modelId stringlengths 4 111 | lastModified stringlengths 24 24 | tags list | pipeline_tag stringlengths 5 30 ⌀ | author stringlengths 2 34 ⌀ | config null | securityStatus null | id stringlengths 4 111 | likes int64 0 9.53k | downloads int64 2 73.6M | library_name stringlengths 2 84 ⌀ | created timestamp[us] | card stringlengths 101 901k | card_len int64 101 901k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TheBloke/Llama-2-7B-Chat-GPTQ | 2023-09-27T12:44:48.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-2",
"en",
"arxiv:2307.09288",
"license:llama2",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/Llama-2-7B-Chat-GPTQ | 165 | 101,944 | transformers | 2023-07-18T17:38:15 | ---
language:
- en
license: llama2
tags:
- facebook
- meta
- pytorch
- llama
- llama-2
model_name: Llama 2 7B Chat
arxiv: 2307.09288
base_model: meta-llama/Llama-2-7b-chat-hf
inference: false
model_creator: Meta Llama 2
model_type: llama
pipeline_tag: text-generation
prompt_template: '[INST] <<SYS>>
You are a helpfu... | 25,013 | [
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pysentimiento/robertuito-emotion-analysis | 2023-02-20T19:04:28.000Z | [
"pysentimiento",
"pytorch",
"roberta",
"emotion-analysis",
"twitter",
"es",
"arxiv:2106.09462",
"region:us"
] | null | pysentimiento | null | null | pysentimiento/robertuito-emotion-analysis | 13 | 101,688 | pysentimiento | 2022-03-02T23:29:05 | ---
language:
- es
library_name: pysentimiento
tags:
- emotion-analysis
- twitter
---
# Emotion Analysis in Spanish
## robertuito-emotion-analysis
Repository: [https://github.com/pysentimiento/pysentimiento/](https://github.com/finiteautomata/pysentimiento/)
Model trained with TASS 2020 Task 2 corpus for ... | 4,100 | [
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jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn | 2022-12-14T01:58:32.000Z | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"zh",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | jonatasgrosman | null | null | jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn | 53 | 101,491 | transformers | 2022-03-02T23:29:05 | ---
language: zh
datasets:
- common_voice
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Chinese (zh-CN) by Jonatas Grosman
results:
- task:
name: Speech Recognition
type: automatic-speech-recogni... | 7,036 | [
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gsdf/Counterfeit-V2.5 | 2023-03-14T17:41:46.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | gsdf | null | null | gsdf/Counterfeit-V2.5 | 1,469 | 101,398 | diffusers | 2023-02-02T14:02:11 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
# Update
V2.5 has been updated for ease of use as anime-style model.
I use this embedding for negative prompts.
https://huggingface.co/datasets/gsdf/EasyNegative
Share by-pro... | 4,056 | [
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segmind/SSD-1B | 2023-11-06T12:08:15.000Z | [
"diffusers",
"text-to-image",
"ultra-realistic",
"stable-diffusion",
"distilled-model",
"knowledge-distillation",
"dataset:zzliang/GRIT",
"dataset:wanng/midjourney-v5-202304-clean",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionXLPipeline",
"region:us"
... | text-to-image | segmind | null | null | segmind/SSD-1B | 430 | 101,199 | diffusers | 2023-10-19T05:18:22 | ---
license: apache-2.0
tags:
- text-to-image
- ultra-realistic
- text-to-image
- stable-diffusion
- distilled-model
- knowledge-distillation
pinned: true
datasets:
- zzliang/GRIT
- wanng/midjourney-v5-202304-clean
library_name: diffusers
---
# Segmind Stable Diffusion 1B (SSD-1B) Model Card
![image/png](https://cdn-... | 10,378 | [
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facebook/hubert-large-ls960-ft | 2022-05-24T10:43:42.000Z | [
"transformers",
"pytorch",
"tf",
"hubert",
"automatic-speech-recognition",
"speech",
"audio",
"hf-asr-leaderboard",
"en",
"dataset:libri-light",
"dataset:librispeech_asr",
"arxiv:2106.07447",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | facebook | null | null | facebook/hubert-large-ls960-ft | 42 | 101,158 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- libri-light
- librispeech_asr
tags:
- speech
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
model-index:
- name: hubert-large-ls960-ft
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
n... | 3,325 | [
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THUDM/chatglm-6b | 2023-09-04T15:49:45.000Z | [
"transformers",
"pytorch",
"chatglm",
"glm",
"thudm",
"custom_code",
"zh",
"en",
"arxiv:2103.10360",
"arxiv:2210.02414",
"endpoints_compatible",
"has_space",
"region:us"
] | null | THUDM | null | null | THUDM/chatglm-6b | 2,646 | 100,796 | transformers | 2023-03-13T16:28:04 | ---
language:
- zh
- en
tags:
- glm
- chatglm
- thudm
---
# ChatGLM-6B
<p align="center">
🌐 <a href="https://chatglm.cn/blog" target="_blank">Blog</a> • 💻 <a href="https://github.com/THUDM/ChatGLM-6B" target="_blank">Github Repo</a> • 🐦 <a href="https://twitter.com/thukeg" target="_blank">Twitter</a> • 📃 <a href... | 5,122 | [
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openlm-research/open_llama_3b_v2 | 2023-07-16T08:32:00.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"dataset:tiiuae/falcon-refinedweb",
"dataset:bigcode/starcoderdata",
"dataset:togethercomputer/RedPajama-Data-1T",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | openlm-research | null | null | openlm-research/open_llama_3b_v2 | 69 | 99,894 | transformers | 2023-07-16T00:39:43 | ---
license: apache-2.0
datasets:
- tiiuae/falcon-refinedweb
- bigcode/starcoderdata
- togethercomputer/RedPajama-Data-1T
---
# OpenLLaMA: An Open Reproduction of LLaMA
**TL;DR**: we are releasing our public preview of OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA. We are releasing a ... | 12,194 | [
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0.006309... |
liuhaotian/llava-v1.5-7b | 2023-10-22T05:16:14.000Z | [
"transformers",
"pytorch",
"llava",
"text-generation",
"has_space",
"region:us"
] | text-generation | liuhaotian | null | null | liuhaotian/llava-v1.5-7b | 108 | 99,810 | transformers | 2023-10-05T18:25:51 | ---
inference: false
---
<br>
<br>
# LLaVA Model Card
## Model details
**Model type:**
LLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
It is an auto-regressive language model, based on the transformer architecture.
**Model date:**
LLaVA-v1... | 1,364 | [
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-... |
nvidia/mit-b0 | 2022-08-06T10:24:41.000Z | [
"transformers",
"pytorch",
"tf",
"segformer",
"image-classification",
"vision",
"dataset:imagenet_1k",
"arxiv:2105.15203",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | nvidia | null | null | nvidia/mit-b0 | 19 | 99,706 | transformers | 2022-03-02T23:29:05 | ---
license: other
tags:
- vision
datasets:
- imagenet_1k
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000002.jpg
example_tit... | 3,354 | [
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0.00747680... |
SimianLuo/LCM_Dreamshaper_v7 | 2023-11-06T14:56:09.000Z | [
"diffusers",
"text-to-image",
"en",
"arxiv:2310.04378",
"license:mit",
"has_space",
"diffusers:LatentConsistencyModelPipeline",
"region:us"
] | text-to-image | SimianLuo | null | null | SimianLuo/LCM_Dreamshaper_v7 | 138 | 99,101 | diffusers | 2023-10-14T08:26:52 | ---
license: mit
language:
- en
pipeline_tag: text-to-image
tags:
- text-to-image
---
# Latent Consistency Models
Official Repository of the paper: *[Latent Consistency Models](https://arxiv.org/abs/2310.04378)*.
Project Page: https://latent-consistency-models.github.io
## Try our Hugging Face demos:
[![Hugging Fa... | 3,498 | [
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microsoft/speecht5_tts | 2023-10-05T12:24:56.000Z | [
"transformers",
"pytorch",
"speecht5",
"text-to-audio",
"audio",
"text-to-speech",
"dataset:libritts",
"arxiv:2110.07205",
"arxiv:1910.09700",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | text-to-speech | microsoft | null | null | microsoft/speecht5_tts | 308 | 98,550 | transformers | 2023-02-02T12:56:54 | ---
license: mit
tags:
- audio
- text-to-speech
datasets:
- libritts
---
# SpeechT5 (TTS task)
SpeechT5 model fine-tuned for speech synthesis (text-to-speech) on LibriTTS.
This model was introduced in [SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing](https://arxiv.org/abs/2110.072... | 10,807 | [
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TheBloke/Llama-2-13B-chat-GPTQ | 2023-09-27T12:44:48.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-2",
"en",
"arxiv:2307.09288",
"license:llama2",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/Llama-2-13B-chat-GPTQ | 298 | 98,464 | transformers | 2023-07-18T18:28:36 | ---
language:
- en
license: llama2
tags:
- facebook
- meta
- pytorch
- llama
- llama-2
model_name: Llama 2 13B Chat
base_model: meta-llama/Llama-2-13b-chat-hf
inference: false
model_creator: Meta Llama 2
model_type: llama
pipeline_tag: text-generation
prompt_template: '[INST] <<SYS>>
You are a helpful, respectful an... | 26,299 | [
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flair/pos-english | 2023-04-10T15:54:36.000Z | [
"flair",
"pytorch",
"token-classification",
"sequence-tagger-model",
"en",
"dataset:ontonotes",
"has_space",
"region:us"
] | token-classification | flair | null | null | flair/pos-english | 18 | 97,775 | flair | 2022-03-02T23:29:05 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- ontonotes
inference: false
---
## English Part-of-Speech Tagging in Flair (default model)
This is the standard part-of-speech tagging model for English that ships with [Flair](https://github.com/flairNLP/flair/).
F1-Score: **98... | 4,962 | [
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alisawuffles/roberta-large-wanli | 2023-06-14T04:58:48.000Z | [
"transformers",
"pytorch",
"safetensors",
"roberta",
"text-classification",
"en",
"dataset:alisawuffles/WANLI",
"endpoints_compatible",
"region:us"
] | text-classification | alisawuffles | null | null | alisawuffles/roberta-large-wanli | 6 | 97,577 | transformers | 2022-03-30T20:00:10 | ---
language:
- en
tags:
- text-classification
widget:
- text: "I almost forgot to eat lunch.</s></s>I didn't forget to eat lunch."
- text: "I almost forgot to eat lunch.</s></s>I forgot to eat lunch."
- text: "I ate lunch.</s></s>I almost forgot to eat lunch."
datasets:
- alisawuffles/WANLI
---
This is an off-th... | 3,145 | [
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EleutherAI/gpt-neo-125m | 2023-07-09T15:54:09.000Z | [
"transformers",
"pytorch",
"jax",
"rust",
"safetensors",
"gpt_neo",
"text-generation",
"text generation",
"causal-lm",
"en",
"dataset:EleutherAI/pile",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | text-generation | EleutherAI | null | null | EleutherAI/gpt-neo-125m | 134 | 97,540 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
tags:
- text generation
- pytorch
- causal-lm
license: mit
datasets:
- EleutherAI/pile
---
# GPT-Neo 125M
## Model Description
GPT-Neo 125M is a transformer model designed using EleutherAI's replication of the GPT-3 architecture. GPT-Neo refers to the class of models, while 125M represents the num... | 3,446 | [
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microsoft/infoxlm-large | 2021-08-04T11:43:05.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"fill-mask",
"arxiv:2007.07834",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | microsoft | null | null | microsoft/infoxlm-large | 8 | 97,460 | transformers | 2022-03-02T23:29:05 | # InfoXLM
**InfoXLM** (NAACL 2021, [paper](https://arxiv.org/pdf/2007.07834.pdf), [repo](https://github.com/microsoft/unilm/tree/master/infoxlm), [model](https://huggingface.co/microsoft/infoxlm-base)) InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training.
**MD5**
```
05b95b7d9774... | 1,246 | [
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dbmdz/bert-base-turkish-cased | 2021-05-19T15:14:46.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"tr",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | null | dbmdz | null | null | dbmdz/bert-base-turkish-cased | 44 | 97,392 | transformers | 2022-03-02T23:29:05 | ---
language: tr
license: mit
---
# 🤗 + 📚 dbmdz Turkish BERT model
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a cased model for Turkish 🎉
# 🇹🇷 BERTurk
BERTurk is a community-driven cased BERT model for Turkish.
Some datasets used for pretraining and eval... | 2,858 | [
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-0.0086... |
emilianJR/epiCRealism | 2023-07-23T14:14:35.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | emilianJR | null | null | emilianJR/epiCRealism | 22 | 97,300 | diffusers | 2023-06-25T12:13:26 | ---
language:
- en
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
Diffuser model for this SD checkpoint:
https://civitai.com/models/25694/epicrealism
**emilianJR/epiCRealism** is the HuggingFace diffuser that you can use with **diff... | 2,382 | [
[
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0.0253448486328125,
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bert-base-german-cased | 2023-04-06T13:41:34.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"exbert",
"de",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | bert-base-german-cased | 49 | 96,977 | transformers | 2022-03-02T23:29:04 | ---
language: de
license: mit
thumbnail: https://static.tildacdn.com/tild6438-3730-4164-b266-613634323466/german_bert.png
tags:
- exbert
---
<a href="https://huggingface.co/exbert/?model=bert-base-german-cased">
<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
</a>
# German BERT
![bert_im... | 4,194 | [
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EK12317/Ekmix-Diffusion | 2023-03-20T15:28:39.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | EK12317 | null | null | EK12317/Ekmix-Diffusion | 57 | 96,870 | diffusers | 2022-12-18T06:45:54 | ---
language:
- en
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
## Example:
”Negative prompt: (worst quality, low quality:1.4)” is really useful in anywhere
I think all models are great with correct Hires.fix
## Ekmix-Pa... | 4,033 | [
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-0.04315185546875,
0.0002975463... |
Helsinki-NLP/opus-mt-en-ru | 2023-08-16T11:30:58.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"en",
"ru",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-en-ru | 31 | 96,463 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-ru
* source languages: en
* target languages: ru
* OPUS readme: [en-ru](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-ru/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 1,123 | [
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0... |
dbmdz/distilbert-base-turkish-cased | 2021-01-24T01:01:22.000Z | [
"transformers",
"pytorch",
"tf",
"distilbert",
"tr",
"arxiv:1910.01108",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | null | dbmdz | null | null | dbmdz/distilbert-base-turkish-cased | 8 | 96,230 | transformers | 2022-03-02T23:29:05 | ---
language: tr
license: mit
---
# 🤗 + 📚 dbmdz Distilled Turkish BERT model
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a (cased) distilled model for Turkish 🎉
# 🇹🇷 DistilBERTurk
DistilBERTurk is a community-driven cased distilled BERT model for Turkish.
... | 3,142 | [
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-0.049072265625,
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google/long-t5-tglobal-base | 2023-01-24T17:08:42.000Z | [
"transformers",
"pytorch",
"jax",
"longt5",
"text2text-generation",
"en",
"arxiv:2112.07916",
"arxiv:1912.08777",
"arxiv:1910.10683",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | text2text-generation | google | null | null | google/long-t5-tglobal-base | 28 | 95,976 | transformers | 2022-04-16T11:05:48 | ---
license: apache-2.0
language: en
---
# LongT5 (transient-global attention, base-sized model)
LongT5 model pre-trained on English language. The model was introduced in the paper [LongT5: Efficient Text-To-Text Transformer for Long Sequences](https://arxiv.org/pdf/2112.07916.pdf) by Guo et al. and first released in... | 2,385 | [
[
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-0.042022705078125,
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padmajabfrl/Gender-Classification | 2023-01-09T10:52:54.000Z | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | padmajabfrl | null | null | padmajabfrl/Gender-Classification | 13 | 95,834 | transformers | 2023-01-09T10:13:14 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Gender-Classification
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. ... | 1,600 | [
[
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0.017333984375,
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facebook/opt-2.7b | 2023-09-15T13:04:38.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | facebook | null | null | facebook/opt-2.7b | 47 | 95,544 | transformers | 2022-05-11T08:26:30 | ---
language: en
inference: false
tags:
- text-generation
- opt
license: other
commercial: false
---
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://g... | 8,785 | [
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DionTimmer/controlnet_qrcode-control_v1p_sd15 | 2023-06-15T23:34:29.000Z | [
"diffusers",
"stable-diffusion",
"controlnet",
"image-to-image",
"en",
"license:openrail++",
"has_space",
"diffusers:ControlNetModel",
"region:us"
] | image-to-image | DionTimmer | null | null | DionTimmer/controlnet_qrcode-control_v1p_sd15 | 187 | 94,524 | diffusers | 2023-06-15T21:50:00 | ---
tags:
- stable-diffusion
- controlnet
- image-to-image
license: openrail++
language:
- en
library_name: diffusers
pipeline_tag: image-to-image
---
# QR Code Conditioned ControlNet Models for Stable Diffusion 1.5
## Model Description
This repo holds the ... | 4,826 | [
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0.0044326782226... |
sociocom/MedNERN-CR-JA | 2023-04-17T07:06:31.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"NER",
"medical documents",
"ja",
"dataset:MedTxt-CR-JA-training-v2.xml",
"doi:10.57967/hf/0620",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | sociocom | null | null | sociocom/MedNERN-CR-JA | 2 | 94,357 | transformers | 2023-04-13T08:25:56 | ---
language:
- ja
license:
- cc-by-4.0
tags:
- NER
- medical documents
datasets:
- MedTxt-CR-JA-training-v2.xml
metrics:
- NTCIR-16 Real-MedNLP subtask 1
---
This is a model for named entity recognition of Japanese medical documents.
### How to use
Download the following five files and put into the sam... | 2,227 | [
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google/owlvit-base-patch32 | 2023-10-23T09:20:36.000Z | [
"transformers",
"pytorch",
"owlvit",
"zero-shot-object-detection",
"vision",
"object-detection",
"arxiv:2205.06230",
"license:apache-2.0",
"has_space",
"region:us"
] | object-detection | google | null | null | google/owlvit-base-patch32 | 53 | 94,284 | transformers | 2022-07-05T06:30:01 | ---
license: apache-2.0
tags:
- vision
- object-detection
inference: false
---
# Model Card: OWL-ViT
## Model Details
The OWL-ViT (short for Vision Transformer for Open-World Localization) was proposed in [Simple Open-Vocabulary Object Detection with Vision Transformers](https://arxiv.org/abs/2205.06230) by Matthias... | 5,136 | [
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0.030242919921875,
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-0.049957275390625,
-0.042449951171875,
... |
timm/efficientnet_b3.ra2_in1k | 2023-04-27T21:10:28.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2110.00476",
"arxiv:1905.11946",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/efficientnet_b3.ra2_in1k | 0 | 93,980 | timm | 2022-12-12T23:56:39 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for efficientnet_b3.ra2_in1k
A EfficientNet image classification model. Trained on ImageNet-1k in `timm` using recipe template described below.
Recipe details:
* RandAugment `RA2` recipe. Inspired ... | 4,737 | [
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0.0184478759765625,
0.03265380859375,
-0.032257080078125,
-0.04046630859375,
-0.0565490722656... |
t5-3b | 2023-01-02T16:15:40.000Z | [
"transformers",
"pytorch",
"tf",
"t5",
"text2text-generation",
"summarization",
"translation",
"en",
"fr",
"ro",
"de",
"multilingual",
"dataset:c4",
"arxiv:1805.12471",
"arxiv:1708.00055",
"arxiv:1704.05426",
"arxiv:1606.05250",
"arxiv:1808.09121",
"arxiv:1810.12885",
"arxiv:19... | translation | null | null | null | t5-3b | 25 | 92,993 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
- fr
- ro
- de
- multilingual
license: apache-2.0
tags:
- summarization
- translation
datasets:
- c4
---
# Model Card for T5-3B
![model image](https://camo.githubusercontent.com/623b4dea0b653f2ad3f36c71ebfe749a677ac0a1/68747470733a2f2f6d69726f2e6d656469756d2e636f6d2f6d61782f343030362f312a44304a316... | 7,865 | [
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0.0242... |
microsoft/git-base | 2023-04-24T09:52:15.000Z | [
"transformers",
"pytorch",
"safetensors",
"git",
"text-generation",
"vision",
"image-to-text",
"image-captioning",
"en",
"arxiv:2205.14100",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | image-to-text | microsoft | null | null | microsoft/git-base | 25 | 92,527 | transformers | 2022-12-06T09:22:35 | ---
language: en
license: mit
tags:
- vision
- image-to-text
- image-captioning
model_name: microsoft/git-base
pipeline_tag: image-to-text
---
# GIT (GenerativeImage2Text), base-sized
GIT (short for GenerativeImage2Text) model, base-sized version. It was introduced in the paper [GIT: A Generative Image-to-text Transf... | 3,125 | [
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-0.0281829833984375,
-0.067626953125,
-0.0014... |
lmsys/vicuna-13b-v1.5 | 2023-08-03T11:06:24.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"arxiv:2307.09288",
"arxiv:2306.05685",
"license:llama2",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | lmsys | null | null | lmsys/vicuna-13b-v1.5 | 114 | 92,224 | transformers | 2023-07-29T04:44:46 | ---
inference: false
license: llama2
---
# Vicuna Model Card
## Model Details
Vicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT.
- **Developed by:** [LMSYS](https://lmsys.org/)
- **Model type:** An auto-regressive language model based on the transformer a... | 1,965 | [
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-0... |
facebook/sam-vit-base | 2023-07-11T15:21:19.000Z | [
"transformers",
"pytorch",
"tf",
"sam",
"mask-generation",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | facebook | null | null | facebook/sam-vit-base | 35 | 91,156 | transformers | 2023-04-19T14:15:29 | ---
license: apache-2.0
---
# Model Card for Segment Anything Model (SAM) - ViT Base (ViT-B) version
<p>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/sam-architecture.png" alt="Model architecture">
<em> Detailed architecture of Segment Anything Model... | 6,712 | [
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CAMeL-Lab/bert-base-arabic-camelbert-mix-ner | 2021-10-17T11:13:00.000Z | [
"transformers",
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | CAMeL-Lab | null | null | CAMeL-Lab/bert-base-arabic-camelbert-mix-ner | 7 | 91,118 | transformers | 2022-03-02T23:29:04 | ---
language:
- ar
license: apache-2.0
widget:
- text: "إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع"
---
# CAMeLBERT-Mix NER Model
## Model description
**CAMeLBERT-Mix NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Mix](https://huggingface.co/CAM... | 3,803 | [
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-0.0699462890625,
... |
cl-tohoku/bert-base-japanese-char | 2021-09-23T13:45:29.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ja",
"dataset:wikipedia",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | cl-tohoku | null | null | cl-tohoku/bert-base-japanese-char | 7 | 91,105 | transformers | 2022-03-02T23:29:05 | ---
language: ja
license: cc-by-sa-4.0
datasets:
- wikipedia
widget:
- text: 仙台は「[MASK]の都」と呼ばれている。
---
# BERT base Japanese (character tokenization)
This is a [BERT](https://github.com/google-research/bert) model pretrained on texts in the Japanese language.
This version of the model processes input texts with word-... | 1,719 | [
[
-0.031402587890625,
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0.029541015625,
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0.0318603515625,
0.0369873046875,
-0.05120849609375,
-0.0369873046875,
-0.045074462890625,
0.007057189941... |
facebook/opt-6.7b | 2023-01-24T17:10:29.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | facebook | null | null | facebook/opt-6.7b | 79 | 91,020 | transformers | 2022-05-11T08:26:52 | ---
language: en
inference: false
tags:
- text-generation
- opt
license: other
commercial: false
---
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://g... | 10,019 | [
[
-0.02325439453125,
-0.061798095703125,
0.01433563232421875,
0.017852783203125,
-0.01334381103515625,
-0.01096343994140625,
-0.0323486328125,
-0.033416748046875,
0.0027561187744140625,
0.03155517578125,
-0.04254150390625,
-0.03289794921875,
-0.048126220703125,
... |
openlm-research/open_llama_7b | 2023-06-16T00:45:23.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"dataset:togethercomputer/RedPajama-Data-1T",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | openlm-research | null | null | openlm-research/open_llama_7b | 104 | 90,543 | transformers | 2023-06-07T08:54:38 | ---
license: apache-2.0
datasets:
- togethercomputer/RedPajama-Data-1T
---
# OpenLLaMA: An Open Reproduction of LLaMA
In this repo, we present a permissively licensed open source reproduction of Meta AI's [LLaMA](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/) large language model. We are releasing... | 10,507 | [
[
-0.0233001708984375,
-0.0538330078125,
0.01861572265625,
0.030181884765625,
-0.0186767578125,
-0.0037078857421875,
-0.0243682861328125,
-0.044158935546875,
0.0281219482421875,
0.0193023681640625,
-0.029937744140625,
-0.050628662109375,
-0.04962158203125,
0.0... |
ckiplab/bert-base-chinese-ws | 2022-05-10T03:28:12.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"token-classification",
"zh",
"license:gpl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | ckiplab | null | null | ckiplab/bert-base-chinese-ws | 6 | 89,147 | transformers | 2022-03-02T23:29:05 | ---
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- token-classification
- bert
- zh
license: gpl-3.0
---
# CKIP BERT Base Chinese
This project provides traditional Chinese transformers models (including ALBERT, BERT, GPT2) and NLP tools (including word segment... | 1,122 | [
[
-0.0223541259765625,
-0.0253753662109375,
0.0019502639770507812,
0.056121826171875,
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0.00405120849609375,
-0.01433563232421875,
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0.03167724609375,
-0.0279541015625,
-0.0219268798828125,
-0.0440673828125,
... |
openai/whisper-base | 2023-09-08T13:08:06.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"whisper",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"en",
"zh",
"de",
"es",
"ru",
"ko",
"fr",
"ja",
"pt",
"tr",
"pl",
"ca",
"nl",
"ar",
"sv",
"it",
"id",
"hi",
"fi",
"vi",
"he",
"... | automatic-speech-recognition | openai | null | null | openai/whisper-base | 132 | 89,068 | transformers | 2022-09-26T06:50:46 | ---
language:
- en
- zh
- de
- es
- ru
- ko
- fr
- ja
- pt
- tr
- pl
- ca
- nl
- ar
- sv
- it
- id
- hi
- fi
- vi
- he
- uk
- el
- ms
- cs
- ro
- da
- hu
- ta
- no
- th
- ur
- hr
- bg
- lt
- la
- mi
- ml
- cy
- sk
- te
- fa
- lv
- bn
- sr
- az
- sl
- kn
- et
- mk
- br
- eu
- is
- hy
- ne
- mn
- bs
- kk
- sq
- sw
- gl
... | 19,774 | [
[
-0.01335906982421875,
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0.007419586181640625,
0.035186767578125,
-0.009002685546875,
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0.034820556640625,
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-0.043914794921875,
-0.057708740234375,
... |
michellejieli/NSFW_text_classifier | 2022-12-10T19:59:37.000Z | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"distilroberta",
"sentiment",
"NSFW",
"inappropriate",
"spam",
"twitter",
"reddit",
"en",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | michellejieli | null | null | michellejieli/NSFW_text_classifier | 35 | 88,585 | transformers | 2022-12-10T01:42:56 | ---
language: "en"
tags:
- distilroberta
- sentiment
- NSFW
- inappropriate
- spam
- twitter
- reddit
widget:
- text: "I like you. You remind me of me when I was young and stupid."
- text: "I see you’ve set aside this special time to humiliate yourself in public."
- text: "Have a great weekend! See you next week!"
-... | 1,392 | [
[
-0.0330810546875,
-0.061737060546875,
0.01273345947265625,
0.035797119140625,
-0.034515380859375,
-0.0027599334716796875,
0.00518798828125,
-0.0220947265625,
0.0002810955047607422,
0.00408172607421875,
-0.038818359375,
-0.04156494140625,
-0.06793212890625,
0... |
lambdalabs/sd-image-variations-diffusers | 2023-02-08T15:10:13.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"image-to-image",
"dataset:ChristophSchuhmann/improved_aesthetics_6plus",
"license:creativeml-openrail-m",
"has_space",
"diffusers:StableDiffusionImageVariationPipeline",
"region:us"
] | image-to-image | lambdalabs | null | null | lambdalabs/sd-image-variations-diffusers | 294 | 88,035 | diffusers | 2022-09-09T14:53:35 | ---
thumbnail: "https://repository-images.githubusercontent.com/523487884/fdb03a69-8353-4387-b5fc-0d85f888a63f"
datasets:
- ChristophSchuhmann/improved_aesthetics_6plus
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- image-to-image
---
# Stable Diffusion Image Variations Model Ca... | 10,569 | [
[
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-0.061981201171875,
0.0137786865234375,
0.01041412353515625,
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-0.0208740234375,
-0.0008406639099121094,
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0.0257415771484375,
-0.034942626953125,
-0.0355224609375,
-0.05865478515625,
... |
thenlper/gte-large | 2023-09-25T12:54:54.000Z | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"bert",
"mteb",
"sentence-similarity",
"Sentence Transformers",
"en",
"arxiv:2308.03281",
"license:mit",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | thenlper | null | null | thenlper/gte-large | 140 | 87,662 | sentence-transformers | 2023-07-27T09:55:39 | ---
tags:
- mteb
- sentence-similarity
- sentence-transformers
- Sentence Transformers
model-index:
- name: gte-large
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revi... | 67,907 | [
[
-0.04010009765625,
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0.022796630859375,
0.0186309814453125,
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0.005390167236328125,
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-0.05413818359375,
-0.05572509765625,
-0.00113... |
MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 | 2023-03-20T08:26:54.000Z | [
"transformers",
"pytorch",
"safetensors",
"deberta-v2",
"text-classification",
"zero-shot-classification",
"nli",
"multilingual",
"zh",
"ja",
"ar",
"ko",
"de",
"fr",
"es",
"pt",
"hi",
"id",
"it",
"tr",
"ru",
"bn",
"ur",
"mr",
"ta",
"vi",
"fa",
"pl",
"uk",
"n... | zero-shot-classification | MoritzLaurer | null | null | MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 | 126 | 87,578 | transformers | 2022-08-22T16:59:35 | ---
language:
- multilingual
- zh
- ja
- ar
- ko
- de
- fr
- es
- pt
- hi
- id
- it
- tr
- ru
- bn
- ur
- mr
- ta
- vi
- fa
- pl
- uk
- nl
- sv
- he
- sw
- ps
tags:
- zero-shot-classification
- text-classification
- nli
- pytorch
license: mit
metrics:
- accuracy
datasets:
- MoritzLaurer/multilingual-NLI-26lang-2mil7
-... | 16,132 | [
[
-0.0271453857421875,
-0.0283355712890625,
-0.00140380859375,
0.024078369140625,
-0.002521514892578125,
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0.030364990234375,
0.01512908935546875,
-0.037750244140625,
-0.040802001953125,
-0.0341796875,
... |
sentence-transformers/paraphrase-MiniLM-L3-v2 | 2022-07-08T04:08:35.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"dataset:flax-sentence-embeddings/stackexchange_xml",
"dataset:s2orc",
"dataset:ms_marco",
"dataset:wiki_atomic_edits",
"dataset:snli",
"dataset:multi_nli",
"dataset:embedding-dat... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/paraphrase-MiniLM-L3-v2 | 14 | 87,205 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
datasets:
- flax-sentence-embeddings/stackexchange_xml
- s2orc
- ms_marco
- wiki_atomic_edits
- snli
- multi_nli
- embedding-data/altlex
- embedding-data/simple-wiki
- embedd... | 4,008 | [
[
-0.0163726806640625,
-0.054656982421875,
0.0309600830078125,
0.0178375244140625,
-0.027740478515625,
-0.03302001953125,
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0.00122833251953125,
0.00806427001953125,
0.033935546875,
-0.040069580078125,
-0.0223236083984375,
-0.043304443359375,
... |
Helsinki-NLP/opus-mt-id-en | 2023-08-16T11:58:05.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"id",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-id-en | 8 | 87,072 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-id-en
* source languages: id
* target languages: en
* OPUS readme: [id-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/id-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 818 | [
[
-0.0189971923828125,
-0.0287017822265625,
0.018585205078125,
0.03228759765625,
-0.0345458984375,
-0.0282440185546875,
-0.028289794921875,
-0.0041656494140625,
0.0009107589721679688,
0.029144287109375,
-0.05072021484375,
-0.047210693359375,
-0.044097900390625,
... |
Open-Orca/Mistral-7B-OpenOrca | 2023-10-10T21:07:16.000Z | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"en",
"dataset:Open-Orca/OpenOrca",
"arxiv:2306.02707",
"arxiv:2301.13688",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | Open-Orca | null | null | Open-Orca/Mistral-7B-OpenOrca | 423 | 86,455 | transformers | 2023-09-29T19:18:38 | ---
datasets:
- Open-Orca/OpenOrca
language:
- en
library_name: transformers
pipeline_tag: text-generation
license: apache-2.0
---
<p><h1>🐋 Mistral-7B-OpenOrca 🐋</h1></p>
[<img src="htt... | 8,848 | [
[
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0.01708984375,
-0.027679443359375,
-0.04547119140625,
-0.03265380859375,
-0.00... |
shi-labs/oneformer_ade20k_swin_large | 2023-01-19T14:36:03.000Z | [
"transformers",
"pytorch",
"oneformer",
"vision",
"image-segmentation",
"universal-image-segmentation",
"dataset:scene_parse_150",
"arxiv:2211.06220",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | image-segmentation | shi-labs | null | null | shi-labs/oneformer_ade20k_swin_large | 6 | 86,319 | transformers | 2022-11-15T19:00:56 | ---
license: mit
tags:
- vision
- image-segmentation
- universal-image-segmentation
datasets:
- scene_parse_150
widget:
- src: https://praeclarumjj3.github.io/files/ade20k.jpeg
example_title: House
- src: https://praeclarumjj3.github.io/files/demo_2.jpg
example_title: Airplane
- src: https://praeclarumjj3.github.io... | 3,694 | [
[
-0.0489501953125,
-0.056304931640625,
0.0250091552734375,
0.0102996826171875,
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-0.047149658203125,
0.02130126953125,
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0.00301361083984375,
0.0506591796875,
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-0.04510498046875,
-0.046234130859375,
-0.01... |
laion/CLIP-ViT-L-14-laion2B-s32B-b82K | 2023-04-18T17:46:39.000Z | [
"open_clip",
"pytorch",
"tensorboard",
"clip",
"zero-shot-image-classification",
"arxiv:2110.09456",
"arxiv:2111.09883",
"arxiv:1910.04867",
"license:mit",
"has_space",
"region:us"
] | zero-shot-image-classification | laion | null | null | laion/CLIP-ViT-L-14-laion2B-s32B-b82K | 32 | 86,084 | open_clip | 2022-09-14T22:51:37 | ---
license: mit
widget:
- src: >-
https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-dog-music.png
candidate_labels: playing music, playing sports
example_title: Cat & Dog
library_name: open_clip
pipeline_tag: zero-shot-image-classification
---
# Model Card for CLIP ViT-L/14 - LAION-2B
# T... | 11,366 | [
[
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-0.0222625732421875,
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0.0059051513671875,
0.025482177734375,
-0.034942626953125,
-0.0223541259765625,
-0.04861450195312... |
bvanaken/clinical-assertion-negation-bert | 2022-06-01T12:28:45.000Z | [
"transformers",
"pytorch",
"bert",
"text-classification",
"medical",
"clinical",
"assertion",
"negation",
"en",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | bvanaken | null | null | bvanaken/clinical-assertion-negation-bert | 19 | 85,964 | transformers | 2022-03-02T23:29:05 | ---
language: "en"
tags:
- bert
- medical
- clinical
- assertion
- negation
- text-classification
widget:
- text: "Patient denies [entity] SOB [entity]."
---
# Clinical Assertion / Negation Classification BERT
## Model description
The Clinical Assertion and Negation Classification BERT is introduced in the paper [A... | 2,503 | [
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0.0004363059997558594,
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0.0201416015625,
-0.03082275390625,
-0.04925537109375,
-0.056884765625,
0.0... |
Helsinki-NLP/opus-mt-mul-en | 2023-08-16T12:01:25.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"ca",
"es",
"os",
"eo",
"ro",
"fy",
"cy",
"is",
"lb",
"su",
"an",
"sq",
"fr",
"ht",
"rm",
"cv",
"ig",
"am",
"eu",
"tr",
"ps",
"af",
"ny",
"ch",
"uk",
"sl",
"lt",
"tk",
... | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-mul-en | 45 | 85,693 | transformers | 2022-03-02T23:29:04 | ---
language:
- ca
- es
- os
- eo
- ro
- fy
- cy
- is
- lb
- su
- an
- sq
- fr
- ht
- rm
- cv
- ig
- am
- eu
- tr
- ps
- af
- ny
- ch
- uk
- sl
- lt
- tk
- sg
- ar
- lg
- bg
- be
- ka
- gd
- ja
- si
- br
- mh
- km
- th
- ty
- rw
- te
- mk
- or
- wo
- kl
- mr
- ru
- yo
- hu
- fo
- zh
- ti
- co
- ee
- oc
- sn
- mt
- ts
... | 24,356 | [
[
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-0.01512908935546875,
-0.0316162109375,
-0.0160369873046875,
-0.030975341796875,
... |
sentence-transformers/LaBSE | 2023-11-02T09:18:45.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"multilingual",
"af",
"sq",
"am",
"ar",
"hy",
"as",
"az",
"eu",
"be",
"bn",
"bs",
"bg",
"my",
"ca",
"ceb",
"zh",
"co",
"hr",
"cs",
"da",
"nl... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/LaBSE | 98 | 85,400 | sentence-transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- af
- sq
- am
- ar
- hy
- as
- az
- eu
- be
- bn
- bs
- bg
- my
- ca
- ceb
- zh
- co
- hr
- cs
- da
- nl
- en
- eo
- et
- fi
- fr
- fy
- gl
- ka
- de
- el
- gu
- ht
- ha
- haw
- he
- hi
- hmn
- hu
- is
- ig
- id
- ga
- it
- ja
- jv
- kn
- kk
- km
- rw
- ko
- ku
- ky
- lo
- la
- lv
- lt
- l... | 2,195 | [
[
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0.00850677490234375,
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... |
facebook/nllb-200-distilled-600M | 2023-02-11T20:19:06.000Z | [
"transformers",
"pytorch",
"m2m_100",
"text2text-generation",
"nllb",
"translation",
"ace",
"acm",
"acq",
"aeb",
"af",
"ajp",
"ak",
"als",
"am",
"apc",
"ar",
"ars",
"ary",
"arz",
"as",
"ast",
"awa",
"ayr",
"azb",
"azj",
"ba",
"bm",
"ban",
"be",
"bem",
"b... | translation | facebook | null | null | facebook/nllb-200-distilled-600M | 211 | 85,233 | transformers | 2022-07-08T09:43:57 | ---
language:
- ace
- acm
- acq
- aeb
- af
- ajp
- ak
- als
- am
- apc
- ar
- ars
- ary
- arz
- as
- ast
- awa
- ayr
- azb
- azj
- ba
- bm
- ban
- be
- bem
- bn
- bho
- bjn
- bo
- bs
- bug
- bg
- ca
- ceb
- cs
- cjk
- ckb
- crh
- cy
- da
- de
- dik
- dyu
- dz
- el
- en
- eo
- et
- eu
- ee
- fo
- fj
- fi
- fon
- fr
- fu... | 7,645 | [
[
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ckiplab/bert-base-chinese-pos | 2022-05-10T03:28:12.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"token-classification",
"zh",
"license:gpl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | ckiplab | null | null | ckiplab/bert-base-chinese-pos | 13 | 84,909 | transformers | 2022-03-02T23:29:05 | ---
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- token-classification
- bert
- zh
license: gpl-3.0
---
# CKIP BERT Base Chinese
This project provides traditional Chinese transformers models (including ALBERT, BERT, GPT2) and NLP tools (including word segment... | 1,123 | [
[
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Salesforce/blip2-flan-t5-xl | 2023-09-13T08:46:20.000Z | [
"transformers",
"pytorch",
"blip-2",
"visual-question-answering",
"vision",
"image-to-text",
"image-captioning",
"en",
"arxiv:2301.12597",
"arxiv:2210.11416",
"license:mit",
"has_space",
"region:us"
] | image-to-text | Salesforce | null | null | Salesforce/blip2-flan-t5-xl | 33 | 84,867 | transformers | 2023-02-06T20:28:29 | ---
language: en
license: mit
tags:
- vision
- image-to-text
- image-captioning
- visual-question-answering
pipeline_tag: image-to-text
inference: false
---
# BLIP-2, Flan T5-xl, pre-trained only
BLIP-2 model, leveraging [Flan T5-xl](https://huggingface.co/google/flan-t5-xl) (a large language model).
It was introduce... | 6,508 | [
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colorfulscoop/sbert-base-ja | 2021-08-08T06:47:42.000Z | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"ja",
"arxiv:1908.10084",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"region:us",
"has_space"
] | sentence-similarity | colorfulscoop | null | null | colorfulscoop/sbert-base-ja | 12 | 84,558 | sentence-transformers | 2022-03-02T23:29:05 | ---
language: ja
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
widget:
source_sentence: "走るのが趣味です"
sentences:
- 外をランニングするのが好きです
- 運動はそこそこです
- 走るのは嫌いです
license: cc-by-sa-4.0
---
# Sentence BERT base Japanese model
This reposit... | 4,706 | [
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Helsinki-NLP/opus-mt-pl-en | 2023-08-16T12:02:38.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"pl",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-pl-en | 14 | 84,546 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-pl-en
* source languages: pl
* target languages: en
* OPUS readme: [pl-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/pl-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 818 | [
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Helsinki-NLP/opus-mt-tc-big-en-pt | 2023-10-10T10:20:34.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"marian",
"text2text-generation",
"translation",
"opus-mt-tc",
"en",
"pt",
"pt_br",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-tc-big-en-pt | 17 | 84,461 | transformers | 2022-04-13T14:49:04 | ---
language:
- en
- pt
- pt_br
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-en-pt
results:
- task:
name: Translation eng-por
type: translation
args: eng-por
dataset:
name: flores101-devtest
type: flores_101
args: eng por devtest
... | 6,264 | [
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0.0283... |
cardiffnlp/twitter-roberta-base-emotion | 2023-05-28T05:08:00.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"arxiv:2010.12421",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | cardiffnlp | null | null | cardiffnlp/twitter-roberta-base-emotion | 35 | 83,876 | transformers | 2022-03-02T23:29:05 | # Twitter-roBERTa-base for Emotion Recognition
This is a RoBERTa-base model trained on ~58M tweets and finetuned for emotion recognition with the TweetEval benchmark.
- Paper: [_TweetEval_ benchmark (Findings of EMNLP 2020)](https://arxiv.org/pdf/2010.12421.pdf).
- Git Repo: [Tweeteval official repository](https://g... | 2,753 | [
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0.... |
EleutherAI/pythia-70m-deduped | 2023-07-09T16:07:33.000Z | [
"transformers",
"pytorch",
"safetensors",
"gpt_neox",
"text-generation",
"causal-lm",
"pythia",
"en",
"dataset:EleutherAI/the_pile_deduplicated",
"arxiv:2304.01373",
"arxiv:2101.00027",
"arxiv:2201.07311",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-infe... | text-generation | EleutherAI | null | null | EleutherAI/pythia-70m-deduped | 16 | 83,703 | transformers | 2023-02-13T16:01:41 | ---
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- EleutherAI/the_pile_deduplicated
---
The *Pythia Scaling Suite* is a collection of models developed to facilitate
interpretability research [(see paper)](https://arxiv.org/pdf/2304.01373.pdf).
It contains two sets of eight models... | 13,654 | [
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-0... |
stabilityai/sdxl-vae | 2023-08-04T10:12:16.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"arxiv:2112.10752",
"license:mit",
"has_space",
"diffusers:AutoencoderKL",
"region:us"
] | null | stabilityai | null | null | stabilityai/sdxl-vae | 366 | 83,508 | diffusers | 2023-06-21T17:47:40 | ---
license: mit
tags:
- stable-diffusion
- stable-diffusion-diffusers
inference: false
---
# SDXL - VAE
#### How to use with 🧨 diffusers
You can integrate this fine-tuned VAE decoder to your existing `diffusers` workflows, by including a `vae` argument to the `StableDiffusionPipeline`
```py
from diffusers.models imp... | 3,169 | [
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google/mobilebert-uncased | 2021-04-19T13:32:58.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"mobilebert",
"pretraining",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | google | null | null | google/mobilebert-uncased | 24 | 82,643 | transformers | 2022-03-02T23:29:05 | ---
language: en
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
## MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices
MobileBERT is a thin version of BERT_LARGE, while equipped with bottleneck structures and a carefully designed balance
between self-attention... | 918 | [
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Helsinki-NLP/opus-mt-nl-en | 2023-08-16T12:01:39.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"nl",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-nl-en | 8 | 82,564 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-nl-en
* source languages: nl
* target languages: en
* OPUS readme: [nl-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/nl-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 818 | [
[
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0.0... |
Helsinki-NLP/opus-mt-en-fr | 2023-08-16T11:29:35.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"marian",
"text2text-generation",
"translation",
"en",
"fr",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-en-fr | 21 | 82,506 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-fr
* source languages: en
* target languages: fr
* OPUS readme: [en-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 1,205 | [
[
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timm/vit_base_r50_s16_384.orig_in21k_ft_in1k | 2023-05-06T00:43:14.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"dataset:imagenet-21k",
"arxiv:2010.11929",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/vit_base_r50_s16_384.orig_in21k_ft_in1k | 2 | 82,446 | timm | 2022-12-23T00:27:16 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- imagenet-21k
---
# Model card for vit_base_r50_s16_384.orig_in21k_ft_in1k
A ResNet - Vision Transformer (ViT) hybrid image classification model. Trained on ImageNet-21k and fine-tuned on ImageNet-1k in JAX by paper... | 3,410 | [
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CiaraRowles/TemporalNet | 2023-04-05T22:59:34.000Z | [
"diffusers",
"controlnet",
"stable-diffusion",
"license:openrail",
"diffusers:ControlNetModel",
"region:us"
] | null | CiaraRowles | null | null | CiaraRowles/TemporalNet | 308 | 82,258 | diffusers | 2023-03-23T22:31:31 | ---
license: openrail
tags:
- controlnet
- stable-diffusion
- diffusers
base_model: runwayml/stable-diffusion-v1-5
---
Introducing the Beta Version of TemporalNet
TemporalNet is a ControlNet model designed to enhance the temporal consistency of generated outputs, as demonstrated in this example: https://twitter.com/Ci... | 1,743 | [
[
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HuggingFaceH4/zephyr-7b-alpha | 2023-10-26T08:18:58.000Z | [
"transformers",
"pytorch",
"safetensors",
"mistral",
"text-generation",
"generated_from_trainer",
"en",
"dataset:stingning/ultrachat",
"dataset:openbmb/UltraFeedback",
"arxiv:2305.18290",
"license:mit",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | HuggingFaceH4 | null | null | HuggingFaceH4/zephyr-7b-alpha | 913 | 82,136 | transformers | 2023-10-09T08:45:10 | ---
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-alpha
results: []
license: mit
datasets:
- stingning/ultrachat
- openbmb/UltraFeedback
language:
- en
base_model: mistralai/Mistral-7B-v0.1
---
<!-- This model card has been generated automatically according to the information the Trainer had access t... | 9,554 | [
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sentence-transformers/distiluse-base-multilingual-cased-v1 | 2023-11-02T09:17:53.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"distilbert",
"feature-extraction",
"sentence-similarity",
"transformers",
"multilingual",
"ar",
"zh",
"nl",
"en",
"fr",
"de",
"it",
"ko",
"pl",
"pt",
"ru",
"es",
"tr",
"arxiv:1908.10084",
"license:apache-2.0",
"endpoints_compat... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/distiluse-base-multilingual-cased-v1 | 56 | 82,021 | sentence-transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- ar
- zh
- nl
- en
- fr
- de
- it
- ko
- pl
- pt
- ru
- es
- tr
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/distiluse-base-multilingual-cased-v1
This is a [sente... | 2,446 | [
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0.0152053833... |
Helsinki-NLP/opus-mt-en-zh | 2023-08-16T11:31:42.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"marian",
"text2text-generation",
"translation",
"en",
"zh",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-en-zh | 207 | 81,956 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
- zh
tags:
- translation
license: apache-2.0
---
### eng-zho
* source group: English
* target group: Chinese
* OPUS readme: [eng-zho](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-zho/README.md)
* model: transformer
* source language(s): eng
* target language(s): cjy... | 2,670 | [
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0.027847... |
Helsinki-NLP/opus-mt-sv-en | 2023-08-16T12:05:00.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"sv",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-sv-en | 7 | 81,925 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-sv-en
* source languages: sv
* target languages: en
* OPUS readme: [sv-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sv-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 818 | [
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0.0... |
OpenAssistant/reward-model-deberta-v3-large-v2 | 2023-02-01T00:55:05.000Z | [
"transformers",
"pytorch",
"deberta-v2",
"text-classification",
"reward-model",
"reward_model",
"RLHF",
"en",
"dataset:openai/summarize_from_feedback",
"dataset:openai/webgpt_comparisons",
"dataset:Dahoas/instruct-synthetic-prompt-responses",
"dataset:Anthropic/hh-rlhf",
"license:mit",
"en... | text-classification | OpenAssistant | null | null | OpenAssistant/reward-model-deberta-v3-large-v2 | 116 | 80,030 | transformers | 2023-02-01T00:13:05 | ---
license: mit
datasets:
- openai/summarize_from_feedback
- openai/webgpt_comparisons
- Dahoas/instruct-synthetic-prompt-responses
- Anthropic/hh-rlhf
language:
- en
metrics:
- accuracy
tags:
- reward-model
- reward_model
- RLHF
---
# Reward model trained from human feedback
Reward model (RM) trained to predict whic... | 3,875 | [
[
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0.01198577880859375,
0.00994873046875,
-0.045654296875,
-0.025634765625,
-0.047607421875,
... |
diffusers/stable-diffusion-xl-1.0-inpainting-0.1 | 2023-09-03T16:36:39.000Z | [
"diffusers",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"text-to-image",
"inpainting",
"arxiv:2112.10752",
"license:openrail++",
"has_space",
"diffusers:StableDiffusionXLInpaintPipeline",
"region:us"
] | text-to-image | diffusers | null | null | diffusers/stable-diffusion-xl-1.0-inpainting-0.1 | 142 | 79,822 | diffusers | 2023-09-01T14:07:10 |
---
license: openrail++
base_model: stabilityai/stable-diffusion-xl-base-1.0
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- text-to-image
- diffusers
- inpainting
inference: false
---
# SD-XL Inpainting 0.1 Model Card
SD-XL Inpainting 0.1 is a latent text-... | 4,857 | [
[
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0.03369140625,
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-0.044464111328125,
-0.... |
Salesforce/instructblip-vicuna-7b | 2023-07-17T12:36:58.000Z | [
"transformers",
"pytorch",
"instructblip",
"text2text-generation",
"vision",
"image-captioning",
"image-to-text",
"en",
"arxiv:2305.06500",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-to-text | Salesforce | null | null | Salesforce/instructblip-vicuna-7b | 44 | 79,467 | transformers | 2023-05-22T19:28:03 | ---
language: en
license: other
tags:
- vision
- image-captioning
pipeline_tag: image-to-text
---
# InstructBLIP model
InstructBLIP model using [Vicuna-7b](https://github.com/lm-sys/FastChat#model-weights) as language model. InstructBLIP was introduced in the paper [InstructBLIP: Towards General-purpose Vision-Langua... | 2,140 | [
[
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0.037872314453125,
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-0.04031372070312... |
BAAI/bge-small-en | 2023-10-12T03:35:23.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"feature-extraction",
"mteb",
"sentence transformers",
"en",
"arxiv:2310.07554",
"arxiv:2309.07597",
"license:mit",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | BAAI | null | null | BAAI/bge-small-en | 48 | 78,957 | transformers | 2023-08-05T08:04:07 | ---
tags:
- mteb
- sentence transformers
model-index:
- name: bge-small-en
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba... | 89,684 | [
[
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0.0248565673828125,
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-0.0626220703125,
-0.03729248046875,
-0.0029907... |
google/byt5-large | 2023-01-24T16:36:56.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"multilingual",
"af",
"am",
"ar",
"az",
"be",
"bg",
"bn",
"ca",
"ceb",
"co",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fil",
"fr",
"fy",
"ga",
"gd",
... | text2text-generation | google | null | null | google/byt5-large | 5 | 78,911 | transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- af
- am
- ar
- az
- be
- bg
- bn
- ca
- ceb
- co
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fil
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- haw
- hi
- hmn
- ht
- hu
- hy
- ig
- is
- it
- iw
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lb
- lo
- lt
- lv
- mg
- mi
- mk
-... | 4,229 | [
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0.0251922607421875,
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... |
google/tapas-large-finetuned-wtq | 2023-09-05T14:48:42.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"tapas",
"table-question-answering",
"en",
"dataset:wikitablequestions",
"arxiv:2004.02349",
"arxiv:2010.00571",
"arxiv:1508.00305",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | table-question-answering | google | null | null | google/tapas-large-finetuned-wtq | 67 | 78,851 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- tapas
- table-question-answering
license: apache-2.0
datasets:
- wikitablequestions
---
# TAPAS large model fine-tuned on WikiTable Questions (WTQ)
This model has 2 versions which can be used. The default version corresponds to the `tapas_wtq_wikisql_sqa_inter_masklm_large_reset` checkpoint o... | 7,221 | [
[
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0.00191... |
mosaicml/mpt-7b | 2023-10-30T21:53:24.000Z | [
"transformers",
"pytorch",
"mpt",
"text-generation",
"Composer",
"MosaicML",
"llm-foundry",
"StreamingDatasets",
"custom_code",
"dataset:mc4",
"dataset:c4",
"dataset:togethercomputer/RedPajama-Data-1T",
"dataset:bigcode/the-stack",
"dataset:allenai/s2orc",
"arxiv:2108.12409",
"arxiv:23... | text-generation | mosaicml | null | null | mosaicml/mpt-7b | 1,092 | 78,696 | transformers | 2023-05-05T00:48:02 | ---
license: apache-2.0
tags:
- Composer
- MosaicML
- llm-foundry
- StreamingDatasets
datasets:
- mc4
- c4
- togethercomputer/RedPajama-Data-1T
- bigcode/the-stack
- allenai/s2orc
inference: false
---
# MPT-7B
MPT-7B is a decoder-style transformer pretrained from scratch on 1T tokens of English text and code.
This mo... | 12,034 | [
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0.0286712646484375,
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-0.046875,
0.00477... |
Helsinki-NLP/opus-mt-fi-en | 2023-08-16T11:34:26.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"fi",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-fi-en | 3 | 78,199 | transformers | 2022-03-02T23:29:04 | ---
language:
- fi
- en
tags:
- translation
license: apache-2.0
---
### fin-eng
* source group: Finnish
* target group: English
* OPUS readme: [fin-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fin-eng/README.md)
* model: transformer-align
* source language(s): fin
* target languag... | 2,557 | [
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0... |
hf-internal-testing/tiny-stable-diffusion-torch | 2023-05-05T15:28:20.000Z | [
"diffusers",
"license:apache-2.0",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | hf-internal-testing | null | null | hf-internal-testing/tiny-stable-diffusion-torch | 2 | 78,043 | diffusers | 2022-11-03T13:35:38 | ---
license: apache-2.0
---
```python
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained("hf-internal-testing/tiny-stable-diffusion-torch")
```
| 189 | [
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0... |
timm/mobilenetv3_large_100.miil_in21k_ft_in1k | 2023-04-27T22:49:19.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"dataset:imagenet-21k-p",
"arxiv:1905.02244",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/mobilenetv3_large_100.miil_in21k_ft_in1k | 1 | 77,234 | timm | 2022-12-16T05:37:59 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- imagenet-21k-p
---
# Model card for mobilenetv3_large_100.miil_in21k_ft_in1k
A MobileNet-v3 image classification model. Petrained on ImageNet-21k-P and fine-tuned on ImageNet-1k by Alibaba MIIL.
## Model Details
... | 4,152 | [
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DeepFloyd/IF-I-XL-v1.0 | 2023-06-02T19:05:00.000Z | [
"diffusers",
"pytorch",
"if",
"text-to-image",
"arxiv:2205.11487",
"arxiv:2110.02861",
"license:deepfloyd-if-license",
"has_space",
"diffusers:IFPipeline",
"region:us"
] | text-to-image | DeepFloyd | null | null | DeepFloyd/IF-I-XL-v1.0 | 524 | 77,150 | diffusers | 2023-04-06T21:22:41 | ---
license: deepfloyd-if-license
extra_gated_prompt: "DeepFloyd LICENSE AGREEMENT\nThis License Agreement (as may be amended in accordance with this License Agreement, “License”), between you, or your employer or other entity (if you are entering into this agreement on behalf of your employer or other entity) (“Licens... | 23,443 | [
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0.0220947265625,
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-0.0430908203125,
-0.048126220703125,
-0.01502... |
VoVanPhuc/sup-SimCSE-VietNamese-phobert-base | 2023-05-24T08:47:42.000Z | [
"transformers",
"pytorch",
"roberta",
"sentence-similarity",
"vi",
"arxiv:2104.08821",
"endpoints_compatible",
"region:us"
] | sentence-similarity | VoVanPhuc | null | null | VoVanPhuc/sup-SimCSE-VietNamese-phobert-base | 7 | 76,338 | transformers | 2022-03-02T23:29:05 | ---
language:
- vi
pipeline_tag: sentence-similarity
---
#### Table of contents
1. [Introduction](#introduction)
2. [Pretrain model](#models)
3. [Using SimeCSE_Vietnamese with `sentences-transformers`](#sentences-transformers)
- [Installation](#install1)
- [Example usage](#usage1)
4. [Using SimeCSE_Vietnamese with `... | 4,905 | [
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0.... |
facebook/encodec_32khz | 2023-09-04T16:32:53.000Z | [
"transformers",
"pytorch",
"safetensors",
"encodec",
"feature-extraction",
"arxiv:2306.05284",
"has_space",
"region:us"
] | feature-extraction | facebook | null | null | facebook/encodec_32khz | 7 | 76,329 | transformers | 2023-06-15T12:01:17 | ---
inference: false
---
# Model Card for EnCodec
This model card provides details and information about EnCodec 32kHz, a state-of-the-art real-time audio codec developed by Meta AI.
This EnCo... | 5,590 | [
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bigscience/bloomz-7b1 | 2023-05-27T17:25:52.000Z | [
"transformers",
"pytorch",
"bloom",
"text-generation",
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"code",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",
"pt",
"rn",
"rw",
"sn",
"... | text-generation | bigscience | null | null | bigscience/bloomz-7b1 | 113 | 76,245 | transformers | 2022-09-27T09:00:57 | ---
datasets:
- bigscience/xP3
license: bigscience-bloom-rail-1.0
language:
- ak
- ar
- as
- bm
- bn
- ca
- code
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zu
programmi... | 24,195 | [
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-0.0400390625,
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0.... |
demdecuong/vihealthbert-base-word | 2022-04-20T07:55:52.000Z | [
"transformers",
"pytorch",
"roberta",
"feature-extraction",
"endpoints_compatible",
"region:us"
] | feature-extraction | demdecuong | null | null | demdecuong/vihealthbert-base-word | 2 | 75,837 | transformers | 2022-04-20T07:49:34 | # <a name="introduction"></a> ViHealthBERT: Pre-trained Language Models for Vietnamese in Health Text Mining
ViHealthBERT is the a strong baseline language models for Vietnamese in Healthcare domain.
We empirically investigate our model with different training strategies, achieving state of the art (SOTA) performa... | 3,596 | [
[
-0.0008559226989746094,
-0.06170654296875,
0.0293731689453125,
0.01146697998046875,
-0.0328369140625,
-0.023773193359375,
-0.00836181640625,
-0.0232696533203125,
0.019561767578125,
0.0421142578125,
-0.0262603759765625,
-0.060089111328125,
-0.06134033203125,
... |
facebook/dinov2-base | 2023-09-06T11:22:58.000Z | [
"transformers",
"pytorch",
"safetensors",
"dinov2",
"feature-extraction",
"dino",
"vision",
"arxiv:2304.07193",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | feature-extraction | facebook | null | null | facebook/dinov2-base | 15 | 75,535 | transformers | 2023-07-17T16:44:29 | ---
license: apache-2.0
tags:
- dino
- vision
---
# Vision Transformer (base-sized model) trained using DINOv2
Vision Transformer (ViT) model trained using the DINOv2 method. It was introduced in the paper [DINOv2: Learning Robust Visual Features without Supervision](https://arxiv.org/abs/2304.07193) by Oquab et al. ... | 3,027 | [
[
-0.03668212890625,
-0.0309906005859375,
0.00659942626953125,
-0.00917816162109375,
-0.0367431640625,
-0.0032749176025390625,
0.008544921875,
-0.0308990478515625,
0.019622802734375,
0.038177490234375,
-0.03515625,
-0.01788330078125,
-0.0513916015625,
-0.01397... |
google/mt5-small | 2023-09-18T09:35:27.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"onnx",
"mt5",
"text2text-generation",
"multilingual",
"af",
"am",
"ar",
"az",
"be",
"bg",
"bn",
"ca",
"ceb",
"co",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fil",
"fr",
"fy",
"ga... | text2text-generation | google | null | null | google/mt5-small | 64 | 75,406 | transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- af
- am
- ar
- az
- be
- bg
- bn
- ca
- ceb
- co
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fil
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- haw
- hi
- hmn
- ht
- hu
- hy
- ig
- is
- it
- iw
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lb
- lo
- lt
- lv
- mg
- mi
- mk
-... | 2,827 | [
[
-0.0369873046875,
-0.01190948486328125,
0.0203704833984375,
0.028778076171875,
-0.02056884765625,
0.0252227783203125,
-0.026824951171875,
-0.03131103515625,
0.0120086669921875,
0.025299072265625,
-0.04913330078125,
-0.059906005859375,
-0.06512451171875,
0.05... |
dbmdz/bert-base-german-uncased | 2023-09-06T22:19:33.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"de",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | dbmdz | null | null | dbmdz/bert-base-german-uncased | 14 | 74,724 | transformers | 2022-03-02T23:29:05 | ---
language: de
license: mit
---
# 🤗 + 📚 dbmdz German BERT models
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources another German BERT models 🎉
# German BERT
## Stats
In addition to the recently released [German BERT](https://deepset.ai/german-bert)
model by [d... | 3,159 | [
[
-0.039794921875,
-0.059478759765625,
0.01387786865234375,
0.0177001953125,
-0.0292510986328125,
-0.0164947509765625,
-0.01763916015625,
-0.0306549072265625,
0.01264190673828125,
0.0233154296875,
-0.05621337890625,
-0.048095703125,
-0.04779052734375,
-0.01335... |
TheBloke/Llama-2-70B-Chat-GPTQ | 2023-09-27T12:44:49.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-2",
"en",
"arxiv:2307.09288",
"license:llama2",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/Llama-2-70B-Chat-GPTQ | 222 | 74,507 | transformers | 2023-07-18T23:33:13 | ---
language:
- en
license: llama2
tags:
- facebook
- meta
- pytorch
- llama
- llama-2
model_name: Llama 2 70B Chat
base_model: meta-llama/Llama-2-70b-chat-hf
inference: false
model_creator: Meta Llama 2
model_type: llama
pipeline_tag: text-generation
prompt_template: '[INST] <<SYS>>
You are a helpful, respectful an... | 25,857 | [
[
-0.040740966796875,
-0.0599365234375,
0.0090179443359375,
0.0240631103515625,
-0.0285186767578125,
-0.0033893585205078125,
0.00405120849609375,
-0.049041748046875,
0.0287628173828125,
0.0214080810546875,
-0.0504150390625,
-0.03704833984375,
-0.03399658203125,
... |
wajidlinux99/gibberish-text-detector | 2023-01-16T12:15:52.000Z | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"text",
"nlp",
"correction",
"en",
"endpoints_compatible",
"region:us"
] | text-classification | wajidlinux99 | null | null | wajidlinux99/gibberish-text-detector | 2 | 74,340 | transformers | 2023-01-16T11:46:09 | ---
language:
- en
pipeline_tag: text-classification
tags:
- text
- nlp
- correction
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 492513457
- CO2 Emissions (in grams): 5.527544460835904
## Validation Metrics
- Loss: 0.07609463483095169
- Accuracy: 0.9735624586913417
- Ma... | 1,420 | [
[
-0.030548095703125,
-0.039581298828125,
0.014495849609375,
0.007183074951171875,
-0.002277374267578125,
-0.0007576942443847656,
-0.00457763671875,
-0.028594970703125,
-0.0006384849548339844,
0.0121612548828125,
-0.0257568359375,
-0.0347900390625,
-0.061614990234... |
d4data/biomedical-ner-all | 2023-07-02T07:28:28.000Z | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"token-classification",
"Token Classification",
"en",
"license:apache-2.0",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | d4data | null | null | d4data/biomedical-ner-all | 100 | 74,214 | transformers | 2022-06-19T14:04:18 | ---
license: apache-2.0
language:
- en
tags:
- Token Classification
co2_eq_emissions: 0.0279399890043426
widget:
- text: "CASE: A 28-year-old previously healthy man presented with a 6-week history of palpitations.
The symptoms occurred during rest, 2–3 times per week, lasted up to 30 minutes at a time and were associat... | 3,060 | [
[
-0.026275634765625,
-0.0447998046875,
0.04486083984375,
0.0013780593872070312,
-0.0118255615234375,
0.002063751220703125,
0.0089111328125,
-0.04571533203125,
0.037353515625,
0.03790283203125,
-0.0399169921875,
-0.03875732421875,
-0.04437255859375,
0.03030395... |
microsoft/phi-1_5 | 2023-11-01T23:40:19.000Z | [
"transformers",
"pytorch",
"mixformer-sequential",
"text-generation",
"custom_code",
"en",
"arxiv:2309.05463",
"license:other",
"has_space",
"region:us"
] | text-generation | microsoft | null | null | microsoft/phi-1_5 | 995 | 74,214 | transformers | 2023-09-10T04:03:46 | ---
license: other
license_name: microsoft-research-license
license_link: https://huggingface.co/microsoft/phi-1_5/resolve/main/Research%20License.docx
language:
- en
pipeline_tag: text-generation
---
## Model Summary
The language model phi-1.5 is a Transformer with **1.3 billion** parameters. It was trained using the... | 7,969 | [
[
-0.015594482421875,
-0.05145263671875,
0.01543426513671875,
0.0229339599609375,
-0.0220489501953125,
-0.040313720703125,
0.0009670257568359375,
-0.0257415771484375,
-0.0157928466796875,
0.0272369384765625,
-0.047332763671875,
-0.032562255859375,
-0.0399475097656... |
timm/tf_efficientnet_b0.ns_jft_in1k | 2023-04-27T21:17:12.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:1905.11946",
"arxiv:1911.04252",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/tf_efficientnet_b0.ns_jft_in1k | 0 | 74,189 | timm | 2022-12-13T00:01:33 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for tf_efficientnet_b0.ns_jft_in1k
A EfficientNet image classification model. Trained on ImageNet-1k and unlabeled JFT-300m using Noisy Student semi-supervised learning in Tensorflow by paper authors... | 4,597 | [
[
-0.0296630859375,
-0.04278564453125,
-0.00662994384765625,
0.00893402099609375,
-0.018402099609375,
-0.02850341796875,
-0.0254058837890625,
-0.0306549072265625,
0.01218414306640625,
0.026641845703125,
-0.026031494140625,
-0.042083740234375,
-0.0545654296875,
... |
Rostlab/prot_bert | 2020-12-11T21:30:07.000Z | [
"transformers",
"pytorch",
"fill-mask",
"protein language model",
"protein",
"dataset:Uniref100",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | Rostlab | null | null | Rostlab/prot_bert | 54 | 73,899 | transformers | 2022-03-02T23:29:04 | ---
language: protein
tags:
- protein language model
datasets:
- Uniref100
---
# ProtBert model
Pretrained model on protein sequences using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://doi.org/10.1101/2020.07.12.199554) and first released in
[this repository](https://github.co... | 7,963 | [
[
-0.01029205322265625,
-0.03948974609375,
0.0200347900390625,
0.004638671875,
-0.0238037109375,
0.016876220703125,
0.004116058349609375,
-0.0224456787109375,
0.02978515625,
0.0278778076171875,
-0.042449951171875,
-0.0305633544921875,
-0.0582275390625,
0.01733... |
MoritzLaurer/mDeBERTa-v3-base-mnli-xnli | 2023-03-22T08:35:38.000Z | [
"transformers",
"pytorch",
"safetensors",
"deberta-v2",
"text-classification",
"zero-shot-classification",
"nli",
"multilingual",
"en",
"ar",
"bg",
"de",
"el",
"es",
"fr",
"hi",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh",
"dataset:multi_nli",
"dataset:xnli",
"arxiv:21... | zero-shot-classification | MoritzLaurer | null | null | MoritzLaurer/mDeBERTa-v3-base-mnli-xnli | 163 | 73,856 | transformers | 2022-03-02T23:29:04 | ---
language:
- multilingual
- en
- ar
- bg
- de
- el
- es
- fr
- hi
- ru
- sw
- th
- tr
- ur
- vi
- zh
license: mit
tags:
- zero-shot-classification
- text-classification
- nli
- pytorch
metrics:
- accuracy
datasets:
- multi_nli
- xnli
pipeline_tag: zero-shot-classification
widget:
- text: "Angela Merke... | 6,498 | [
[
-0.03411865234375,
-0.0285797119140625,
0.0114898681640625,
0.0199737548828125,
-0.00115203857421875,
-0.0032558441162109375,
-0.0156402587890625,
-0.047576904296875,
0.021881103515625,
0.023101806640625,
-0.0462646484375,
-0.034332275390625,
-0.04248046875,
... |
dreamlike-art/dreamlike-diffusion-1.0 | 2023-01-27T14:44:44.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"art",
"artistic",
"en",
"license:other",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | dreamlike-art | null | null | dreamlike-art/dreamlike-diffusion-1.0 | 997 | 73,097 | diffusers | 2022-12-11T04:16:04 | ---
language:
- en
license: other
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- art
- artistic
- diffusers
inference: false
---
# Dreamlike Diffusion 1.0 is SD 1.5 fine tuned on high quality art, made by [dreamlike.art](https://dreamlike.art/).
# If you want to use dreamlike models on your w... | 4,989 | [
[
-0.0413818359375,
-0.05523681640625,
0.031951904296875,
0.037322998046875,
-0.03228759765625,
-0.00934600830078125,
0.00844573974609375,
-0.047943115234375,
0.0565185546875,
0.04644775390625,
-0.050689697265625,
-0.057891845703125,
-0.04144287109375,
-0.0225... |
ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition | 2021-09-21T20:59:32.000Z | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | audio-classification | ehcalabres | null | null | ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition | 84 | 72,717 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model_index:
name: wav2vec2-lg-xlsr-en-speech-emotion-recognition
---
# Speech Emotion Recognition By Fine-Tuning Wav2Vec 2.0
The model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatas... | 2,633 | [
[
-0.04217529296875,
-0.0307464599609375,
0.00801849365234375,
-0.005680084228515625,
-0.002422332763671875,
-0.005817413330078125,
-0.0084991455078125,
-0.02532958984375,
0.014678955078125,
0.0189056396484375,
-0.061126708984375,
-0.04547119140625,
-0.05496215820... |
cardiffnlp/twitter-roberta-base-hate | 2023-04-19T07:54:22.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"arxiv:2010.12421",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | cardiffnlp | null | null | cardiffnlp/twitter-roberta-base-hate | 12 | 72,692 | transformers | 2022-03-02T23:29:05 | # Twitter-roBERTa-base for Hate Speech Detection
This is a roBERTa-base model trained on ~58M tweets and finetuned for hate speech detection with the TweetEval benchmark.
This model is specialized to detect hate speech against women and immigrants.
**NEW!** We have made available a more recent and robust hate speech... | 2,670 | [
[
-0.004940032958984375,
-0.05133056640625,
0.00814056396484375,
0.01995849609375,
-0.006282806396484375,
0.013763427734375,
-0.0222015380859375,
-0.01213836669921875,
0.01212310791015625,
0.0127105712890625,
-0.0269622802734375,
-0.06414794921875,
-0.063049316406... |
ai-forever/ruRoberta-large | 2023-11-03T12:47:18.000Z | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"PyTorch",
"Transformers",
"ru",
"arxiv:2309.10931",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | ai-forever | null | null | ai-forever/ruRoberta-large | 33 | 72,532 | transformers | 2022-03-02T23:29:05 | ---
language:
- ru
tags:
- PyTorch
- Transformers
thumbnail: "https://github.com/sberbank-ai/model-zoo"
---
# ruRoberta-large
The model architecture design, pretraining, and evaluation are documented in our preprint: [**A Family of Pretrained Transformer Language Models for Russian**](https://arxiv.org/abs/2309.10931)... | 1,135 | [
[
-0.025390625,
-0.0084381103515625,
0.013916015625,
0.02252197265625,
-0.0291900634765625,
-0.000476837158203125,
-0.0271759033203125,
-0.0166015625,
-0.00011712312698364258,
0.0252685546875,
-0.03936767578125,
-0.0267791748046875,
-0.046630859375,
-0.0051574... |
Helsinki-NLP/opus-mt-en-de | 2023-08-16T11:29:21.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"marian",
"text2text-generation",
"translation",
"en",
"de",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-en-de | 17 | 72,440 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: cc-by-4.0
---
### opus-mt-en-de
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Citation Information](#citation-information)
- [How to Get St... | 3,310 | [
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0.0190887451171875,
-0.037109375,
-0.041839599609375,
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0.018890... |
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