repo_id stringlengths 4 110 | author stringlengths 2 27 ⌀ | model_type stringlengths 2 29 ⌀ | files_per_repo int64 2 15.4k | downloads_30d int64 0 19.9M | library stringlengths 2 37 ⌀ | likes int64 0 4.34k | pipeline stringlengths 5 30 ⌀ | pytorch bool 2
classes | tensorflow bool 2
classes | jax bool 2
classes | license stringlengths 2 30 | languages stringlengths 4 1.63k ⌀ | datasets stringlengths 2 2.58k ⌀ | co2 stringclasses 29
values | prs_count int64 0 125 | prs_open int64 0 120 | prs_merged int64 0 15 | prs_closed int64 0 28 | discussions_count int64 0 218 | discussions_open int64 0 148 | discussions_closed int64 0 70 | tags stringlengths 2 513 | has_model_index bool 2
classes | has_metadata bool 1
class | has_text bool 1
class | text_length int64 401 598k | is_nc bool 1
class | readme stringlengths 0 598k | hash stringlengths 32 32 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
susnato/bert-base-uncased-issues-128 | susnato | bert | 10 | 0 | 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 | 1,918 | 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-issues-128
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased)... | 0c36919bc38928cbfe31f404bdbe6315 |
FUXI/yuyan-11b | FUXI | null | 9 | 0 | null | 1 | text-generation | true | false | false | apache-2.0 | ['zh'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['text-generation', 'story-generation', 'pytorch', 'inference acceleration', 'gpt2', 'gpt3'] | false | true | true | 4,725 | false | # YuYan: Pre-training of Language Models for Story Generation
YuYan is a series of Chinese language models with different size, developed by Fuxi AI lab, Netease.Inc. They are trained on a large Chinese novel dataset of high quality.
YuYan is in the same family of decoder-only models like [GPT2 and GPT-3](https://ar... | e0e9f748f8efa87c14cb74d862837ee0 |
sanchit-gandhi/whisper-medium-es-4k-1e-7-bs-32 | sanchit-gandhi | whisper | 15 | 6 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['es'] | ['facebook/multilingual_librispeech'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['hf-asr-leaderboard', 'generated_from_trainer'] | true | true | true | 1,557 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small Es - Sanchit Gandhi
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/wh... | 7430e5605e8ff17d8bcb630a664acd5b |
sd-concepts-library/venice | sd-concepts-library | null | 13 | 0 | null | 1 | null | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,390 | false | ### venice on Stable Diffusion
This is the `<venice>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) notebook. You can also trai... | ad6d3718973b8a107b34fa7c3e95a842 |
Krishadow/biobert-finetuned-ner | Krishadow | bert | 8 | 3 | transformers | 0 | token-classification | false | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 1,531 | 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. -->
# Krishadow/biobert-finetuned-ner
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on... | 695315c94aaa7e69fc27cf0665f4099a |
adsjklfsd/distilbert-base-uncased-finetuned-emotion | adsjklfsd | distilbert | 12 | 6 | 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 |
<!-- 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... | 981ca25bc509683a4189970673e54e90 |
hkunlp/instructor-xl | hkunlp | t5 | 14 | 279 | sentence-transformers | 12 | sentence-similarity | true | false | false | apache-2.0 | ['en'] | null | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | ['text-embedding', 'embeddings', 'information-retrieval', 'beir', 'text-classification', 'language-model', 'text-clustering', 'text-semantic-similarity', 'text-evaluation', 'prompt-retrieval', 'text-reranking', 'sentence-transformers', 'feature-extraction', 'sentence-similarity', 'transformers', 't5', 'English', 'Sente... | true | true | true | 6,303 | false |
# hkunlp/instructor-xl
We introduce **Instructor**👨🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e.g., classification, retrieval, clustering, text evaluation, etc.) and domains (e.g., science, finance, etc.) ***by simply providing the task instruction, with... | 23c06254f67b8ad723affed51716e3f4 |
mchochowski/test-model | mchochowski | null | 4 | 14 | transformers | 0 | image-classification | false | false | false | apache-2.0 | null | ['imagenet'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['image-classification', 'resnet'] | false | true | true | 4,180 | false |
### Model Description
The ***ResNet50 v1.5*** model is a modified version of the [original ResNet50 v1 model](https://arxiv.org/abs/1512.03385).
The difference between v1 and v1.5 is that, in the bottleneck blocks which requires
downsampling, v1 has stride = 2 in the first 1x1 convolution, whereas v1.5 has stride = ... | 0da925f8cdec0ab06a770d8ae3e5a813 |
abishanth/crpf_analysis_trail_1 | abishanth | distilbert | 15 | 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 | 1,037 | 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. -->
# crpf_analysis_trail_1
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-unc... | 7294f44b996a90b477e343f6ae32cbc2 |
DrishtiSharma/whisper-large-v2-ml-700-steps | DrishtiSharma | whisper | 15 | 0 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['ml'] | ['mozilla-foundation/common_voice_11_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['whisper-event', 'generated_from_trainer'] | true | true | true | 1,323 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Large V2 Malayalam- Drishti Sharma
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.c... | e1ae60f04f4fe80440a79b9a17d03737 |
vishwasgautam/HuBERT-base-libriSpeech-demo-colab | vishwasgautam | hubert | 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 | 1,359 | 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. -->
# HuBERT-base-libriSpeech-demo-colab
This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co... | 508ce17af20be0246419d3a38f6463d1 |
wietsedv/xlm-roberta-base-ft-udpos28-cy | wietsedv | xlm-roberta | 8 | 13 | transformers | 0 | token-classification | true | false | false | apache-2.0 | ['cy'] | ['universal_dependencies'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['part-of-speech', 'token-classification'] | true | true | true | 565 | false |
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Welsh
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the [Space](https://huggingface.co/spaces/wietsedv/xpos) for more details.
## Usage
```python
from transformer... | 8aa568fb46e55a8e84c605896eb885de |
kingabzpro/wav2vec2-large-xls-r-300m-Indonesian | kingabzpro | wav2vec2 | 16 | 6 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['id'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'hf-asr-leaderboard', 'robust-speech-event'] | true | true | true | 1,927 | 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-Indonesian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co... | 2248a0490959902fdcd159557f83cf7e |
AlekseyKorshuk/1.3b-dalio-principles-book | AlekseyKorshuk | opt | 13 | 2 | transformers | 0 | text-generation | true | false | false | other | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 2,115 | 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. -->
# 1.3b-dalio-principles-book
This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) o... | d325a95dafb4aba8931b374c744c2d02 |
sasuke/bert-base-uncased-finetuned-sst2 | sasuke | bert | 29 | 3 | 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 | 1,463 | 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-sst2
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-unca... | f51121dce2febf1abda52abda04cce20 |
jgammack/MTL-roberta-base | jgammack | roberta | 22 | 4 | transformers | 0 | fill-mask | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,884 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# MTL-roberta-base
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
... | 1a42fb08f72de6f194875a6f0d6a7d67 |
jonatasgrosman/exp_w2v2t_th_wav2vec2_s664 | jonatasgrosman | wav2vec2 | 10 | 3 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['th'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'th'] | false | true | true | 459 | false | # exp_w2v2t_th_wav2vec2_s664
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on Thai 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 that your speech ... | f0b8c7bfbd1733bdfc143aec9d70d3f6 |
StarwingDigital/Oldjourney | StarwingDigital | null | 25 | 0 | diffusers | 6 | null | false | false | false | creativeml-openrail-m | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['Text-to-image', 'Diffusers', 'stable-diffusion'] | false | true | true | 6,858 | false | <b>Oldjourney</b>
Oldjourney is a finetuned Stable Diffusion 2.1 model trained on images from Midjourney 3 using Dreambooth. That older version of Midjourney was often messy and imprecise, but had a great artistic style. These two versions of Oldjourney can recreate the essence of that art style with added details, pr... | ce1c44f3f6793ffa1be68e8dd8177758 |
spacy/fr_core_news_lg | spacy | null | 28 | 30 | spacy | 1 | token-classification | false | false | false | lgpl-lr | ['fr'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['spacy', 'token-classification'] | false | true | true | 11,828 | false | ### Details: https://spacy.io/models/fr#fr_core_news_lg
French pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.
| Feature | Description |
| --- | --- |
| **Name** | `fr_core_news_lg` |
| **Version** | `3.5.0` |
| **spaCy** | `>=3.5.0,<3.6.0` |
| **Defau... | 5e2a6466e7c2ed2a03fe988d87d3486f |
heziiiii/ddpm-butterflies-128 | heziiiii | null | 13 | 0 | 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 | 1,230 | 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... | 1d9ac641223f45476fb771d4848b4b72 |
TheSkinnyRat/TI-EMB_elaina | TheSkinnyRat | null | 23 | 0 | null | 4 | null | false | false | false | creativeml-openrail-m | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['stable-diffusion'] | false | true | true | 1,933 | false |
# Info
> Trainer: [TheSkinnyRat](https://huggingface.co/TheSkinnyRat)\
> Type: Textual Inversion Embeddings
# Description
> Elaina (イレイナ, Ireina) is the main protagonist of the Wandering Witch series.
> She is a witch with the witch name of The Ashen Witch.
> ([Fandom](https://wandering-witch.fandom.com/wiki/Elaina))... | a6af81dbf17d0ce280f1fc326c07c815 |
annahaz/xlm-roberta-base-misogyny-sexism-tweets | annahaz | xlm-roberta | 10 | 139 | transformers | 0 | text-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,864 | 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-misogyny-sexism-tweets
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-robe... | 904eb9c1e6f7faf20262fc071b839843 |
mattthew/technicolor-50s-diffusion | mattthew | null | 9 | 0 | null | 0 | null | false | false | false | cc-by-sa-4.0 | null | null | null | 1 | 0 | 0 | 1 | 0 | 0 | 0 | [] | false | true | true | 2,283 | false | # 🌈 Technicolor-50s Diffusion
## Style Description
- highly-saturated postcard-like colors, flat high-key lighting, strong rim-lighting, 40s and 50s lifestyle
## Sample Output (Raw Output)
<sub... | 484c28e3c6b7e38859a451398a2bbbec |
Zlikwid/zlikwidv2 | Zlikwid | null | 18 | 3 | diffusers | 0 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 2 | 2 | 0 | 0 | 0 | 0 | 0 | ['text-to-image', 'stable-diffusion'] | false | true | true | 418 | false | ### ZlikwidV2 Dreambooth model trained by Zlikwid 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-... | 2b49a1e7bf066806e97791b1feec57df |
mrsteyk/openchatgpt-neo-125m | mrsteyk | gpt_neo | 11 | 0 | transformers | 0 | text-generation | true | false | false | mit | ['en'] | null | null | 1 | 0 | 1 | 0 | 3 | 0 | 3 | ['generated_from_trainer', 'text generation', 'pytorch', 'casual-lm'] | true | true | true | 2,955 | false |
# --- Disclaimer ---
# "Neo is an incredibly cursed codebase, it should not be used by anyone" (C) co-founder of EleutherAI - Connor Leahy
# !!! USE [openchatgpt-neox-125m](https://huggingface.co/mrsteyk/openchatgpt-neox-125m) INSTEAD !!!
# --- Archived ---
# openchatgpt-neo-r1
This model is a fine-tuned version ... | 363a38baa41437aac5164884c2768719 |
Siddu0406/gpt-2-model-2 | Siddu0406 | gpt2 | 13 | 0 | transformers | 0 | text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,026 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt-2-model-2
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
## Model descrip... | f086e22089fd1f2875c22a8e19035a33 |
cammy/bart-large-cnn-100-lit-evalMA-NOpad2 | cammy | bart | 11 | 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 | 1,552 | 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-100-lit-evalMA-NOpad2
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/face... | 2904c5d06d606c80b84944cc19b49c00 |
Mehtap/whisper-base | Mehtap | whisper | 25 | 20 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['tr'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['hf-asr-leaderboard', 'generated_from_trainer'] | true | true | true | 2,002 | 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 Turkish Whisper (BTW)
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-bas... | 4de42494bf32c06be6b744bc961bde5e |
fathyshalab/all-roberta-large-v1-meta-6-16-5 | 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 | 1,507 | 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. -->
# all-roberta-large-v1-meta-6-16-5
This model is a fine-tuned version of [sentence-transformers/all-roberta-large-v1](https://hugg... | f263b49c8773eee9a7f13bdb4ac4bad4 |
Helsinki-NLP/opus-mt-fi-xh | 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-fi-xh
* source languages: fi
* target languages: xh
* OPUS readme: [fi-xh](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fi-xh/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-08.zip](http... | 033987db784f4f88bd650c5730a9f0ac |
lgris/bp500-base100k_voxpopuli | lgris | wav2vec2 | 9 | 8 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['pt'] | ['common_voice', 'mls', 'cetuc', 'lapsbm', 'voxforge', 'tedx', 'sid'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['audio', 'speech', 'wav2vec2', 'pt', 'portuguese-speech-corpus', 'automatic-speech-recognition', 'speech', 'PyTorch'] | false | true | true | 12,406 | false |
# bp500-base100k_voxpopuli: Wav2vec 2.0 with Brazilian Portuguese (BP) Dataset
This is a the demonstration of a fine-tuned Wav2vec model for Brazilian Portuguese using the following datasets:
- [CETUC](http://www02.smt.ufrj.br/~igor.quintanilha/alcaim.tar.gz): contains approximately 145 hours of Brazilian Portuguese... | dfb57b0c3b85eeeade2b272e16bf346b |
birgermoell/psst-fairseq-larger-rir | birgermoell | wav2vec2 | 5 | 7 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition'] | false | true | true | 410 | false |
This model is trained on the PSST Challenge data, with a subset of TIMIT that was augmented using Room Impulse Response (RIR). A file containing the list of TIMIT IDs is in the repository (`timit-ids.txt`)
The model was finetuned on [Wav2vec 2.0 Large, No finetuning](https://github.com/pytorch/fairseq/tree/main/examp... | 330b8788ffa202e8ee922d131a574a4e |
Mizuiro-sakura/deberta-v2-base-japanese-finetuned-ner | Mizuiro-sakura | deberta-v2 | 12 | 10 | transformers | 0 | token-classification | true | false | false | mit | ['ja'] | ['wikipedia', 'cc100', 'oscar'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['pytorch', 'deberta', 'deberta-v2', 'named entity recognition', 'named-entity-recognition', 'ner'] | false | true | true | 2,101 | false |
# このモデルはdeberta-v2-base-japaneseをファインチューニングして固有表現抽出（NER）に用いれるようにしたものです。
このモデルはdeberta-v2-base-japaneseを Wikipediaを用いた日本語の固有表現抽出データセット(ストックマーク社、https://github.com/stockmarkteam/ner-wikipedia-dataset )を用いてファインチューニングしたものです。
# This model is fine-tuned model for Named Entity Recognition (NER) which is based on deberta-v2-... | 08052a58606c65d69b357d8b908b6794 |
stanfordnlp/stanza-swl | stanfordnlp | null | 6 | 4 | stanza | 0 | token-classification | false | false | false | apache-2.0 | ['swl'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['stanza', 'token-classification'] | false | true | true | 595 | false | # Stanza model for Swedish_Sign_Language (swl)
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing.
Find more about it in [... | afd409c3b660a0f11d7a3218304d7115 |
muhtasham/small-mlm-glue-wnli | muhtasham | bert | 12 | 0 | 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 | 2,025 | 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. -->
# small-mlm-glue-wnli
This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert... | 6c6e33522eb1b94005eca3344ade1a12 |
Supreeth/roberta-base-MLM | Supreeth | roberta | 17 | 15 | transformers | 0 | fill-mask | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,010 | 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-MLM
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset... | 53bd78deedd074ccc37b59ec68d52802 |
Hoax0930/kyoto_marian_mod_2_0 | Hoax0930 | marian | 14 | 1 | transformers | 0 | translation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['translation', 'generated_from_trainer'] | true | true | true | 1,068 | 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. -->
# kyoto_marian_mod_3
This model is a fine-tuned version of [Hoax0930/kyoto_marian_mod_2](https://huggingface.co/Hoax0930/kyoto_mar... | 3d8541aaf4120f20a2306374088add81 |
lucio/xls-r-uyghur-cv7 | lucio | wav2vec2 | 25 | 12 | transformers | 1 | automatic-speech-recognition | true | false | false | apache-2.0 | ['ug'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'mozilla-foundation/common_voice_7_0', 'generated_from_trainer', 'ug', 'robust-speech-event', 'hf-asr-leaderboard'] | true | true | true | 4,457 | false |
# XLS-R-300M Uyghur CV7
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - UG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1772
- Wer: 0.2589
## Model description
For a ... | ebb1e0eb12296c4ba49c65c2380fa740 |
anas-awadalla/roberta-large-houlsby-few-shot-k-64-finetuned-squad-seed-2 | anas-awadalla | null | 19 | 0 | null | 0 | null | false | false | false | mit | null | ['squad'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,096 | 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-large-houlsby-few-shot-k-64-finetuned-squad-seed-2
This model is a fine-tuned version of [roberta-large](https://hugging... | 0a2e72399a33eee619c751acdb2dbcc9 |
bigmorning/distilbert_oscarth_0040 | bigmorning | distilbert | 4 | 2 | transformers | 0 | fill-mask | false | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 2,787 | 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. -->
# distilbert_oscarth_0040
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased... | 9162d8213ad4568c7d48c661d2348e86 |
Helsinki-NLP/opus-mt-pap-en | Helsinki-NLP | marian | 10 | 12 | transformers | 0 | translation | true | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['translation'] | false | true | true | 812 | false |
### opus-mt-pap-en
* source languages: pap
* target languages: en
* OPUS readme: [pap-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/pap-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | 74baa4e53dc7b66e8979c9e6f10ec015 |
meongracun/nmt-mpst-id-en-lr_1e-4-ep_10-seq_128_bs-64 | meongracun | t5 | 9 | 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 | 1,858 | 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. -->
# nmt-mpst-id-en-lr_1e-4-ep_10-seq_128_bs-64
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on ... | 66704caee828d2a6dc50091d7b5584cb |
facebook/s2t-small-covost2-es-en-st | facebook | speech_to_text | 11 | 18 | transformers | 0 | automatic-speech-recognition | true | true | false | mit | ['es', 'en'] | ['covost2'] | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['audio', 'speech-translation', 'automatic-speech-recognition'] | false | true | true | 4,012 | false |
# S2T-SMALL-COVOST2-ES-EN-ST
`s2t-small-covost2-es-en-st` is a Speech to Text Transformer (S2T) model trained for end-to-end Speech Translation (ST).
The S2T model was proposed in [this paper](https://arxiv.org/abs/2010.05171) and released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/... | 30f7e1591924e0561b42b7d062cc9c36 |
echarlaix/bart-base-cnn-r2-19.4-d35-hybrid | echarlaix | bart | 111 | 6 | transformers | 0 | summarization | true | false | false | apache-2.0 | ['en'] | ['cnn_dailymail'] | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['summarization'] | false | true | true | 1,187 | false |
## facebook/bart-base model fine-tuned on CNN/DailyMail
This model was created using the [nn_pruning](https://github.com/huggingface/nn_pruning) python library: the linear layers contains **35%** of the original weights.
The model contains **53%** of the original weights **overall** (the embeddings account for a ... | 429401019a8e860f1645bad606d37ac9 |
silviacamplani/distilbert-finetuned-dapt_tapt-ner-music | silviacamplani | distilbert | 18 | 8 | transformers | 1 | token-classification | false | true | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_keras_callback'] | true | true | true | 2,776 | 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. -->
# silviacamplani/distilbert-finetuned-dapt_tapt-ner-music
This model is a fine-tuned version of [silviacamplani/distilbert-finetuned-dap... | 9f8c1991a45776d203ae7a8f5b70bfaf |
arnepeine/mona_speech | arnepeine | whisper | 21 | 29 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['de'] | ['mozilla-foundation/common_voice_11_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['hf-asr-leaderboard', 'generated_from_trainer'] | true | true | true | 1,495 | 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. -->
# Mona Speech Model (Trained on ICU Data)
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/open... | a088061f3539b6bb08e55cefd08d35c0 |
AFreud/bert-base-romanian-ner-finetuned-ner | AFreud | bert | 13 | 18 | transformers | 0 | token-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,397 | 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-romanian-ner-finetuned-ner
This model is a fine-tuned version of [dumitrescustefan/bert-base-romanian-ner](https://hug... | d9b7f864644eeec17d45b54bc1c63fae |
fanpu/model_output_sorted_by_upvotes_positive_subreddit-wallstreetbets_1 | fanpu | gpt2 | 11 | 4 | transformers | 0 | text-generation | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,711 | 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_output_sorted_by_upvotes_positive_subreddit-wallstreetbets_1
This model is a fine-tuned version of [gpt2](https://huggingf... | bc184a76933f92c482bb29673b4d8cd6 |
superb/hubert-large-superb-sid | superb | hubert | 5 | 56 | transformers | 0 | audio-classification | true | false | false | apache-2.0 | ['en'] | ['superb'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['speech', 'audio', 'hubert', 'audio-classification'] | false | true | true | 3,044 | false |
# Hubert-Large for Speaker Identification
## Model description
This is a ported version of
[S3PRL's Hubert for the SUPERB Speaker Identification task](https://github.com/s3prl/s3prl/tree/master/s3prl/downstream/voxceleb1).
The base model is [hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k), ... | f1039ff28fd12e58f92cf042a1262050 |
dominguesm/legal-bert-base-cased-ptbr | dominguesm | bert | 11 | 5 | transformers | 0 | fill-mask | true | false | false | apache-2.0 | ['pt'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | false | true | true | 4,036 | false |
## (BERT base) Language modeling in the legal domain in Portuguese
**legal-bert-base-cased-ptbr** is a Language Model in the legal domain in Portuguese based on the model [BERTimbau base](https://huggingface.co/neuralmind/bert-base-portuguese-cased) by using a MASK objective.
The model is intended to assist NLP re... | 8708b6361ef06b03e38e3ba4a5062059 |
kejian/fanatic-conditional | kejian | gpt2 | 25 | 7 | transformers | 0 | null | true | false | false | apache-2.0 | ['en'] | ['kejian/codeparrot-train-more-filter-3.3b-cleaned'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 5,565 | 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. -->
# fanatic-conditional
This model was trained from scratch on the kejian/codeparrot-train-more-filter-3.3b-cleaned dataset.
## Mod... | 4dee306ed1689d8705723053da2f3606 |
Helsinki-NLP/opus-mt-tc-big-en-hu | Helsinki-NLP | marian | 13 | 59 | transformers | 0 | translation | true | true | false | cc-by-4.0 | ['en', 'hu'] | null | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | ['translation', 'opus-mt-tc'] | true | true | true | 5,415 | false | # opus-mt-tc-big-en-hu
Neural machine translation model for translating from English (en) to Hungarian (hu).
This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All mo... | b510a7de99048f86f2568c36c837d730 |
apurik-parv/ilayaraja | apurik-parv | null | 56 | 5 | diffusers | 0 | null | false | false | false | mit | null | null | null | 2 | 0 | 2 | 0 | 0 | 0 | 0 | [] | false | true | true | 5,208 | false | ### ilayaraja 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 apurik-parv
This is the Stable Diffusion model fine-tuned to the art style of Elayaraja,... | f77e0fdb468008764576c3c6fff3b671 |
emre/wav2vec2-xls-r-300m-Turkish-Tr-med | emre | wav2vec2 | 14 | 5 | 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', 'robust-speech-event'] | true | true | true | 2,146 | 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-xls-r-300m-Turkish-Tr-med
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/f... | a90ccf8bf246b69ab3ca67022e6fd20f |
ultra-coder54732/3-way-detection-prop-16 | ultra-coder54732 | roberta | 21 | 0 | transformers | 0 | text-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 946 | 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. -->
# 3-way-detection-prop-16
This model is a fine-tuned version of [ultra-coder54732/3-way-detection-prop-16](https://huggingface.co/... | 51a60d34820a32524b63e45b0287f16b |
Helsinki-NLP/opus-mt-de-mt | Helsinki-NLP | marian | 10 | 16 | 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-de-mt
* source languages: de
* target languages: mt
* OPUS readme: [de-mt](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-mt/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-20.zip](http... | 1c7073186681db613bb1d9955c938beb |
Jinchen/t5-small-finetuned-xsum | Jinchen | t5 | 7 | 1 | transformers | 0 | text2text-generation | true | false | false | apache-2.0 | null | ['xsum'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,283 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-xsum
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
I... | 5b7496eee01ae1b0b3d44410e846225f |
eugenesiow/rcan-bam | eugenesiow | RCAN | 6 | 103 | transformers | 0 | null | false | false | false | apache-2.0 | null | ['eugenesiow/Div2k', 'eugenesiow/Set5', 'eugenesiow/Set14', 'eugenesiow/BSD100', 'eugenesiow/Urban100'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['super-image', 'image-super-resolution'] | false | true | true | 9,182 | false | # Residual Channel Attention Networks (RCAN)
RCAN model pre-trained on DIV2K (800 images training, augmented to 4000 images, 100 images validation) for 2x, 3x and 4x image super resolution. It was introduced in the paper [Image Super-Resolution Using Very Deep Residual Channel Attention Networks](https://arxiv.org/abs... | 413d8c48f26da67263267fb42c976de5 |
emiyasstar/ch-w2v-conformer-norelpos | emiyasstar | null | 3 | 0 | null | 0 | null | false | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,667 | false | The ch-w2v-conformer model uses following datasets to pretrain:
ISML datasets (6 languages,70k hours): internal dataset contains 40k hours Chinese, Cantonese, Tibetan, Inner Mongolian, Inner Kazakh, Uighur.
Babel datasets (17 languages, 2k hours): Assamese, Bengali, Cantonese, Cebuano, Georgian, Haitian, Kazakh, Ku... | 573d0a65fa405d0a581842859c6ffafa |
wiem87/swin-tiny-patch4-window7-224-finetuned-eurosat | wiem87 | swin | 9 | 1 | transformers | 0 | image-classification | true | false | false | apache-2.0 | null | ['imagefolder'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,492 | 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. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | 26e51391e1991330390c8754a74e18ed |
Helsinki-NLP/opus-mt-yap-fr | Helsinki-NLP | marian | 10 | 12 | 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-yap-fr
* source languages: yap
* target languages: fr
* OPUS readme: [yap-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yap-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | 8a3136e7ac181328f771c9cb59533aa6 |
dominguesm/pt_core_news_trf | dominguesm | null | 27 | 16 | spacy | 1 | token-classification | false | false | false | cc-by-sa-4.0 | ['pt'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['spacy', 'token-classification'] | false | true | true | 43,344 | false |
Portuguese transformer pipeline ([neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased)). Components: transformer, morphologizer, parser, ner, attribute_ruler, lemmatizer (trainable_lemmatizer).
| Feature | Description |
| --- | --- |
| **Name** | `pt_core_news_trf` |
| ... | 60d1f8cc178c5c1bd8a9459591a5da32 |
Fhrozen/test_an4 | Fhrozen | null | 31 | 1 | espnet | 0 | automatic-speech-recognition | false | false | false | cc-by-4.0 | ['en'] | ['an4'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['espnet', 'audio', 'automatic-speech-recognition'] | false | true | true | 7,699 | false |
## ESPnet2 ASR model
### `Fhrozen/test_an4`
This model was trained by Fhrozen using an4 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```bash
cd espnet
git checkout b8df4c928e132acff78d196988bdb68a66987952
pip install -e .
cd egs2/an4/asr1
./run.sh --skip_data_prep false -... | 6fa244cd2fe0524b9b46c9c149349166 |
jonatasgrosman/exp_w2v2r_en_vp-100k_gender_male-8_female-2_s859 | jonatasgrosman | wav2vec2 | 10 | 3 | 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-8_female-2_s859
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 ... | 4c59ea635d5a80ba0a6f5f36b5f7e61e |
Sercan/whisper-small-tr | Sercan | whisper | 28 | 1 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['tr'] | ['mozilla-foundation/common_voice_11_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['whisper', 'generated_from_trainer'] | true | true | true | 1,642 | false |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small Turkish
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) ... | 7830a334a4304178ad0a98dfacd10674 |
gossminn/predict-perception-bertino-focus-object | gossminn | distilbert | 12 | 5 | transformers | 0 | text-classification | true | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 3,970 | 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. -->
# predict-perception-bertino-focus-object
This model is a fine-tuned version of [indigo-ai/BERTino](https://huggingface.co/indigo-... | 01f35b10b8456e0c84c21e4d2755e9a0 |
sd-concepts-library/kaleido | sd-concepts-library | null | 10 | 0 | null | 1 | null | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,100 | false | ### kaleido on Stable Diffusion
This is the `<kaleido>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) notebook. You can also tr... | 4f37b5f7a89dc83181324353952275ad |
jonatasgrosman/exp_w2v2t_pt_vp-100k_s69 | jonatasgrosman | wav2vec2 | 10 | 5 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['pt'] | ['mozilla-foundation/common_voice_7_0'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'pt'] | false | true | true | 474 | false | # exp_w2v2t_pt_vp-100k_s69
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 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure th... | 08f9f0d9d54585b72584d1536e9aa872 |
juancavallotti/t5-base-gec | juancavallotti | t5 | 52 | 2 | transformers | 2 | text2text-generation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 889 | 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-gec
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
## Model descr... | bca2ae06405e129a9134222dadaaef78 |
Helsinki-NLP/opus-mt-fi-hil | 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-fi-hil
* source languages: fi
* target languages: hil
* OPUS readme: [fi-hil](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fi-hil/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-24.zip](... | 0e1a3e6abfa9684a9a6b438b97c3811b |
misterbrainley/ddpm-butterflies-128 | misterbrainley | 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 | 1,236 | 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... | b8bbc6564e441ece0aaa4ae229682375 |
cmarkea/distilcamembert-base-nli | cmarkea | camembert | 9 | 1,125 | transformers | 7 | zero-shot-classification | true | true | false | mit | ['fr'] | ['flue'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['zero-shot-classification', 'sentence-similarity', 'nli'] | false | true | true | 7,982 | false |
DistilCamemBERT-NLI
===================
We present DistilCamemBERT-NLI, which is [DistilCamemBERT](https://huggingface.co/cmarkea/distilcamembert-base) fine-tuned for the Natural Language Inference (NLI) task for the french language, also known as recognizing textual entailment (RTE). This model is constructed on the... | 1eb211c15a29465f564fbdf4b4e27eac |
speechbrain/asr-transformer-transformerlm-librispeech | speechbrain | null | 9 | 767 | speechbrain | 4 | automatic-speech-recognition | true | false | false | apache-2.0 | ['en'] | ['librispeech'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'CTC', 'Attention', 'Transformer', 'pytorch', 'speechbrain', 'hf-asr-leaderboard'] | true | true | true | 4,029 | 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/>
# Transformer for LibriSpeech (with Transformer LM)
This repository provides all the necessary tools to perf... | f80b26f950cadc6cd5ff925d1ff4cd34 |
bobber/terrier-dog | bobber | null | 17 | 24 | diffusers | 0 | 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', 'animal'] | false | true | true | 2,028 | false |
# DreamBooth model for the terrier concept trained by bobber on the bobber/Terrier-images dataset.
This is a Stable Diffusion model fine-tuned on the terrier concept with DreamBooth. It can be used by modifying the `instance_prompt`: **a photo of terrier dog**
This model was created as part of the DreamBooth Hackath... | d386bd115ec46b4400991998874ee6ce |
izumi-lab/electra-small-paper-japanese-fin-discriminator | izumi-lab | electra | 7 | 12 | transformers | 0 | null | true | false | false | cc-by-sa-4.0 | ['ja'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['finance'] | false | true | true | 2,101 | false |
# ELECTRA small Japanese finance discriminator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model archit... | b93352fe1b1880cc1187ad75cbc1b5c6 |
DOOGLAK/Tagged_One_50v7_NER_Model_3Epochs_AUGMENTED | DOOGLAK | bert | 13 | 5 | transformers | 0 | token-classification | true | false | false | apache-2.0 | null | ['tagged_one50v7_wikigold_split'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,539 | 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_50v7_NER_Model_3Epochs_AUGMENTED
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-... | ffcac8683c3ae04284552f2844322b5f |
nvidia/stt_fr_conformer_ctc_large | nvidia | null | 3 | 35 | nemo | 4 | automatic-speech-recognition | true | false | false | cc-by-4.0 | ['fr'] | ['multilingual_librispeech', 'mozilla-foundation/common_voice_7_0', 'VoxPopuli'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'speech', 'audio', 'CTC', 'Conformer', 'Transformer', 'pytorch', 'NeMo', 'hf-asr-leaderboard', 'Riva'] | true | true | true | 6,361 | false |
# NVIDIA Conformer-CTC Large (fr)
<style>
img {
display: inline;
}
</style>
| [](#model-architecture)
| [](#model-architecture)
| [![Languag... | b26f45ff093948e65542c79aadd8cbff |
tanviraumi/bert-base-uncased-issues-128 | tanviraumi | bert | 10 | 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 | 1,932 | 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-issues-128
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased)... | 5f641c56cbb10eac37364ff54d0ec6e1 |
muhtasham/small-mlm-squad | muhtasham | bert | 12 | 1 | transformers | 1 | fill-mask | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,350 | 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. -->
# small-mlm-squad-plain_text
This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/goog... | c60604a61b32b6b6b65e8efb7f13476e |
kadirnar/SORT | kadirnar | null | 2 | 0 | null | 0 | object-detection | false | false | false | mit | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['object-detection', 'computer-vision', 'sort', 'tracker', 'ocsort'] | false | true | true | 1,030 | false |
### Model Description
[Sort](https://arxiv.org/abs/1602.00763): A simple online and realtime tracking algorithm for 2D multiple object tracking in video sequences<img src="https://raw.githubusercontent.com/noahcao/OC_SORT/master/assets/teaser.png" width="600"/>
### Installation
```
pip install sort-track
```
### Tra... | 98bbb20e4c5651a0b7a23ff32d01fae4 |
tftransformers/albert-base-v1 | tftransformers | null | 6 | 3 | null | 0 | null | false | false | false | apache-2.0 | ['en'] | ['bookcorpus', 'wikipedia'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['exbert'] | false | true | true | 6,683 | false |
# ALBERT Base v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). This model, as all ALBERT models, is uncased: it does not make... | 075a0a207182f0cbf24f6c04da030697 |
espnet/Wangyou_Zhang_chime4_enh_train_enh_beamformer_mvdr_raw | espnet | null | 15 | 66 | espnet | 0 | audio-to-audio | false | false | false | cc-by-4.0 | null | ['chime4'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['espnet', 'audio', 'audio-to-audio'] | false | true | true | 5,642 | false |
## ESPnet2 ENH model
### `espnet/Wangyou_Zhang_chime4_enh_train_enh_beamformer_mvdr_raw`
This model was trained by Wangyou Zhang using chime4 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```bash
cd espnet
pip install -e .
cd egs2/chime4/enh1
./run.sh --skip_data_prep fal... | 81b12e20a472652e7535d1c7ab207231 |
EnsarEmirali/distilbert-base-uncased-finetuned-emotion | EnsarEmirali | distilbert | 12 | 6 | transformers | 0 | text-classification | true | false | false | apache-2.0 | null | ['emotion'] | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,339 | 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... | bff1edd388a301def284f8d29f09be75 |
pulkitkumar13/dark-bert-finetuned-ner1 | pulkitkumar13 | bert | 10 | 7 | transformers | 0 | token-classification | true | false | false | apache-2.0 | null | ['conll2003'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,518 | 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. -->
# dark-bert-finetuned-ner1
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the ... | c88e1abbead437968f5bfdd017830df9 |
liyijing024/swin-base-patch4-window7-224-in22k-finetuned | liyijing024 | swin | 11 | 11 | transformers | 0 | image-classification | true | false | false | apache-2.0 | null | ['imagefolder'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,508 | 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. -->
# swin-base-patch4-window7-224-in22k-finetuned
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k... | d6a2dbf67949a0edb35e6b538738d9a5 |
google/multiberts-seed_2-step_1800k | google | bert | 8 | 14 | transformers | 0 | null | true | true | false | apache-2.0 | ['en'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['multiberts', 'multiberts-seed_2', 'multiberts-seed_2-step_1800k'] | false | true | true | 3,527 | false |
# MultiBERTs, Intermediate Checkpoint - Seed 2, Step 1800k
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... | 7a32a55bd042884075cef2c8c959df03 |
l-tran/distilroberta-base-OLID-MLM | l-tran | roberta | 9 | 16 | transformers | 0 | text-generation | true | false | false | apache-2.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,256 | 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-OLID-MLM
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base... | 8607875ac3eb8d6171fa685c1789e722 |
domdomreloaded/bert-base-uncased-finetuned-swag | domdomreloaded | bert | 22 | 5 | transformers | 0 | multiple-choice | true | false | false | apache-2.0 | null | ['swag'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 1,272 | 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-swag
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-unca... | d306d34bc39b5903f59d54a462aa471c |
cardiffnlp/twitter-roberta-base-sep2021 | cardiffnlp | roberta | 9 | 5 | transformers | 0 | fill-mask | true | false | false | mit | ['en'] | ['twitter-api'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['timelms', 'twitter'] | false | true | true | 4,657 | false |
# Twitter September 2021 (RoBERTa-base, 120M)
This is a RoBERTa-base model trained on 119.66M tweets until the end of September 2021.
More details and performance scores are available in the [TimeLMs paper](https://arxiv.org/abs/2202.03829).
Below, we provide some usage examples using the standard Transformers inter... | 2ba18a0d275b347413a624d09766471d |
CompVis/stable-diffusion-v1-3 | CompVis | null | 18 | 848 | diffusers | 24 | text-to-image | false | false | false | creativeml-openrail-m | null | null | null | 5 | 3 | 2 | 0 | 0 | 0 | 0 | ['stable-diffusion', 'stable-diffusion-diffusers', 'text-to-image'] | false | true | true | 12,886 | false |
# Stable Diffusion v1-3 Model Card
Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
For more information about how Stable Diffusion functions, please have a look at [🤗's Stable Diffusion with D🧨iffusers blog](https://huggingface.co/blog/st... | 3f41400f83f4634a329b0fea07df24ab |
facebook/regnet-x-120 | facebook | regnet | 6 | 11 | transformers | 0 | image-classification | true | true | false | apache-2.0 | null | ['imagenet-1k'] | null | 2 | 0 | 1 | 1 | 0 | 0 | 0 | ['vision', 'image-classification'] | false | true | true | 1,893 | false |
# RegNet
RegNet model trained on imagenet-1k. It was introduced in the paper [Designing Network Design Spaces](https://arxiv.org/abs/2003.13678) and first released in [this repository](https://github.com/facebookresearch/pycls).
Disclaimer: The team releasing RegNet did not write a model card for this model so this... | a2097c1f1a800116809b7b8148c121d0 |
samitizerxu/wav2vec2-xls-r-300m-fr | samitizerxu | wav2vec2 | 23 | 6 | transformers | 0 | automatic-speech-recognition | true | false | false | apache-2.0 | ['fr'] | ['common_voice'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['automatic-speech-recognition', 'common_voice', 'fr', 'generated_from_trainer', 'hf-asr-leaderboard', 'robust-speech-event'] | true | true | true | 1,936 | 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-cls-r-300m-fr
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2... | cdb8b09f9948d844a5c47024c7bff8de |
muhtasham/tiny-mlm-glue-mrpc-custom-tokenizer-expand-vocab | muhtasham | bert | 12 | 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 | 1,683 | 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-glue-mrpc-custom-tokenizer-expand-vocab
This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https... | 4ead2fe9b148442afddca8cfa02581ac |
amitjohn007/second-mobil-bert-finetuned-squad | amitjohn007 | mobilebert | 8 | 4 | 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 | 1,369 | 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. -->
# amitjohn007/second-mobil-bert-finetuned-squad
This model is a fine-tuned version of [csarron/mobilebert-uncased-squad-v2](https://hugg... | fa88bd5d6bb1a247d9f2e21664589f71 |
hfl/chinese-pert-large-mrc | hfl | bert | 8 | 35 | transformers | 3 | question-answering | true | true | false | apache-2.0 | ['zh'] | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | [] | false | true | true | 1,449 | false |
## A Chinese MRC model built on Chinese PERT-large
**Please use `BertForQuestionAnswering` to load this model!**
This is a Chinese machine reading comprehension (MRC) model built on PERT-large and fine-tuned on a mixture of Chinese MRC datasets.
PERT is a pre-trained model based on permuted language model (PerLM) t... | 232f029f8e82f311a60ab165999d23f8 |
dipteshkanojia/hing-roberta-CM-run-5 | dipteshkanojia | xlm-roberta | 9 | 4 | transformers | 0 | text-classification | true | false | false | cc-by-4.0 | null | null | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['generated_from_trainer'] | true | true | true | 3,101 | 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. -->
# hing-roberta-CM-run-5
This model is a fine-tuned version of [l3cube-pune/hing-roberta](https://huggingface.co/l3cube-pune/hing-r... | 9bb33454676308d2da58f87817db1be4 |
Shashidhar/distilbert-base-uncased-finetuned-squad | Shashidhar | distilbert | 29 | 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 | 1,179 | 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... | 36e2a2fd479c5c1590bec511e3938606 |
KoichiYasuoka/deberta-large-chinese-erlangshen-ud-goeswith | KoichiYasuoka | deberta-v2 | 9 | 16 | transformers | 0 | token-classification | true | false | false | apache-2.0 | ['zh'] | ['universal_dependencies'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['chinese', 'token-classification', 'pos', 'dependency-parsing'] | false | true | true | 2,799 | false |
# deberta-large-chinese-erlangshen-ud-goeswith
## Model Description
This is a DeBERTa(V2) model pre-trained on Chinese texts (both simplified and traditional) for POS-tagging and dependency-parsing (using `goeswith` for subwords), derived from [deberta-large-chinese-erlangshen-upos](https://huggingface.co/KoichiYasu... | 3b144bbede853b9fbfd941507a30b20c |
jonatasgrosman/exp_w2v2r_es_xls-r_age_teens-10_sixties-0_s900 | 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 | 476 | false | # exp_w2v2r_es_xls-r_age_teens-10_sixties-0_s900
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure ... | 358b0ca6113b8380cecf85130e9c2997 |
KoichiYasuoka/chinese-roberta-large-upos | KoichiYasuoka | bert | 8 | 8 | transformers | 0 | token-classification | true | false | false | apache-2.0 | ['zh'] | ['universal_dependencies'] | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ['chinese', 'token-classification', 'pos', 'wikipedia', 'dependency-parsing'] | false | true | true | 902 | false |
# chinese-roberta-large-upos
## Model Description
This is a BERT model pre-trained on Chinese Wikipedia texts (both simplified and traditional) for POS-tagging and dependency-parsing, derived from [chinese-roberta-wwm-ext-large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large). Every word is tagged by [UPOS... | 542314d3d10d3a038776c33db49274f8 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.