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google/multiberts-seed_4-step_1000k | google | bert | 8 | 33 | transformers | 0 | null | true | true | false | apache-2.0 | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['multiberts', 'multiberts-seed_4', 'multiberts-seed_4-step_1000k'] | false | true | true | 3,527 | false |
# MultiBERTs, Intermediate Checkpoint - Seed 4, Step 1000k
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://github.com/google-research/bert) but
with differe... | 4285762bf791210792aadcc46a504ed0 |
ajtamayoh/NER_ehealth_Spanish_mBERT_fine_tuned | ajtamayoh | bert | 14 | 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 | 2,386 | 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. -->
# NER_ehealth_Spanish_mBERT_fine_tuned
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co... | 2e99b273e09ef1abea549261ae7f52fb |
jonatasgrosman/exp_w2v2t_fr_wav2vec2_s227 | jonatasgrosman | wav2vec2 | 10 | 5 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['fr'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'fr'] | false | true | true | 456 | false | # exp_w2v2t_fr_wav2vec2_s227
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 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | 2831799ebf9edcdb62fa1f29f9f9ac5d |
PabloZubeldia/distilbert-base-uncased-finetuned-tweets | PabloZubeldia | distilbert | 24 | 3 | 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 | 1,553 | 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-tweets
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | 930663fede03e36c860572151020e87a |
DOOGLAK/Tagged_One_250v5_NER_Model_3Epochs_AUGMENTED | DOOGLAK | bert | 13 | 5 | transformers | 0 | token-classification | true | false | false | apache-2.0 | null | ['tagged_one250v5_wikigold_split'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,565 | 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. -->
# Tagged_One_250v5_NER_Model_3Epochs_AUGMENTED
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert... | 99f1f86f32061ea33e81a2f56508090b |
Khalsuu/english-filipino-wav2vec2-l-xls-r-test-06 | Khalsuu | wav2vec2 | 13 | 7 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | ['filipino_voice'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,187 | 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. -->
# english-filipino-wav2vec2-l-xls-r-test-06
This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](... | 6c50bb99da5b8b391bbaec9d697c1232 |
mqy/mt5-small-finetuned-18jan-4 | mqy | mt5 | 15 | 4 | transformers | 0 | summarization | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['summarization', 'generated_from_trainer'] | true | true | true | 2,152 | 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-small-finetuned-18jan-4
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on... | fe6bf9f509391e9766194257746c0028 |
mqy/mt5-small-finetuned-12feb-1 | mqy | mt5 | 17 | 0 | transformers | 0 | summarization | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['summarization', 'generated_from_trainer'] | true | true | true | 1,904 | 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-small-finetuned-12feb-1
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on... | 9b6560da7f4ae4395a9443934980224e |
burakyldrm/wav2vec2-full-small_gpu_deneme4 | burakyldrm | wav2vec2 | 15 | 8 | 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 | 1,087 | 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-full-small_gpu_deneme4
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | fff0164b615714fe587a80fc6c799223 |
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s306 | jonatasgrosman | unispeech-sat | 10 | 7 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['it'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'it'] | false | true | true | 463 | false | # exp_w2v2t_it_unispeech-sat_s306
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | a1286de1106a94d18ff8bf8a96b12cbd |
fulviodan/ddpm-butterflies-128 | fulviodan | null | 13 | 3 | diffusers | 0 | null | false | false | false | apache-2.0 | ['en'] | ['huggan/smithsonian_butterflies_subset'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,231 | false |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# ddpm-butterflies-128
## Model description
This diffusion model is trained with the [🤗 Diffusers](https://github.com/hu... | dc27bd8ec5d6c47110b97d2dd507f948 |
Arnold/wav2vec2-large-xlsr-hausa2-demo-colab | Arnold | wav2vec2 | 18 | 11 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | ['common_voice'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,556 | 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-large-xlsr-hausa2-demo-colab
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingfac... | 898ae311392f4a39d1148bcb3d08be09 |
Helsinki-NLP/opus-mt-kqn-sv | 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-kqn-sv
* source languages: kqn
* target languages: sv
* OPUS readme: [kqn-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/kqn-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-09.zip](... | e86dc333cf9326f5c640871f3c0df897 |
IMSyPP/hate_speech_en | IMSyPP | bert | 7 | 1,747 | transformers | 5 | text-classification | true | false | false | mit | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 652 | false |
# Hate Speech Classifier for Social Media Content in English Language
A monolingual model for hate speech classification of social media content in English language. The model was trained on 103190 YouTube comments and tested on an independent test set of 20554 YouTube comments. It is based on English BERT base pre-t... | a547308e307eecba97e5b065d552b3e8 |
Avrik/abstract-anim-spritesheets | Avrik | null | 22 | 44 | diffusers | 16 | text-to-image | false | false | false | creativeml-openrail-m | ['en'] | null | null | 3 | 0 | 3 | 0 | 2 | 2 | 0 | ['stable-diffusion', 'text-to-image', 'image-to-image'] | false | true | true | 2,246 | false | # Abstract Animation Sprite Sheets
An experimental Dreambooth model trained on individual frames of looping 3D animations that were then laid out on a 4x4 grid. Generates sprite sheets that can create very interesting abstract animations.
Use the token **AbstrAnm spritesheet**. Size must be set at 512x512 or your out... | 4b27bce4148f90dcdad8f6cc1859912e |
fahadtouseef/wav2vec2-base-timit-demo-colab_3 | fahadtouseef | wav2vec2 | 12 | 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 | 1,670 | 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_3
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/... | d45cdc5ff710ad38df692dd048cbc979 |
rajat99/Fine_Tuning_XLSR_300M_testing_6_model | rajat99 | wav2vec2 | 9 | 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 | 1,349 | 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. -->
# Fine_Tuning_XLSR_300M_testing_6_model
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.c... | e7d04393e4cea72629c5891105c8850f |
Helsinki-NLP/opus-mt-de-nso | 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-de-nso
* source languages: de
* target languages: nso
* OPUS readme: [de-nso](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-nso/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-20.zip](... | 5d82ae29ce4508767cbf2358b7b2f5a7 |
edugp/kenlm | edugp | null | 167 | 0 | null | 9 | null | false | false | false | mit | ['es', 'af', 'ar', 'arz', 'as', 'bn', 'fr', 'sw', 'eu', 'ca', 'zh', 'en', 'hi', 'ur', 'id', 'pt', 'vi', 'gu', 'kn', 'ml', 'mr', 'ta', 'te', 'yo'] | ['wikipedia', 'oscar'] | null | 0 | 0 | 0 | 0 | 2 | 1 | 1 | ['kenlm', 'perplexity', 'n-gram', 'kneser-ney', 'bigscience'] | false | true | true | 2,467 | false |
# KenLM models
This repo contains several KenLM models trained on different tokenized datasets and languages.
KenLM models are probabilistic n-gram languge models that models. One use case of these models consist on fast perplexity estimation for [filtering or sampling large datasets](https://huggingface.co/bertin-p... | a07f4937d88c6260c98058dceb7f5f34 |
NimaBoscarino/efficientformer-l7-300 | NimaBoscarino | null | 5 | 0 | timm | 0 | image-classification | false | false | false | apache-2.0 | ['en'] | ['imagenet-1k'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['mobile', 'vison', 'image-classification'] | false | true | true | 3,704 | false |
# EfficientFormer-L7
## Table of Contents
- [EfficientFormer-L7](#-model_id--defaultmymodelname-true)
- [Table of Contents](#table-of-contents)
- [Model Details](#model-details)
- [How to Get Started with the Model](#how-to-get-started-with-the-model)
- [Uses](#uses)
- [Direct Use](#direct-use)
- ... | 1d63eaf4c91a9f3db544afe686fb5bee |
SirVeggie/mixes | SirVeggie | null | 8 | 0 | null | 5 | null | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 4,723 | false |
# Model mixes
Custom models created by combining different models together.
You can and should influence the style of these models by mentioning the keywords of the artists included at a sufficiently high weight:\
For example (m_wlop illustration style:1.3)
## Symbol legend
```
A + B = weighted sum
A + (B - C) = ad... | 3f9447ac19e9fe5f398271b4765e43d2 |
gsdf/Replicant | gsdf | null | 11 | 0 | diffusers | 24 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['stable-diffusion', 'stable-diffusion-diffusers', 'text-to-image', 'diffusers'] | false | true | true | 6,595 | false | # Please enable hires. fix when using it.
Replicant is built by merging several models with fine-tuning WD1.4 and photorealistic SD2.0 models that works with danbooru tags.I trained 4 models to merge and prepared several LoRa models for tuning.As with SD1.x, merging individually trained models is better quality tha... | 22fc35ea63a98a789b7ef833037c49d7 |
leokai/distilroberta-base-wikitextepoch_50 | leokai | roberta | 6 | 2 | 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 | 3,757 | 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. -->
# distilroberta-base-wikitextepoch_50
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilrobe... | 7bcac475ce8cbc81eaf835ed180d9f71 |
cemsubakan/cnn14-esc50 | cemsubakan | null | 7 | 4 | null | 0 | null | false | false | false | apache-2.0 | ['en'] | ['ESC50'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['Sound Classification', 'CNN14'] | false | true | true | 2,570 | false |
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
<br/><br/>
# CNN14 Trained on VGGSound dataset with SimCLR and Fine Tuned on ESC50
This repository provides all the nec... | e944b495c9e72a23881adb0a7de73b19 |
ArBert/bert-base-uncased-finetuned-ner | ArBert | bert | 12 | 4 | 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 | 1,533 | 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-finetuned-ner
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncas... | 5a466f5a017335b3f0a7df182392be0d |
Helsinki-NLP/opus-mt-en-itc | Helsinki-NLP | marian | 11 | 8 | transformers | 1 | translation | true | true | false | apache-2.0 | ['en', 'it', 'ca', 'rm', 'es', 'ro', 'gl', 'sc', 'co', 'wa', 'pt', 'oc', 'an', 'id', 'fr', 'ht', 'itc'] | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 5,233 | false |
### eng-itc
* source group: English
* target group: Italic languages
* OPUS readme: [eng-itc](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-itc/README.md)
* model: transformer
* source language(s): eng
* target language(s): arg ast cat cos egl ext fra frm_Latn gcf_Latn glg hat ind ita ... | 582bc4d60fc0f2ac280aff045e7638a9 |
Helsinki-NLP/opus-mt-tr-az | Helsinki-NLP | marian | 11 | 28 | transformers | 1 | translation | true | true | false | apache-2.0 | ['tr', 'az'] | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 1,997 | false |
### tur-aze
* source group: Turkish
* target group: Azerbaijani
* OPUS readme: [tur-aze](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/tur-aze/README.md)
* model: transformer-align
* source language(s): tur
* target language(s): aze_Latn
* model: transformer-align
* pre-processing: normali... | 83b4ded85f8f36f3eb2bb59456790697 |
DrishtiSharma/lwg_chebakia | DrishtiSharma | null | 4 | 0 | transformers | 0 | null | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['huggan', 'gan'] | false | true | true | 775 | false |
# MyModelName
## Model description
Describe the model here (what it does, what it's used for, etc.)
## Intended uses & limitations
#### How to use
```python
# You can include sample code which will be formatted
```
#### Limitations and bias
Provide examples of latent issues and potential remediations.
## Train... | a6e2b485983a99e6ad784e4da1cc69ad |
Sounak/bert-large-finetuned | Sounak | bert | 8 | 3 | transformers | 0 | question-answering | false | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 1,413 | 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. -->
# Sounak/bert-large-finetuned
This model is a fine-tuned version of [bert-large-uncased-whole-word-masking-finetuned-squad](https://hugg... | 6e6c6349af641ecc064f5931f78225b3 |
Lemswasabi/wav2vec2-base-luxembourgish-4h-with-lm | Lemswasabi | wav2vec2 | 14 | 0 | transformers | 0 | automatic-speech-recognition | true | false | false | mit | ['lb'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'generated_from_trainer'] | false | true | true | 1,810 | 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 description
We pre-trained a wav2vec 2.0 base model on 842h of unlabelled Luxembourgish speech
collected from [RTL.lu... | 0fe3f510417ccd3f78dfcdf1b2ed2c03 |
ali2066/finetuned_token_itr0_3e-05_all_16_02_2022-20_12_04 | ali2066 | distilbert | 13 | 10 | 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 | 1,796 | 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_token_itr0_3e-05_all_16_02_2022-20_12_04
This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-... | e8fdbd38ea2daf07cb68a1056a4e7e93 |
BatuhanYilmaz/dummy-model | BatuhanYilmaz | camembert | 4 | 2 | transformers | 0 | fill-mask | false | true | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 822 | 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. -->
# dummy-model
This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
It ac... | ebbbab8e6fe4f894d488bd5864f09a10 |
tucan9389/distilbert-base-uncased-finetuned-squad | tucan9389 | distilbert | 12 | 5 | transformers | 0 | question-answering | true | false | false | apache-2.0 | null | ['squad'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,285 | 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-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | e32cd619dd700a951c49f20c6623b5c0 |
elliotthwang/mt5-small-finetuned-tradition-zh | elliotthwang | mt5 | 16 | 1 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | ['xlsum'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,802 | 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-small-finetuned-tradition-zh
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-smal... | c3ac2f23cad9b3bdea266e0766021ef3 |
tomekkorbak/hopeful_newton | tomekkorbak | null | 2 | 0 | null | 0 | null | false | false | false | mit | ['en'] | ['tomekkorbak/pii-pile-chunk3-0-50000', 'tomekkorbak/pii-pile-chunk3-50000-100000', 'tomekkorbak/pii-pile-chunk3-100000-150000', 'tomekkorbak/pii-pile-chunk3-150000-200000', 'tomekkorbak/pii-pile-chunk3-200000-250000', 'tomekkorbak/pii-pile-chunk3-250000-300000', 'tomekkorbak/pii-pile-chunk3-300000-350000', 'tomekkorba... | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 8,009 | 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. -->
# hopeful_newton
This model was trained from scratch on the tomekkorbak/pii-pile-chunk3-0-50000, the tomekkorbak/pii-pile-chunk3-5... | 40fa81d3952f09a1a9d01a888751dd05 |
google/mt5-small | google | mt5 | 10 | 193,292 | transformers | 37 | text2text-generation | true | true | true | apache-2.0 | ['multilingual', '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',... | ['mc4'] | null | 2 | 0 | 1 | 1 | 0 | 0 | 0 | [] | false | true | true | 2,246 | false |
[Google's mT5](https://github.com/google-research/multilingual-t5)
mT5 is pretrained on the [mC4](https://www.tensorflow.org/datasets/catalog/c4#c4multilingual) corpus, covering 101 languages:
Afrikaans, Albanian, Amharic, Arabic, Armenian, Azerbaijani, Basque, Belarusian, Bengali, Bulgarian, Burmese, Catalan, Cebua... | 8ece6e015d555d9189ab3b98c4314480 |
gokuls/mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_cola_128 | gokuls | mobilebert | 17 | 0 | 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 | 1,717 | false |
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# mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_cola_128
This model is a fine-tuned version of [google/mobilebert-uncased](https... | e24b075767c2c8235c3621ff86306811 |
jonatasgrosman/exp_w2v2t_nl_vp-sv_s607 | jonatasgrosman | wav2vec2 | 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 | 469 | false | # exp_w2v2t_nl_vp-sv_s607
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | 2f0e4d618eda41f349bdd47589e9efac |
Williamlokok/ddpm-butterflies-128 | Williamlokok | null | 27 | 1 | diffusers | 0 | null | false | false | false | apache-2.0 | ['en'] | ['cars'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,201 | false |
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# ddpm-butterflies-128
## Model description
This diffusion model is trained with the [🤗 Diffusers](https://github.com/hu... | 38e12942043eeea386af6ee37f583fef |
ykleeee/wav2vec2-5epochs-3e4 | ykleeee | wav2vec2 | 13 | 0 | 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 | 2,056 | false |
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# wav2vec2-owndata
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec... | 342cc7b45d1018ff040fc9baec2e8164 |
Supreeth/distilbert-base-uncased-MLM | Supreeth | distilbert | 16 | 9 | 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 | 1,045 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-MLM
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-ba... | a39b54c63153549fee14fcc2397f3237 |
dxiao/bert-finetuned-ner-80percent | dxiao | 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 | 1,525 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-finetuned-ner-80percent
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on ... | d005a1662dbc974eb9518fa07f78ef72 |
jonatasgrosman/exp_w2v2r_en_xls-r_gender_male-10_female-0_s287 | jonatasgrosman | wav2vec2 | 10 | 1 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['en'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'en'] | false | true | true | 477 | false | # exp_w2v2r_en_xls-r_gender_male-10_female-0_s287
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure... | acfc69349df5810b18802642226131c4 |
google/t5-efficient-small-nl8 | google | t5 | 12 | 7 | 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 | 6,251 | false |
# T5-Efficient-SMALL-NL8 (Deep-Narrow version)
T5-Efficient-SMALL-NL8 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* checkpoint ... | a0cc0a3dca479e6c28936121e4b83f07 |
Helsinki-NLP/opus-mt-es-bzs | 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-bzs
* source languages: es
* target languages: bzs
* OPUS readme: [es-bzs](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/es-bzs/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | 5628ddbbcd2fcb3e5ebab076d15658e6 |
gunyoung/distilbert-base-uncased-finetuned-emotion | gunyoung | distilbert | 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 | 1,325 | false |
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# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | 623b1697506f0ed2067216f5f9dac8be |
AokiDaiki/distilbert-base-uncased-finetuned-emotion | AokiDaiki | distilbert | 12 | 5 | 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 | 1,344 | false |
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# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | 8a3877888be8cdb642ef6f975d54f686 |
avtanh/wav2vec2-large-xls-r-300m-vietnamese-cv11.0-colab | avtanh | wav2vec2 | 42 | 5 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | ['common_voice_11_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,685 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-large-xls-r-300m-vietnamese-cv11.0-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://h... | 4c6e705bdfacd6710b4103baf0518df1 |
jonatasgrosman/exp_w2v2t_et_hubert_s390 | jonatasgrosman | hubert | 10 | 4 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['et'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'et'] | false | true | true | 452 | false | # exp_w2v2t_et_hubert_s390
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | 3378f65997425ff3be371c4076149b12 |
steja/whisper-large-shona | steja | whisper | 11 | 0 | transformers | 1 | automatic-speech-recognition | true | false | false | apache-2.0 | null | ['google/fleurs'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['whisper-event', 'generated_from_trainer'] | true | true | true | 1,446 | false |
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# Whisper_large_Shona
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-... | de8b90d993d4748910bd15a5a9dcc8b4 |
kapilkd13/xls-r-300m-hi-prod | kapilkd13 | wav2vec2 | 19 | 8 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['hi'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'generated_from_trainer', 'hf-asr-leaderboard', 'mozilla-foundation/common_voice_7_0', 'robust-speech-event'] | true | true | true | 2,444 | false |
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#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | 3ddb9aa2cd0f4863d69f5b9bee71e492 |
carblacac/twitter-sentiment-analysis | carblacac | distilbert | 14 | 1 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['new_dataset'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,396 | false |
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# sentiment-analysis-twitter
This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggi... | 91d08f72b8f473ede08f84d59757f89c |
nandysoham16/Warsaw_Pact-clustered | nandysoham16 | distilbert | 8 | 10 | transformers | 0 | question-answering | false | true | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 1,863 | false |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# nandysoham16/Warsaw_Pact-clustered
This model is a fine-tuned version of [nandysoham16/12-clustered_aug](https://huggingface.co/nandys... | 44dfc852ca733c71e0747295f84deedd |
Wizounovziki/t5-small-devices-sum-ver2 | Wizounovziki | t5 | 11 | 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 | 2,350 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-small-devices-sum-ver2
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown datase... | 4726430561003e05159b71210b6c72c3 |
lucasgbezerra/classification_text_model | lucasgbezerra | distilbert | 16 | 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 | 1,270 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# classification_text_model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base... | 1abab2cef288655de3b5f8fd36bd88c9 |
imjunaidafzal/saqib-14-dec | imjunaidafzal | null | 15 | 4 | diffusers | 0 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | ['text-to-image', 'stable-diffusion'] | false | true | true | 620 | false | ### saqib_14_dec Dreambooth model trained by imjunaidafzal 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/fas... | 00d39f45ffce37f18b97d88af8051ccf |
yanaiela/roberta-base-epoch_53 | yanaiela | roberta | 9 | 2 | transformers | 0 | fill-mask | true | false | false | mit | ['en'] | ['wikipedia', 'bookcorpus'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['roberta-base', 'roberta-base-epoch_53'] | false | true | true | 2,102 | false |
# RoBERTa, Intermediate Checkpoint - Epoch 53
This model is part of our reimplementation of the [RoBERTa model](https://arxiv.org/abs/1907.11692),
trained on Wikipedia and the Book Corpus only.
We train this model for almost 100K steps, corresponding to 83 epochs.
We provide the 84 checkpoints (including the randoml... | 89c5cd85d048531b4e63ea290d519f55 |
bondarchukb/minicooper | bondarchukb | null | 18 | 2 | diffusers | 1 | 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 | 616 | false | ### minicooper Dreambooth model trained by bondarchukb 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-st... | 3344b8a39e8ec6f835d68f9b6f51fee3 |
Helsinki-NLP/opus-mt-pa-en | Helsinki-NLP | marian | 10 | 389 | transformers | 1 | translation | true | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 803 | false |
### opus-mt-pa-en
* source languages: pa
* target languages: en
* OPUS readme: [pa-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/pa-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | fbda15bb940e304eec1abf581d170bb0 |
ShussarSDFA/MitoAzX | ShussarSDFA | null | 10 | 0 | null | 1 | null | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 669 | false | Just finetuned [DrBob2142's](https://huggingface.co/DrBob2142) [MidnightMix model](https://huggingface.co/DrBob2142/Mix-Models/blob/main/Midnight%20Mix.safetensors)
Usable model Recipe:
(Add Difference 1)MitoAzXEP62 + F222 + S.D. 1.4 = MitoMix
(Weighted Sum 0.3) MitoMix + Blossom-extract = MitoExtract
(Weighted Sum... | 1b6b8ac501e78b230e8e493de7c0c3d0 |
gsarti/it5-small | gsarti | t5 | 12 | 120 | transformers | 1 | text2text-generation | true | true | true | apache-2.0 | ['it'] | ['gsarti/clean_mc4_it'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['seq2seq', 'lm-head'] | false | true | true | 5,697 | false |
# Italian T5 Small 🇮🇹
The [IT5](https://huggingface.co/models?search=it5) model family represents the first effort in pretraining large-scale sequence-to-sequence transformer models for the Italian language, following the approach adopted by the original [T5 model](https://github.com/google-research/text-to-text-tr... | 406ec9332d32914e0d56a0e1504f0d7f |
kevinbram/testarbaraz | kevinbram | distilbert | 12 | 5 | transformers | 0 | question-answering | true | false | false | apache-2.0 | null | ['squad'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,143 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# testarbaraz
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on t... | d728f020ba8d10bc231fa811a7ef909d |
arrafmousa/SimQA-roberta-base | arrafmousa | roberta | 9 | 5 | transformers | 0 | question-answering | false | true | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 1,294 | false |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# SimQA-roberta-base
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It... | a040439d4a4ae8dc9eccc97efeec76e9 |
peterhsu/tf-bert-finetuned-squad | peterhsu | bert | 8 | 5 | transformers | 0 | question-answering | false | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 1,334 | false |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# tf-bert-finetuned-squad
This model is a fine-tuned version of [peterhsu/tf-bert-finetuned-squad](https://huggingface.co/peterhsu/tf-be... | beef9d0beed8e8623d935af346357a10 |
Intel/distilbert-base-uncased-sparse-90-unstructured-pruneofa | Intel | distilbert | 9 | 30 | transformers | 2 | fill-mask | true | true | false | apache-2.0 | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 427 | false | # 90% Sparse DistilBERT-Base (uncased) Prune OFA
This model is a result from our paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754) presented in ENLSP NeurIPS Workshop 2021.
For further details on the model and its result, see our paper and our implementation available [he... | 651bbf218cfc6ce32509385dbaf9cf54 |
Ussen/whisper-medium-finetuned-on-fleurs-ln_cd1 | Ussen | whisper | 15 | 1 | 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 | 1,572 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-medium-finetuned-on-fleurs-ln_cd1
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/o... | dfedf7ce2154e35463f780b422136b9b |
facebook/wav2vec2-xls-r-2b-en-to-15 | facebook | speech-encoder-decoder | 9 | 9 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['multilingual', 'en', 'de', 'tr', 'fa', 'sv', 'mn', 'zh', 'cy', 'ca', 'sl', 'et', 'id', 'ar', 'ta', 'lv', 'ja'] | ['common_voice', 'multilingual_librispeech', 'covost2'] | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | ['speech', 'xls_r', 'automatic-speech-recognition', 'xls_r_translation'] | false | true | true | 4,400 | false |
# Wav2Vec2-XLS-R-2B-EN-15
Facebook's Wav2Vec2 XLS-R fine-tuned for **Speech Translation.**
This is a [SpeechEncoderDecoderModel](https://huggingface.co/transformers/model_doc/speechencoderdecoder.html) model.
The ... | 4cfae72bf49f3dbbfe96d07a3cf52dcc |
alibaba-pai/pai-ckbert-base-zh | alibaba-pai | bert | 5 | 3 | transformers | 1 | fill-mask | true | false | false | apache-2.0 | ['zh'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['bert'] | false | true | true | 1,851 | false | ## Chinese Kowledge-enhanced BERT (CKBERT)
Knowledge-enhanced pre-trained language models (KEPLMs) improve context-aware representations via learning from structured relations in knowledge graphs, and/or linguistic knowledge from syntactic or dependency analysis. Unlike English, there is a lack of high-performing ope... | 66adad4d909ddecca3c1dba75ad43ccf |
fathyshalab/massive_play-roberta-large-v1-2-0.64 | fathyshalab | roberta | 14 | 2 | 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 | 1,462 | false |
# fathyshalab/massive_play-roberta-large-v1-2-0.64
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 Transformer](https://www.sbert.net) with con... | dd87ebfdb40fca60a98a5d63bb2a344f |
rifkat/uztext-3Gb-BPE-Roberta | rifkat | roberta | 7 | 7 | transformers | 3 | fill-mask | true | false | false | apache-2.0 | ['uz'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['transformers', 'mit', 'robert', 'uzrobert', 'uzbek', 'cyrillic', 'latin'] | false | true | true | 2,959 | false |
<p><b>UzRoBerta model.</b>
Pre-prepared model in Uzbek (Cyrillic and latin script) to model the masked language and predict the next sentences.
<p><b>How to use.</b>
You can use this model directly with a pipeline for masked language modeling:
<pre><code class="language-python">
from transformers import pipeline
... | 1167a1d814f61251ec6c496e55256ff9 |
ravinduj/finetuning-sentiment-model-3000-samples | ravinduj | distilbert | 13 | 11 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['imdb'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,055 | 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](https://huggingface.co/d... | 8524958b0401a7dd8eed637e5a16db7f |
transformersbook/xlm-roberta-base-finetuned-panx-fr | transformersbook | xlm-roberta | 11 | 13 | transformers | 0 | token-classification | true | false | false | mit | null | ['xtreme'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,676 | 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-fr
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | e1b15b6bf1acde548deea3c11407a385 |
cometrain/neurotitle-rugpt3-small | cometrain | gpt2 | 9 | 5 | transformers | 1 | text-generation | true | false | false | mit | ['ru', 'en'] | ['All-NeurIPS-Papers-Scraper'] | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['Cometrain AutoCode', 'Cometrain AlphaML'] | false | true | true | 819 | false |
# neurotitle-rugpt3-small
Model based on [ruGPT-3](https://huggingface.co/sberbank-ai) for generating scientific paper titles.
Trained on [All NeurIPS (NIPS) Papers](https://www.kaggle.com/rowhitswami/nips-papers-1987-2019-updated) dataset.
Use exclusively as a crazier alternative to SCIgen.
## Made with Cometrain Al... | 86590bebf25927e54dd2c66b27592543 |
gokuls/distilbert_sa_GLUE_Experiment_logit_kd_stsb_192 | gokuls | distilbert | 17 | 2 | 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 | 2,156 | 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_sa_GLUE_Experiment_logit_kd_stsb_192
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingf... | 20ac04b753a3851aeb0148bdd5dc9065 |
FluxML/wideresnet101 | FluxML | null | 3 | 0 | null | 0 | null | false | false | false | mit | null | null | null | 2 | 0 | 2 | 0 | 0 | 0 | 0 | [] | false | true | true | 527 | false |
WideResNet101 model ported from [torchvision](https://pytorch.org/vision/stable/index.html) for use with [Metalhead.jl](https://github.com/FluxML/Metalhead.jl). The scripts for creating this file can be found at [this gist](https://gist.github.com/darsnack/bfb8594cf5fdc702bdacb66586f518ef).
To use this model in Julia... | e51fa7166cda055fd51e9353799f03a4 |
samiulhaq/iwslt-bt-en-ur | samiulhaq | null | 5 | 0 | fairseq | 0 | translation | false | false | false | apache-2.0 | ['en', 'ur'] | ['iwslt14'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,374 | false |
### English to Urdu Translation
English to Urdu translation model is a Transformer model trained on IWSLT back-translated data using Faireq.
This model is produced during the experimentation related to building Context-Aware NMT models for low-resourced languages such as Urdu, Hindi, Sindhi, Pashtu and Punjabi. This ... | 3efbf90e714cc51fe4615aa9bac0148a |
icelab/spaceroberta | icelab | roberta | 12 | 106 | transformers | 0 | fill-mask | true | false | false | mit | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 973 | false |
### SpaceRoBERTa
This is one of the 3 further pre-trained models from the SpaceTransformers family presented in [SpaceTransformers: Language Modeling for Space Systems](https://ieeexplore.ieee.org/document/9548078). The original Git repo is [strath-ace/smart-nlp](https://github.com/strath-ace/smart-nlp).
The further... | bba25517099f5ed432afc43c5642c6ec |
adache/tf-distilbert-base-uncased-finetuned-emotion | adache | distilbert | 4 | 6 | transformers | 0 | text-classification | false | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 973 | 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. -->
# tf-distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | 8293d0071853a24d2f8f60131347ff94 |
Eleven/distilbert-base-uncased-finetuned-emotion | Eleven | distilbert | 14 | 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 | 1,326 | 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... | e6e7d7b1552c97a469f390a3a546a216 |
speechbrain/sepformer-wham | speechbrain | null | 14 | 216 | speechbrain | 7 | audio-to-audio | false | false | false | apache-2.0 | ['en'] | ['WHAM!'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['audio-to-audio', 'audio-source-separation', 'Source Separation', 'Speech Separation', 'Audio Source Separation', 'WHAM!', 'SepFormer', 'Transformer', 'speechbrain'] | false | true | true | 3,794 | false |
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
<br/><br/>
# SepFormer trained on WHAM!
This repository provides all the necessary tools to perform audio source separat... | 7d676ca81b8469aa5b1ad8f820719aef |
Jungwonchang/wav2vec2-large-xls-r-300m-vietnamese-colab | Jungwonchang | wav2vec2 | 13 | 8 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | null | ['common_voice'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,108 | 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-large-xls-r-300m-vietnamese-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingf... | 86a348d2732b10b7fb3d885b6ac55b11 |
inverse-scaling/opt-66b_eval | inverse-scaling | opt | 53 | 3 | transformers | 0 | text-generation | true | true | true | other | ['en'] | null | null | 14 | 4 | 5 | 5 | 0 | 0 | 0 | ['text-generation', 'opt'] | true | true | true | 9,908 | false |
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing OP... | 53834aa35d3436f0f4f3cee27b530468 |
Ktolodozo/Beau | Ktolodozo | null | 2 | 0 | null | 0 | null | false | false | false | openrail | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,432 | false | pip install --upgrade diffusers transformers scipy
huggingface-cli login
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline
model_id = "CompVis/stable-diffusion-v1-4"
device = "cuda"
pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True)
pipe = pipe.to(device... | ed5d8331f7cd4c2a256a90833615620c |
anmol-chawla/animecharacters1 | anmol-chawla | null | 15 | 50 | diffusers | 1 | 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 | 623 | false | ### animecharacters1 Dreambooth model trained by anmol-chawla 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/... | cf5ba08195c757b86df582e38272ac27 |
clhuang/albert-sentiment | clhuang | bert | 7 | 39 | transformers | 0 | text-classification | true | false | false | afl-3.0 | ['tw'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['albert', 'classification'] | false | true | true | 1,102 | false |
# 繁體中文情緒分類: 負面(0)、正面(1)
依據ckiplab/albert預訓練模型微調，訓練資料集只有8萬筆，做為課程的範例模型。
# 使用範例:
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("clhuang/albert-sentiment")
model = AutoModelForSequenceClassification.from_pretrained("clhuang/albert-sent... | e78cdfea809d46d6a371dced57054789 |
jEVVB/dillyg | jEVVB | null | 23 | 4 | diffusers | 0 | null | false | false | false | mit | null | null | null | 2 | 2 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,255 | false | ### DillyG on Stable Diffusion via Dreambooth
#### model by jEVVB
This your the Stable Diffusion model fine-tuned the DillyG concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the `instance_prompt`: **a photo of sks man**
You can also train your own concepts and upload them to the library ... | fa1c4d00b7434cc154fbea30cfd0fea6 |
Eto-Demerzel/core | Eto-Demerzel | null | 18 | 7 | 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 | 418 | false | ### Core Dreambooth model trained by Eto-Demerzel 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-... | 1c72a407ca2b248a17c7db3f5ab65b11 |
fathyshalab/bert-uncased-massive-intent-classification-banking-1 | fathyshalab | bert | 10 | 3 | 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 | 1,287 | 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-uncased-massive-intent-classification-banking-1
This model is a fine-tuned version of [gokuls/bert-uncased-massive-intent-c... | 52dbc6fcd589f67acd3ec0f260992f1f |
lmqg/mt5-small-ruquad-ae | lmqg | mt5 | 13 | 33 | transformers | 0 | text2text-generation | true | false | false | cc-by-4.0 | ['ru'] | ['lmqg/qg_ruquad'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['answer extraction'] | true | true | true | 4,781 | false |
# Model Card of `lmqg/mt5-small-ruquad-ae`
This model is fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) for answer extraction on the [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generatio... | d9e7c45da6cf3806479f6d0566a4d6c4 |
juancopi81/mt5-small-finetuned-amazon-en-es | juancopi81 | mt5 | 8 | 1 | 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 | 1,645 | 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. -->
# juancopi81/mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5... | 0067fdd4b5adb6ebd04b4e8916d2fdf9 |
mrizalf7/indobert-qa-finetuned-small-squad-indonesian-rizal | mrizalf7 | bert | 24 | 4 | transformers | 0 | question-answering | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,355 | 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. -->
# indobert-finetuned-small-squad-indonesian-rizal
This model is a fine-tuned version of [indolem/indobert-base-uncased](https://hu... | 7bd5cd4add89492baafa410541024bfc |
sd-dreambooth-library/mertgunhan | sd-dreambooth-library | null | 35 | 9 | diffusers | 0 | null | false | false | false | mit | null | null | null | 2 | 2 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 3,074 | false | ### mertgunhan on Stable Diffusion via Dreambooth trained on the [fast-DreamBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
#### model by teragron
This your the Stable Diffusion model fine-tuned the mertgunhan concept taught ... | 33056975faea85d3c016cf1ab7590ed5 |
freedomtw/stable_diffusion_tflite | freedomtw | null | 13 | 0 | null | 0 | null | false | false | false | openrail | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['tflite', 'stable_diffusion'] | false | true | true | 1,045 | false |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
Stable Diffusion TFLite models
# Model Details
converted from [Keras CV Stable Diffusion](https://github.com/keras-team/keras-cv/tree/master/keras_cv/models/stable_diffusion)
## Model Description
<!-- Provide a longer summary of... | 6dd5ae0f80d809d34b2cc2b7a872318d |
tmobaggins/marian-finetuned-kde4-en-to-es | tmobaggins | marian | 15 | 3 | transformers | 0 | translation | true | false | false | apache-2.0 | null | ['kde4'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['translation', 'generated_from_trainer'] | true | true | true | 987 | 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. -->
# marian-finetuned-kde4-en-to-es
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-es](https://huggingface.co/Helsink... | 96128110c7f5b55917d71434cb48556d |
Helsinki-NLP/opus-mt-bzs-fr | Helsinki-NLP | marian | 10 | 9 | 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-bzs-fr
* source languages: bzs
* target languages: fr
* OPUS readme: [bzs-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bzs-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-08.zip](... | e6749702aae9923e2c363f019f47a8b4 |
jonatasgrosman/exp_w2v2r_es_vp-100k_age_teens-8_sixties-2_s130 | jonatasgrosman | wav2vec2 | 10 | 0 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['es'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'es'] | false | true | true | 497 | false | # exp_w2v2r_es_vp-100k_age_teens-8_sixties-2_s130
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using t... | a0570e11ab6a617213ca0518e9f0960d |
MrPotato/ner-bert-multilingual-uncased-geocite | MrPotato | bert | 12 | 12 | 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 | 997 | 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. -->
# ner-bert-multilingual-uncased-geocite
This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface... | 6b19250876c982ff49535f5f05f118a5 |
espnet/kamo-naoyuki_librispeech_asr_train_asr_conformer5_raw_bpe5000_frontend-truncated-55c091 | espnet | null | 31 | 0 | 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 | 1,983 | false | ## Example ESPnet2 ASR model
### `kamo-naoyuki/librispeech_asr_train_asr_conformer5_raw_bpe5000_frontend_confn_fft400_frontend_confhop_length160_scheduler_confwarmup_steps25000_batch_bins140000000_optim_conflr0.0015_initnone_sp_valid.acc.ave`
♻️ Imported from https://zenodo.org/record/4543003/
This model was trained ... | 1e4ee85e628a444c8768897dc7cded4b |
Helsinki-NLP/opus-mt-it-lt | Helsinki-NLP | marian | 11 | 14 | transformers | 0 | translation | true | true | false | apache-2.0 | ['it', 'lt'] | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 2,004 | false |
### ita-lit
* source group: Italian
* target group: Lithuanian
* OPUS readme: [ita-lit](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ita-lit/README.md)
* model: transformer-align
* source language(s): ita
* target language(s): lit
* model: transformer-align
* pre-processing: normalization... | 206f48917be024ba438fb7fc8b1310d7 |
vvincentt/roberta-base-squad2 | vvincentt | bert | 12 | 4 | transformers | 0 | question-answering | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 952 | 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-squad2
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None ... | 86abf34a29980f2220aa5ecfd70b273a |
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