repo_id stringlengths 4 110 | author stringlengths 2 27 ⌀ | model_type stringlengths 2 29 ⌀ | files_per_repo int64 2 15.4k | downloads_30d int64 0 19.9M | library stringlengths 2 37 ⌀ | likes int64 0 4.34k | pipeline stringlengths 5 30 ⌀ | pytorch bool 2
classes | tensorflow bool 2
classes | jax bool 2
classes | license stringlengths 2 30 | languages stringlengths 4 1.63k ⌀ | datasets stringlengths 2 2.58k ⌀ | co2 stringclasses 29
values | prs_count int64 0 125 | prs_open int64 0 120 | prs_merged int64 0 15 | prs_closed int64 0 28 | discussions_count int64 0 218 | discussions_open int64 0 148 | discussions_closed int64 0 70 | tags stringlengths 2 513 | has_model_index bool 2
classes | has_metadata bool 1
class | has_text bool 1
class | text_length int64 401 598k | is_nc bool 1
class | readme stringlengths 0 598k | hash stringlengths 32 32 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
flboehm/reddit-bert-text4 | flboehm | bert | 14 | 6 | transformers | 0 | fill-mask | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,247 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# reddit-bert-text4
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unkn... | 647c6123bff3d42e1da30437e46e7138 |
Helsinki-NLP/opus-mt-ru-da | Helsinki-NLP | marian | 11 | 46 | transformers | 0 | translation | true | true | false | apache-2.0 | ['ru', 'da'] | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 1,997 | false |
### rus-dan
* source group: Russian
* target group: Danish
* OPUS readme: [rus-dan](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/rus-dan/README.md)
* model: transformer-align
* source language(s): rus
* target language(s): dan
* model: transformer-align
* pre-processing: normalization + S... | 428666dfbbcc9b758a5e416e3aad4a5e |
Salesforce/codegen-6B-nl | Salesforce | codegen | 9 | 990 | transformers | 1 | text-generation | true | false | false | bsd-3-clause | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 2,786 | false | # CodeGen (CodeGen-NL 6B)
## Model description
CodeGen is a family of autoregressive language models for **program synthesis** from the paper: [A Conversational Paradigm for Program Synthesis](https://arxiv.org/abs/2203.13474) by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese... | b8914b5de95df3c94b51ad07effb2c43 |
facebook/s2t-wav2vec2-large-en-ar | facebook | speech-encoder-decoder | 10 | 16 | transformers | 5 | automatic-speech-recognition | true | false | false | mit | ['en', 'ar'] | ['covost2', 'librispeech_asr'] | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['audio', 'speech-translation', 'automatic-speech-recognition', 'speech2text2'] | false | true | true | 3,517 | false |
# S2T2-Wav2Vec2-CoVoST2-EN-AR-ST
`s2t-wav2vec2-large-en-ar` is a Speech to Text Transformer model trained for end-to-end Speech Translation (ST).
The S2T2 model was proposed in [Large-Scale Self- and Semi-Supervised Learning for Speech Translation](https://arxiv.org/pdf/2104.06678.pdf) and officially released in
[Fa... | bb08b09cdee07897c5a9852ed2d257ab |
zboxi7/finetuning-sentiment-model-3000-samples | zboxi7 | distilbert | 23 | 1 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,088 | false |
<!-- 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. -->
# finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](... | 12f9a205fd5fe5d7a886d2e16559822a |
bochaowei/t5-small-finetuned-xsum-wei2 | bochaowei | t5 | 11 | 1 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | ['xsum'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,423 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-xsum-wei2
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum datas... | 1f7d305e7102f0416cbbd0e77b62e9c4 |
gokuls/tiny-bert-sst2-distilled-model | gokuls | bert | 16 | 1 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['glue'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,660 | false |
<!-- 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. -->
# tiny-bert-sst2-distilled-model
This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/... | e1c9595c2e758f95c0dd06a80ff35ad0 |
fathyshalab/domain_transfer_clinic_credit_cards-massive_cooking-roberta-large-v1-2-4 | fathyshalab | roberta | 14 | 0 | sentence-transformers | 0 | text-classification | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['setfit', 'sentence-transformers', 'text-classification'] | false | true | true | 1,534 | false |
# fathyshalab/domain_transfer_clinic_credit_cards-massive_cooking-roberta-large-v1-2-4
This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
1. Fine-tuning a [Sentence Transfor... | ba27e99428b60b29a6d041854632502a |
ahmeddbahaa/mt5-base-finetuned-ar-wikilingua | ahmeddbahaa | mt5 | 10 | 4 | transformers | 0 | summarization | true | false | false | apache-2.0 | null | ['wiki_lingua'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['summarization', 'generated_from_trainer'] | true | true | true | 2,194 | false |
<!-- 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. -->
# mt5-base-finetuned-ar-wikilingua
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base)... | 1b45bb2611e473746b8199787eebcbdd |
Alred/t5-small-finetuned-summarization-cnn | Alred | t5 | 13 | 3 | transformers | 0 | summarization | true | false | false | apache-2.0 | null | ['cnn_dailymail'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['summarization', 'generated_from_trainer'] | true | true | true | 1,441 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-summarization-cnn
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cn... | b396c1debf698a05de5b6d4b091f85d1 |
rahul77/t5-small-finetuned-xsum-rahul2 | rahul77 | t5 | 11 | 3 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,221 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-xsum-rahul2
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown d... | e8b59f6effd436b3bc50d7a64c3e27c7 |
ksenon07147/NLP_Opt350M | ksenon07147 | opt | 17 | 0 | transformers | 0 | text-generation | true | false | false | other | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,243 | false |
<!-- 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. -->
# NLP_Opt350M
This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the None data... | bb88e4cf2306fe0e88c50745060235f8 |
brad1141/oldData_BERT | brad1141 | bert | 10 | 4 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,498 | false |
<!-- 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. -->
# oldData_BERT
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset... | 0e2a7a171822b2235e055b8e20877838 |
sahita/language-identification | sahita | null | 8 | 26 | speechbrain | 1 | audio-classification | true | false | false | apache-2.0 | ['multilingual', 'en', 'hi', 'ot'] | ['VoxLingua107'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['audio-classification', 'speechbrain', 'embeddings', 'Language', 'Identification', 'pytorch', 'ECAPA-TDNN', 'TDNN', 'VoxLingua107'] | false | true | true | 6,991 | false |
# VoxLingua107 ECAPA-TDNN Spoken Language Identification Model
## Model description
This is a spoken language recognition model trained on the VoxLingua107 dataset using SpeechBrain.
The model uses the ECAPA-TDNN architecture that has previously been used for speaker recognition. However, it uses
more fully connecte... | 1a1d63261f67dcb28d29247fda113107 |
DeividasM/wav2vec2-large-xlsr-53-lithuanian | DeividasM | wav2vec2 | 9 | 17 | transformers | 0 | automatic-speech-recognition | true | false | true | apache-2.0 | ['lt'] | ['common_voice'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['audio', 'automatic-speech-recognition', 'speech', 'xlsr-fine-tuning-week'] | true | true | true | 3,365 | false |
# Wav2Vec2-Large-XLSR-53-Lithuanian
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Lithuanian using the [Common Voice](https://huggingface.co/datasets/common_voice)
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The mod... | d9d90f3e3e6345fd1372bfe34c43d907 |
KES/GEC-English | KES | t5 | 8 | 0 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['text2text-generation', 'Guyanese Creole', 'Caribbean dialect'] | false | true | true | 923 | false |
# Guyanese English Creole to English Translator
This model utilises T5-base pre-trained model. It was fine tuned using a custom dataset for translation of Guyanese English Creole to English. This model will be updated periodically as more data is compiled. For more on the Caribbean English Creoles checkout the librar... | a086dd07e554557e9f4d296dfd3efa03 |
SaiNikhileshReddy/xlm-roberta-large-finetuned-ner | SaiNikhileshReddy | xlm-roberta | 9 | 13 | transformers | 0 | token-classification | true | false | false | mit | null | ['hi_ner_config'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,196 | false |
<!-- 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. -->
# xlm-roberta-large-finetuned-ner
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-lar... | f4c214d9d50400ca474977ff7818b5d7 |
tarteel-ai/whisper-tiny-ar-quran | tarteel-ai | whisper | 30 | 13 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,832 | false |
<!-- 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. -->
# whisper-tiny-ar-quran
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on... | 69bb9b19fbd5fcb25dcd8b8a194251de |
sagawa/ZINC-t5-v2 | sagawa | t5 | 8 | 4 | transformers | 0 | text2text-generation | true | false | true | mit | null | ['sagawa/ZINC-canonicalized'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | true | true | true | 1,987 | false |
# ZINC-t5
This model is a fine-tuned version of [google/t5-v1_1-base](https://huggingface.co/microsoft/deberta-base) on the sagawa/ZINC-canonicalized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1228
- Accuracy: 0.9476
## Model description
We trained t5 on SMILES from ZINC using the... | 7807010734e1460562106c38dbc2f1c6 |
facebook/hubert-large-ls960-ft | facebook | hubert | 9 | 26,932 | transformers | 27 | automatic-speech-recognition | true | true | false | apache-2.0 | ['en'] | ['libri-light', 'librispeech_asr'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['speech', 'audio', 'automatic-speech-recognition', 'hf-asr-leaderboard'] | true | true | true | 2,809 | false |
# Hubert-Large-Finetuned
[Facebook's Hubert](https://ai.facebook.com/blog/hubert-self-supervised-representation-learning-for-speech-recognition-generation-and-compression)
The large model fine-tuned on 960h of Librispeech on 16kHz sampled speech audio. When using the model make sure that your speech input is also sa... | 72f2b3dfdcfe321de5de1fe72142d6db |
timm/convnext_tiny.fb_in22k_ft_in1k | timm | null | 4 | 518 | timm | 0 | image-classification | true | false | false | apache-2.0 | null | ['imagenet-1k', 'imagenet-22k'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['image-classification', 'timm'] | false | true | true | 21,428 | false | # Model card for convnext_tiny.fb_in22k_ft_in1k
A ConvNeXt image classification model. Pretrained on ImageNet-22k and fine-tuned on ImageNet-1k by paper authors.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model Stats:**
- Params (M): 28.6
- GMACs: 4.5
- Activations (M): 13.4... | 8f9d8c9355b2cbe4ec90cdd8779c62fd |
Xxanderr/ScraperTrainer | Xxanderr | gpt2 | 17 | 4 | transformers | 0 | text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 888 | false |
<!-- 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. -->
# ScraperTrainer
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
## Model descri... | b8afc79e8489762b252e911ee406aad3 |
GinaYang/xlm-roberta-base-finetuned-panx-en | GinaYang | xlm-roberta | 9 | 19 | transformers | 0 | token-classification | true | false | false | mit | null | ['xtreme'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,319 | false |
<!-- 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. -->
# xlm-roberta-base-finetuned-panx-en
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | cbc9cb369bd865aabb30a5b79af77f1e |
debbiesoon/longformer_summarise | debbiesoon | led | 13 | 29 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | ['scientific_papers'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,585 | false |
<!-- 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. -->
# longformer_summarise
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-1638... | ce94bbf07969f0e31070be6957b498c9 |
jonatasgrosman/exp_w2v2t_id_wav2vec2_s226 | jonatasgrosman | wav2vec2 | 10 | 7 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['id'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'id'] | false | true | true | 456 | false | # exp_w2v2t_id_wav2vec2_s226
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (id)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | 005e0282d749df332c10820a6ba56d63 |
spacy/de_core_news_lg | spacy | null | 32 | 13 | spacy | 0 | token-classification | false | false | false | mit | ['de'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['spacy', 'token-classification'] | false | true | true | 31,288 | false | ### Details: https://spacy.io/models/de#de_core_news_lg
German pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner.
| Feature | Description |
| --- | --- |
| **Name** | `de_core_news_lg` |
| **Version** | `3.5.0` |
| **spaCy** | `>=3.5.0,<3.6.... | c5d28b6d137c9ff9b6db956fa5034dc0 |
Helsinki-NLP/opus-mt-tc-base-tr-uk | Helsinki-NLP | marian | 13 | 3 | transformers | 0 | translation | true | true | false | cc-by-4.0 | ['tr', 'uk'] | null | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | ['translation', 'opus-mt-tc'] | true | true | true | 5,252 | false | # opus-mt-tc-base-tr-uk
Neural machine translation model for translating from Turkish (tr) to Ukrainian (uk).
This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All m... | a67b82c3537c9a5198392c1a98eb0413 |
Tirendaz/distilbert-base-uncased-finetuned-emotion | Tirendaz | distilbert | 14 | 7 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['emotion'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,343 | false |
<!-- 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. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | 7e82126e676ecb6285d897d0edf521e7 |
Nobody138/xlm-roberta-base-finetuned-panx-en | Nobody138 | xlm-roberta | 10 | 7 | transformers | 0 | token-classification | true | false | false | mit | null | ['xtreme'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,319 | false |
<!-- 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. -->
# xlm-roberta-base-finetuned-panx-en
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | a239a7bacf8cdf14503c957e07b35b79 |
KoichiYasuoka/deberta-base-thai-ud-goeswith | KoichiYasuoka | deberta-v2 | 10 | 444 | transformers | 0 | token-classification | true | false | false | apache-2.0 | ['th'] | ['universal_dependencies'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['thai', 'token-classification', 'pos', 'dependency-parsing'] | false | true | true | 2,713 | false |
# deberta-base-thai-ud-goeswith
## Model Description
This is a DeBERTa(V2) model pre-trained on Thai Wikipedia texts for POS-tagging and dependency-parsing (using `goeswith` for subwords), derived from [deberta-base-thai](https://huggingface.co/KoichiYasuoka/deberta-base-thai).
## How to Use
```py
class UDgoeswith... | a449056c5c39d290a50b53e7000802cc |
ricardo-filho/bert_base_tcm_no_objeto_0.8 | ricardo-filho | bert | 19 | 7 | transformers | 0 | token-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 9,334 | false |
<!-- 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. -->
# bert_base_tcm_no_objeto_0.8
This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co... | 0260721f35671450970a311a020a1b3f |
kit-nlp/bert-base-japanese-sentiment-cyberbullying | kit-nlp | bert | 9 | 177 | transformers | 1 | text-classification | true | false | true | cc-by-sa-4.0 | ['ja'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,227 | false |
# electra-base-cyberbullying
This is a BERT Base model for the Japanese language finetuned for automatic cyberbullying detection.
The model was based on [daigo's BERT Base for Japanese sentiment analysis](https://huggingface.co/daigo/bert-base-japanese-sentiment), and later finetuned on a balanced dataset created b... | f3b078fc87b9a90136d5a7bf39de91eb |
danielsaggau/lbert_scotus_classsification | danielsaggau | bert | 10 | 5 | transformers | 0 | text-classification | true | false | false | cc-by-sa-4.0 | null | ['lex_glue'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 934 | false |
<!-- 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. -->
# lbert_scotus_classsification
This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpa... | 4cf7cb517c694ae5008f1841621e39ba |
kontur-ai/sbert_punc_case_ru | kontur-ai | bert | 10 | 344 | transformers | 10 | token-classification | true | false | false | apache-2.0 | ['ru'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['PyTorch', 'Transformers'] | false | true | true | 1,445 | false |
# SbertPuncCase
SbertPuncCase - модель восстановления пунктуации и регистра для русского языка. Модель способна расставлять точки, запятые и знаки вопроса;
определять регистр - слово в нижнем регистре, слово с первой буквой в верхнем регистре, слово в верхнем регистре.
Модель разработана для восстановления текста по... | 3c5ff0d69fdb9d3ccd50ab2d92ccb3af |
WillHeld/en-bert-xnli | WillHeld | bert | 13 | 3 | transformers | 0 | text-classification | true | false | false | apache-2.0 | ['en'] | ['xnli'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 909 | false |
<!-- 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. -->
# en-bert-xnli
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the xnli dataset... | 488e14250d86984eea14a6f6427aedbc |
christofid/pgt | christofid | gpt2 | 10 | 2 | transformers | 0 | text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 3,509 | false | ### PGT
PGT is a GPT-2 prompt-based model trained to facilitate 3 patent generation-related tasks, namely: *part-of-patent generation*, *part-of-patent editing* and *patent coherence check*. For more information about the dataset and the training procedure with refer the reader to [our paper](https://openreview.net/p... | 394ca01da22102c5b387849658e762ce |
niclas/model_en | niclas | wav2vec2 | 10 | 7 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 5,250 | false |
<!-- 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. -->
# model_en
This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the ... | ca7602bd34b9aba50cdb813a1bc1ffc8 |
fimster/whisper-small-sv-SE | fimster | whisper | 12 | 9 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['sv'] | ['mozilla-foundation/common_voice_11_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['i-dont-know-what-im-doing', 'generated_from_trainer'] | true | true | true | 1,482 | false |
<!-- 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. -->
# Whisper Small sv-SE - Lab 2
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-s... | 660ad473cf5e98d33917fcdd6cbc3dae |
moaiz237/wav2vec2-base-timit-moaiz_exp2_new | moaiz237 | wav2vec2 | 12 | 6 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,345 | false |
<!-- 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-base-timit-moaiz_exp2_new
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/faceboo... | 1a087cd002266e67a48efbe9ea754507 |
responsibility-framing/predict-perception-bert-blame-assassin | responsibility-framing | bert | 12 | 19 | transformers | 0 | text-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 7,663 | false |
<!-- 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. -->
# predict-perception-bert-blame-assassin
This model is a fine-tuned version of [dbmdz/bert-base-italian-xxl-cased](https://hugging... | 0626fb33eb37e68553212cf0fc7fb835 |
jonatasgrosman/exp_w2v2t_nl_unispeech-ml_s498 | jonatasgrosman | unispeech | 10 | 5 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['nl'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'nl'] | false | true | true | 500 | false | # exp_w2v2t_nl_unispeech-ml_s498
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | 7cc8f935f8c6e2295d50dd09aa9da188 |
aXhyra/emotion_trained_1234567 | aXhyra | distilbert | 10 | 5 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['tweet_eval'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,401 | false |
<!-- 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. -->
# emotion_trained_1234567
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-u... | e31124506264fea723ad937d347ab17d |
jonatasgrosman/exp_w2v2t_de_r-wav2vec2_s460 | jonatasgrosman | wav2vec2 | 10 | 3 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['de'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'de'] | false | true | true | 462 | false | # exp_w2v2t_de_r-wav2vec2_s460
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | 53bb6ded9dd6b3fbb50b67cf95cc2092 |
comehu/sm64-ost | comehu | null | 13 | 0 | null | 0 | null | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['audio', 'music', 'generation', 'tensorflow'] | false | true | true | 1,034 | false |
# Musika Model: musika_sm64_ost
## Model provided by: comehu
Pretrained musika_sm64_ost model for the [Musika system](https://github.com/marcoppasini/musika) for fast infinite waveform music generation.
Introduced in [this paper](https://arxiv.org/abs/2208.08706).
## How to use
You can generate music from this pret... | 96af76f74e7d707b279551f8c3dbe229 |
tiennvcs/bert-large-uncased-finetuned-docvqa | tiennvcs | bert | 12 | 5 | transformers | 0 | question-answering | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | false | true | true | 7,214 | false |
<!-- 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. -->
# bert-large-uncased-finetuned-docvqa
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large... | 125c7fb70134c0c57c9ffd98c2286544 |
Helsinki-NLP/opus-mt-ig-fi | Helsinki-NLP | marian | 10 | 10 | transformers | 0 | translation | true | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 768 | false |
### opus-mt-ig-fi
* source languages: ig
* target languages: fi
* OPUS readme: [ig-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ig-fi/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-09.zip](http... | 25772c498f3977cf84807d5f1377a8d7 |
SiddharthaM/mbert-profane-final | SiddharthaM | bert | 12 | 1 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,192 | false |
<!-- 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. -->
# mbert-profane-final
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multil... | 343e48a039e74b44ed64413e8a161cf9 |
figfig/whisper-small-en | figfig | whisper | 26 | 55 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['en'] | ['figfig/restaurant_order_test'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['hf-asr-leaderboard', 'generated_from_trainer'] | true | true | true | 1,464 | false |
<!-- 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. -->
# restaurant_test_model
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) ... | d19cd7eb4579f5390db5c1cadd6f0c72 |
Hayoung/my_awesome_ko_en_model | Hayoung | t5 | 60 | 3 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,337 | false |
<!-- 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. -->
# my_awesome_ko_en_model
This model is a fine-tuned version of [KETI-AIR/ke-t5-small](https://huggingface.co/KETI-AIR/ke-t5-small)... | ed7bf59befcc6b7328d2268f2364859c |
cafeai/cafe_aesthetic | cafeai | beit | 9 | 9,275 | transformers | 12 | image-classification | true | false | false | agpl-3.0 | null | null | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | [] | false | true | true | 1,617 | false |
# Info
Since people are downloading this and I don't know why, I'll add some information. This model is an image classifier fine-tuned on `microsoft/beit-base-patch16-384`.
Its purpose is to be used in the dataset conditioning step for the [Waifu Diffusion project](https://huggingface.co/hakurei/waifu-diffusion), a f... | e4501fb3676335705fc70b72e88bca03 |
mictiong85/wav2vec2-base-timit-demo-colab | mictiong85 | wav2vec2 | 12 | 7 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,640 | false |
<!-- 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-base-timit-demo-colab
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wa... | fc5aaab529b28aec8bece9d332d16de3 |
Hetarth/marian-finetuned-hi-hinglish | Hetarth | marian | 9 | 3 | transformers | 0 | text2text-generation | false | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 1,361 | false |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# marian-finetuned-hi-hinglish
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-hi-en](https://huggingface.co/Helsinki-NLP/op... | 3b73a83f456e3e03f2ea7fdcacdf9c6a |
Qiliang/distilbart-xsum-12-3-whole_summary_chatGPT_and_tweetsum | Qiliang | bart | 13 | 718 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,692 | false |
<!-- 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. -->
# distilbart-xsum-12-3-whole_summary_chatGPT_and_tweetsum
This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-3](h... | 6ec2ef595911bb8e3c272a373222ee00 |
google/tapas-mini-finetuned-wtq | google | tapas | 8 | 44 | transformers | 1 | table-question-answering | true | true | false | apache-2.0 | ['en'] | ['wikitablequestions'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['tapas', 'table-question-answering'] | false | true | true | 7,105 | false |
# TAPAS mini model fine-tuned on WikiTable Questions (WTQ)
This model has 2 versions which can be used. The default version corresponds to the `tapas_wtq_wikisql_sqa_inter_masklm_mini_reset` checkpoint of the [original Github repository](https://github.com/google-research/tapas).
This model was pre-trained on MLM and... | 6335a70a7c99c7112601cfb62c2c768c |
ajtamayoh/Negation_Scope_Detection_SFU_Spanish_NLP-CIC-WFU_DisTEMIST_fine_tuned | ajtamayoh | bert | 12 | 5 | transformers | 0 | token-classification | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,000 | false |
<!-- 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. -->
# Negation_Scope_Detection_SFU_Spanish_NLP-CIC-WFU_DisTEMIST_fine_tuned
This model is a fine-tuned version of [ajtamayoh/NER_EHR_S... | 7d56278fbffbe58f84d98e40ae8ee2ca |
sd-concepts-library/nouns-glasses | sd-concepts-library | null | 9 | 0 | null | 0 | null | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,105 | false | ### nouns glasses on Stable Diffusion
This is the `<nouns glasses>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) notebook. You... | 3c4fbe623b7ff31a3c04cdf4ef6fd747 |
Oleksandr2003/QA_model | Oleksandr2003 | xlm-roberta | 29 | 20 | transformers | 0 | question-answering | true | true | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,263 | false |
<!-- 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. -->
# QA_model
This model is a fine-tuned version of [ukr-models/xlm-roberta-base-uk](https://huggingface.co/ukr-models/xlm-roberta-ba... | 1e8adb1103e9d4386625d28abb0b260e |
gchhablani/bert-large-cased-finetuned-mrpc | gchhablani | bert | 71 | 16 | transformers | 1 | text-classification | true | false | false | apache-2.0 | ['en'] | ['glue'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,678 | false |
<!-- 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. -->
# bert-large-cased-finetuned-mrpc
This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased... | 509ae55760aee726d70cdc10041cf0a4 |
Huyen2310/Vin-P2-14000 | Huyen2310 | whisper | 15 | 0 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['vi'] | ['mozilla-foundation/common_voice_11_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['hf-asr-leaderboard', 'generated_from_trainer'] | true | true | true | 1,012 | false |
<!-- 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. -->
# HuyenNguyen
This model is a fine-tuned version of [Huyen2310/FPT-S15000](https://huggingface.co/Huyen2310/FPT-S15000) on the Com... | cb81e78601f4f454c4bba93b16281612 |
PrimeQA/listqa_nq-task-xlm-roberta-large | PrimeQA | xlm-roberta | 9 | 0 | transformers | 0 | null | true | false | false | apache-2.0 | ['multilingual'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['MRC', 'Natural Questions List', 'xlm-roberta-large'] | false | true | true | 2,587 | false |
# Model description
An XLM-RoBERTa reading comprehension model for List Question Answering using a fine-tuned [xlm-roberta-large](https://huggingface.co/xlm-roberta-large/) model that is further fine-tuned on the list questions in the [Natural Questions](https://huggingface.co/datasets/natural_questions) dataset.
##... | 1995f4856a4208f495e76ee86f9cf565 |
jonatasgrosman/exp_w2v2t_zh-cn_r-wav2vec2_s79 | jonatasgrosman | wav2vec2 | 10 | 5 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['zh-CN'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'zh-CN'] | false | true | true | 467 | false | # exp_w2v2t_zh-cn_r-wav2vec2_s79
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (zh-CN)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your... | c8aec4187a5d5a9f4de5e7296faf4d31 |
microsoft/git-base-textcaps | microsoft | git | 10 | 145 | transformers | 0 | image-to-text | true | false | false | mit | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['vision', 'image-captioning'] | false | true | true | 3,031 | false |
# GIT (GenerativeImage2Text), base-sized, fine-tuned on TextCaps
GIT (short for GenerativeImage2Text) model, base-sized version, fine-tuned on TextCaps. It was introduced in the paper [GIT: A Generative Image-to-text Transformer for Vision and Language](https://arxiv.org/abs/2205.14100) by Wang et al. and first relea... | d320e2f76b7384f76075809cae0fbc98 |
KarelDO/bert-base-uncased.CEBaB_confounding.uniform.absa.5-class.seed_44 | KarelDO | bert | 14 | 2 | transformers | 0 | null | true | false | false | apache-2.0 | ['en'] | ['OpenTable'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,124 | false |
<!-- 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. -->
# bert-base-uncased.CEBaB_confounding.uniform.absa.5-class.seed_44
This model is a fine-tuned version of [bert-base-uncased](https... | 2f08e2bf9de5c2e483c65f7da8ef502e |
bigscience/mt0-large | bigscience | mt5 | 8 | 956 | transformers | 8 | text-generation | true | false | false | apache-2.0 | ['af', 'am', 'ar', 'az', 'be', 'bg', 'bn', 'ca', 'ceb', 'co', 'cs', 'cy', 'da', 'de', 'el', 'en', 'eo', 'es', 'et', 'eu', 'fa', 'fi', 'fil', 'fr', 'fy', 'ga', 'gd', 'gl', 'gu', 'ha', 'haw', 'hi', 'hmn', 'ht', 'hu', 'hy', 'ig', 'is', 'it', 'iw', 'ja', 'jv', 'ka', 'kk', 'km', 'kn', 'ko', 'ku', 'ky', 'la', 'lb', 'lo', 'lt... | ['bigscience/xP3', 'mc4'] | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | [] | true | true | true | 8,932 | false |
# Table of Contents
1. [Model Summary](#model-summary)
2. [Use](#use)
3. [Limitations](#limitations)
4. [Training](#training)
5. [Evaluation](#evaluation)
7. [Citation](#citation)
# Model Summary
> We present BLOOMZ & mT0, a... | 7ab4a8168099b69ac0fd5562e798494d |
ontocord/vlt5 | ontocord | t5 | 7 | 15 | transformers | 0 | null | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,475 | false | Install lumi:
```
git clone https://github.com/ontocord/lumi
pip install transformers sentencepiece
```
Install models:
```
from lumi.modeling_vlt5 import *
from lumi.tokenization_vlt5 import *
from lumi.modeling_dalle import *
import torch
minidalle = DalleModel.from_pretrained("ontocord/minidalle").eval().half().to... | 3944b9af25690dfedbbb6d055d4fbf44 |
sasi2400/GFMgenderDetection | sasi2400 | bert | 17 | 39 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer', 'gender'] | true | true | true | 1,278 | false |
<!-- 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. -->
# GFMgenderDetection
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multili... | 60d56a2a92cae79ed203026c5bc8ffe7 |
nguyenkhoa2407/xlm-roberta-base-NER-favsbot | nguyenkhoa2407 | xlm-roberta | 10 | 11 | transformers | 0 | token-classification | true | false | false | mit | null | ['favsbot'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 3,091 | false |
<!-- 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. -->
# xlm-roberta-base-NER-favsbot
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) o... | ca9fed22bccd1e3a9aff487761813635 |
cjvt/t5-sl-small | cjvt | t5 | 8 | 139 | transformers | 0 | text2text-generation | true | false | false | cc-by-sa-4.0 | ['sl'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 866 | false |
# t5-sl-small
t5-sl-small model is a Slovene T5 model. It has 8 encoder and 8 decoder layers, in total about 60 million parameters.
It was trained for 5 epochs on the following corpora:
## Corpora
The following corpora were used for training the model:
* Gigafida 2.0
* Kas 1.0
* Janes 1.0 (only Janes-news, Janes-foru... | c6cf7a8be24bcec26def1db182ac1cbb |
jonatasgrosman/exp_w2v2t_pl_vp-nl_s632 | jonatasgrosman | wav2vec2 | 10 | 5 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['pl'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'pl'] | false | true | true | 469 | false | # exp_w2v2t_pl_vp-nl_s632
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | 4a684bad2ba145fe92849ba8bf6d8540 |
bigcode/santacoder-megatron | bigcode | null | 4 | 0 | null | 1 | text-generation | false | false | false | openrail | ['code'] | ['bigcode/the-stack'] | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | [] | true | true | true | 3,000 | false |
# SantaCoder
Play with the model on the [SantaCoder Space Demo](https://huggingface.co/spaces/bigcode/santacoder-demo).
# Table of Contents
1. [Model Summary](#model-summary)
2. [Use](#use)
3. [Limitations](#limitations)
4. [Training... | e1a3050abee5b7538807a12b298ae35f |
G80/detr-resnet-50_finetuned_cppe5 | G80 | detr | 9 | 15 | transformers | 0 | object-detection | true | false | false | apache-2.0 | null | ['cppe-5'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 982 | false |
<!-- 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. -->
# detr-resnet-50_finetuned_cppe5
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/d... | 278e6e232b5d3c3aff83e8f51a0197fc |
hfl/rbt4-h312 | hfl | bert | 6 | 986 | transformers | 3 | fill-mask | true | true | false | apache-2.0 | ['zh'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['bert'] | false | true | true | 914 | false |
# Please use 'Bert' related functions to load this model!
## Chinese small pre-trained model MiniRBT
In order to further promote the research and development of Chinese information processing, we launched a Chinese small pre-training model MiniRBT based on the self-developed knowledge distillation tool TextBrewer, c... | 18f94a0889631c7789df00803d171966 |
Ruth/gbert-large-germaner | Ruth | bert | 19 | 11 | transformers | 0 | token-classification | false | true | false | mit | ['de'] | ['germaner'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | true | true | true | 975 | false |
<!-- 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. -->
# gbert-large-germaner
This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on ... | eecbbd633538ae01d52f5c4b5f06b3cc |
qBob/BART_corrector | qBob | bart | 29 | 1 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,503 | false |
<!-- 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_corrector
This model is a fine-tuned version of [ainize/bart-base-cnn](https://huggingface.co/ainize/bart-base-cnn) on a ho... | 91705ed3e252783718ecb340e2ee37f6 |
elRivx/megaPals2.1 | elRivx | null | 3 | 0 | null | 0 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['stable-diffusion', 'text-to-image'] | false | true | true | 1,522 | false |
**megaPals2.1**
Hi guys! Do you remember the superhero vintage animated series? Do you like the 70s style? This Stable Diffusion 2.1 embedding is for you! Some recomendations: the magic word for your prompts is megaPals.
If you enjoy my work, please consider supporting me:
[ for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | 3067a847c980b48e3cc70a419139c92c |
Yotta/XpCoDir2 | Yotta | bert | 6 | 1 | transformers | 0 | feature-extraction | true | false | false | apache-2.0 | null | ['XpCo'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 884 | false |
<!-- 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. -->
# XpCoDir2
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the XpCoDataset ... | d0ab9816a07d03c87016e3d8b005c95e |
gary109/wav2vec2-base-finetuned-ks | gary109 | wav2vec2 | 10 | 3 | transformers | 0 | audio-classification | true | false | false | apache-2.0 | null | ['superb'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,560 | false |
<!-- 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-base-finetuned-ks
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2ve... | 1869ae818e73ea96b728516ad0ac8bb1 |
augustocsc/gpt-m0 | augustocsc | gpt2 | 7 | 0 | transformers | 0 | text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,103 | false |
<!-- 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. -->
# gpt-m0
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following ... | 3cd3343d9b949805f3ca7e6d2722eca8 |
Qiliang/bart-large-cnn-samsum-ElectrifAi_v8.3 | Qiliang | bart | 13 | 303 | transformers | 0 | text2text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,679 | false |
<!-- 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-large-cnn-samsum-ElectrifAi_v8.3
This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingfa... | 7bcc5af26b44366c99f5708309644aa7 |
ankurani/roberta-base-finetuned-ner | ankurani | roberta | 11 | 3 | transformers | 0 | token-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 892 | false |
<!-- 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. -->
# roberta-base-finetuned-ner
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unkno... | cac06f7ae16ac5a84cc3cd111963ecb6 |
Helsinki-NLP/opus-mt-sv-hu | Helsinki-NLP | marian | 10 | 15 | transformers | 0 | translation | true | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 770 | false |
### opus-mt-sv-hu
* source languages: sv
* target languages: hu
* OPUS readme: [sv-hu](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sv-hu/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-26.zip](http... | 2550a84beec69f4f5d20641af1e82c2f |
gokuls/distilbert_add_GLUE_Experiment_stsb_192 | gokuls | distilbert | 17 | 4 | transformers | 0 | text-classification | true | false | false | apache-2.0 | ['en'] | ['glue'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,238 | false |
<!-- 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. -->
# distilbert_add_GLUE_Experiment_stsb_192
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | 4c1470bf9c5b8c9383761add56255bbd |
eslamxm/mt5-base-finetuned-persian | eslamxm | mt5 | 13 | 5 | transformers | 0 | summarization | true | false | false | apache-2.0 | null | ['xlsum'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['summarization', 'persian', 'generated_from_trainer'] | true | true | true | 1,892 | false |
<!-- 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. -->
# mt5-base-finetuned-persian
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on th... | c8eeae615dca0d970068294e52d0d2be |
jhu-clsp/LegalBert | jhu-clsp | bert | 9 | 6 | transformers | 0 | null | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,383 | false | # Model description
LegalBert is a BERT-base-cased model fine-tuned on a subset of the `case.law` corpus. Further details can be found in this paper:
[A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering](http://ceur-ws.org/Vol-2645/paper5.pdf)
Nils Holzenberger, Andrew Blair-Stanek and Be... | a63983cde61f6f83f4da77b5baee6998 |
huawei-noah/AutoTinyBERT-S4 | huawei-noah | null | 5 | 1 | transformers | 0 | null | true | false | false | other | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 561 | false | Pre-trained language models (PLMs) have achieved great success in natural language processing. Most of PLMs follow the default setting of architecture hyper-parameters (e.g., the hidden dimension is a quarter of the intermediate dimension in feed-forward sub-networks) in BERT. In this paper, we adopt the one-shot Neura... | 2361910815607479c0006311d517de5e |
bayartsogt/whisper-small-mn-12 | bayartsogt | whisper | 19 | 23 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['mn'] | ['mozilla-foundation/common_voice_11_0', 'google/fleurs', 'bayartsogt/ulaanbal-v0', 'bayartsogt/youtube-mongolian-v1'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['whisper-event', 'hf-asr-leaderboard', 'generated_from_multiple_datasets'] | true | true | true | 3,061 | false |
<!-- 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. -->
# whisper-small-mn-12
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on... | 5e29a034c1b0d08647e37279f76d88ac |
Helsinki-NLP/opus-mt-es-zai | Helsinki-NLP | marian | 10 | 7 | transformers | 0 | translation | true | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 776 | false |
### opus-mt-es-zai
* source languages: es
* target languages: zai
* OPUS readme: [es-zai](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/es-zai/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | 66664ce80639b0fe1d1319e9e66068c7 |
osyvokon/xslr-commonvoice | osyvokon | wav2vec2 | 18 | 8 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['tr'] | ['common_voice'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'common_voice', 'generated_from_trainer'] | true | true | true | 2,265 | false |
<!-- 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. -->
# xslr-commonvoice
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec... | 2defe4c1ce477680e7a469371923d236 |
Shubham09/complete_Wav2Vec2_500 | Shubham09 | wav2vec2 | 17 | 3 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,039 | false |
<!-- 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. -->
# complete_Wav2Vec2_500
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2v... | a289840734a8db155f1bdc8314b50f1f |
sd-concepts-library/dovin-baan | sd-concepts-library | null | 26 | 0 | null | 0 | null | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 2,631 | false | ### Magic: The Gathering Stable Diffusion Textual Inversion Embeddings
Check all MTG related models [here](https://darioft.github.io/stable-diffusion-textual-inversion-mtg-models/)!
### dovin-baan on Stable Diffusion
This is the `<dovin-baan>` concept taught to Stable Diffusion via Textual Inversion. You can load this... | a82399e75ebb248f044f1ab9a1a4c491 |
jhaochenz/finetuned_distilgpt2_sst2_negation0.001_pretrainedTrue_epochs3 | jhaochenz | gpt2 | 17 | 1 | transformers | 0 | text-generation | true | false | false | apache-2.0 | null | ['sst2'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,266 | false |
<!-- 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. -->
# finetuned_distilgpt2_sst2_negation0.001_pretrainedTrue_epochs3
This model is a fine-tuned version of [distilgpt2](https://huggin... | 480b175952f1227698cb80139bb12658 |
gababas/m3rrw3 | gababas | null | 16 | 2 | diffusers | 0 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['text-to-image', 'stable-diffusion'] | false | true | true | 415 | false | ### m3rrw3 Dreambooth model trained by gababas with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable-dif... | d3f2447f45cbecd55d58a6ac5be614d3 |
KeaponLaffin/tippy | KeaponLaffin | null | 18 | 11 | diffusers | 0 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['text-to-image', 'stable-diffusion'] | false | true | true | 612 | false | ### Tippy Dreambooth model trained by KeaponLaffin with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable... | 9c720d329e0b404a8c37cad494c383cc |
espnet/Shinji_Watanabe_librispeech_asr_train_asr_transformer_e18_raw_bpe_sp_valid.acc.best | espnet | null | 10 | 1 | espnet | 0 | automatic-speech-recognition | false | false | false | cc-by-4.0 | ['en'] | ['librispeech'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['espnet', 'audio', 'automatic-speech-recognition'] | false | true | true | 1,862 | false | ## Example ESPnet2 ASR model
### `Shinji_Watanabe/librispeech_asr_train_asr_transformer_e18_raw_bpe_sp_valid.acc.best`
♻️ Imported from https://zenodo.org/record/4030677/
This model was trained by Shinji Watanabe using librispeech/asr1 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESP... | 2d3c0619b667e7a31e4b9f90f54780da |
Zeynabrz/movie_recommender | Zeynabrz | null | 8 | 0 | null | 0 | null | false | false | false | zlib | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 4,907 | false |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
# Mod... | 5cf4c6c82ca7f379d52993debbd383ed |
google/t5-efficient-tiny-ff12000 | google | t5 | 12 | 8 | transformers | 0 | text2text-generation | true | true | true | apache-2.0 | ['en'] | ['c4'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['deep-narrow'] | false | true | true | 6,263 | false |
# T5-Efficient-TINY-FF12000 (Deep-Narrow version)
T5-Efficient-TINY-FF12000 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://huggingface.co/docs/transformers/model_doc/t5).
It is a *pretrained-only* check... | 2b010a61efdeb5b81297707ac41295fc |
doc2query/stackexchange-title-body-t5-base-v1 | doc2query | t5 | 11 | 3 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | ['en'] | ['flax-sentence-embeddings/stackexchange_title_body_jsonl'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 2,841 | false |
# doc2query/stackexchange-title-body-t5-base-v1
This is a [doc2query](https://arxiv.org/abs/1904.08375) model based on T5 (also known as [docT5query](https://cs.uwaterloo.ca/~jimmylin/publications/Nogueira_Lin_2019_docTTTTTquery-v2.pdf)).
It can be used for:
- **Document expansion**: You generate for your para... | 96894d3f86bdd5df6b9c837fb1c9e2e2 |
sameearif88/wav2vec2-base-timit-demo-colab3 | sameearif88 | wav2vec2 | 14 | 5 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,341 | false |
<!-- 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-base-timit-demo-colab3
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/w... | d7392021e2ba0504ea0f88d92dcfe0b5 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.