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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
jonatasgrosman/wav2vec2-large-xlsr-53-english | 2023-03-25T10:56:55.000Z | [
"transformers",
"pytorch",
"jax",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"en",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_vo... | automatic-speech-recognition | jonatasgrosman | null | null | jonatasgrosman/wav2vec2-large-xlsr-53-english | 299 | 73,582,776 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- common_voice
- mozilla-foundation/common_voice_6_0
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- en
- hf-asr-leaderboard
- mozilla-foundation/common_voice_6_0
- robust-speech-event
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 ... | 5,327 | [
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timm/mobilenetv3_large_100.ra_in1k | 2023-04-27T22:49:21.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2110.00476",
"arxiv:1905.02244",
"license:apache-2.0",
"region:us",
"has_space"
] | image-classification | timm | null | null | timm/mobilenetv3_large_100.ra_in1k | 9 | 61,880,982 | timm | 2022-12-16T05:38:07 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for mobilenetv3_large_100.ra_in1k
A MobileNet-v3 image classification model. Trained on ImageNet-1k in `timm` using recipe template described below.
Recipe details:
* RandAugment `RA` recipe. Inspi... | 4,793 | [
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bert-base-uncased | 2023-06-30T01:42:19.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"coreml",
"onnx",
"safetensors",
"bert",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | bert-base-uncased | 1,182 | 52,250,055 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT base model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](http... | 10,517 | [
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distilbert-base-uncased-finetuned-sst-2-english | 2023-10-26T16:14:11.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"onnx",
"safetensors",
"distilbert",
"text-classification",
"en",
"dataset:sst2",
"dataset:glue",
"arxiv:1910.01108",
"doi:10.57967/hf/0181",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | null | null | null | distilbert-base-uncased-finetuned-sst-2-english | 331 | 41,670,892 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- sst2
- glue
model-index:
- name: distilbert-base-uncased-finetuned-sst-2-english
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: glue
type: glue
config: sst2
split: validation
metrics:
... | 10,458 | [
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openai/clip-vit-large-patch14 | 2023-09-15T15:49:35.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"clip",
"zero-shot-image-classification",
"vision",
"arxiv:2103.00020",
"arxiv:1908.04913",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-image-classification | openai | null | null | openai/clip-vit-large-patch14 | 676 | 26,212,915 | transformers | 2022-03-02T23:29:05 | ---
tags:
- vision
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
---
# Model Card: CLIP
Disclaimer: The model card is taken and modified from the official CLIP repository, it can be found ... | 7,935 | [
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gpt2 | 2023-06-30T02:19:43.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"tflite",
"rust",
"onnx",
"safetensors",
"gpt2",
"text-generation",
"exbert",
"en",
"doi:10.57967/hf/0039",
"license:mit",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | null | null | null | gpt2 | 1,471 | 23,269,709 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- exbert
license: mit
---
# GPT-2
Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large
Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
[this paper](https://d4mucfpksywv.cloudfront.net/better... | 8,090 | [
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tiiuae/falcon-7b-instruct | 2023-09-29T14:32:23.000Z | [
"transformers",
"pytorch",
"coreml",
"falcon",
"text-generation",
"custom_code",
"en",
"dataset:tiiuae/falcon-refinedweb",
"arxiv:2205.14135",
"arxiv:1911.02150",
"arxiv:2005.14165",
"arxiv:2104.09864",
"arxiv:2306.01116",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"t... | text-generation | tiiuae | null | null | tiiuae/falcon-7b-instruct | 710 | 15,487,847 | transformers | 2023-04-25T06:21:01 | ---
datasets:
- tiiuae/falcon-refinedweb
language:
- en
inference: true
widget:
- text: "Hey Falcon! Any recommendations for my holidays in Abu Dhabi?"
example_title: "Abu Dhabi Trip"
- text: "What's the Everett interpretation of quantum mechanics?"
example_title: "Q/A: Quantum & Answers"
- text: "Giv... | 9,798 | [
[
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xlm-roberta-base | 2023-04-07T12:46:17.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"onnx",
"safetensors",
"xlm-roberta",
"fill-mask",
"exbert",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi... | fill-mask | null | null | null | xlm-roberta-base | 406 | 12,048,443 | transformers | 2022-03-02T23:29:04 | ---
tags:
- exbert
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
... | 5,238 | [
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distilbert-base-uncased | 2023-08-18T14:59:41.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"distilbert",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1910.01108",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | distilbert-base-uncased | 292 | 11,014,465 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# DistilBERT base model (uncased)
This model is a distilled version of the [BERT base model](https://huggingface.co/bert-base-uncased). It was
introduced in [this paper](https://arxiv.org/abs/1910.01108). The code for the disti... | 8,577 | [
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sentence-transformers/all-mpnet-base-v2 | 2023-11-02T09:35:52.000Z | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"en",
"dataset:s2orc",
"dataset:flax-sentence-embeddings/stackexchange_xml",
"dataset:ms_marco",
"dataset:gooaq",
"dataset:yahoo_answers_topics",
"dataset:code_search_net",
"dataset:search_qa",
"datas... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/all-mpnet-base-v2 | 452 | 10,816,338 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language: en
license: apache-2.0
datasets:
- s2orc
- flax-sentence-embeddings/stackexchange_xml
- ms_marco
- gooaq
- yahoo_answers_topics
- code_search_net
- search_qa
- eli5
- snli
- multi_nli
- wikihow
- nat... | 10,571 | [
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0.0... |
stabilityai/stable-diffusion-xl-base-1.0 | 2023-10-30T16:03:47.000Z | [
"diffusers",
"onnx",
"text-to-image",
"stable-diffusion",
"arxiv:2307.01952",
"arxiv:2211.01324",
"arxiv:2108.01073",
"arxiv:2112.10752",
"license:openrail++",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | stabilityai | null | null | stabilityai/stable-diffusion-xl-base-1.0 | 3,405 | 9,097,397 | diffusers | 2023-07-25T13:25:51 | ---
license: openrail++
tags:
- text-to-image
- stable-diffusion
---
# SD-XL 1.0-base Model Card
## Model
[SDXL](https://arxiv.org/abs/2307.01952) consists of an [ensemble of experts](https://arxiv.org/abs/2211.01324) pipeline for latent diffusion:
In a first step, the bas... | 8,661 | [
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cardiffnlp/twitter-roberta-base-sentiment | 2023-01-20T09:52:13.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"en",
"dataset:tweet_eval",
"arxiv:2010.12421",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | cardiffnlp | null | null | cardiffnlp/twitter-roberta-base-sentiment | 219 | 8,846,250 | transformers | 2022-03-02T23:29:05 | ---
datasets:
- tweet_eval
language:
- en
---
# Twitter-roBERTa-base for Sentiment Analysis
This is a roBERTa-base model trained on ~58M tweets and finetuned for sentiment analysis with the TweetEval benchmark. This model is suitable for English (for a similar multilingual model, see [XLM-T](https://huggingface.co/car... | 3,717 | [
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openai/clip-vit-base-patch32 | 2022-10-04T09:42:04.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"clip",
"zero-shot-image-classification",
"vision",
"arxiv:2103.00020",
"arxiv:1908.04913",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-image-classification | openai | null | null | openai/clip-vit-base-patch32 | 262 | 8,682,996 | transformers | 2022-03-02T23:29:05 | ---
tags:
- vision
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
---
# Model Card: CLIP
Disclaimer: The model card is taken and modified from the official CLIP repository, it can be found ... | 7,930 | [
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stabilityai/stable-diffusion-xl-refiner-1.0 | 2023-09-25T13:42:56.000Z | [
"diffusers",
"stable-diffusion",
"image-to-image",
"arxiv:2307.01952",
"arxiv:2211.01324",
"arxiv:2108.01073",
"arxiv:2112.10752",
"license:openrail++",
"has_space",
"diffusers:StableDiffusionXLImg2ImgPipeline",
"region:us"
] | image-to-image | stabilityai | null | null | stabilityai/stable-diffusion-xl-refiner-1.0 | 1,032 | 8,432,740 | diffusers | 2023-07-26T07:38:01 | ---
license: openrail++
tags:
- stable-diffusion
- image-to-image
---
# SD-XL 1.0-refiner Model Card
## Model
[SDXL](https://arxiv.org/abs/2307.01952) consists of an [ensemble of experts](https://arxiv.org/abs/2211.01324) pipeline for latent diffusion:
In a first step, the... | 5,535 | [
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roberta-base | 2023-03-06T15:14:53.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"roberta",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1907.11692",
"arxiv:1806.02847",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | roberta-base | 236 | 8,107,369 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- exbert
license: mit
datasets:
- bookcorpus
- wikipedia
---
# RoBERTa base model
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1907.11692) and first released in
[this repository](https://github.com... | 9,064 | [
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MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli | 2023-03-20T08:28:44.000Z | [
"transformers",
"pytorch",
"safetensors",
"deberta-v2",
"text-classification",
"zero-shot-classification",
"en",
"dataset:multi_nli",
"dataset:anli",
"dataset:fever",
"arxiv:2006.03654",
"license:mit",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-classification | MoritzLaurer | null | null | MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli | 105 | 8,058,718 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
license: mit
tags:
- text-classification
- zero-shot-classification
datasets:
- multi_nli
- anli
- fever
metrics:
- accuracy
pipeline_tag: zero-shot-classification
model-index:
- name: MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli
results:
- task:
type: natural-language-inference
name:... | 23,366 | [
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-0.03302001953125,
-0.049285888671875,... |
runwayml/stable-diffusion-v1-5 | 2023-08-23T21:14:19.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"arxiv:2207.12598",
"arxiv:2112.10752",
"arxiv:2103.00020",
"arxiv:2205.11487",
"arxiv:1910.09700",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"re... | text-to-image | runwayml | null | null | runwayml/stable-diffusion-v1-5 | 9,529 | 7,769,173 | diffusers | 2022-10-19T23:38:35 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
inference: true
extra_gated_prompt: |-
This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
The CreativeML OpenRAIL License specifies:
1. ... | 14,448 | [
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stabilityai/StableBeluga-7B | 2023-08-29T20:21:36.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:conceptofmind/cot_submix_original",
"dataset:conceptofmind/flan2021_submix_original",
"dataset:conceptofmind/t0_submix_original",
"dataset:conceptofmind/niv2_submix_original",
"arxiv:2307.09288",
"arxiv:2306.02707",
"end... | text-generation | stabilityai | null | null | stabilityai/StableBeluga-7B | 119 | 7,521,844 | transformers | 2023-07-27T02:01:15 | ---
datasets:
- conceptofmind/cot_submix_original
- conceptofmind/flan2021_submix_original
- conceptofmind/t0_submix_original
- conceptofmind/niv2_submix_original
language:
- en
pipeline_tag: text-generation
---
# Stable Beluga 7B
Use [Stable Chat (Research Preview)](https://chat.stability.ai/chat) to test Stability A... | 5,307 | [
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cardiffnlp/twitter-roberta-base-irony | 2023-08-02T00:36:09.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"en",
"dataset:tweet_eval",
"arxiv:2010.12421",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | cardiffnlp | null | null | cardiffnlp/twitter-roberta-base-irony | 13 | 7,044,288 | transformers | 2022-03-02T23:29:05 | ---
datasets:
- tweet_eval
language:
- en
---
# Twitter-roBERTa-base for Irony Detection
This is a roBERTa-base model trained on ~58M tweets and finetuned for irony detection with the TweetEval benchmark.
This model has integrated into the [TweetNLP Python library](https://github.com/cardiffnlp/tweetnlp/).
- Paper: ... | 3,305 | [
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SamLowe/roberta-base-go_emotions | 2023-10-04T10:00:58.000Z | [
"transformers",
"pytorch",
"safetensors",
"roberta",
"text-classification",
"emotions",
"multi-class-classification",
"multi-label-classification",
"en",
"dataset:go_emotions",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | SamLowe | null | null | SamLowe/roberta-base-go_emotions | 159 | 6,800,543 | transformers | 2022-09-15T13:04:21 | ---
language: en
tags:
- text-classification
- pytorch
- roberta
- emotions
- multi-class-classification
- multi-label-classification
datasets:
- go_emotions
license: mit
widget:
- text: I am not having a great day.
---
#### Overview
Model trained from [roberta-base](https://huggingface.co/roberta-base) on the [go_em... | 9,565 | [
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marieke93/MiniLM-evidence-types | 2022-06-11T13:32:27.000Z | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | marieke93 | null | null | marieke93/MiniLM-evidence-types | 3 | 6,543,049 | transformers | 2022-06-07T14:19:25 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MiniLM-evidence-types
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. -->
# ... | 3,742 | [
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Ashishkr/query_wellformedness_score | 2023-10-13T16:08:29.000Z | [
"transformers",
"pytorch",
"jax",
"safetensors",
"roberta",
"text-classification",
"dataset:google_wellformed_query",
"license:apache-2.0",
"region:us"
] | text-classification | Ashishkr | null | null | Ashishkr/query_wellformedness_score | 13 | 6,540,192 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
inference: false
datasets: google_wellformed_query
---
**Model name**: Query Wellformedness Scoring
**Description** : Evaluate the well-formedness of sentences by checking grammatical correctness and completeness. Sensitive to case and penalizes sentences for incorrect grammar and case.
**Fea... | 2,209 | [
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benjamin/wtp-canine-s-1l | 2023-05-31T09:10:23.000Z | [
"transformers",
"pytorch",
"la-canine",
"token-classification",
"multilingual",
"am",
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"fy",
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"gd",
"gl",
"gu",
"ha",
"he",
"... | token-classification | benjamin | null | null | benjamin/wtp-canine-s-1l | 0 | 6,521,575 | transformers | 2023-05-10T20:48:35 | ---
license: mit
language:
- multilingual
- am
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- be
- bg
- bn
- ca
- ceb
- cs
- cy
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- de
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- ... | 551 | [
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stabilityai/stable-diffusion-2-1 | 2023-07-05T16:19:17.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"arxiv:2112.10752",
"arxiv:2202.00512",
"arxiv:1910.09700",
"license:openrail++",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | stabilityai | null | null | stabilityai/stable-diffusion-2-1 | 3,284 | 6,158,960 | diffusers | 2022-12-06T17:24:51 | ---
license: openrail++
tags:
- stable-diffusion
- text-to-image
pinned: true
---
# Stable Diffusion v2-1 Model Card
This model card focuses on the model associated with the Stable Diffusion v2-1 model, codebase available [here](https://github.com/Stability-AI/stablediffusion).
This `stable-diffusion-2-1` model is fi... | 12,209 | [
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albert-base-v2 | 2023-05-30T07:52:10.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | albert-base-v2 | 72 | 6,140,346 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# ALBERT Base v2
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-rese... | 9,719 | [
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microsoft/deberta-base | 2022-09-26T08:50:43.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"deberta",
"deberta-v1",
"fill-mask",
"en",
"arxiv:2006.03654",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | microsoft | null | null | microsoft/deberta-base | 53 | 5,097,824 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- deberta-v1
- fill-mask
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT and RoBERTa models using disentangled attention and enhanced m... | 1,303 | [
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distilbert-base-multilingual-cased | 2023-04-06T13:40:24.000Z | [
"transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"distilbert",
"fill-mask",
"multilingual",
"af",
"sq",
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"hy",
"ast",
"az",
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"eu",
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"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",... | fill-mask | null | null | null | distilbert-base-multilingual-cased | 78 | 5,091,482 | transformers | 2022-03-02T23:29:04 | ---
language:
- multilingual
- af
- sq
- ar
- an
- hy
- ast
- az
- ba
- eu
- bar
- be
- bn
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- ko
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- roa
- nds
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- mk... | 7,316 | [
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roberta-large | 2023-03-22T09:25:01.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"onnx",
"safetensors",
"roberta",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1907.11692",
"arxiv:1806.02847",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | roberta-large | 133 | 5,073,263 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- exbert
license: mit
datasets:
- bookcorpus
- wikipedia
---
# RoBERTa large model
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1907.11692) and first released in
[this repository](htt... | 9,280 | [
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bert-base-cased | 2022-11-16T15:18:28.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"exbert",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | bert-base-cased | 157 | 5,046,520 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT base model (cased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https:... | 8,982 | [
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microsoft/layoutlmv3-base | 2023-04-12T12:49:21.000Z | [
"transformers",
"pytorch",
"tf",
"onnx",
"layoutlmv3",
"en",
"arxiv:2204.08387",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | microsoft | null | null | microsoft/layoutlmv3-base | 199 | 4,904,052 | transformers | 2022-04-18T06:53:05 | ---
language: en
license: cc-by-nc-sa-4.0
---
# LayoutLMv3
[Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [GitHub](https://aka.ms/layoutlmv3)
## Model description
LayoutLMv3 is a pre-trained multimodal Transformer for Document AI with unified text and image masking. The sim... | 1,672 | [
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bert-base-multilingual-cased | 2022-11-16T23:22:54.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"multilingual",
"af",
"sq",
"ar",
"an",
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"ast",
"az",
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"eu",
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"bn",
"inc",
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"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",
"nl"... | fill-mask | null | null | null | bert-base-multilingual-cased | 241 | 4,807,995 | transformers | 2022-03-02T23:29:04 | ---
language:
- multilingual
- af
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- mk... | 7,104 | [
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CompVis/stable-diffusion-safety-checker | 2022-11-25T17:21:38.000Z | [
"transformers",
"pytorch",
"clip",
"arxiv:2103.00020",
"arxiv:1910.09700",
"endpoints_compatible",
"has_space",
"region:us"
] | null | CompVis | null | null | CompVis/stable-diffusion-safety-checker | 79 | 4,714,020 | transformers | 2022-08-22T10:22:34 | ---
tags:
- clip
---
# Model Card for stable-diffusion-safety-checker
# Model Details
## Model Description
More information needed
- **Developed by:** More information needed
- **Shared by [Optional]:** CompVis
- **Model type:** Image Identification
- **Language(s) (NLP):** More information needed
- **License... | 5,359 | [
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mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis | 2023-03-16T20:03:13.000Z | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"financial",
"stocks",
"sentiment",
"dataset:financial_phrasebank",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | mrm8488 | null | null | mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis | 109 | 4,468,850 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- generated_from_trainer
- financial
- stocks
- sentiment
widget:
- text: "Operating profit totaled EUR 9.4 mn , down from EUR 11.7 mn in 2004 ."
datasets:
- financial_phrasebank
metrics:
- accuracy
model-index:
- name: distilRoberta-financial-sentiment
results:
- task:
name: Tex... | 2,044 | [
[
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lxyuan/distilbert-base-multilingual-cased-sentiments-student | 2023-06-24T04:09:07.000Z | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"text-classification",
"sentiment-analysis",
"zero-shot-distillation",
"distillation",
"zero-shot-classification",
"debarta-v3",
"en",
"ar",
"de",
"es",
"fr",
"ja",
"zh",
"id",
"hi",
"it",
"ms",
"pt",
"dataset:tyqian... | text-classification | lxyuan | null | null | lxyuan/distilbert-base-multilingual-cased-sentiments-student | 38 | 4,349,010 | transformers | 2023-05-05T16:22:55 | ---
license: apache-2.0
tags:
- sentiment-analysis
- text-classification
- zero-shot-distillation
- distillation
- zero-shot-classification
- debarta-v3
model-index:
- name: distilbert-base-multilingual-cased-sentiments-student
results: []
datasets:
- tyqiangz/multilingual-sentiments
language:
- en
- ar
- de
- es
- f... | 5,577 | [
[
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allenai/longformer-base-4096 | 2023-04-05T18:24:00.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"longformer",
"en",
"arxiv:2004.05150",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | allenai | null | null | allenai/longformer-base-4096 | 107 | 4,035,450 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: apache-2.0
---
# longformer-base-4096
[Longformer](https://arxiv.org/abs/2004.05150) is a transformer model for long documents.
`longformer-base-4096` is a BERT-like model started from the RoBERTa checkpoint and pretrained for MLM on long documents. It supports sequences of length up to 4,0... | 1,253 | [
[
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facebook/bart-large-cnn | 2023-10-03T04:52:04.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"bart",
"text2text-generation",
"summarization",
"en",
"dataset:cnn_dailymail",
"arxiv:1910.13461",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | summarization | facebook | null | null | facebook/bart-large-cnn | 647 | 3,952,883 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
tags:
- summarization
license: mit
thumbnail: https://huggingface.co/front/thumbnails/facebook.png
datasets:
- cnn_dailymail
model-index:
- name: facebook/bart-large-cnn
results:
- task:
type: summarization
name: Summarization
dataset:
name: cnn_dailymail
type: cnn_dai... | 6,003 | [
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cl-tohoku/bert-base-japanese | 2021-09-23T13:45:36.000Z | [
"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 | 15 | 3,830,390 | transformers | 2022-03-02T23:29:05 | ---
language: ja
license: cc-by-sa-4.0
datasets:
- wikipedia
widget:
- text: 東北大学で[MASK]の研究をしています。
---
# BERT base Japanese (IPA dictionary)
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-level to... | 1,743 | [
[
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camembert-base | 2023-05-30T14:36:19.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"camembert",
"fill-mask",
"fr",
"dataset:oscar",
"arxiv:1911.03894",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | camembert-base | 44 | 3,827,519 | transformers | 2022-03-02T23:29:04 | ---
language: fr
license: mit
datasets:
- oscar
---
# CamemBERT: a Tasty French Language Model
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Citation Information](#citation-... | 6,969 | [
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sentence-transformers/all-MiniLM-L6-v2 | 2022-11-07T08:44:33.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"rust",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"dataset:s2orc",
"dataset:flax-sentence-embeddings/stackexchange_xml",
"dataset:ms_marco",
"dataset:gooaq",
"dataset:yahoo_answers_topics",
"dataset:code_search_net",
"dataset:sea... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/all-MiniLM-L6-v2 | 1,078 | 3,768,075 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language: en
license: apache-2.0
datasets:
- s2orc
- flax-sentence-embeddings/stackexchange_xml
- ms_marco
- gooaq
- yahoo_answers_topics
- code_search_net
- search_qa
- eli5
- snli
- multi_nli
- wikihow
- nat... | 10,610 | [
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0.0092620... |
facebook/mbart-large-50 | 2023-03-28T08:28:50.000Z | [
"transformers",
"pytorch",
"tf",
"mbart",
"text2text-generation",
"mbart-50",
"multilingual",
"ar",
"cs",
"de",
"en",
"es",
"et",
"fi",
"fr",
"gu",
"hi",
"it",
"ja",
"kk",
"ko",
"lt",
"lv",
"my",
"ne",
"nl",
"ro",
"ru",
"si",
"tr",
"vi",
"zh",
"af",
... | text2text-generation | facebook | null | null | facebook/mbart-large-50 | 90 | 3,361,559 | transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- ar
- cs
- de
- en
- es
- et
- fi
- fr
- gu
- hi
- it
- ja
- kk
- ko
- lt
- lv
- my
- ne
- nl
- ro
- ru
- si
- tr
- vi
- zh
- af
- az
- bn
- fa
- he
- hr
- id
- ka
- km
- mk
- ml
- mn
- mr
- pl
- ps
- pt
- sv
- sw
- ta
- te
- th
- tl
- uk
- ur
- xh
- gl
- sl
license: mit
tags:
- mbart-50... | 4,595 | [
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0.0... |
distilbert-base-uncased-distilled-squad | 2023-04-06T13:40:56.000Z | [
"transformers",
"pytorch",
"tf",
"tflite",
"coreml",
"safetensors",
"distilbert",
"question-answering",
"en",
"dataset:squad",
"arxiv:1910.01108",
"arxiv:1910.09700",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | question-answering | null | null | null | distilbert-base-uncased-distilled-squad | 64 | 3,358,757 | transformers | 2022-03-02T23:29:04 | ---
language: en
datasets:
- squad
widget:
- text: "Which name is also used to describe the Amazon rainforest in English?"
context: "The Amazon rainforest (Portuguese: Floresta Amazônica or Amazônia; Spanish: Selva Amazónica, Amazonía or usually Amazonia; French: Forêt amazonienne; Dutch: Amazoneregenwoud), also know... | 10,955 | [
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google/electra-base-discriminator | 2021-04-30T07:33:10.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"electra",
"pretraining",
"en",
"arxiv:1406.2661",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | google | null | null | google/electra-base-discriminator | 37 | 3,318,249 | transformers | 2022-03-02T23:29:05 | ---
language: en
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
## ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
**ELECTRA** is a new method for self-supervised language representation learning. It can be used to pre-train transformer networks usi... | 2,199 | [
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pyannote/segmentation | 2023-10-04T18:52:36.000Z | [
"pyannote-audio",
"pytorch",
"pyannote",
"pyannote-audio-model",
"audio",
"voice",
"speech",
"speaker",
"speaker-segmentation",
"voice-activity-detection",
"overlapped-speech-detection",
"resegmentation",
"arxiv:2104.04045",
"license:mit",
"has_space",
"region:us"
] | voice-activity-detection | pyannote | null | null | pyannote/segmentation | 309 | 3,189,524 | pyannote-audio | 2022-03-02T23:29:05 | ---
tags:
- pyannote
- pyannote-audio
- pyannote-audio-model
- audio
- voice
- speech
- speaker
- speaker-segmentation
- voice-activity-detection
- overlapped-speech-detection
- resegmentation
license: mit
inference: false
extra_gated_prompt: "The collected information will help acquire a better knowledge of pyannote.a... | 5,844 | [
[
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... |
distilroberta-base | 2022-11-16T23:22:40.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"roberta",
"fill-mask",
"exbert",
"en",
"dataset:openwebtext",
"arxiv:1910.01108",
"arxiv:1910.09700",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | distilroberta-base | 86 | 3,140,871 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- openwebtext
---
# Model Card for DistilRoBERTa base
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training Details](#training-details)
5. [Evaluation](#evaluat... | 7,498 | [
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pyannote/speaker-diarization | 2023-10-04T18:53:17.000Z | [
"pyannote-audio",
"pyannote",
"pyannote-audio-pipeline",
"audio",
"voice",
"speech",
"speaker",
"speaker-diarization",
"speaker-change-detection",
"voice-activity-detection",
"overlapped-speech-detection",
"automatic-speech-recognition",
"dataset:ami",
"dataset:dihard",
"dataset:voxconve... | automatic-speech-recognition | pyannote | null | null | pyannote/speaker-diarization | 537 | 2,981,173 | pyannote-audio | 2022-03-02T23:29:05 | ---
tags:
- pyannote
- pyannote-audio
- pyannote-audio-pipeline
- audio
- voice
- speech
- speaker
- speaker-diarization
- speaker-change-detection
- voice-activity-detection
- overlapped-speech-detection
- automatic-speech-recognition
datasets:
- ami
- dihard
- voxconverse
- aishell
- repere
- voxceleb
license: mit
e... | 11,494 | [
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... |
prajjwal1/bert-small | 2021-10-27T18:31:52.000Z | [
"transformers",
"pytorch",
"BERT",
"MNLI",
"NLI",
"transformer",
"pre-training",
"en",
"arxiv:1908.08962",
"arxiv:2110.01518",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | prajjwal1 | null | null | prajjwal1/bert-small | 12 | 2,935,794 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
license:
- mit
tags:
- BERT
- MNLI
- NLI
- transformer
- pre-training
---
The following model is a Pytorch pre-trained model obtained from converting Tensorflow checkpoint found in the [official Google BERT repository](https://github.com/google-research/bert).
This is one of the smaller ... | 2,572 | [
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... |
facebook/bart-large-mnli | 2023-09-05T14:49:34.000Z | [
"transformers",
"pytorch",
"jax",
"rust",
"safetensors",
"bart",
"text-classification",
"zero-shot-classification",
"dataset:multi_nli",
"arxiv:1910.13461",
"arxiv:1909.00161",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-classification | facebook | null | null | facebook/bart-large-mnli | 726 | 2,909,045 | transformers | 2022-03-02T23:29:05 | ---
license: mit
thumbnail: https://huggingface.co/front/thumbnails/facebook.png
pipeline_tag: zero-shot-classification
datasets:
- multi_nli
---
# bart-large-mnli
This is the checkpoint for [bart-large](https://huggingface.co/facebook/bart-large) after being trained on the [MultiNLI (MNLI)](https://huggingface.co/da... | 3,793 | [
[
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xlm-roberta-large | 2023-09-29T13:04:24.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"onnx",
"safetensors",
"xlm-roberta",
"fill-mask",
"exbert",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi... | fill-mask | null | null | null | xlm-roberta-large | 219 | 2,582,394 | transformers | 2022-03-02T23:29:04 | ---
tags:
- exbert
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
-... | 5,241 | [
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... |
openai/clip-vit-base-patch16 | 2022-10-04T09:42:28.000Z | [
"transformers",
"pytorch",
"jax",
"clip",
"zero-shot-image-classification",
"vision",
"arxiv:2103.00020",
"arxiv:1908.04913",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-image-classification | openai | null | null | openai/clip-vit-base-patch16 | 41 | 2,560,286 | transformers | 2022-03-02T23:29:05 | ---
tags:
- vision
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
---
# Model Card: CLIP
Disclaimer: The model card is taken and modified from the official CLIP repository, it can be found [h... | 7,916 | [
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nlpconnect/vit-gpt2-image-captioning | 2023-02-27T15:00:09.000Z | [
"transformers",
"pytorch",
"vision-encoder-decoder",
"image-to-text",
"image-captioning",
"doi:10.57967/hf/0222",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | image-to-text | nlpconnect | null | null | nlpconnect/vit-gpt2-image-captioning | 591 | 2,485,193 | transformers | 2022-03-02T23:29:05 | ---
tags:
- image-to-text
- image-captioning
license: apache-2.0
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
example_title: Savanna
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
example_title: Football Match
- src: https:... | 2,702 | [
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t5-small | 2023-06-30T02:31:26.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"onnx",
"safetensors",
"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:... | translation | null | null | null | t5-small | 161 | 2,346,088 | 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 Small
![model image](https://camo.githubusercontent.com/623b4dea0b653f2ad3f36c71ebfe749a677ac0a1/68747470733a2f2f6d69726f2e6d656469756d2e636f6d2f6d61782f343030362f312a44304a... | 8,473 | [
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0.030792236328125,
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0... |
patrickjohncyh/fashion-clip | 2023-06-09T01:03:16.000Z | [
"transformers",
"pytorch",
"safetensors",
"clip",
"zero-shot-image-classification",
"vision",
"language",
"fashion",
"ecommerce",
"en",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-image-classification | patrickjohncyh | null | null | patrickjohncyh/fashion-clip | 94 | 2,161,565 | transformers | 2023-02-21T19:51:47 | ---
license: mit
tags:
- vision
- language
- fashion
- ecommerce
library_name: transformers
language:
- en
widget:
- src: https://cdn-images.farfetch-contents.com/19/76/05/56/19760556_44221665_1000.jpg
candidate_labels: black shoe, red shoe, a cat
example_title: Black Shoe
---
[![Youtube Video](https://img.s... | 7,002 | [
[
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0.00... |
Intel/dpt-hybrid-midas | 2023-03-06T16:35:15.000Z | [
"transformers",
"pytorch",
"dpt",
"depth-estimation",
"vision",
"arxiv:2103.13413",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | depth-estimation | Intel | null | null | Intel/dpt-hybrid-midas | 38 | 2,114,701 | transformers | 2022-12-06T09:12:55 | ---
license: apache-2.0
tags:
- vision
- depth-estimation
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https://huggingface.co/datasets/m... | 7,825 | [
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-0.034942626953125,
-0.049102783203125,
-0.010986... |
jonatasgrosman/wav2vec2-large-xlsr-53-portuguese | 2022-12-14T01:59:47.000Z | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"pt",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | automatic-speech-recognition | jonatasgrosman | null | null | jonatasgrosman/wav2vec2-large-xlsr-53-portuguese | 18 | 2,088,717 | transformers | 2022-03-02T23:29:05 | ---
language: pt
license: apache-2.0
datasets:
- common_voice
- mozilla-foundation/common_voice_6_0
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- mozilla-foundation/common_voice_6_0
- pt
- robust-speech-event
- speech
- xlsr-fine-tuning-week
model-index:
- name: XLSR Wav2Vec2 ... | 5,291 | [
[
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-... |
distilgpt2 | 2023-04-29T12:24:21.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"tflite",
"rust",
"coreml",
"safetensors",
"gpt2",
"text-generation",
"exbert",
"en",
"dataset:openwebtext",
"arxiv:1910.01108",
"arxiv:2201.08542",
"arxiv:2203.12574",
"arxiv:1910.09700",
"arxiv:1503.02531",
"license:apache-2.0",
"model-... | text-generation | null | null | null | distilgpt2 | 267 | 1,992,862 | transformers | 2022-03-02T23:29:04 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- openwebtext
model-index:
- name: distilgpt2
results:
- task:
type: text-generation
name: Text Generation
dataset:
type: wikitext
name: WikiText-103
metrics:
- type: perplexity
name: Perplexity
... | 10,966 | [
[
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nateraw/vit-age-classifier | 2023-09-19T15:53:10.000Z | [
"transformers",
"pytorch",
"vit",
"image-classification",
"dataset:fairface",
"doi:10.57967/hf/1259",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | nateraw | null | null | nateraw/vit-age-classifier | 58 | 1,954,882 | transformers | 2022-03-02T23:29:05 | ---
tags:
- image-classification
- pytorch
datasets:
- fairface
---
A vision transformer finetuned to classify the age of a given person's face.
```python
import requests
from PIL import Image
from io import BytesIO
from transformers import ViTFeatureExtractor, ViTForImageClassification
# Get example image fr... | 943 | [
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0.0307464599609375,
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jonatasgrosman/wav2vec2-large-xlsr-53-russian | 2022-12-14T01:58:43.000Z | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"robust-speech-event",
"ru",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | automatic-speech-recognition | jonatasgrosman | null | null | jonatasgrosman/wav2vec2-large-xlsr-53-russian | 28 | 1,952,331 | transformers | 2022-03-02T23:29:05 | ---
language: ru
license: apache-2.0
datasets:
- common_voice
- mozilla-foundation/common_voice_6_0
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- mozilla-foundation/common_voice_6_0
- robust-speech-event
- ru
- speech
- xlsr-fine-tuning-week
model-index:
- name: XLSR Wav2Vec2 ... | 5,855 | [
[
-0.035858154296875,
-0.043670654296875,
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t5-base | 2023-04-06T13:42:36.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"t5",
"text2text-generation",
"summarization",
"translation",
"en",
"fr",
"ro",
"de",
"dataset:c4",
"arxiv:1805.12471",
"arxiv:1708.00055",
"arxiv:1704.05426",
"arxiv:1606.05250",
"arxiv:1808.09121",
"arxiv:1810.1... | translation | null | null | null | t5-base | 361 | 1,853,138 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
- fr
- ro
- de
datasets:
- c4
tags:
- summarization
- translation
license: apache-2.0
---
# Model Card for T5 Base
![model image](https://camo.githubusercontent.com/623b4dea0b653f2ad3f36c71ebfe749a677ac0a1/68747470733a2f2f6d69726f2e6d656469756d2e636f6d2f6d61782f343030362f312a44304a31674e516638767... | 8,454 | [
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... |
Davlan/distilbert-base-multilingual-cased-ner-hrl | 2023-08-14T19:34:34.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"distilbert",
"token-classification",
"license:afl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | Davlan | null | null | Davlan/distilbert-base-multilingual-cased-ner-hrl | 67 | 1,808,811 | transformers | 2022-03-02T23:29:04 | ---
license: afl-3.0
---
Hugging Face's logo
---
language:
- ar
- de
- en
- es
- fr
- it
- lv
- nl
- pt
- zh
- multilingual
---
# distilbert-base-multilingual-cased-ner-hrl
## Model description
**distilbert-base-multilingual-cased-ner-hrl** is a **Named Entity Recognition** model for 10 high resourced languages (Arab... | 3,135 | [
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0.031... |
ckiplab/bert-base-chinese-ner | 2022-05-10T03:28:12.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"token-classification",
"zh",
"license:gpl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | ckiplab | null | null | ckiplab/bert-base-chinese-ner | 60 | 1,748,813 | 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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0... |
facebook/wav2vec2-base-960h | 2022-11-14T21:37:23.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"en",
"dataset:librispeech_asr",
"arxiv:2006.11477",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | facebook | null | null | facebook/wav2vec2-base-960h | 162 | 1,741,258 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: https://cdn-media.huggingface.... | 4,431 | [
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microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext | 2023-11-06T18:03:43.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"fill-mask",
"exbert",
"en",
"arxiv:2007.15779",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | fill-mask | microsoft | null | null | microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext | 131 | 1,685,260 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- exbert
license: mit
widget:
- text: "[MASK] is a tumor suppressor gene."
---
## MSR BiomedBERT (abstracts + full text)
<div style="border: 2px solid orange; border-radius:10px; padding:0px 10px; width: fit-content;">
* This model was previously named **"PubMedBERT (abstracts + full text)"**.... | 2,436 | [
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google/fnet-base | 2021-10-31T07:33:21.000Z | [
"transformers",
"pytorch",
"rust",
"fnet",
"pretraining",
"en",
"dataset:c4",
"arxiv:2105.03824",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | google | null | null | google/fnet-base | 13 | 1,611,942 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- fnet
license: apache-2.0
datasets:
- c4
---
# FNet base model
Pretrained model on English language using a masked language modeling (MLM) and next sentence prediction (NSP) objective. It was
introduced in [this paper](https://arxiv.org/abs/2105.03824) and first released in [this repository](... | 12,614 | [
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shibing624/text2vec-base-chinese | 2023-08-28T08:58:03.000Z | [
"transformers",
"pytorch",
"onnx",
"bert",
"feature-extraction",
"text2vec",
"sentence-similarity",
"zh",
"dataset:shibing624/nli_zh",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | shibing624 | null | null | shibing624/text2vec-base-chinese | 473 | 1,589,826 | transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- text2vec
- feature-extraction
- sentence-similarity
- transformers
datasets:
- shibing624/nli_zh
language:
- zh
metrics:
- spearmanr
library_name: transformers
---
# shibing624/text2vec-base-chinese
This is a CoSENT(Cosine Sentence) model: shibing624/tex... | 9,285 | [
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timm/resnet50.a1_in1k | 2023-04-05T18:08:16.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"arxiv:2110.00476",
"arxiv:1512.03385",
"license:apache-2.0",
"has_space",
"region:us"
] | image-classification | timm | null | null | timm/resnet50.a1_in1k | 9 | 1,577,731 | timm | 2023-04-05T18:07:45 | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnet50.a1_in1k
A ResNet-B image classification model.
This model features:
* ReLU activations
* single layer 7x7 convolution with pooling
* 1x1 convolution shortcut downsample
Trained on ImageNet-1k in `timm` usin... | 38,406 | [
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0.0867919921875,
0.0216217041015625,
-0.04901123046875,
-0.040283203125,
-0.04541015625,
-0.0006422996... |
nlptown/bert-base-multilingual-uncased-sentiment | 2023-07-27T18:14:29.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"en",
"nl",
"de",
"fr",
"it",
"es",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | nlptown | null | null | nlptown/bert-base-multilingual-uncased-sentiment | 196 | 1,572,780 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
- nl
- de
- fr
- it
- es
license: mit
---
# bert-base-multilingual-uncased-sentiment
This is a bert-base-multilingual-uncased model finetuned for sentiment analysis on product reviews in six languages: English, Dutch, German, French, Spanish, and Italian. It predicts the sentiment of the review as... | 1,903 | [
[
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0.03662109375,
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0.003... |
bert-large-cased | 2023-04-06T13:41:58.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | bert-large-cased | 13 | 1,569,927 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT large model (cased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/g... | 9,214 | [
[
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0.03924560546875,
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... |
openai/clip-vit-large-patch14-336 | 2022-10-04T09:41:39.000Z | [
"transformers",
"pytorch",
"tf",
"clip",
"zero-shot-image-classification",
"generated_from_keras_callback",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-image-classification | openai | null | null | openai/clip-vit-large-patch14-336 | 59 | 1,534,763 | transformers | 2022-04-22T14:57:43 | ---
tags:
- generated_from_keras_callback
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
model-index:
- name: clip-vit-large-patch14-336
results: []
---
<!-- This model card has been gener... | 1,045 | [
[
-0.038055419921875,
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0.03253173828125,
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0.00014650821685791016,
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0.01114654541015625,
0.037322998046875,
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-0.036285400390625,
-0.0634765625,
... |
meta-llama/Llama-2-70b-chat-hf | 2023-10-12T16:19:08.000Z | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"llama-2",
"en",
"arxiv:2307.09288",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | meta-llama | null | null | meta-llama/Llama-2-70b-chat-hf | 1,561 | 1,531,804 | transformers | 2023-07-14T18:02:07 | ---
extra_gated_heading: Access Llama 2 on Hugging Face
extra_gated_description: >-
This is a form to enable access to Llama 2 on Hugging Face after you have been
granted access from Meta. Please visit the [Meta website](https://ai.meta.com/resources/models-and-libraries/llama-downloads) and accept our
license te... | 9,960 | [
[
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0.00212860107421875,
0.026336669921875,
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... |
pyannote/segmentation-3.0 | 2023-10-04T18:53:59.000Z | [
"pyannote-audio",
"pytorch",
"pyannote",
"pyannote-audio-model",
"audio",
"voice",
"speech",
"speaker",
"speaker-diarization",
"speaker-change-detection",
"speaker-segmentation",
"voice-activity-detection",
"overlapped-speech-detection",
"resegmentation",
"license:mit",
"has_space",
... | voice-activity-detection | pyannote | null | null | pyannote/segmentation-3.0 | 25 | 1,512,995 | pyannote-audio | 2023-09-22T12:03:10 | ---
tags:
- pyannote
- pyannote-audio
- pyannote-audio-model
- audio
- voice
- speech
- speaker
- speaker-diarization
- speaker-change-detection
- speaker-segmentation
- voice-activity-detection
- overlapped-speech-detection
- resegmentation
license: mit
inference: false
extra_gated_prompt: "The collected information w... | 4,648 | [
[
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-0.0428466796875,
-0.017242431640625,
-0.0239... |
pyannote/speaker-diarization-3.0 | 2023-10-04T18:54:33.000Z | [
"pyannote-audio",
"pyannote",
"pyannote-audio-pipeline",
"audio",
"voice",
"speech",
"speaker",
"speaker-diarization",
"speaker-change-detection",
"voice-activity-detection",
"overlapped-speech-detection",
"automatic-speech-recognition",
"arxiv:2111.14448",
"arxiv:2012.01477",
"license:m... | automatic-speech-recognition | pyannote | null | null | pyannote/speaker-diarization-3.0 | 91 | 1,511,968 | pyannote-audio | 2023-09-22T13:40:36 | ---
tags:
- pyannote
- pyannote-audio
- pyannote-audio-pipeline
- audio
- voice
- speech
- speaker
- speaker-diarization
- speaker-change-detection
- voice-activity-detection
- overlapped-speech-detection
- automatic-speech-recognition
license: mit
extra_gated_prompt: "The collected information will help acquire a bet... | 10,655 | [
[
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0.008392333984375,
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0... |
facebook/wav2vec2-xlsr-53-espeak-cv-ft | 2021-12-10T17:18:39.000Z | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"speech",
"audio",
"phoneme-recognition",
"multi-lingual",
"dataset:common_voice",
"arxiv:2109.11680",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | facebook | null | null | facebook/wav2vec2-xlsr-53-espeak-cv-ft | 16 | 1,507,688 | transformers | 2022-03-02T23:29:05 | ---
language: multi-lingual
datasets:
- common_voice
tags:
- speech
- audio
- automatic-speech-recognition
- phoneme-recognition
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: https://cdn-media.huggingface.co... | 3,012 | [
[
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0.01059722900390625,
0.02642822265625,
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-0.0467529296875,
-0.041168212890625,
... |
QCRI/bert-base-multilingual-cased-pos-english | 2023-01-25T06:00:31.000Z | [
"transformers",
"pytorch",
"bert",
"token-classification",
"part-of-speech",
"finetuned",
"en",
"license:cc-by-nc-3.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | QCRI | null | null | QCRI/bert-base-multilingual-cased-pos-english | 21 | 1,504,084 | transformers | 2022-04-27T08:15:20 | ---
language:
- en
tags:
- part-of-speech
- finetuned
license: cc-by-nc-3.0
---
# BERT-base-multilingual-cased finetuned for Part-of-Speech tagging
This is a multilingual BERT model fine tuned for part-of-speech tagging for English. It is trained using the Penn TreeBank (Marcus et al., 1993) and achieves an F1-... | 1,468 | [
[
-0.03271484375,
-0.050994873046875,
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-0.... |
indobenchmark/indobert-base-p1 | 2021-05-19T20:22:23.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"indobert",
"indobenchmark",
"indonlu",
"id",
"dataset:Indo4B",
"arxiv:2009.05387",
"license:mit",
"has_space",
"region:us"
] | feature-extraction | indobenchmark | null | null | indobenchmark/indobert-base-p1 | 8 | 1,496,629 | transformers | 2022-03-02T23:29:05 | ---
language: id
tags:
- indobert
- indobenchmark
- indonlu
license: mit
inference: false
datasets:
- Indo4B
---
# IndoBERT Base Model (phase1 - uncased)
[IndoBERT](https://arxiv.org/abs/2009.05387) is a state-of-the-art language model for Indonesian based on the BERT model. The pretrained model is trained using a ma... | 2,712 | [
[
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... |
google/flan-t5-large | 2023-07-17T12:49:05.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"t5",
"text2text-generation",
"en",
"fr",
"ro",
"de",
"multilingual",
"dataset:svakulenk0/qrecc",
"dataset:taskmaster2",
"dataset:djaym7/wiki_dialog",
"dataset:deepmind/code_contests",
"dataset:lambada",
"dataset:gsm8k",
"dat... | text2text-generation | google | null | null | google/flan-t5-large | 299 | 1,485,728 | transformers | 2022-10-21T10:07:08 | ---
language:
- en
- fr
- ro
- de
- multilingual
widget:
- text: "Translate to German: My name is Arthur"
example_title: "Translation"
- text: "Please answer to the following question. Who is going to be the next Ballon d'or?"
example_title: "Question Answering"
- text: "Q: Can Geoffrey Hinton have a conversatio... | 10,818 | [
[
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0.00968170166015625,
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... |
microsoft/layoutlm-base-uncased | 2022-12-16T16:25:46.000Z | [
"transformers",
"pytorch",
"tf",
"layoutlm",
"arxiv:1912.13318",
"endpoints_compatible",
"has_space",
"region:us"
] | null | microsoft | null | null | microsoft/layoutlm-base-uncased | 25 | 1,444,971 | transformers | 2022-03-02T23:29:05 | # LayoutLM
**Multimodal (text + layout/format + image) pre-training for document AI**
[Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [GitHub](https://aka.ms/layoutlm)
## Model description
LayoutLM is a simple but effective pre-training method of text and layout for document ... | 1,500 | [
[
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0.02734375,
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-0.04010009765625,
-0.0221405... |
ProsusAI/finbert | 2023-05-23T12:43:35.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"financial-sentiment-analysis",
"sentiment-analysis",
"en",
"arxiv:1908.10063",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | ProsusAI | null | null | ProsusAI/finbert | 373 | 1,423,334 | transformers | 2022-03-02T23:29:04 | ---
language: "en"
tags:
- financial-sentiment-analysis
- sentiment-analysis
widget:
- text: "Stocks rallied and the British pound gained."
---
FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financi... | 1,476 | [
[
-0.0447998046875,
-0.042938232421875,
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0.0264434814453125,
0.05767822265625,
-0.05206298828125,
-0.0552978515625,
-0.031829833984375,
-0.009... |
cardiffnlp/twitter-roberta-base-sentiment-latest | 2023-05-28T05:45:10.000Z | [
"transformers",
"pytorch",
"tf",
"roberta",
"text-classification",
"en",
"dataset:tweet_eval",
"arxiv:2202.03829",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | cardiffnlp | null | null | cardiffnlp/twitter-roberta-base-sentiment-latest | 258 | 1,386,030 | transformers | 2022-03-15T01:21:58 | ---
language: en
widget:
- text: Covid cases are increasing fast!
datasets:
- tweet_eval
---
# Twitter-roBERTa-base for Sentiment Analysis - UPDATED (2022)
This is a RoBERTa-base model trained on ~124M tweets from January 2018 to December 2021, and finetuned for sentiment analysis with the TweetEval benchmark.
The ... | 4,310 | [
[
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0.0010271072387695312,
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0.... |
alexandrainst/scandi-nli-large | 2023-09-20T11:55:47.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"zero-shot-classification",
"da",
"no",
"nb",
"sv",
"dataset:strombergnlp/danfever",
"dataset:KBLab/overlim",
"dataset:MoritzLaurer/multilingual-NLI-26lang-2mil7",
"license:apache-2.0",
"endpoints_compatible",
"ha... | zero-shot-classification | alexandrainst | null | null | alexandrainst/scandi-nli-large | 5 | 1,356,428 | transformers | 2022-11-28T07:05:27 | ---
pipeline_tag: zero-shot-classification
language:
- da
- 'no'
- nb
- sv
license: apache-2.0
datasets:
- strombergnlp/danfever
- KBLab/overlim
- MoritzLaurer/multilingual-NLI-26lang-2mil7
widget:
- example_title: Danish
text: >-
Mexicansk bokser advarer Messi - 'Du skal bede til gud, om at jeg ikke
finder d... | 9,788 | [
[
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0.059661865234375,
0.0005970001220703125,
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... |
laion/CLIP-ViT-H-14-laion2B-s32B-b79K | 2023-04-18T17:45:56.000Z | [
"open_clip",
"pytorch",
"clip",
"zero-shot-image-classification",
"arxiv:1910.04867",
"license:mit",
"has_space",
"region:us"
] | zero-shot-image-classification | laion | null | null | laion/CLIP-ViT-H-14-laion2B-s32B-b79K | 181 | 1,340,812 | open_clip | 2022-09-14T22:52:28 | ---
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-H/14 - LAION-2B
# T... | 8,203 | [
[
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-0.01512908935546875,
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0.034027099609375,
-0.0330810546875,
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-0.045806884765625,
... |
dslim/bert-base-NER | 2023-05-09T16:37:55.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"token-classification",
"en",
"dataset:conll2003",
"arxiv:1810.04805",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | dslim | null | null | dslim/bert-base-NER | 278 | 1,323,754 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- conll2003
license: mit
---
# bert-base-NER
## Model description
**bert-base-NER** is a fine-tuned BERT model that is ready to use for **Named Entity Recognition** and achieves **state-of-the-art performance** for the NER task. It has been trained to recognize four types of entities: locat... | 4,804 | [
[
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-0.050384521484375,
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-0.033782958984375,
-0.043060302734375,
0.0230865478515625,
0.0251007080078125,
-0.033477783203125,
-0.03985595703125,
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0... |
microsoft/resnet-50 | 2023-03-10T17:35:03.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"resnet",
"image-classification",
"vision",
"dataset:imagenet-1k",
"arxiv:1512.03385",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | microsoft | null | null | microsoft/resnet-50 | 168 | 1,259,553 | transformers | 2022-03-16T15:42:43 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
---
# ResNet-50 v1.5
ResNet model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) by He et al.
Disclaimer: The team ... | 2,642 | [
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0.03277587890625,
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-0.02362060546875,
-0.04098510742187... |
bigscience/bloom-560m | 2023-09-26T09:16:49.000Z | [
"transformers",
"pytorch",
"jax",
"onnx",
"safetensors",
"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",... | text-generation | bigscience | null | null | bigscience/bloom-560m | 274 | 1,235,084 | transformers | 2022-05-19T11:51:24 | ---
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
- zhs
- zht
- zu
pipeline_tag: text-gener... | 20,187 | [
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deepset/roberta-base-squad2 | 2023-09-26T11:36:30.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"roberta",
"question-answering",
"en",
"dataset:squad_v2",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | question-answering | deepset | null | null | deepset/roberta-base-squad2 | 483 | 1,212,516 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: cc-by-4.0
datasets:
- squad_v2
model-index:
- name: deepset/roberta-base-squad2
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validation
metrics:
- type: exac... | 8,387 | [
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martin-ha/toxic-comment-model | 2022-05-06T02:24:31.000Z | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"en",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | martin-ha | null | null | martin-ha/toxic-comment-model | 29 | 1,196,172 | transformers | 2022-03-02T23:29:05 | ---
language: en
---
## Model description
This model is a fine-tuned version of the [DistilBERT model](https://huggingface.co/transformers/model_doc/distilbert.html) to classify toxic comments.
## How to use
You can use the model with the following code.
```python
from transformers import AutoModelForSequenceClass... | 3,184 | [
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0.0025634765625,
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0.016815185546875,
-0.03814697265625,
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0.... |
google/flan-t5-base | 2023-07-17T12:48:39.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"t5",
"text2text-generation",
"en",
"fr",
"ro",
"de",
"multilingual",
"dataset:svakulenk0/qrecc",
"dataset:taskmaster2",
"dataset:djaym7/wiki_dialog",
"dataset:deepmind/code_contests",
"dataset:lambada",
"dataset:gsm8k",
"dat... | text2text-generation | google | null | null | google/flan-t5-base | 395 | 1,145,305 | transformers | 2022-10-21T10:02:31 | ---
language:
- en
- fr
- ro
- de
- multilingual
tags:
- text2text-generation
widget:
- text: "Translate to German: My name is Arthur"
example_title: "Translation"
- text: "Please answer to the following question. Who is going to be the next Ballon d'or?"
example_title: "Question Answering"
- text: "Q: Can Geof... | 13,375 | [
[
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0.009124755859375,
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-0.039306640625,
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0.0036735... |
google/vit-base-patch16-224 | 2023-09-05T15:27:12.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"vit",
"image-classification",
"vision",
"dataset:imagenet-1k",
"dataset:imagenet-21k",
"arxiv:2010.11929",
"arxiv:2006.03677",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | google | null | null | google/vit-base-patch16-224 | 362 | 1,108,207 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
- imagenet-21k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teap... | 5,688 | [
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EleutherAI/pythia-1.4b | 2023-07-09T16:01:57.000Z | [
"transformers",
"pytorch",
"safetensors",
"gpt_neox",
"text-generation",
"causal-lm",
"pythia",
"en",
"dataset:EleutherAI/the_pile",
"arxiv:2304.01373",
"arxiv:2101.00027",
"arxiv:2201.07311",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"re... | text-generation | EleutherAI | null | null | EleutherAI/pythia-1.4b | 9 | 1,101,663 | transformers | 2023-02-09T14:08:20 | ---
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- EleutherAI/the_pile
---
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 of sizes
70... | 13,574 | [
[
-0.02484130859375,
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0.0118408203125,
-0.0277557373046875,
-0.0219879150390625,
-0.03173828125,
-0.004... |
WarriorMama777/OrangeMixs | 2023-06-28T10:00:13.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"dataset:Nerfgun3/bad_prompt",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | WarriorMama777 | null | null | WarriorMama777/OrangeMixs | 3,464 | 1,093,124 | diffusers | 2022-12-04T14:18:34 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
datasets: Nerfgun3/bad_prompt
---
----
# OrangeMixs
"OrangeMixs" shares various Merge models that can be used with StableDiffusionWebui:Automatic1111 and others.
<img src="https://i.imgur.com/VZg0LqQ.png" width="1000" height="">
Ma... | 61,021 | [
[
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0.021... |
sentence-transformers/msmarco-distilbert-dot-v5 | 2023-11-02T09:31:39.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"distilbert",
"feature-extraction",
"sentence-similarity",
"transformers",
"en",
"arxiv:1908.10084",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | sentence-transformers | null | null | sentence-transformers/msmarco-distilbert-dot-v5 | 7 | 1,072,480 | sentence-transformers | 2022-03-02T23:29:05 | ---
language:
- en
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# msmarco-distilbert-dot-v5
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vect... | 6,479 | [
[
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... |
microsoft/tapex-base-finetuned-wikisql | 2023-01-24T16:57:17.000Z | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"tapex",
"table-question-answering",
"en",
"dataset:wikisql",
"arxiv:2107.07653",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | table-question-answering | microsoft | null | null | microsoft/tapex-base-finetuned-wikisql | 13 | 1,067,188 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- tapex
- table-question-answering
datasets:
- wikisql
license: mit
---
# TAPEX (base-sized model)
TAPEX was proposed in [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://arxiv.org/abs/2107.07653) by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jia... | 3,149 | [
[
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0.041259765625,
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-0.... |
bert-large-uncased | 2022-11-14T21:36:14.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | bert-large-uncased | 56 | 1,040,642 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT large model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com... | 8,961 | [
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0.014... |
cardiffnlp/twitter-xlm-roberta-base-sentiment | 2023-07-19T20:41:38.000Z | [
"transformers",
"pytorch",
"tf",
"xlm-roberta",
"text-classification",
"multilingual",
"arxiv:2104.12250",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | cardiffnlp | null | null | cardiffnlp/twitter-xlm-roberta-base-sentiment | 147 | 1,038,434 | transformers | 2022-03-02T23:29:05 | ---
language: multilingual
widget:
- text: "🤗"
- text: "T'estimo! ❤️"
- text: "I love you!"
- text: "I hate you 🤮"
- text: "Mahal kita!"
- text: "사랑해!"
- text: "난 너가 싫어"
- text: "😍😍😍"
---
# twitter-XLM-roBERTa-base for Sentiment Analysis
This is a multilingual XLM-roBERTa-base model trained on ~198M tweets and ... | 3,249 | [
[
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0.... |
nvidia/speakerverification_en_titanet_large | 2023-03-13T19:13:57.000Z | [
"nemo",
"speaker",
"speech",
"audio",
"speaker-verification",
"speaker-recognition",
"speaker-diarization",
"titanet",
"NeMo",
"pytorch",
"en",
"dataset:VOXCELEB-1",
"dataset:VOXCELEB-2",
"dataset:FISHER",
"dataset:switchboard",
"dataset:librispeech_asr",
"dataset:SRE(2004-2010)",
... | null | nvidia | null | null | nvidia/speakerverification_en_titanet_large | 35 | 1,036,656 | nemo | 2022-07-15T00:26:00 | ---
language:
- en
library_name: nemo
datasets:
- VOXCELEB-1
- VOXCELEB-2
- FISHER
- switchboard
- librispeech_asr
- SRE(2004-2010)
thumbnail: null
tags:
- speaker
- speech
- audio
- speaker-verification
- speaker-recognition
- speaker-diarization
- titanet
- NeMo
- pytorch
license: cc-by-4.0
widget:
- src: https://hu... | 8,124 | [
[
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... |
pysentimiento/robertuito-sentiment-analysis | 2023-02-25T14:25:07.000Z | [
"pysentimiento",
"pytorch",
"tf",
"roberta",
"twitter",
"sentiment-analysis",
"es",
"arxiv:2106.09462",
"has_space",
"region:us"
] | null | pysentimiento | null | null | pysentimiento/robertuito-sentiment-analysis | 30 | 1,008,941 | pysentimiento | 2022-03-02T23:29:05 | ---
language:
- es
library_name: pysentimiento
tags:
- twitter
- sentiment-analysis
---
# Sentiment Analysis in Spanish
## robertuito-sentiment-analysis
Repository: [https://github.com/pysentimiento/pysentimiento/](https://github.com/finiteautomata/pysentimiento/)
Model trained with TASS 2020 corpus (around... | 4,583 | [
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0.015670776... |
vinai/bertweet-base | 2022-10-22T08:52:39.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | vinai | null | null | vinai/bertweet-base | 21 | 1,007,895 | transformers | 2022-03-02T23:29:05 | # <a name="introduction"></a> BERTweet: A pre-trained language model for English Tweets
BERTweet is the first public large-scale language model pre-trained for English Tweets. BERTweet is trained based on the [RoBERTa](https://github.com/pytorch/fairseq/blob/master/examples/roberta/README.md) pre-training procedure.... | 1,890 | [
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-0.047119140625,
-0.01444244384... |
CIDAS/clipseg-rd64-refined | 2023-01-04T11:56:08.000Z | [
"transformers",
"pytorch",
"clipseg",
"vision",
"image-segmentation",
"arxiv:2112.10003",
"license:apache-2.0",
"has_space",
"region:us"
] | image-segmentation | CIDAS | null | null | CIDAS/clipseg-rd64-refined | 58 | 980,137 | transformers | 2022-11-01T14:25:57 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
inference: false
---
# CLIPSeg model
CLIPSeg model with reduce dimension 64, refined (using a more complex convolution). It was introduced in the paper [Image Segmentation Using Text and Image Prompts](https://arxiv.org/abs/2112.10003) by Lüddecke et al. an... | 595 | [
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EleutherAI/pythia-2.8b | 2023-06-09T00:35:37.000Z | [
"transformers",
"pytorch",
"safetensors",
"gpt_neox",
"text-generation",
"causal-lm",
"pythia",
"en",
"dataset:EleutherAI/pile",
"arxiv:2304.01373",
"arxiv:2101.00027",
"arxiv:2201.07311",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region... | text-generation | EleutherAI | null | null | EleutherAI/pythia-2.8b | 9 | 962,527 | transformers | 2023-02-13T14:37:12 | ---
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- EleutherAI/pile
---
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 of sizes
70M, 1... | 13,570 | [
[
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-0.03289794921875,
-... |
laion/CLIP-ViT-B-16-laion2B-s34B-b88K | 2023-04-19T18:55:10.000Z | [
"open_clip",
"zero-shot-image-classification",
"arxiv:1910.04867",
"license:mit",
"has_space",
"region:us"
] | zero-shot-image-classification | laion | null | null | laion/CLIP-ViT-B-16-laion2B-s34B-b88K | 18 | 959,561 | open_clip | 2023-01-03T00:16:18 | ---
license: mit
pipeline_tag: zero-shot-image-classification
library_name: open_clip
---
# Model Card for CLIP ViT-B/16 - LAION-2B
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Training Details](#training-details)
4. [Evaluation](#evaluation)
5. [Acknowledgements](#acknowledgements)
6.... | 7,755 | [
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-0.042724609375,
-0.00... |
Bingsu/clip-vit-base-patch32-ko | 2022-11-08T11:02:10.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"clip",
"zero-shot-image-classification",
"ko",
"arxiv:2004.09813",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | zero-shot-image-classification | Bingsu | null | null | Bingsu/clip-vit-base-patch32-ko | 3 | 956,648 | transformers | 2022-09-16T05:18:05 | ---
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-dog-music.png
candidate_labels: 기타치는 고양이, 피아노 치는 강아지
example_title: Guitar, cat and dog
language: ko
license: mit
---
# clip-vit-base-patch32-ko
Korean CLIP model trained by [Making Monolingual Sentence Embeddings Multilingua... | 2,625 | [
[
-0.034637451171875,
-0.050933837890625,
0.0167388916015625,
0.0254669189453125,
-0.034332275390625,
0.0036296844482421875,
-0.0171356201171875,
0.0026950836181640625,
0.0303192138671875,
0.021575927734375,
-0.0305938720703125,
-0.046051025390625,
-0.054656982421... |
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