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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
JacksonYan/Real-CUGAN | JacksonYan | null | 16 | 0 | null | 1 | null | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,219 | false |
> From <https://github.com/bilibili/ailab/tree/main/Real-CUGAN>
# Configuration
`title`: _string_
Display title for the Space
`emoji`: _string_
Space emoji (emoji-only character allowed)
`colorFrom`: _string_
Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
`colorTo`: _string_
C... | 5b1b899e5e6b856c2ee8dc6e79213714 |
sd-concepts-library/naval-portrait | sd-concepts-library | null | 12 | 0 | null | 3 | null | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,416 | false | ### naval-portrait on Stable Diffusion
This is the `<naval-portrait>` 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. Y... | 51069597e1f5f452de37cf8bb92187b4 |
Kilgori/correct-yes-model | Kilgori | null | 20 | 84 | 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 | 426 | false | ### Correct-Yes-model Dreambooth model trained by Kilgori 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... | d7238b6dbdcc625b9bf3d330e9ce4f61 |
bofenghuang/whisper-large-v2-french | bofenghuang | whisper | 44 | 331 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['fr'] | ['mozilla-foundation/common_voice_11_0', 'facebook/multilingual_librispeech', 'facebook/voxpopuli', 'google/fleurs', 'gigant/african_accented_french'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'hf-asr-leaderboard', 'whisper-event'] | true | true | true | 6,342 | false |
<style>
img {
display: inline;
}
</style>
# Fine-tuned whisper-large-v2 model for ASR in Fre... | f376cdb21885a53eb0708fe994e5f498 |
jmparejaz/qa_bert_finetuned-squad | jmparejaz | distilbert | 12 | 8 | 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 | 1,275 | 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_bert_finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-u... | 223044ba277776a580487661e231e94c |
Helsinki-NLP/opus-mt-sv-ny | Helsinki-NLP | marian | 10 | 8 | 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-sv-ny
* source languages: sv
* target languages: ny
* OPUS readme: [sv-ny](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sv-ny/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-21.zip](http... | d98900166af193d0998db1d4c7d017c8 |
AymanMansour/Whisper-Sudanese-Dialect-medium | AymanMansour | whisper | 41 | 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 | 1,532 | 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. -->
# openai/whisper-medium
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium... | 587a6d3e186e2eae1a19ab1a16b14319 |
gokuls/bert-base-uncased-sst2 | gokuls | bert | 17 | 66 | 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 | 1,737 | 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-sst2
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on th... | 5ebd7924e3c39ebb821afc8aa93a0055 |
MichaelHarborg/NMT_da-en_translator | MichaelHarborg | marian | 10 | 1 | transformers | 0 | text2text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 633 | false | Transformer model based on Vaswani et al., 2017 for Danish-English Neural Machine Translation.
It has ~74M parameters and is a fine-tuned version of Helsinki-Opus-NLP da-en.
The model achieves a BLEU score of 49.16 on a hold-out test set for the TED2020 dataset (in-domain dataset).
The model achieves a BLEU score ... | 3243754312ae30219fed80e5c0071787 |
sibyl/BART-large-commongen | sibyl | bart | 13 | 6 | transformers | 0 | text2text-generation | true | false | false | mit | null | ['gem'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | false | true | true | 1,957 | 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-commongen
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on ... | 7fb6c1391761bc3f2b8f1e11f6a7736d |
tomekkorbak/compassionate_elion | 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 | 8,594 | 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. -->
# compassionate_elion
This model was trained from scratch on the tomekkorbak/pii-pile-chunk3-0-50000, the tomekkorbak/pii-pile-chu... | 49693d943965cd0f1be23abfcd2253c8 |
mrgreat1110/bert-finetuned-ner | mrgreat1110 | bert | 12 | 1 | transformers | 0 | token-classification | true | false | false | mit | null | ['conll2003'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,526 | 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-finetuned-ner
This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on th... | dff385ea9713defb3a2e03049960b217 |
muhtasham/base-vanilla-target-tweet | muhtasham | bert | 10 | 3 | 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 | 1,708 | 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. -->
# base-vanilla-target-tweet
This model is a fine-tuned version of [google/bert_uncased_L-12_H-768_A-12](https://huggingface.co/goo... | b53e09cf9258e6bed065e0b984579bb9 |
jonatasgrosman/exp_w2v2r_de_xls-r_age_teens-10_sixties-0_s460 | jonatasgrosman | wav2vec2 | 10 | 0 | 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 | 476 | false | # exp_w2v2r_de_xls-r_age_teens-10_sixties-0_s460
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 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure ... | 7714c2878922714bfd57dcd8340f404f |
bitsanlp/roberta-finetuned-DA-task-B-100k-5-labels | bitsanlp | roberta | 13 | 1 | transformers | 0 | text-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 970 | 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-finetuned-DA-task-B-100k-5-labels
This model is a fine-tuned version of [bitsanlp/roberta-retrained-100k](https://huggin... | 1432c1a3bed2858bb207bbce23f3f8b7 |
jonatasgrosman/exp_w2v2t_en_vp-nl_s281 | jonatasgrosman | wav2vec2 | 10 | 5 | 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 | 475 | false | # exp_w2v2t_en_vp-nl_s281
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | 31db89cd67826277449f0558d813fc9e |
google/realm-cc-news-pretrained-encoder | google | realm | 7 | 309 | transformers | 0 | null | true | false | false | apache-2.0 | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 524 | false |
# realm-cc-news-pretrained-encoder
## Model description
The REALM checkpoint pretrained with CC-News as target corpus and Wikipedia as knowledge corpus, converted from the TF checkpoint provided by Google Language.
The original paper, code, and checkpoints can be found [here](https://github.com/google-research/lang... | 466d9688cce13307fb756abdb96c1037 |
coreml/coreml-stable-diffusion-2-1-base | coreml | null | 6 | 0 | null | 10 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 1 | 0 | 1 | ['coreml', 'stable-diffusion', 'text-to-image'] | false | true | true | 12,899 | false |
# Core ML Converted Model
This model was converted to Core ML for use on Apple Silicon devices by following Apple's instructions [here](https://github.com/apple/ml-stable-diffusion#-converting-models-to-core-ml).<br>
Provide the model to an app such as [Mochi Diffusion](https://github.com/godly-devotion/MochiDiffusio... | 560f0ce05d6602e6fb692b55f9da6dbd |
Qiliang/bart-large-cnn-samsum-ElectrifAi_v10 | Qiliang | bart | 13 | 11 | transformers | 0 | text2text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,685 | 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_v10
This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingfac... | 57b92ebb20bff8e624ff9c364f91f862 |
akahnn/aaureeliaav3 | akahnn | null | 13 | 0 | null | 0 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['text-to-image', 'stable-diffusion'] | false | true | true | 420 | false | ### aaureeliaav3 Dreambooth model trained by akahnn 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-stabl... | 4f277c6edef71e43895de21689730ac2 |
paola-md/distilr2-lr1e05-wd0.08-bs16 | paola-md | roberta | 6 | 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 | 1,441 | 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. -->
# distilr2-lr1e05-wd0.08-bs16
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base... | 81a6a53930da15773a005f3eb61e310a |
WillHeld/t5-base-adv-mtop | WillHeld | mt5 | 41 | 3 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | ['en'] | ['mtop'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,180 | 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-base-adv-mtop
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the mtop dat... | 3b67c1666072f3d7a2528f3083edbc3c |
blizrys/distilbert-base-uncased-finetuned-mnli | blizrys | distilbert | 13 | 1 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['glue'] | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,489 | 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-mnli
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | 3a031583a5fb571636f020d384720510 |
Helsinki-NLP/opus-mt-fr-ms | Helsinki-NLP | marian | 11 | 8 | transformers | 0 | translation | true | true | false | apache-2.0 | ['fr', 'ms'] | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 2,167 | false |
### fra-msa
* source group: French
* target group: Malay (macrolanguage)
* OPUS readme: [fra-msa](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fra-msa/README.md)
* model: transformer-align
* source language(s): fra
* target language(s): ind zsm_Latn
* model: transformer-align
* pre-proces... | b543e2a5b3ea088aef74dfb05cad1f30 |
WillHeld/t5-base-adv-cstop_artificial | WillHeld | mt5 | 23 | 2 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | ['en'] | ['cstop_artificial'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,204 | 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-base-adv-cstop_artificial
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on ... | 1c3b2513fb310959b01be420f7cbcc3e |
sureshchinta/wav2vec2-base-finetuned-ks | sureshchinta | wav2vec2 | 9 | 3 | transformers | 0 | audio-classification | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,241 | 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... | f2ab542db889ee38fb57858785758391 |
google/ddpm-cat-256 | google | null | 10 | 35 | diffusers | 0 | unconditional-image-generation | true | false | false | apache-2.0 | null | null | null | 2 | 0 | 1 | 1 | 0 | 0 | 0 | ['pytorch', 'diffusers', 'unconditional-image-generation'] | false | true | true | 2,874 | false |
# Denoising Diffusion Probabilistic Models (DDPM)
**Paper**: [Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239)
**Authors**: Jonathan Ho, Ajay Jain, Pieter Abbeel
**Abstract**:
*We present high quality image synthesis results using diffusion probabilistic models, a class of latent variabl... | 9dd32a7799e1b7deb83af917316df292 |
gabella/bert-emotion | gabella | distilbert | 18 | 4 | 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 | 1,455 | 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-emotion
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the ... | 5806e680324907514ec53e31a5819c85 |
chrommium/xlm-roberta-large-finetuned-sent_in_news | chrommium | xlm-roberta | 12 | 1 | transformers | 0 | text-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,665 | 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-sent_in_news
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-ro... | 87bdb4174cd125b1db2444c29f42a94a |
kornosk/bert-political-election2020-twitter-mlm | kornosk | bert | 11 | 1,099 | transformers | 3 | fill-mask | true | false | true | gpl-3.0 | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['twitter', 'masked-token-prediction', 'election2020', 'politics'] | false | true | true | 2,433 | false |
# Pre-trained BERT on Twitter US Political Election 2020
Pre-trained weights for [Knowledge Enhance Masked Language Model for Stance Detection](https://www.aclweb.org/anthology/2021.naacl-main.376), NAACL 2021.
We use the initialized weights from BERT-base (uncased) or `bert-base-uncased`.
# Training Data
This mod... | 45190e9ca19aac98d0cff6f9846f9d6f |
ChattychipsHuggingFace/DecentGenerate | ChattychipsHuggingFace | null | 2 | 0 | null | 0 | null | false | false | false | openrail | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,231 | false | pip install transformers
from transformers import Trainer, TrainingArguments
# Load the training and validation data
train_data = ...
validation_data = ...
# Define the model architecture and hyperparameters
model_name = "bert-base-cased"
num_labels = 2
# Define the training arguments
training_args = TrainingArgumen... | 706e0e2e8d49db0f6cbae3368ca4c19a |
sonoisa/t5-base-japanese-question-generation | sonoisa | t5 | 7 | 341 | transformers | 2 | text2text-generation | true | false | false | cc-by-sa-4.0 | ['ja'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['t5', 'text2text-generation', 'seq2seq'] | false | true | true | 572 | false |
# 回答と回答が出てくるパラグラフを与えると質問文を生成するモデル
SEE: https://github.com/sonoisa/deep-question-generation
## 本モデルの作成ステップ概要
1. [SQuAD 1.1](https://rajpurkar.github.io/SQuAD-explorer/)を日本語に機械翻訳し、不正なデータをクレンジング（有効なデータは約半分）。
回答が含まれるコンテキスト、質問文、解答の3つ組ができる。
2. [日本語T5モデル](https://huggingface.co/sonoisa/t5-base-japanese)を次の設定でファインチューニング... | c80df0eadd72ea1491f315767ea0ebe1 |
mujerry/bert-base-uncased-finetuned-QnA | mujerry | bert | 11 | 4 | transformers | 0 | fill-mask | true | false | false | apache-2.0 | null | [] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | false | true | true | 1,613 | 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-QnA
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncas... | e9a2a6a4f17d18e8d252976b8ddf5f2c |
henryscheible/eval_v2_qnli | henryscheible | bert | 13 | 1 | 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 | 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. -->
# eval_v2_qnli
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE QNL... | ef6d413420bc478fa193fd6b91dd5f0b |
raw-vitor/jowx | raw-vitor | null | 19 | 27 | diffusers | 0 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['text-to-image', 'stable-diffusion'] | false | true | true | 415 | false | ### jowx Dreambooth model trained by raw-vitor 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... | 2005f4db8e95c9ee1e44d9ddd8fbe6bc |
gokuls/distilbert_sa_GLUE_Experiment_logit_kd_pretrain_qqp | 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 | 2,100 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert_sa_GLUE_Experiment_logit_kd_pretrain_qqp
This model is a fine-tuned version of [gokuls/distilbert_sa_pre-training-com... | e996cf5d3b9ea2c58299ab4a0e25da3c |
atowey01/hostel-reviews-sentiment-model | atowey01 | distilbert | 8 | 353 | 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 | 1,831 | false |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# atowey01/hostel-reviews-sentiment-model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilb... | 81e87bd13234e1ddf8ece61e37e7b22c |
gvin/testmodel | gvin | distilbert | 14 | 1 | 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 | 1,029 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# testmodel
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the... | 85f5038ac0bcd540845d91f4e4c9cb39 |
VanessaSchenkel/pt-opus-news | VanessaSchenkel | marian | 14 | 1 | transformers | 0 | translation | true | false | false | apache-2.0 | null | ['news_commentary'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['translation', 'generated_from_trainer'] | true | true | true | 1,070 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pt-opus-news
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-mul](https://huggingface.co/Helsinki-NLP/opus-mt-en-... | ddfb3dd1d82f736cd292d3f881340d24 |
bdickson/albert-base-v2-finetuned-squad | bdickson | albert | 11 | 3 | 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 | 1,095 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# albert-base-v2-finetuned-squad
This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on ... | af42fc0250dc64320cf75aeb31e6b856 |
alphatozeta/nasa-potw-hbbltls-astronomy | alphatozeta | null | 16 | 32 | diffusers | 4 | text-to-image | true | false | false | creativeml-openrail-m | null | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['pytorch', 'diffusers', 'stable-diffusion', 'text-to-image', 'diffusion-models-class', 'dreambooth-hackathon', 'astronomy'] | false | true | true | 881 | false |
# DreamBooth model for the astronomy concept trained by Dhruv Singal on the NASA Astronomy Picture of the Week dataset.
This is a Stable Diffusion 2.1 model fine-tuned on the astronomy concept with DreamBooth. It can be used by modifying the `instance_prompt`: a photo of the solar system hbbltls astronomy****
This m... | f08e836495d780a049843bdaa3e503b8 |
annahaz/xlm-roberta-base-finetuned-misogyny-sexism | annahaz | xlm-roberta | 10 | 3 | transformers | 0 | text-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,320 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# xlm-roberta-base-finetuned-misogyny-sexism
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-r... | 6066036931c94f5b6b26d7bbc476d48a |
jonatasgrosman/exp_w2v2t_uk_wavlm_s21 | jonatasgrosman | wavlm | 10 | 5 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['uk'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'uk'] | false | true | true | 438 | false | # exp_w2v2t_uk_wavlm_s21
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (uk)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 1... | 59092655c43833bad912e4b4ba34cdc8 |
csikasote/xls-r-300m-bemba-20hrs | csikasote | wav2vec2 | 17 | 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 | 2,371 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# xls-r-300m-bemba-20hrs
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2... | 25ad3eb3630bbbdf728296684bdc51f8 |
deepmind/vision-perceiver-fourier | deepmind | perceiver | 5 | 681 | transformers | 1 | image-classification | true | false | false | apache-2.0 | null | ['imagenet'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 4,958 | false |
# Perceiver IO for vision (fixed Fourier position embeddings)
Perceiver IO model pre-trained on ImageNet (14 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [Perceiver IO: A General Architecture for Structured Inputs & Outputs](https://arxiv.org/abs/2107.14795) by Jaegle et al. an... | 1b8130fd3a56038c256539079cfee054 |
thkkvui/xlm-roberta-base-finetuned-panx-all | thkkvui | xlm-roberta | 10 | 4 | transformers | 0 | token-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,324 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# xlm-roberta-base-finetuned-panx-all
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-... | fe411dbb8acbd5d88e1e879b552b152b |
julien-c/reactiongif-roberta | julien-c | roberta | 26 | 145 | transformers | 1 | text-classification | true | false | false | apache-2.0 | null | ['julien-c/reactiongif'] | null | 18 | 0 | 0 | 18 | 0 | 0 | 0 | ['generated-from-trainer'] | false | true | true | 1,498 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# model
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unkown dataset... | 7fc0a8d8fadd39f9942761d25fb57082 |
Helsinki-NLP/opus-mt-he-it | Helsinki-NLP | marian | 12 | 13 | transformers | 0 | translation | true | true | false | apache-2.0 | ['he', 'it'] | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 2,012 | false | ### he-it
* source group: Hebrew
* target group: Italian
* OPUS readme: [heb-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/heb-ita/README.md)
* model: transformer
* source language(s): heb
* target language(s): ita
* model: transformer
* pre-processing: normalization + SentencePiece (s... | 62a79e848b4328acca982e8b0d32bc92 |
hamzab/roberta-fake-news-classification | hamzab | roberta | 9 | 5 | transformers | 0 | text-classification | true | false | false | mit | ['en'] | ['fake-and-real-news-dataset on kaggle'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['classification'] | false | true | true | 1,684 | false | ## Overview
The model is a `roberta-base` fine-tuned on [fake-and-real-news-dataset](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset). It has a 100% accuracy on that dataset.
The model takes a news article and predicts if it is true or fake.
The format of the input should be:
```
<title> ... | 0e7173ddcf12671ead4feaf6a9f55dc4 |
elopezlopez/distilbert-base-uncased_fold_3_binary_v1 | elopezlopez | distilbert | 13 | 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 | 2,658 | 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_fold_3_binary_v1
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | 536eac13e6db2ab8aeac43255448e42e |
Helsinki-NLP/opus-mt-ko-en | Helsinki-NLP | marian | 11 | 3,758 | transformers | 9 | translation | true | true | false | apache-2.0 | ['ko', 'en'] | null | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 2,051 | false |
### kor-eng
* source group: Korean
* target group: English
* OPUS readme: [kor-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/kor-eng/README.md)
* model: transformer-align
* source language(s): kor kor_Hang kor_Latn
* target language(s): eng
* model: transformer-align
* pre-processing:... | 1845f114f1c35724dade1c130c0eb452 |
vasista22/whisper-hindi-small | vasista22 | whisper | 12 | 54 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['hi'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['whisper-event'] | true | true | true | 1,322 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Hindi Small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on... | 4e9d4c25489b15b7a80625909db34b9c |
EleutherAI/pythia-410m-deduped | EleutherAI | gpt_neox | 7 | 5,137 | transformers | 4 | text-generation | true | false | false | apache-2.0 | ['en'] | ['EleutherAI/raw_deduplicated_pile'] | null | 2 | 1 | 1 | 0 | 1 | 0 | 1 | ['pytorch', 'causal-lm', 'pythia'] | false | true | true | 10,888 | false |
The *Pythia Scaling Suite* is a collection of models developed to facilitate
interpretability research. It contains two sets of eight models of sizes
70M, 160M, 410M, 1B, 1.4B, 2.8B, 6.9B, and 12B. For each size, there are two
models: one trained on the Pile, and one trained on the Pile after the dataset
has been ... | 6c3809b8b7f3cd3aa2595ff0d1fda3ad |
Bistolero/genlen2ep | Bistolero | t5 | 9 | 2 | 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 | 882 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# genlen2ep
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.... | a5c17aeeb51847cb3ca6ded186d4d5dc |
Akumetsu971/SD_Samurai_Anime_Style | Akumetsu971 | null | 11 | 0 | null | 3 | text-to-image | false | false | false | creativeml-openrail-m | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['stable-diffusion', 'text-to-image'] | false | true | true | 4,936 | false |
# SD_Samurai_Anime_Style is an open source Stable Diffusion Embedding on art style of Samurai, by Akumetsu971 (https://www.tiktok.com/@akumetsu971)
---
### Model used to train:
wd-v1-3-full-opt.ckpt (https://huggingface.co/hakurei/waifu-diffusion-v1-3)
### Files
5 files available (Best version is 4000steps):
-S... | b5b9a2a0de1fdefc5a9c51a839ce34c8 |
rmihaylov/gpt2-small-bg | rmihaylov | gpt2 | 10 | 3 | transformers | 0 | text-generation | true | false | false | mit | ['bg'] | ['oscar', 'chitanka', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['torch'] | false | true | true | 2,635 | false |
# GPT-2
Pretrained model on Bulgarian language using a causal language modeling (CLM) objective. It was introduced in
[this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)
and first released at [this page](https://openai.com/blog/better-langua... | b0683631a7408a0c5463fef84cdcd068 |
pupubear/pupu_girl_ver1 | pupubear | null | 20 | 125 | diffusers | 3 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['text-to-image', 'stable-diffusion'] | false | true | true | 648 | false | ### girl Dreambooth model trained by pupubear with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
trianed from c_PVC_mix
Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/The... | f034eec712da47879948a1e1b71818aa |
fathyshalab/all-roberta-large-v1-credit_cards-3-16-5 | fathyshalab | roberta | 11 | 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 | 1,517 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# all-roberta-large-v1-credit_cards-3-16-5
This model is a fine-tuned version of [sentence-transformers/all-roberta-large-v1](http... | ee50410735d99c78107c0014dcc813c4 |
Hamine/distilbert-base-uncased-finetuned-mnli | Hamine | distilbert | 13 | 1 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['glue'] | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,356 | 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-finetuned-mnli
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | 116ae73710b075b2c8801c55fba3fae7 |
ariesutiono/finetuned-test-1 | ariesutiono | bert | 16 | 2 | transformers | 0 | fill-mask | true | false | false | apache-2.0 | null | ['conll2003'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,155 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# finetuned-test-1
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conl... | 81b0760f4bd8af43bb5cdc4eee54bc10 |
pjox/dalembert-classical-fr-ner | pjox | null | 8 | 0 | flair | 0 | token-classification | false | false | false | apache-2.0 | ['fr'] | ['freemner'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['Early Modern French', 'Historical', 'NER', 'flair'] | false | true | true | 2,371 | false |
<a href="https://portizs.eu/publication/2022/lrec/dalembert/">
<img width="300px" src="https://portizs.eu/publication/2022/lrec/dalembert/featured_hu18bf34d40cdc71c744bdd15e48ff0b23_61788_720x2500_fit_q100_h2_lanczos_3.webp">
</a>
# D'AlemBERT-NER model
This model is fine-tuned version of a [D'AlemBERT](https://hu... | 086343507570053696aa448d3894d1e3 |
jonatasgrosman/exp_w2v2t_de_unispeech-ml_s750 | jonatasgrosman | unispeech | 10 | 4 | 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 | 500 | false | # exp_w2v2t_de_unispeech-ml_s750
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 (de)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | 24295145163a1af37d387ada11ce8c82 |
facebook/convnext-base-224-22k | facebook | convnext | 6 | 795 | transformers | 0 | image-classification | true | true | false | apache-2.0 | null | ['imagenet-21k'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['vision', 'image-classification'] | false | true | true | 2,664 | false |
# ConvNeXT (base-sized model)
ConvNeXT model trained on ImageNet-22k at resolution 224x224. It was introduced in the paper [A ConvNet for the 2020s](https://arxiv.org/abs/2201.03545) by Liu et al. and first released in [this repository](https://github.com/facebookresearch/ConvNeXt).
Disclaimer: The team releasing ... | a6cff181fe289e8e2d6c1ceb2e267079 |
anas-awadalla/t5-base-few-shot-k-16-finetuned-squad-infilling-seed-4 | anas-awadalla | t5 | 17 | 1 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | ['squad'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 968 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-base-few-shot-k-16-finetuned-squad-infilling-seed-4
This model is a fine-tuned version of [google/t5-v1_1-base](https://huggi... | e4c078fdc180f963489192d3330c8ccc |
microsoft/reacc-py-retriever | microsoft | roberta | 9 | 3 | transformers | 3 | feature-extraction | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,043 | false |
# ReACC-py-retriever
This is the retrieval model for [ReACC: A Retrieval-Augmented Code Completion Framework](https://arxiv.org/abs/2203.07722).
In this paper, the model is used to retrieve similar codes given an incompletion code snippet as query. The model can be also used for incomplete code-to-code search, code ... | d552b1a1276f9b039a3e863017dd1485 |
theojolliffe/bart-cnn-science-v3-e2 | theojolliffe | bart | 13 | 1 | transformers | 0 | text2text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,568 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bart-cnn-science-v3-e2
This model is a fine-tuned version of [theojolliffe/bart-cnn-science](https://huggingface.co/theojolliffe... | ca48f118485232b118e7a51668b1096f |
anas-awadalla/t5-small-few-shot-k-512-finetuned-squad-seed-0 | anas-awadalla | t5 | 15 | 1 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | ['squad'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 960 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-small-few-shot-k-512-finetuned-squad-seed-0
This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.... | ab6465a9cc086db6ccc7b33108d9b98e |
google/t5-efficient-base-kv32 | google | t5 | 12 | 19 | 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 | 6,252 | false |
# T5-Efficient-BASE-KV32 (Deep-Narrow version)
T5-Efficient-BASE-KV32 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 ... | 19dd9c633fedec170889ad836b5e1c72 |
okho0653/Bio_ClinicalBERT-zero-shot | okho0653 | bert | 11 | 4 | transformers | 0 | text-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,142 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Bio_ClinicalBERT-zero-shot
This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilya... | 3aae72d4c05f68e35a4d01ce22eed250 |
dandelin/vilt-b32-finetuned-nlvr2 | dandelin | vilt | 9 | 375 | transformers | 1 | null | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 2,071 | false |
# Vision-and-Language Transformer (ViLT), fine-tuned on NLVR2
Vision-and-Language Transformer (ViLT) model fine-tuned on [NLVR2](https://lil.nlp.cornell.edu/nlvr/). It was introduced in the paper [ViLT: Vision-and-Language Transformer
Without Convolution or Region Supervision](https://arxiv.org/abs/2102.03334) by Kim... | e686b400b849b6fa5d044dd49ecf2452 |
freedomfrier/my-128dim-model2 | freedomfrier | bert | 14 | 14 | sentence-transformers | 0 | sentence-similarity | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['sentence-transformers', 'feature-extraction', 'sentence-similarity', 'transformers'] | false | true | true | 3,533 | false |
# sentence-transformers/msmarco-MiniLM-L-6-v3
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you... | 9d1a421ec6ca66b718fd9374640c7b53 |
Reggie/muppet-roberta-base-joke_detector | Reggie | roberta | 8 | 55 | transformers | 0 | text-classification | true | false | false | mit | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['roberta'] | false | true | true | 1,858 | false |
### What is this?
This model has been developed to detect "narrative-style" jokes, stories and anecdotes (i.e. they are narrated as a story) spoken during speeches or conversations etc. It works best when jokes/anecdotes are at least 40 words or longer. It is based on Facebook's [RoBerta-MUPPET](https://huggingface.co... | 586a9f7895a15545415d62a4938253f6 |
redevaaa/fin4 | redevaaa | bert | 12 | 5 | transformers | 0 | token-classification | true | false | false | cc-by-sa-4.0 | null | ['fin'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,153 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fin4
This model is a fine-tuned version of [nlpaueb/sec-bert-num](https://huggingface.co/nlpaueb/sec-bert-num) on the fin datase... | 5a987fb10ca5862a4f9be8e46b38f51b |
Celal11/beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-7e-05-32 | Celal11 | beit | 11 | 6 | transformers | 0 | image-classification | true | false | false | apache-2.0 | null | ['image_folder'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,505 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-7e-05-32
This model is a fine-tuned version of [Celal11/beit-base-patch16-22... | 0b3f5a6aa7ac037f55988857dfd55c95 |
Helsinki-NLP/opus-mt-kg-fr | Helsinki-NLP | marian | 10 | 7 | transformers | 1 | 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-kg-fr
* source languages: kg
* target languages: fr
* OPUS readme: [kg-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/kg-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-09.zip](http... | c19ed754e218a19b96091a83a999fbc3 |
MeshalAlamr/wav2vec2-xls-r-300m-ar-4 | MeshalAlamr | wav2vec2 | 7 | 6 | 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 | 4,403 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-xls-r-300m-ar-4
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wa... | 41ed1d5580751f054c7e1338f459f3df |
debbiesoon/summarise_v11 | debbiesoon | led | 13 | 7 | transformers | 1 | text2text-generation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 7,878 | 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. -->
# summarise_v11
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on t... | 81593e4d038f404304d010bd38aaeb47 |
google/t5-efficient-xl-nl16 | google | t5 | 12 | 12 | 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 | 6,247 | false |
# T5-Efficient-XL-NL16 (Deep-Narrow version)
T5-Efficient-XL-NL16 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 and ... | 82a591b11936ec3e10a8caf444ae6060 |
AI-Ahmed/deberta-v3-base-funetuned-cls-qqa | AI-Ahmed | deberta-v2 | 61 | 15 | transformers | 0 | text-classification | true | false | false | cc-by-4.0 | ['en'] | ['SetFit/qqp'] | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | ['classification'] | true | true | true | 1,789 | false |
A fine-tuned model based on the **DeBERTaV3** model of Microsoft and fine-tuned on **Glue QQP**, which detects the linguistical similarities between two questions and whether they are duplicates questions or different.
## Model Hyperparameters
```python
epoch=4
per_device_train_batch_size=32
per_device_eval_batch_si... | 192c508932f59879f54a42b027389dd6 |
jeraldflowers/distilroberts-base-mrpc-glue-jeraldflowers | jeraldflowers | roberta | 17 | 3 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['glue'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['text-classification', 'generated_from_trainer'] | true | true | true | 1,344 | 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. -->
# distilroberts-base-mrpc-glue-jeraldflowers
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/dis... | 198ce21dee5b672deb2990c399e58308 |
YasinShihab/asr-en-bn-test | YasinShihab | null | 2 | 0 | null | 0 | automatic-speech-recognition | false | false | false | cc-by-sa-4.0 | ['Bengali'] | ['OpenSLR'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['bn', 'audio', 'automatic-speech-recognition', 'speech'] | true | true | true | 1,660 | false | # Wav2Vec2-Large-XLSR-Bengali
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) Bengali using a subset of 40,000 utterances from [Bengali ASR training data set containing ~196K utterances](https://www.openslr.org/53/). Tested WER using ~4200 held out from training.
Whe... | 79df9741d1bf656211ca2a3a0ac54ddc |
jonatasgrosman/exp_w2v2t_uk_unispeech-sat_s27 | jonatasgrosman | unispeech-sat | 10 | 2 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['uk'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'uk'] | false | true | true | 462 | false | # exp_w2v2t_uk_unispeech-sat_s27
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 (uk)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | e61d0f2e5cb304ba20de27a178f1a5c3 |
gustavecortal/flan-t5-large-dream-character | gustavecortal | t5 | 10 | 4 | 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 | 2,017 | 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. -->
# flan-t5-large-dream-character
This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5... | 08eb6e5d27f14fb850a6bb34b318cafe |
agungbesti/house | agungbesti | null | 5 | 0 | null | 0 | null | false | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 779 | false |
# Configuration
`title`: _string_
Display title for the Space
`emoji`: _string_
Space emoji (emoji-only character allowed)
`colorFrom`: _string_
Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
`colorTo`: _string_
Color for Thumbnail gradient (red, yellow, green, blue, indigo... | 93eaa78d7f0056b64c5516ac1f78b64f |
AMAN-B/Demo-Dreambooth | AMAN-B | null | 18 | 69 | diffusers | 1 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 3 | 3 | 0 | 0 | 0 | 0 | 0 | ['stable-diffusion', 'stable-diffusion-diffusers', 'text-to-image'] | false | true | true | 572 | false |
### Diffusers
```py
from diffusers import StableDiffusionPipeline
import torch
model_id = "runwayml/stable-diffusion-v1-5"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, revision="fp16")
pipe = pipe.to("cuda")
prompt = "a photo of an astronaut riding a horse on mars"
image = pipe... | 6af3f44627dbf33e0ce399b6129c582b |
CCMat/ddpm-bored-apes-128 | CCMat | null | 7 | 0 | diffusers | 0 | unconditional-image-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['pytorch', 'diffusers', 'unconditional-image-generation', 'diffusion-models-class'] | false | true | true | 413 | false |
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of bored apes 🦧.
## Usage
```python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('CCMat/diff-bored-apes... | d7fddf96df1b6b98b01a158367ad6fdb |
jonatasgrosman/exp_w2v2t_nl_r-wav2vec2_s925 | 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 | 462 | false | # exp_w2v2t_nl_r-wav2vec2_s925
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 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | 2b4056bdd23ed48bfac4fd72756e4c0a |
CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-msa | CAMeL-Lab | bert | 12 | 154 | transformers | 0 | token-classification | true | true | false | apache-2.0 | ['ar'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 3,770 | false | # CAMeLBERT-CA POS-MSA Model
## Model description
**CAMeLBERT-CA POS-MSA Model** is a Modern Standard Arabic (MSA) POS tagging model that was built by fine-tuning the [CAMeLBERT-CA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca/) model.
For the fine-tuning, we used the [PATB](https://dl.acm.org/doi/pdf... | 66b1bdec6921430b8cb2224e766c2fe0 |
Praboda/xlm-roberta-base-finetuned-panx-it | Praboda | xlm-roberta | 10 | 3 | transformers | 0 | token-classification | true | false | false | mit | null | ['xtreme'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,320 | 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-it
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | 7cb96e6d28eede79721dbc43f46a8213 |
Adil617/wav2vec2-base-timit-demo-colab | Adil617 | 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 | 2,237 | 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... | 6ba065814b7e0d723c2ebc89b4b5e551 |
danghuy1999/gpt2-viwiki | danghuy1999 | gpt2 | 7 | 10 | transformers | 3 | null | true | true | false | mit | ['vi'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['gpt2-viwiki'] | false | true | true | 3,121 | false |
# GPT-2 Fine-tuning in Vietnamese Wikipedia
## Model description
This is a Vietnamese GPT-2 model which is finetuned on the [Latest pages articles of Vietnamese Wikipedia](https://dumps.wikimedia.org/viwiki/latest/viwiki-latest-pages-articles.xml.bz2).
## Dataset
The dataset is about 800MB, includes many articles ... | 315b1ed6a9c1a650d68e4a788b69ae45 |
LinfO/yerlearsi | LinfO | null | 31 | 2 | diffusers | 0 | null | false | false | false | mit | null | null | null | 2 | 2 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,961 | false | ### yerlearsi on Stable Diffusion via Dreambooth
#### model by LinfO
This your the Stable Diffusion model fine-tuned the yerlearsi concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the `instance_prompt`: **yerlearsi**
You can also train your own concepts and upload them to the library by ... | 8020df3a9fb76ea5ef512c60995469de |
sd-concepts-library/boris-anderson | 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 | 1,070 | false | ### Boris Anderson on Stable Diffusion
This is the `<boris-anderson>` 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. Y... | 9e4af5f64a3d47558463a1db267446d3 |
StonyBrookNLP/preasm-large-drop | StonyBrookNLP | t5 | 8 | 3 | transformers | 0 | text2text-generation | true | false | false | cc-by-4.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['question-answering, multi-step-reasoning, multi-hop-reasoning'] | false | true | true | 2,603 | false |
# What's this?
This is one of the models reported in the paper: ["Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts".](https://arxiv.org/abs/2205.12496).
This paper proposes a procedure to synthetically generate a QA dataset, TeaBReaC, for pretraining language models for robust multi-step... | 3d213ef898085b2fa80998bb098c4f21 |
YoungMasterFromSect/ManyColors | YoungMasterFromSect | null | 8 | 0 | null | 2 | null | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 848 | false | Depending on tags and length of tags artstyle will vary, so experiment with them! |
wral artstyle - artstyle tag |
watercolor \(medium\) - helps to bring out watercolor |
multicolored hair - helps to make image multicolored
Sample images:
<style>
img {
display: inline-block;
}
</style>
<img src="https://huggin... | baf2b4518d03a8bc32b1a03c7805410a |
muhtasham/tiny-mlm-imdb-target-rotten_tomatoes | muhtasham | 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 | 1,578 | 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-mlm-imdb-target-rotten_tomatoes
This model is a fine-tuned version of [muhtasham/small-mlm-wikitext](https://huggingface.co... | d74078bee176ab1437a869e6677dc0ef |
gokuls/mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_qnli_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 | 1,617 | 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. -->
# mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_qnli_128
This model is a fine-tuned version of [google/mobilebert-uncased](https... | 9819670ec436558fe43ff5048d9ee0ef |
MadMarx37/mt5-small-finetuned-cnn-dailymail | MadMarx37 | mt5 | 17 | 3 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | ['cnn_dailymail'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,029 | 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-cnn-dailymail
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-sma... | f958e60efe693de5e330344da91ff967 |
jonatasgrosman/exp_w2v2r_en_vp-100k_gender_male-2_female-8_s320 | 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 | 498 | false | # exp_w2v2r_en_vp-100k_gender_male-2_female-8_s320
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 (en)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using ... | 8d5fec508fac974560e7eb8b4fd017f2 |
davidlekve/distilroberta-base-finetuned-the-beatles | davidlekve | roberta | 8 | 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 | 1,267 | 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-finetuned-the-beatles
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/disti... | 5687f04595678814935816019e4ba434 |
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