorch",
"coreml",
"mobilenet_v2",
"dataset:pascal-voc",
"arxiv:1801.04381",
"arxiv:1802.02611",
"transformers",
"vision",
"image-segmentation",
"license:other"
] | image-segmentation | false | Matthijs | null | Matthijs/deeplabv3_mobilenet_v2_1.0_513 | 31 | null | transformers | 7,115 | ---
license: other
tags:
- vision
- image-segmentation
datasets:
- pascal-voc
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-2.jpg
example_title: Cat
---
# MobileNetV2 with DeepLabV3+
MobileNet V2 model pre-trained on PASCAL VOC at resolution 513x513. It was introduced in [Mobi... |
emilylearning/cond_ft_none_on_reddit__prcnt_100__test_run_False__roberta-base | 00dfd2e873cc709381e84c99471e685666add3e5 | 2022-07-01T03:07:41.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | emilylearning | null | emilylearning/cond_ft_none_on_reddit__prcnt_100__test_run_False__roberta-base | 31 | null | transformers | 7,116 | Entry not found |
Mimita6654/test | 936f107cd2e99ea098715e748dc4db9d8d95dc17 | 2022-07-02T07:47:08.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | fill-mask | false | Mimita6654 | null | Mimita6654/test | 31 | null | transformers | 7,117 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: test
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# test
This model is a fine-tuned vers... |
Gerwin/legal-bert-dutch-english | 1204ca4dc23788999f63e602214bc0dd4c5e60b7 | 2022-07-21T09:18:09.000Z | [
"pytorch",
"tf",
"bert",
"feature-extraction",
"en",
"nl",
"transformers",
"legal",
"license:apache-2.0"
] | feature-extraction | false | Gerwin | null | Gerwin/legal-bert-dutch-english | 31 | null | transformers | 7,118 | ---
language:
- en
- nl
tags:
- bert
- legal
license: apache-2.0
metrics:
- F1
---
# Legal BERT model applicable for Dutch and English
A BERT model further trained from [mBERT](https://huggingface.co/bert-base-multilingual-uncased) on legal documents. The thesis can be downloaded [here](https://www.ru.nl/publish/pages... |
dingusagar/vit-base-avengers-v1 | 1a077fe19b4a2c013fd360f9f0dba187f7974b7a | 2022-07-10T10:47:03.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"dataset:imagefolder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | dingusagar | null | dingusagar/vit-base-avengers-v1 | 31 | null | transformers | 7,119 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-avengers-v1
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
args: avengers-dataset
... |
nloc2578/new_ques2 | 9ba4f05a4474a41aa47b5403a1a151b003f72b62 | 2022-07-12T09:11:39.000Z | [
"pytorch",
"tensorboard",
"pegasus",
"text2text-generation",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | nloc2578 | null | nloc2578/new_ques2 | 31 | null | transformers | 7,120 | ---
tags:
- generated_from_trainer
model-index:
- name: new_ques2
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. -->
# new_ques2
This model is a fine-tuned version... |
davanstrien/clip-roberta-finetuned | aaf97d71276b9d75118a7e6ef392c73a6019922c | 2022-07-15T16:09:56.000Z | [
"pytorch",
"tensorboard",
"vision-text-dual-encoder",
"feature-extraction",
"dataset:davanstrien/manuscript_noisy_labels_iiif",
"transformers",
"generated_from_trainer",
"model-index"
] | feature-extraction | false | davanstrien | null | davanstrien/clip-roberta-finetuned | 31 | null | transformers | 7,121 | ---
tags:
- generated_from_trainer
datasets:
- davanstrien/manuscript_noisy_labels_iiif
model-index:
- name: clip-roberta-finetuned
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 ... |
Supreeth/DeBERTa-Twitter-Emotion-Classification | 35ad6af4e1d828b0838d95589ac437c55f3f6bc0 | 2022-07-17T16:47:32.000Z | [
"pytorch",
"deberta",
"text-classification",
"transformers",
"license:mit"
] | text-classification | false | Supreeth | null | Supreeth/DeBERTa-Twitter-Emotion-Classification | 31 | null | transformers | 7,122 | ---
license: mit
---
# Label - Emotion Table
| Emotion | LABEL |
| -------------- |:-------------: |
| Anger | LABEL_0 |
| Boredom | LABEL_1 |
| Empty | LABEL_2 |
| Enthusiasm | LABEL_3 |
| Fear | LABEL_4 |
| Fun ... |
anahitapld/dbd_t5 | 06bac9dd72a82134449b4f5b0d9f497e558e631c | 2022-07-18T07:47:17.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | anahitapld | null | anahitapld/dbd_t5 | 31 | null | transformers | 7,123 | ---
license: apache-2.0
---
|
tahercoolguy/nllb-8bit-600 | 82f292f223ff1439b71fea14773d6655281b4206 | 2022-07-23T11:34:42.000Z | [
"pytorch",
"m2m_100",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | tahercoolguy | null | tahercoolguy/nllb-8bit-600 | 31 | null | transformers | 7,124 | ---
license: apache-2.0
---
|
HMHMlee/BioLinkBERT-base-finetuned-ner | 4469ece8896907001be8f15b78ccb7d295bd033f | 2022-07-26T08:05:20.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | HMHMlee | null | HMHMlee/BioLinkBERT-base-finetuned-ner | 31 | 1 | transformers | 7,125 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BioLinkBERT-base-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comp... |
Perselope/thesis-audio-1 | 380fa4c32e09b4bbc6a8c8120e1e18423bca71de | 2022-07-28T13:27:40.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Perselope | null | Perselope/thesis-audio-1 | 31 | null | transformers | 7,126 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: thesis-audio-1
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. -->
# thesis-audio-1
This... |
Aleksandra/herbert-base-cased-finetuned-squad | 4cbf8e1987f9367451c884520c75022619d2111a | 2022-01-20T13:14:11.000Z | [
"pytorch",
"tensorboard",
"bert",
"question-answering",
"transformers",
"generated_from_trainer",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | Aleksandra | null | Aleksandra/herbert-base-cased-finetuned-squad | 30 | null | transformers | 7,127 | ---
license: cc-by-4.0
tags:
- generated_from_trainer
model-index:
- name: herbert-base-cased-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 remove this comment. -->
# h... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth | 25af6aa7dc6a787aa0525be1604aa0ae45e2a9cf | 2021-09-14T14:29:52.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth | 30 | 2 | transformers | 7,128 | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
Capreolus/electra-base-msmarco | a973d2976540da0777ebea375173a4e2a6a540db | 2020-09-08T14:53:10.000Z | [
"pytorch",
"tf",
"electra",
"text-classification",
"arxiv:2008.09093",
"transformers"
] | text-classification | false | Capreolus | null | Capreolus/electra-base-msmarco | 30 | null | transformers | 7,129 | # capreolus/electra-base-msmarco
## Model description
ELECTRA-Base model (`google/electra-base-discriminator`) fine-tuned on the MS MARCO passage classification task. It is intended to be used as a `ForSequenceClassification` model, but requires some modification since it contains a BERT classification head rather tha... |
FuriouslyAsleep/markuplm-large-finetuned-qa | ed8e8dd012ad26dcfac4b7edbf8b192d5b0e5e1d | 2022-02-10T20:30:55.000Z | [
"pytorch",
"markuplm",
"question-answering",
"arxiv:2110.08518",
"transformers",
"autotrain_compatible"
] | question-answering | false | FuriouslyAsleep | null | FuriouslyAsleep/markuplm-large-finetuned-qa | 30 | null | transformers | 7,130 | # MarkupLM Large fine-tuned on WebSRC to allow Question Answering.
This model is adapted from Microsoft's MarkupLM. This fine-tuned model is the result of partially following instructions in the MarkupLM git repo (with adjustments described farther below under the Fine-tuning args section.) This version not endorsed b... |
Helsinki-NLP/opus-mt-af-fr | d01086028ee2e84b2a9f1517945d1b651bd08acc | 2021-09-09T21:26:04.000Z | [
"pytorch",
"marian",
"text2text-generation",
"af",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-af-fr | 30 | null | transformers | 7,131 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-af-fr
* source languages: af
* target languages: fr
* OPUS readme: [af-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/af-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-bcl-en | 348eac648d5c855db90888990e4033305139c72a | 2021-09-09T21:26:44.000Z | [
"pytorch",
"marian",
"text2text-generation",
"bcl",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-bcl-en | 30 | null | transformers | 7,132 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-bcl-en
* source languages: bcl
* target languages: en
* OPUS readme: [bcl-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bcl-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-efi-en | 0bf437954f943da3d49a172b6f91aa7157c3525a | 2021-09-09T21:33:32.000Z | [
"pytorch",
"marian",
"text2text-generation",
"efi",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-efi-en | 30 | null | transformers | 7,133 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-efi-en
* source languages: efi
* target languages: en
* OPUS readme: [efi-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/efi-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-en-itc | 74d38d3b83efcdfbefc27b958bae6f36760a8698 | 2021-01-18T08:10:20.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"it",
"ca",
"rm",
"es",
"ro",
"gl",
"sc",
"co",
"wa",
"pt",
"oc",
"an",
"id",
"fr",
"ht",
"itc",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-itc | 30 | 1 | transformers | 7,134 | ---
language:
- en
- it
- ca
- rm
- es
- ro
- gl
- sc
- co
- wa
- pt
- oc
- an
- id
- fr
- ht
- itc
tags:
- translation
license: apache-2.0
---
### eng-itc
* source group: English
* target group: Italic languages
* OPUS readme: [eng-itc](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-i... |
Helsinki-NLP/opus-mt-fi-fr | c936f809f49131ec06fe13b1045eeeb455ccf104 | 2021-09-09T21:47:40.000Z | [
"pytorch",
"marian",
"text2text-generation",
"fi",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-fi-fr | 30 | null | transformers | 7,135 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-fi-fr
* source languages: fi
* target languages: fr
* OPUS readme: [fi-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fi-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-no-de | 19e8bdf5de2e254ae25605c0afd0bb68d8bdd6ee | 2020-08-21T14:42:48.000Z | [
"pytorch",
"marian",
"text2text-generation",
"no",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-no-de | 30 | null | transformers | 7,136 | ---
language:
- no
- de
tags:
- translation
license: apache-2.0
---
### nor-deu
* source group: Norwegian
* target group: German
* OPUS readme: [nor-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/nor-deu/README.md)
* model: transformer-align
* source language(s): nno nob
* target la... |
Helsinki-NLP/opus-mt-sg-en | 227bc46ddfc78d4e0caa4b4b5fed91e0db8a0ab0 | 2021-09-10T14:03:02.000Z | [
"pytorch",
"marian",
"text2text-generation",
"sg",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sg-en | 30 | null | transformers | 7,137 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-sg-en
* source languages: sg
* target languages: en
* OPUS readme: [sg-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sg-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
KoichiYasuoka/roberta-classical-chinese-large-upos | 8a3afed02fb70e16f9026b55c30e786074c7ac0a | 2022-07-05T22:11:02.000Z | [
"pytorch",
"roberta",
"token-classification",
"lzh",
"dataset:universal_dependencies",
"transformers",
"classical chinese",
"literary chinese",
"ancient chinese",
"pos",
"dependency-parsing",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/roberta-classical-chinese-large-upos | 30 | null | transformers | 7,138 | ---
language:
- "lzh"
tags:
- "classical chinese"
- "literary chinese"
- "ancient chinese"
- "token-classification"
- "pos"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "apache-2.0"
pipeline_tag: "token-classification"
widget:
- text: "子曰學而時習之不亦説乎有朋自遠方來不亦樂乎人不知而不慍不亦君子乎"
---
# roberta-classical-c... |
NTUYG/SOTitle-Gen-T5 | 6837a37162f274cce6fb79e5580e0938f58a8871 | 2021-09-10T09:51:34.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | NTUYG | null | NTUYG/SOTitle-Gen-T5 | 30 | null | transformers | 7,139 | Entry not found |
Tsubasaz/clinical-pubmed-bert-base-512 | e5a643404ed6bb0e992200a27d07c83a65558b60 | 2022-05-06T10:55:40.000Z | [
"pytorch",
"bert",
"fill-mask",
"en",
"dataset:MIMIC-III",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | Tsubasaz | null | Tsubasaz/clinical-pubmed-bert-base-512 | 30 | 2 | transformers | 7,140 | ---
language:
- en
license: mit
datasets:
- MIMIC-III
widget:
- text: "Due to shortness of breath, the patient is diagnosed with [MASK], and other respiratory problems."
example_title: "Example 1"
- text: "Due to high blood sugar, and very low blood pressure, the patient is diagnosed with [MASK]."
example_title:... |
VoVanPhuc/vietnamese-summarization | a3b4a80e9f148acc8660ecacd2009a854e77be3b | 2021-09-13T03:54:32.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | VoVanPhuc | null | VoVanPhuc/vietnamese-summarization | 30 | null | transformers | 7,141 | Entry not found |
aware-ai/longformer-squadv2 | 74f1fe8292734e4072a24e479cd0482861c27a71 | 2020-08-07T11:30:59.000Z | [
"pytorch",
"tf",
"longformer",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | aware-ai | null | aware-ai/longformer-squadv2 | 30 | null | transformers | 7,142 | Entry not found |
addy88/hindi-wav2vec2-stt | d003bf31d176c67200cd6ca315c5e57ef1bb65a6 | 2021-12-09T03:55:47.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | addy88 | null | addy88/hindi-wav2vec2-stt | 30 | null | transformers | 7,143 | ## Usage
The model can be used directly (without a language model) as follows:
```python
import soundfile as sf
import torch
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import argparse
def parse_transcription(wav_file):
# load pretrained model
processor = Wav2Vec2Processor.from_pretrained("addy88... |
airesearch/xlm-roberta-base-finetune-qa | fb4f5550052f921cdbb04562b8cdf7d62cd00310 | 2021-07-14T07:13:00.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | airesearch | null | airesearch/xlm-roberta-base-finetune-qa | 30 | null | transformers | 7,144 | ---
widget:
- text: "สวนกุหลาบเป็นโรงเรียนอะไร"
context: "โรงเรียนสวนกุหลาบวิทยาลัย (Suankularb Wittayalai School) (อักษรย่อ : ส.ก. / S.K.) เป็นโรงเรียนชายล้วน ระดับชั้นมัธยมศึกษาขนาดใหญ่พิเศษ สังกัดสำนักงานเขตพื้นที่การศึกษามัธยมศึกษาเขต 1 สำนักงานคณะกรรมการการศึกษาขั้นพื้นฐาน (ชื่อเดิม: กรมสามัญศึกษา) กระทรวงศึกษาธ... |
archmagos/HourAI | ba46d38528287c054cc895ad4baf42b25d83978a | 2022-05-03T20:09:49.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | archmagos | null | archmagos/HourAI | 30 | null | transformers | 7,145 | ---
tags:
- conversational
---
#HourAI bot based on DialoGPT |
benjamin/roberta-base-wechsel-french | 5608715c8a81314f3fb2ac0462ccc6d149e16c9f | 2022-07-13T23:44:38.000Z | [
"pytorch",
"roberta",
"fill-mask",
"fr",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | benjamin | null | benjamin/roberta-base-wechsel-french | 30 | 1 | transformers | 7,146 | ---
language: fr
license: mit
---
# roberta-base-wechsel-french
Model trained with WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
See the code here: https://github.com/CPJKU/wechsel
And the paper here: https://aclanthology.org/2022.naacl-main.293/
... |
boychaboy/SNLI_roberta-large | d6ec1fa4829a98fd07ff06f9aa6422f067f0026b | 2021-05-20T14:37:47.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | boychaboy | null | boychaboy/SNLI_roberta-large | 30 | null | transformers | 7,147 | Entry not found |
chinhon/bart-large-chinese-cnhdwriter | cca6399ef69fcfa2b06525924d0e999896d71c56 | 2022-01-22T06:01:33.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | chinhon | null | chinhon/bart-large-chinese-cnhdwriter | 30 | 1 | transformers | 7,148 | ---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-chinese-cnhdwriter
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-lar... |
classla/sloberta-frenk-hate | 99fd4dee852c2a9f9a176d7919c7a11d63251e18 | 2021-11-30T12:42:46.000Z | [
"pytorch",
"camembert",
"text-classification",
"sl",
"arxiv:1907.11692",
"arxiv:1906.02045",
"transformers",
"hate-speech"
] | text-classification | false | classla | null | classla/sloberta-frenk-hate | 30 | null | transformers | 7,149 | ---
language: "sl"
tags:
- text-classification
- hate-speech
widget:
- text: "Silva, ti si grda in neprijazna"
---
Text classification model based on `EMBEDDIA/sloberta` and fine-tuned on the [FRENK dataset](https://www.clarin.si/repository/xmlui/handle/11356/1433) comprising of LGBT and migrant hatespeech. Only the... |
creat89/NER_FEDA_Bg | 83305a32394b78190b385757bf26cb744cdc43cf | 2022-04-13T09:26:23.000Z | [
"pytorch",
"bert",
"multilingual",
"bg",
"mk",
"transformers",
"labse",
"ner",
"license:mit"
] | null | false | creat89 | null | creat89/NER_FEDA_Bg | 30 | null | transformers | 7,150 | ---
license: mit
language:
- multilingual
- bg
- mk
tags:
- labse
- ner
---
This is a multilingual NER system trained using a Frustratingly Easy Domain Adaptation architecture. It is based on LaBSE and supports different tagsets all using IOBES formats:
1. Wikiann (LOC, PER, ORG)
2. SlavNER 19/21 (EVT, LOC,... |
emil2000/dialogpt-for-french-language | 183ec8ed380bebf8fc6142477db0f633dc88ade7 | 2021-09-25T21:50:35.000Z | [
"pytorch",
"gpt2",
"text-generation",
"fr",
"transformers"
] | text-generation | false | emil2000 | null | emil2000/dialogpt-for-french-language | 30 | null | transformers | 7,151 | ---
language:
- fr
tags:
- {fr}
- {gpt2}
---
This model aims at being a french conversational agent. This consists of a fine-tuning of Dialo-GPT for french language. The dataset used gathers 36k conversations extracted from books, movies, interviews and dialogues for learning french.
More details about the model c... |
ffsouza/tiny-mbart-length-128-finetuned-en-to-ro | d87878b027afe7a1ebecde17f4e674288220e564 | 2021-11-30T06:12:22.000Z | [
"pytorch",
"tensorboard",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | ffsouza | null | ffsouza/tiny-mbart-length-128-finetuned-en-to-ro | 30 | null | transformers | 7,152 | Entry not found |
flax-community/bengali-t5-base | e27fdf4c9c55d7c6e12df9ee4209eb2e3c1cd4ba | 2021-07-19T06:27:44.000Z | [
"pytorch",
"jax",
"tensorboard",
"mt5",
"text2text-generation",
"arxiv:1910.10683",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | flax-community | null | flax-community/bengali-t5-base | 30 | null | transformers | 7,153 | # bengali-t5-base
**bengali-t5-base** is a model trained on the Bengali portion of MT5 dataset. We used the `T5-base` model for this model.
[Flax/Jax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104), organized by [HuggingFace](https://huggingface.co... |
gagan3012/project-code-py-small | df793bd9be993ba5842c664b470b5977bfd2ad49 | 2021-05-21T16:06:24.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | gagan3012 | null | gagan3012/project-code-py-small | 30 | null | transformers | 7,154 | # Leetcode using AI :robot:
GPT-2 Model for Leetcode Questions in python
**Note**: the Answers might not make sense in some cases because of the bias in GPT-2
**Contribtuions:** If you would like to make the model better contributions are welcome Check out [CONTRIBUTIONS.md](https://github.com/gagan3012/project-code... |
google/t5-efficient-mini | 094079e325c02e6dcb4a1d22826599c555e70aa2 | 2022-02-15T10:56:20.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"arxiv:2109.10686",
"transformers",
"deep-narrow",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-efficient-mini | 30 | null | transformers | 7,155 | ---
language:
- en
datasets:
- c4
tags:
- deep-narrow
inference: false
license: apache-2.0
---
# T5-Efficient-MINI (Deep-Narrow version)
T5-Efficient-MINI is a variation of [Google's original T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) following the [T5 model architecture](https:/... |
helboukkouri/character-bert-medical | 7fef3ced1b1f6f2ba16c6ee3b95f0865c1c28738 | 2021-05-17T10:41:06.000Z | [
"pytorch",
"character_bert",
"transformers"
] | null | false | helboukkouri | null | helboukkouri/character-bert-medical | 30 | 1 | transformers | 7,156 | Entry not found |
huawei-noah/TinyBERT_6L_zh | f6b4e4a4a3937d95ee0509b3f2c03d4d127ba31b | 2020-10-14T09:05:20.000Z | [
"pytorch",
"transformers"
] | null | false | huawei-noah | null | huawei-noah/TinyBERT_6L_zh | 30 | null | transformers | 7,157 | Entry not found |
huggingtweets/messiah_niko | 5b7ac06353b139944334aa4893992b42105d9cdf | 2021-06-07T08:29:53.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/messiah_niko | 30 | null | transformers | 7,158 | ---
language: en
thumbnail: https://www.huggingtweets.com/messiah_niko/1623054570608/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; w... |
huggingtweets/nintendoamerica | 3f4b92dc125e23a3bec7557e6ba5e1d4bcfa3a64 | 2021-05-22T16:26:49.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/nintendoamerica | 30 | null | transformers | 7,159 | ---
language: en
thumbnail: https://www.huggingtweets.com/nintendoamerica/1601313308462/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
<style>
@media (prefers-color-scheme: dark) {
.prose ... |
jaron-maene/gpt2-medium-nl2bash | fea3a00df96b702af04f6a7aa3f6fbdd7bfb1295 | 2021-05-23T05:42:13.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | jaron-maene | null | jaron-maene/gpt2-medium-nl2bash | 30 | null | transformers | 7,160 | Entry not found |
jpwahle/xlnet-base-plagiarism-detection | bd898e8d4cbe9d1d2ebc71397c1694fd4634954f | 2021-09-24T07:44:27.000Z | [
"pytorch",
"xlnet",
"text-classification",
"ISO 639-1 code for your language, or `multilingual`",
"dataset:array of dataset identifiers",
"arxiv:1906.08237",
"transformers",
"array",
"of",
"tags"
] | text-classification | false | jpwahle | null | jpwahle/xlnet-base-plagiarism-detection | 30 | 1 | transformers | 7,161 | ---
language: ISO 639-1 code for your language, or `multilingual`
thumbnail: url to a thumbnail used in social sharing
tags:
- array
- of
- tags
datasets:
- array of dataset identifiers
metrics:
- array of metric identifiers
widget:
- text: Copyright infringement is viewed as an infringement of scholarly uprightness
... |
keshan/sinhala-roberta-mc4 | a3f63861ccb8c137facaed07fe9c1e3c8a48d148 | 2021-09-23T16:05:07.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"si",
"transformers",
"sinhala",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | keshan | null | keshan/sinhala-roberta-mc4 | 30 | null | transformers | 7,162 | ---
language: si
license: cc-by-4.0
tags:
- sinhala
- roberta
pipeline_tag: fill-mask
widget:
- text: මම සිංහල භාෂාව <mask>
---
# Sinhala roberta on mc4 dataset
|
kz/mt5base-finetuned-ECC-japanese-small | c9b54a17f1652d39c3a1486a6712e094cca47031 | 2022-05-26T13:50:56.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"ja",
"arxiv:2201.11903",
"transformers",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | kz | null | kz/mt5base-finetuned-ECC-japanese-small | 30 | 1 | transformers | 7,163 | ---
language: "ja"
widget:
- text: "吾輩をは猫である。を書いた作家は，夏目漱 <extra_id_0>"
- text: "吾輩をは猫である。名前えはまだない。"
- text: "translate japanese to english: 赤い花． => red flower. 青い花． => <extra_id_0>"
license: "mit"
---
Google's mt5-base fine-tuned in Japanese to solve error detection and correction task.
# 日本語誤り訂正
- "吾輩をは猫である。名前えはまだ... |
lucio/xls-r-uyghur-cv8 | 3aeee04baa659b20258b57368f80ddad58ac6ccb | 2022-03-23T18:28:37.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"ug",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | lucio | null | lucio/xls-r-uyghur-cv8 | 30 | 1 | transformers | 7,164 | ---
language:
- ug
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- ug
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R-300M Uyghur CV8
results:
- task:
name: Automatic... |
mpoyraz/wav2vec2-xls-r-300m-cv8-turkish | bdd0bb878d8bf59509611631e334eb073ba57773 | 2022-03-23T18:29:03.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"common_voice",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | mpoyraz | null | mpoyraz/wav2vec2-xls-r-300m-cv8-turkish | 30 | 1 | transformers | 7,165 | ---
license: apache-2.0
language: tr
tags:
- automatic-speech-recognition
- common_voice
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- tr
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: mpoyraz/wav2vec2-xls-r-300m-cv8-turkish
results:
- task:
name: Aut... |
mrm8488/distilroberta-finetuned-banking77 | 827f854e4028255343744993763901683c0cab8d | 2021-08-21T05:29:11.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:banking77",
"transformers",
"banking",
"intent",
"multiclass"
] | text-classification | false | mrm8488 | null | mrm8488/distilroberta-finetuned-banking77 | 30 | 3 | transformers | 7,166 | ---
language: en
tags:
- banking
- intent
- multiclass
datasets:
- banking77
widget:
- text: "How long until my transfer goes through?"
---
# distilroberta-base fine-tuned on banking77 dataset for intent classification
Test set accuray: 0.896
## How to use
```py
from transformers import AutoTokenizer, AutoModelForSeq... |
pere/nb-nn-translation | 46f078914489b4a00b6f493c0c3e93cf9be53c68 | 2021-09-23T16:19:21.000Z | [
"pytorch",
"jax",
"no",
"dataset:oscar",
"translation",
"license:cc-by-4.0"
] | translation | false | pere | null | pere/nb-nn-translation | 30 | 2 | null | 7,167 | ---
language: no
license: cc-by-4.0
tags:
- translation
datasets:
- oscar
widget:
- text: Skriv inn en tekst som du ønsker å oversette til en annen målform.
---
# 🇳🇴 Bokmål ⇔ Nynorsk 🇳🇴
Norwegian has two relatively similar written languages; Bokmål and Nynorsk. Historically Nynorsk is a written norm based on di... |
persiannlp/wikibert-base-parsinlu-entailment | 0c1bcd3dae471681977503e8381714a5aed5b05b | 2021-09-23T16:20:55.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"fa",
"multilingual",
"dataset:parsinlu",
"transformers",
"entailment",
"wikibert",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0"
] | text-classification | false | persiannlp | null | persiannlp/wikibert-base-parsinlu-entailment | 30 | null | transformers | 7,168 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- entailment
- wikibert
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Textual Entailment (مدل برای پاسخ به استلزام منطقی)
This is a model for textual entailment ... |
pmthangk09/bert-base-uncased-glue-cola | 8ee606fb48f03794a5ef549205f05ae48370d0dc | 2021-05-20T02:47:36.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | pmthangk09 | null | pmthangk09/bert-base-uncased-glue-cola | 30 | null | transformers | 7,169 | Entry not found |
popcornell/FasNetTAC-paper | d87f356489a4d280948080f808c3f02280e97a0c | 2021-09-23T16:21:33.000Z | [
"pytorch",
"dataset:TACDataset",
"dataset:sep_noisy",
"asteroid",
"audio",
"FasNet-TAC",
"audio-to-audio",
"multichannel",
"beamforming",
"license:cc-by-sa-4.0"
] | audio-to-audio | false | popcornell | null | popcornell/FasNetTAC-paper | 30 | 2 | asteroid | 7,170 | ---
tags:
- asteroid
- audio
- FasNet-TAC
- audio-to-audio
- multichannel
- beamforming
datasets:
- TACDataset
- sep_noisy
license: cc-by-sa-4.0
---
## Asteroid model `Samuele Cornell/FasNetTAC_TACDataset_separatenoisy`
Imported from [Zenodo](https://zenodo.org/record/4557489)
### Description:
This model was trained ... |
saichandrapandraju/t5_small_tabqgen | 9ccd2c9af3c17e499d5bd682f9ebf21291aaff3b | 2021-06-23T14:04:49.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | saichandrapandraju | null | saichandrapandraju/t5_small_tabqgen | 30 | null | transformers | 7,171 | Entry not found |
sentence-transformers/nli-bert-large | 8a3386060e2c164316539309ae31e9c5c76e648a | 2021-08-05T08:27:47.000Z | [
"pytorch",
"bert",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/nli-bert-large | 30 | null | sentence-transformers | 7,172 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
**⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: [SBERT.net... |
severinsimmler/german-press-bert | 62bba72d77173c958ee65e09772bbd5fae8703ca | 2021-05-20T05:46:27.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | severinsimmler | null | severinsimmler/german-press-bert | 30 | null | transformers | 7,173 | Entry not found |
sonoisa/sentence-t5-base-ja-mean-tokens | 72d9b3d7fac5b92daa1e7a214abe1266ca9a6571 | 2022-07-28T05:20:27.000Z | [
"pytorch",
"t5",
"feature-extraction",
"ja",
"sentence-transformers",
"sentence-t5",
"sentence-similarity",
"license:cc-by-sa-4.0"
] | feature-extraction | false | sonoisa | null | sonoisa/sentence-t5-base-ja-mean-tokens | 30 | null | sentence-transformers | 7,174 | ---
language: ja
license: cc-by-sa-4.0
tags:
- sentence-transformers
- sentence-t5
- feature-extraction
- sentence-similarity
---
This is a Japanese sentence-T5 model.
日本語用Sentence-T5モデルです。
事前学習済みモデルとして[sonoisa/t5-base-japanese](https://huggingface.co/sonoisa/t5-base-japanese)を利用しました。
推論の実行にはsentencepieceが必要です（pi... |
stmnk/codet5-small-code-summarization-python | 9fc1e2ca74def81717c2e82ee70c3de83419013e | 2021-11-19T17:50:27.000Z | [
"pytorch",
"t5",
"text2text-generation",
"py",
"en",
"dataset:code_x_glue_ct_code_to_text",
"dataset:code_x_glue_ct_code_to_text (python)",
"transformers",
"Code2TextGeneration",
"Code2TextSummarisation",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | stmnk | null | stmnk/codet5-small-code-summarization-python | 30 | null | transformers | 7,175 | ---
language:
- py
- en
thumbnail: "url to a thumbnail used in social sharing"
tags:
- Code2TextGeneration
- Code2TextSummarisation
license: apache-2.0
datasets:
- code_x_glue_ct_code_to_text
- code_x_glue_ct_code_to_text (python)
metrics:
- code-x-bleu
---
pretrained model: https://huggingface.co/Sale... |
tals/albert-xlarge-vitaminc-fever | 7496f8f6c4350e2b151ef982e6d8903fbd77c8c9 | 2022-06-22T23:55:46.000Z | [
"pytorch",
"albert",
"text-classification",
"python",
"dataset:fever",
"dataset:glue",
"dataset:tals/vitaminc",
"transformers"
] | text-classification | false | tals | null | tals/albert-xlarge-vitaminc-fever | 30 | null | transformers | 7,176 | ---
language: python
datasets:
- fever
- glue
- tals/vitaminc
---
# Details
Model used in [Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://aclanthology.org/2021.naacl-main.52/) (Schuster et al., NAACL 21`).
For more details see: https://github.com/TalSchuster/VitaminC
When using this m... |
tesemnikov-av/NER-RUBERT-Per-Loc-Org | 9c9c1bd59cbb1a61999b9735dd73af8ec0ad7ba4 | 2022-02-04T19:40:56.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tesemnikov-av | null | tesemnikov-av/NER-RUBERT-Per-Loc-Org | 30 | null | transformers | 7,177 | ---
widget:
- text: "В город Сергиев Посад приехал Курт Кобейн."
---
Fine-tuning [cointegrated/rubert-tiny](https://huggingface.co/cointegrated/rubert-tiny) model on sentences from Wiki auto annotated with PER, LOC, ORG tags [corus/WiNER](https://pypi.org/project/corus/#reference)
language: RU
NER Class:
-... |
vachonni/wav2vec2-large-xls-r-300m-dansk-CV-80 | 85f4ac5dfea7d89e1b7114f1597294798a626cd8 | 2022-02-01T07:55:36.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:common_voice",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | vachonni | null | vachonni/wav2vec2-large-xls-r-300m-dansk-CV-80 | 30 | 2 | transformers | 7,178 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-dansk-CV-80
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 ... |
valhalla/electra-base-discriminator-finetuned_squadv1 | e70021ecbe89606f35b8d7c2e37fa86ff6cc60cc | 2020-12-11T22:03:34.000Z | [
"pytorch",
"electra",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | valhalla | null | valhalla/electra-base-discriminator-finetuned_squadv1 | 30 | null | transformers | 7,179 | # ELECTRA-BASE-DISCRIMINATOR finetuned on SQuADv1
This is electra-base-discriminator model finetuned on SQuADv1 dataset for for question answering task.
## Model details
As mentioned in the original paper: ELECTRA is a new method for self-supervised language representation learning.
It can be used to pre-train transf... |
w11wo/malaysian-distilbert-small | 5cdb75e9d2059fad16ffb3df956241ff30f6ed12 | 2021-07-11T15:56:09.000Z | [
"pytorch",
"tf",
"distilbert",
"fill-mask",
"ms",
"dataset:oscar",
"arxiv:1910.01108",
"transformers",
"malaysian-distilbert-small",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | w11wo | null | w11wo/malaysian-distilbert-small | 30 | null | transformers | 7,180 | ---
language: ms
tags:
- malaysian-distilbert-small
license: mit
datasets:
- oscar
widget:
- text: "Hari ini adalah hari yang [MASK]!"
---
## Malaysian DistilBERT Small
Malaysian DistilBERT Small is a masked language model based on the [DistilBERT model](https://arxiv.org/abs/1910.01108). It was trained on the [OSCAR]... |
wietsedv/bert-base-multilingual-cased-finetuned-udlassy-ner | 74fd633e7b8efef418a1cb1aaf75230208375357 | 2021-05-20T09:16:27.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | wietsedv | null | wietsedv/bert-base-multilingual-cased-finetuned-udlassy-ner | 30 | null | transformers | 7,181 | Entry not found |
mmaguero/gn-bert-tiny-cased | 3163de7fea4aaddb4074c3a4b58fbf27a4807dc7 | 2022-03-06T08:09:35.000Z | [
"pytorch",
"bert",
"fill-mask",
"gn",
"dataset:wikipedia",
"dataset:wiktionary",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | mmaguero | null | mmaguero/gn-bert-tiny-cased | 30 | null | transformers | 7,182 | ---
language: gn
license: mit
datasets:
- wikipedia
- wiktionary
widget:
- text: "Paraguay ha'e peteĩ táva oĩva [MASK] retãme "
---
# BERT-i-tiny-cased (gnBERT-tiny-cased)
A pre-trained BERT model for **Guarani** (2 layers, cased). Trained on Wikipedia + Wiktionary (~800K tokens).
|
hackathon-pln-es/jurisbert-class-tratados-internacionales-sistema-universal | 575e1de2b39397c7ee6adcd0ee25cdf41b294a64 | 2022-03-28T19:02:27.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"es",
"transformers",
"license:cc-by-nc-4.0"
] | text-classification | false | hackathon-pln-es | null | hackathon-pln-es/jurisbert-class-tratados-internacionales-sistema-universal | 30 | 3 | transformers | 7,183 | ---
license: cc-by-nc-4.0
language: es
widget:
- text: "A los 4 Civiles de Rosarito se les acusó de cometer varios delitos federales en flagrancia, aunque se ha comprobado que no fueron detenidos en el lugar en el que los militares señalaron en su parte informativo. Las cuatro personas refieren que el 17 de junio de 20... |
ai4bharat/MultiIndicHeadlineGeneration | 1332a232585ce151009c5f577cc1418d99f746be | 2022-05-06T10:39:48.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"arxiv:2203.05437",
"transformers",
"multilingual",
"nlp",
"indicnlp",
"autotrain_compatible"
] | text2text-generation | false | ai4bharat | null | ai4bharat/MultiIndicHeadlineGeneration | 30 | null | transformers | 7,184 |
---
languages:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- or
- pa
- ta
- te
tags:
- multilingual
- nlp
- indicnlp
widget:
- text: वैश्विक व्यापार युद्ध की शिकार हुई तुर्की की मुद्रा लीरा के डूबने से अमेरिकी डॉलर के मुकाबले रुपया अब तक के न्यूनतम स्तर पर पहुंच गया। रुपये में रिकॉर्ड गिरावट से सोने की चमक में निखार नहीं आ सकी... |
danjohnvelasco/filipino-sentence-roberta-v1 | b542d6e4e2b37cbb1ce3ecd9d3741afb324e24bf | 2022-04-09T09:45:29.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"tl",
"dataset:newsph_nli",
"arxiv:2204.03251",
"sentence-transformers",
"tagalog",
"filipino",
"license:cc-by-sa-4.0"
] | feature-extraction | false | danjohnvelasco | null | danjohnvelasco/filipino-sentence-roberta-v1 | 30 | 1 | sentence-transformers | 7,185 | ---
language: tl
tags:
- roberta
- tagalog
- filipino
- sentence-transformers
datasets: newsph_nli
license: cc-by-sa-4.0
---
# Filipino Sentence RoBERTa
We finetuned [RoBERTa Tagalog Base (finetuned on COHFIE)](https://huggingface.co/danjohnvelasco/roberta-tagalog-base-cohfie-v1) on [NewsPH-NLI](https://huggingface.co... |
philschmid/roberta-large-finetuned-clinc | 10dab4d778797f61ac2ea488175a6512012a1d90 | 2022-04-14T13:25:42.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"dataset:clinc_oos",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | philschmid | null | philschmid/roberta-large-finetuned-clinc | 30 | null | transformers | 7,186 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: roberta-large-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
- n... |
Intel/roberta-base-mrpc-int8-static | 4a3c353d63adea27b478734ae637aa4f0bc729b8 | 2022-06-10T02:37:58.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:glue",
"transformers",
"text-classfication",
"int8",
"Intel® Neural Compressor",
"PostTrainingStatic",
"license:mit",
"model-index"
] | text-classification | false | Intel | null | Intel/roberta-base-mrpc-int8-static | 30 | null | transformers | 7,187 | ---
language:
- en
license: mit
tags:
- text-classfication
- int8
- Intel® Neural Compressor
- PostTrainingStatic
datasets:
- glue
metrics:
- f1
model-index:
- name: roberta-base-mrpc-int8-static
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
... |
Hate-speech-CNERG/hindi-abusive-MuRIL | a551d03550a8434fb2b3c701fbcfe547f83b7d9b | 2022-05-03T08:51:13.000Z | [
"pytorch",
"bert",
"text-classification",
"hi",
"arxiv:2204.12543",
"transformers",
"license:afl-3.0"
] | text-classification | false | Hate-speech-CNERG | null | Hate-speech-CNERG/hindi-abusive-MuRIL | 30 | null | transformers | 7,188 | ---
language: [hi]
license: afl-3.0
---
This model is used detecting **abusive speech** in **Devanagari Hindi**. It is finetuned on MuRIL model using Hindi abusive speech dataset.
The model is trained with learning rates of 2e-5. Training code can be found at this [url](https://github.com/hate-alert/IndicAbusive)
LAB... |
mikeadimech/bart-qmsum-meeting-summarization | e420b1b303d0fe66761c147a1145f6f76a393e53 | 2022-05-25T16:14:18.000Z | [
"pytorch",
"bart",
"text2text-generation",
"dataset:yawnick/QMSum",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | mikeadimech | null | mikeadimech/bart-qmsum-meeting-summarization | 30 | 1 | transformers | 7,189 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-qmsum-meeting-summarization
results: []
datasets:
- yawnick/QMSum
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and compl... |
Abdelrahman-Rezk/distilbert-base-uncased-finetuned-emotion | 0706687fe4be0de2676a3454d8ca4d3abf440258 | 2022-07-20T15:35:20.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Abdelrahman-Rezk | null | Abdelrahman-Rezk/distilbert-base-uncased-finetuned-emotion | 30 | null | transformers | 7,190 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
BK-V/xlm-roberta-base-finetuned-arman-fa | 2e0c4b6bf0cd329c801ee95fd3ab8eadf5d2a73e | 2022-06-30T13:40:40.000Z | [
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | BK-V | null | BK-V/xlm-roberta-base-finetuned-arman-fa | 30 | null | transformers | 7,191 | ---
license: mit
tags:
- generated_from_trainer
- token-classification
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-arman-fa
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread ... |
Dafa/factcc | 733ef086ec54ec702dd952a00c3368fb8a63d199 | 2022-05-25T23:38:09.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:afl-3.0"
] | text-classification | false | Dafa | null | Dafa/factcc | 30 | null | transformers | 7,192 | ---
license: afl-3.0
---
|
Aktsvigun/bert-base-aeslc | 7d867d676594c398c57ff41ac7e53a470f35ad49 | 2022-05-27T20:45:49.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Aktsvigun | null | Aktsvigun/bert-base-aeslc | 30 | null | transformers | 7,193 | ---
license: apache-2.0
---
|
obokkkk/kc-bert_finetuned_unsmile | e5bbe6489ac56d2b4e18975efef8fa5a98a0edf4 | 2022-06-12T17:22:32.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | obokkkk | null | obokkkk/kc-bert_finetuned_unsmile | 30 | null | transformers | 7,194 | ---
tags:
- generated_from_trainer
model-index:
- name: kc-bert_finetuned_unsmile
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. -->
# kc-bert_finetuned_unsmile
Th... |
microsoft/markuplm-base-finetuned-websrc | 964cf4517792512bfdb1818d767d6799ebe5c06b | 2022-06-14T13:29:20.000Z | [
"pytorch",
"markuplm",
"question-answering",
"arxiv:2110.08518",
"transformers",
"autotrain_compatible"
] | question-answering | false | microsoft | null | microsoft/markuplm-base-finetuned-websrc | 30 | null | transformers | 7,195 | # MarkupLM
**Multimodal (text +markup language) pre-training for [Document AI](https://www.microsoft.com/en-us/research/project/document-ai/)**
## Introduction
MarkupLM is a simple but effective multi-modal pre-training method of text and markup language for visually-rich document understanding and information extra... |
AI-Prize-Challenges/autotrain-finetuned1-1035435583 | 83c9b6604643f236dea486fb6ba1629edc5b9ec5 | 2022-06-24T23:26:04.000Z | [
"pytorch",
"albert",
"text-classification",
"zh",
"dataset:AI-Prize-Challenges/autotrain-data-finetuned1",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | AI-Prize-Challenges | null | AI-Prize-Challenges/autotrain-finetuned1-1035435583 | 30 | null | transformers | 7,196 | ---
tags: autotrain
language: zh
widget:
- text: "I love AutoTrain 🤗"
datasets:
- AI-Prize-Challenges/autotrain-data-finetuned1
co2_eq_emissions: 0.03608660562919794
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1035435583
- CO2 Emissions (in grams): 0.03608660562919794
## Va... |
itzo/bert-base-uncased-fine-tuned-on-clinc_oos-dataset | c72afcfccbe74cb7d6cc1251adcc58c5b7279bce | 2022-07-04T11:05:54.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:clinc_oos",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | itzo | null | itzo/bert-base-uncased-fine-tuned-on-clinc_oos-dataset | 30 | null | transformers | 7,197 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
model-index:
- name: bert-base-uncased-fine-tuned-on-clinc_oos-dataset
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete ... |
dddb/title_generator | b53b1ed6f2847cd37d474efbd1c7e680546e4102 | 2022-06-30T13:27:17.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"unk",
"dataset:dddb/autotrain-data-mt5_chinese_small_finetune",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | dddb | null | dddb/title_generator | 30 | null | transformers | 7,198 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- dddb/autotrain-data-mt5_chinese_small_finetune
co2_eq_emissions: 0.2263611804615655
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1060836848
- CO2 Emissions (in grams): 0.2263611804615655
## Validation... |
abhishek-shrm/roberta-base-finetuned-beer-ner | 2923751dec0bc2a87772a53d48ac95c0c63897fc | 2022-07-03T09:27:51.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | abhishek-shrm | null | abhishek-shrm/roberta-base-finetuned-beer-ner | 30 | null | transformers | 7,199 | Entry not found |
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