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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
EleutherAI/pythia-6.9b | 2023-06-08T10:20:26.000Z | [
"transformers",
"pytorch",
"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:us"
] | text-generation | EleutherAI | null | null | EleutherAI/pythia-6.9b | 27 | 938,200 | transformers | 2023-02-14T04:18:48 | ---
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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bert-base-multilingual-uncased | 2023-04-06T13:39:29.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"multilingual",
"af",
"sq",
"ar",
"an",
"hy",
"ast",
"az",
"ba",
"eu",
"bar",
"be",
"bn",
"inc",
"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",
"nl"... | fill-mask | null | null | null | bert-base-multilingual-uncased | 57 | 936,726 | transformers | 2022-03-02T23:29:04 | ---
language:
- multilingual
- af
- sq
- ar
- an
- hy
- ast
- az
- ba
- eu
- bar
- be
- bn
- inc
- bs
- br
- bg
- my
- ca
- ceb
- ce
- zh
- cv
- hr
- cs
- da
- nl
- en
- et
- fi
- fr
- gl
- ka
- de
- el
- gu
- ht
- he
- hi
- hu
- is
- io
- id
- ga
- it
- ja
- jv
- kn
- kk
- ky
- ko
- la
- lv
- lt
- roa
- nds
- lm
- mk... | 8,930 | [
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0.008... |
facebook/opt-1.3b | 2023-09-15T13:09:33.000Z | [
"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-1.3b | 118 | 917,323 | transformers | 2022-05-11T08:26:00 | ---
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... | 8,820 | [
[
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laion/CLIP-ViT-B-32-laion2B-s34B-b79K | 2023-04-18T06:49:43.000Z | [
"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-B-32-laion2B-s34B-b79K | 46 | 907,929 | open_clip | 2022-09-14T22:49:28 | ---
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
pipeline_tag: zero-shot-image-classification
---
# Model Card for CLIP ViT-B/32 - LAION-2B
# Table of Contents
1. [Mo... | 7,458 | [
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-0... |
WinKawaks/vit-small-patch16-224 | 2023-03-18T22:00:21.000Z | [
"transformers",
"pytorch",
"safetensors",
"vit",
"image-classification",
"vision",
"dataset:imagenet",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | WinKawaks | null | null | WinKawaks/vit-small-patch16-224 | 2 | 903,981 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet
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://... | 765 | [
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meta-llama/Llama-2-7b-chat-hf | 2023-10-22T22:37:38.000Z | [
"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-2-7b-chat-hf | 1,658 | 885,924 | transformers | 2023-07-13T16:45:23 | ---
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... | 10,414 | [
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0.0052... |
EleutherAI/pythia-12b | 2023-06-08T11:06:48.000Z | [
"transformers",
"pytorch",
"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:us"
] | text-generation | EleutherAI | null | null | EleutherAI/pythia-12b | 114 | 866,116 | transformers | 2023-02-28T18:48:12 | ---
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... | 13,547 | [
[
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... |
Salesforce/blip-image-captioning-large | 2023-08-01T14:48:40.000Z | [
"transformers",
"pytorch",
"tf",
"blip",
"text2text-generation",
"image-captioning",
"image-to-text",
"arxiv:2201.12086",
"license:bsd-3-clause",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-to-text | Salesforce | null | null | Salesforce/blip-image-captioning-large | 458 | 858,897 | transformers | 2022-12-13T11:27:40 | ---
pipeline_tag: image-to-text
tags:
- image-captioning
languages:
- en
license: bsd-3-clause
---
# BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Model card for image captioning pretrained on COCO dataset - base architecture (with ViT large backbone).
| ![B... | 5,509 | [
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... |
google/bert_uncased_L-2_H-128_A-2 | 2023-09-05T15:25:24.000Z | [
"transformers",
"pytorch",
"jax",
"safetensors",
"bert",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | google | null | null | google/bert_uncased_L-2_H-128_A-2 | 23 | 833,805 | transformers | 2022-03-02T23:29:05 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... | 4,617 | [
[
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-0.001915... |
Intel/dpt-large | 2023-03-06T16:35:04.000Z | [
"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-large | 99 | 825,014 | transformers | 2022-03-02T23:29:05 | ---
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... | 7,491 | [
[
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-0.05224609375,
-0.01... |
j-hartmann/emotion-english-distilroberta-base | 2023-01-02T13:03:10.000Z | [
"transformers",
"pytorch",
"tf",
"roberta",
"text-classification",
"distilroberta",
"sentiment",
"emotion",
"twitter",
"reddit",
"en",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | j-hartmann | null | null | j-hartmann/emotion-english-distilroberta-base | 246 | 822,006 | transformers | 2022-03-02T23:29:05 | ---
language: "en"
tags:
- distilroberta
- sentiment
- emotion
- twitter
- reddit
widget:
- text: "Oh wow. I didn't know that."
- text: "This movie always makes me cry.."
- text: "Oh Happy Day"
---
# Emotion English DistilRoBERTa-base
# Description ℹ
With this model, you can classify emotions in English text data.... | 4,849 | [
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0.02... |
cl-tohoku/bert-base-japanese-whole-word-masking | 2021-09-23T13:45:34.000Z | [
"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-whole-word-masking | 50 | 814,681 | 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, whole word masking enabled)
This is a [BERT](https://github.com/google-research/bert) model pretrained on texts in the Japanese language.
This version of the model processes in... | 2,107 | [
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0.000... |
T-Systems-onsite/cross-en-de-roberta-sentence-transformer | 2023-04-27T19:29:30.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"xlm-roberta",
"feature-extraction",
"sentence_embedding",
"search",
"roberta",
"xlm-r-distilroberta-base-paraphrase-v1",
"paraphrase",
"de",
"en",
"multilingual",
"dataset:stsb_multi_mt",
"arxiv:1908.10084",
"license:mit",
"endpoints... | feature-extraction | T-Systems-onsite | null | null | T-Systems-onsite/cross-en-de-roberta-sentence-transformer | 36 | 808,160 | transformers | 2022-03-02T23:29:05 | ---
language:
- de
- en
- multilingual
license: mit
tags:
- sentence_embedding
- search
- pytorch
- xlm-roberta
- roberta
- xlm-r-distilroberta-base-paraphrase-v1
- paraphrase
datasets:
- stsb_multi_mt
metrics:
- Spearman’s rank correlation
- cosine similarity
---
# Cross English & German RoBERTa for Sentence Embeddin... | 8,047 | [
[
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-0.04345703125,
-0.05328369140625,
0.023208618... |
lengyue233/content-vec-best | 2023-03-31T08:02:09.000Z | [
"transformers",
"pytorch",
"hubert",
"doi:10.57967/hf/0479",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | null | lengyue233 | null | null | lengyue233/content-vec-best | 4 | 789,644 | transformers | 2023-03-25T04:33:59 | ---
license: mit
---
# Content Vec Best
Official Repo: [ContentVec](https://github.com/auspicious3000/contentvec)
This repo brings fairseq ContentVec model to HuggingFace Transformers.
## How to use
To use this model, you need to define
```python
class HubertModelWithFinalProj(HubertModel):
def __init__(self, c... | 974 | [
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microsoft/mdeberta-v3-base | 2023-04-06T05:32:33.000Z | [
"transformers",
"pytorch",
"tf",
"deberta-v2",
"deberta",
"deberta-v3",
"mdeberta",
"fill-mask",
"multilingual",
"en",
"ar",
"bg",
"de",
"el",
"es",
"fr",
"hi",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh",
"arxiv:2006.03654",
"arxiv:2111.09543",
"license:mit",
"end... | fill-mask | microsoft | null | null | microsoft/mdeberta-v3-base | 94 | 782,343 | transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- en
- ar
- bg
- de
- el
- es
- fr
- hi
- ru
- sw
- th
- tr
- ur
- vi
- zh
tags:
- deberta
- deberta-v3
- mdeberta
- fill-mask
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
---
## DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-T... | 3,667 | [
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cambridgeltl/SapBERT-from-PubMedBERT-fulltext | 2023-06-14T19:03:02.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"feature-extraction",
"biomedical",
"lexical semantics",
"bionlp",
"biology",
"science",
"embedding",
"entity linking",
"en",
"arxiv:2010.11784",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us... | feature-extraction | cambridgeltl | null | null | cambridgeltl/SapBERT-from-PubMedBERT-fulltext | 25 | 760,243 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
language:
- en
tags:
- biomedical
- lexical semantics
- bionlp
- biology
- science
- embedding
- entity linking
---
---
datasets:
- UMLS
**[news]** A cross-lingual extension of SapBERT will appear in the main onference of **ACL 2021**! <br>
**[news]** SapBERT will appear in the conference pro... | 4,084 | [
[
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tiiuae/falcon-40b-instruct | 2023-09-29T14:32:27.000Z | [
"transformers",
"pytorch",
"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",
"text-generati... | text-generation | tiiuae | null | null | tiiuae/falcon-40b-instruct | 1,112 | 736,447 | transformers | 2023-05-25T10:14:36 | ---
datasets:
- tiiuae/falcon-refinedweb
language:
- en
inference: false
license: apache-2.0
---
# ✨ Falcon-40B-Instruct
**Falcon-40B-Instruct is a 40B parameters causal decoder-only model built by [TII](https://www.tii.ae) based on [Falcon-40B](https://huggingface.co/tiiuae/falcon-40b) and finetuned on a mixture of ... | 8,787 | [
[
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dslim/bert-large-NER | 2023-05-02T18:47:40.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"token-classification",
"en",
"dataset:conll2003",
"arxiv:1810.04805",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | dslim | null | null | dslim/bert-large-NER | 97 | 736,394 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- conll2003
license: mit
model-index:
- name: dslim/bert-large-NER
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: conll2003
type: conll2003
config: conll2003
split: test
metrics:
- name: Accuracy
... | 5,493 | [
[
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0.024169921875,
0.022613525390625,
-0.03265380859375,
-0.03851318359375,
-0.054931640625,
0.02006530761... |
google/vit-base-patch16-224-in21k | 2023-02-27T15:04:22.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"vit",
"feature-extraction",
"vision",
"dataset:imagenet-21k",
"arxiv:2010.11929",
"arxiv:2006.03677",
"license:apache-2.0",
"has_space",
"region:us"
] | feature-extraction | google | null | null | google/vit-base-patch16-224-in21k | 79 | 731,746 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- vision
datasets:
- imagenet-21k
inference: false
---
# Vision Transformer (base-sized model)
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224. It was introduced in the paper [An Image is Worth 16x16 Words: Transformer... | 5,392 | [
[
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... |
blanchefort/rubert-base-cased-sentiment | 2023-04-06T04:06:36.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"text-classification",
"sentiment",
"ru",
"endpoints_compatible",
"region:us"
] | text-classification | blanchefort | null | null | blanchefort/rubert-base-cased-sentiment | 8 | 721,951 | transformers | 2022-03-02T23:29:05 | ---
language:
- ru
tags:
- sentiment
- text-classification
---
# RuBERT for Sentiment Analysis
Short Russian texts sentiment classification
This is a [DeepPavlov/rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) model trained on aggregated corpus of 351.797 texts.
... | 1,995 | [
[
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0.0034313201904296875,
-0.033599853515625,
-0.059722900390625,
-0.045928955078125... |
intfloat/e5-small-v2 | 2023-08-16T02:50:15.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"bert",
"mteb",
"Sentence Transformers",
"sentence-similarity",
"en",
"arxiv:2212.03533",
"arxiv:2104.08663",
"arxiv:2210.07316",
"license:mit",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | intfloat | null | null | intfloat/e5-small-v2 | 38 | 705,401 | sentence-transformers | 2023-05-19T06:45:35 | ---
tags:
- mteb
- Sentence Transformers
- sentence-similarity
- sentence-transformers
model-index:
- name: e5-small-v2
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
re... | 67,791 | [
[
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0.021514892578125,
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-0.045806884765625,
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0.01... |
facebook/bart-large | 2022-06-03T10:00:20.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"bart",
"feature-extraction",
"en",
"arxiv:1910.13461",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | facebook | null | null | facebook/bart-large | 126 | 702,125 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
language: en
---
# BART (large-sized model)
BART model pre-trained on English language. It was introduced in the paper [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://arxiv.org/abs/1910.13461) by Lewis et al. and firs... | 2,596 | [
[
-0.046844482421875,
-0.0784912109375,
0.017730712890625,
0.0167694091796875,
-0.024658203125,
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-0.02471923828125,
-0.031402587890625,
0.032012939453125,
0.0307464599609375,
-0.033172607421875,
-0.028289794921875,
-0.0380859375,
0.02726... |
timm/resnet18.a1_in1k | 2023-04-05T18:03:00.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"arxiv:2110.00476",
"arxiv:1512.03385",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/resnet18.a1_in1k | 3 | 698,068 | timm | 2023-04-05T18:02:50 | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
---
# Model card for resnet18.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... | 38,401 | [
[
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0.00024... |
microsoft/deberta-v3-large | 2023-03-19T06:24:32.000Z | [
"transformers",
"pytorch",
"tf",
"deberta-v2",
"deberta",
"deberta-v3",
"fill-mask",
"en",
"arxiv:2006.03654",
"arxiv:2111.09543",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | microsoft | null | null | microsoft/deberta-v3-large | 102 | 695,839 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- deberta
- deberta-v3
- fill-mask
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
---
## DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT... | 3,266 | [
[
-0.0277252197265625,
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0.0267181396484375,
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0.022125244140625,
0.00096893310546875,
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-0.037750244140625,
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-0... |
sshleifer/distilbart-cnn-12-6 | 2021-06-14T07:51:12.000Z | [
"transformers",
"pytorch",
"jax",
"rust",
"bart",
"text2text-generation",
"summarization",
"en",
"dataset:cnn_dailymail",
"dataset:xsum",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | summarization | sshleifer | null | null | sshleifer/distilbart-cnn-12-6 | 183 | 693,821 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- summarization
license: apache-2.0
datasets:
- cnn_dailymail
- xsum
thumbnail: https://huggingface.co/front/thumbnails/distilbart_medium.png
---
### Usage
This checkpoint should be loaded into `BartForConditionalGeneration.from_pretrained`. See the [BART docs](https://huggingface.co/transforme... | 1,705 | [
[
-0.044097900390625,
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0.01354217529296875,
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0.01568603515625,
0.028900146484375,
-0.0628662109375,
-0.039398193359375,
-0.0546875,
-0.01165... |
microsoft/beit-base-patch16-224-pt22k-ft22k | 2023-02-27T15:08:16.000Z | [
"transformers",
"pytorch",
"jax",
"beit",
"image-classification",
"vision",
"dataset:imagenet",
"dataset:imagenet-21k",
"arxiv:2106.08254",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | microsoft | null | null | microsoft/beit-base-patch16-224-pt22k-ft22k | 49 | 685,498 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
- imagenet-21k
---
# BEiT (base-sized model, fine-tuned on ImageNet-22k)
BEiT model pre-trained in a self-supervised fashion on ImageNet-22k - also called ImageNet-21k (14 million images, 21,841 classes) at resolution 224x224, and fin... | 5,477 | [
[
-0.050018310546875,
-0.0206146240234375,
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0.0185546875,
0.040679931640625,
-0.026824951171875,
-0.03509521484375,
-0.054840087890625,... |
distilbert-base-cased | 2023-09-11T20:34:52.000Z | [
"transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"distilbert",
"fill-mask",
"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-cased | 21 | 657,352 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# Model Card for DistilBERT base model (cased)
This model is a distilled version of the [BERT base model](https://huggingface.co/bert-base-cased).
It was introduced in [this paper](https://arxiv.org/abs/1910.01108).
The code for the distillat... | 8,811 | [
[
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0.026824951171875,
0.0303192138671875,
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-0.034027099609375,
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0.... |
sentence-transformers/all-MiniLM-L12-v2 | 2022-07-11T21:05:39.000Z | [
"sentence-transformers",
"pytorch",
"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:search_qa",... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/all-MiniLM-L12-v2 | 58 | 641,266 | 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... | 10,623 | [
[
-0.025848388671875,
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0.024261474609375,
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-0.0220947265625,
0.024688720703125,
0.01232147216796875,
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-0.041046142578125,
-0.0489501953125,
0.0084... |
gpt2-xl | 2023-10-23T13:09:53.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"gpt2",
"text-generation",
"en",
"arxiv:1910.09700",
"license:mit",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | null | null | null | gpt2-xl | 205 | 622,833 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: mit
---
# GPT-2 XL
## Table of Contents
- [Model Details](#model-details)
- [How To Get Started With the Model](#how-to-get-started-with-the-model)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Environm... | 11,967 | [
[
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0.033477783203125,
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-... |
Salesforce/codegen25-7b-multi | 2023-08-18T22:58:45.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"code",
"dataset:bigcode/starcoderdata",
"arxiv:2305.02309",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | Salesforce | null | null | Salesforce/codegen25-7b-multi | 105 | 619,621 | transformers | 2023-07-06T20:09:50 | ---
license: apache-2.0
datasets:
- bigcode/starcoderdata
language:
- code
pipeline_tag: text-generation
---
# CodeGen2.5-7B-multi
Title: [**CodeGen2.5: Small, but mighty**](https://blog.salesforceairesearch.com/codegen25)
Authors: [Erik Nijkamp](https://eriknijkamp.com)\*, [Hiroaki Hayashi](https://hiroakih.me)\*, ... | 5,112 | [
[
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0.030242919921875,
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... |
Salesforce/blip-image-captioning-base | 2023-08-01T14:46:56.000Z | [
"transformers",
"pytorch",
"tf",
"blip",
"text2text-generation",
"image-captioning",
"image-to-text",
"arxiv:2201.12086",
"license:bsd-3-clause",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-to-text | Salesforce | null | null | Salesforce/blip-image-captioning-base | 256 | 611,335 | transformers | 2022-12-12T15:19:02 | ---
pipeline_tag: image-to-text
tags:
- image-captioning
languages:
- en
license: bsd-3-clause
---
# BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Model card for image captioning pretrained on COCO dataset - base architecture (with ViT base backbone).
| ![BL... | 5,681 | [
[
-0.01442718505859375,
-0.03448486328125,
-0.003662109375,
0.03656005859375,
-0.04150390625,
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-0.0267486572265625,
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0.01959228515625,
-0.029388427734375,
-0.0310211181640625,
-0.039306640625,
0.00... |
Helsinki-NLP/opus-mt-de-en | 2023-08-16T11:27:46.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"de",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-de-en | 25 | 590,755 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-de-en
* source languages: de
* target languages: en
* OPUS readme: [de-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 1,372 | [
[
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... |
CompVis/stable-diffusion-v1-4 | 2023-08-23T21:15:42.000Z | [
"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 | CompVis | null | null | CompVis/stable-diffusion-v1-4 | 6,039 | 581,299 | diffusers | 2022-08-20T13:26:13 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
widget:
- text: "A high tech solarpunk utopia in the Amazon rainforest"
example_title: Amazon rainforest
- text: "A pikachu fine dining with a view to the Eiffel Tower"
example_title: Pikachu in Paris
- text: "A... | 17,063 | [
[
-0.0295867919921875,
-0.06103515625,
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0.03302001953125,
-0.0204925537109375,
-0.0352783203125,
-0.04534912109375,
-0... |
NousResearch/Llama-2-13b-hf | 2023-08-26T20:17:04.000Z | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"llama-2",
"en",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | NousResearch | null | null | NousResearch/Llama-2-13b-hf | 59 | 574,682 | transformers | 2023-07-18T19:16:15 | ---
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... | 10,099 | [
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facebook/bart-base | 2022-11-16T23:23:10.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bart",
"feature-extraction",
"en",
"arxiv:1910.13461",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | facebook | null | null | facebook/bart-base | 112 | 559,206 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
language: en
---
# BART (base-sized model)
BART model pre-trained on English language. It was introduced in the paper [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://arxiv.org/abs/1910.13461) by Lewis et al. and first... | 2,593 | [
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timm/efficientnet_b0.ra_in1k | 2023-04-27T21:09:50.000Z | [
"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_b0.ra_in1k | 2 | 550,510 | timm | 2022-12-12T23:52:52 | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
---
# Model card for efficientnet_b0.ra_in1k
A EfficientNet image classification model. Trained on ImageNet-1k in `timm` using recipe template described below.
Recipe details:
* RandAugment `RA` recipe. Inspired by... | 4,704 | [
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WinKawaks/vit-tiny-patch16-224 | 2023-03-30T14:56:06.000Z | [
"transformers",
"pytorch",
"safetensors",
"vit",
"image-classification",
"vision",
"dataset:imagenet",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | WinKawaks | null | null | WinKawaks/vit-tiny-patch16-224 | 5 | 548,108 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet
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://... | 765 | [
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bert-base-chinese | 2023-03-21T17:15:55.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"zh",
"arxiv:1810.04805",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | null | null | null | bert-base-chinese | 603 | 547,908 | transformers | 2022-03-02T23:29:04 | ---
language: zh
---
# Bert-base-chinese
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [How to Get Started With the Model](#how-to-get-started-with-the-model)
## Model Deta... | 1,846 | [
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cardiffnlp/twitter-roberta-base-offensive | 2022-11-28T11:36:23.000Z | [
"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-offensive | 11 | 539,443 | transformers | 2022-03-02T23:29:05 | # Twitter-roBERTa-base for Offensive Language Identification
This is a roBERTa-base model trained on ~58M tweets and finetuned for offensive language identification with the TweetEval benchmark.
- Paper: [_TweetEval_ benchmark (Findings of EMNLP 2020)](https://arxiv.org/pdf/2010.12421.pdf).
- Git Repo: [Tweeteval of... | 2,401 | [
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... |
stabilityai/stable-diffusion-2-1-base | 2023-07-05T16:19:20.000Z | [
"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-base | 510 | 539,214 | diffusers | 2022-12-06T17:25:36 | ---
license: openrail++
tags:
- stable-diffusion
- text-to-image
---
# Stable Diffusion v2-1-base Model Card
This model card focuses on the model associated with the Stable Diffusion v2-1-base model.
This `stable-diffusion-2-1-base` model fine-tunes [stable-diffusion-2-base](https://huggingface.co/stabilityai/stable-... | 12,463 | [
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allenai/scibert_scivocab_uncased | 2022-10-03T22:06:12.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"en",
"endpoints_compatible",
"has_space",
"region:us"
] | null | allenai | null | null | allenai/scibert_scivocab_uncased | 79 | 538,004 | transformers | 2022-03-02T23:29:05 | ---
language: en
---
# SciBERT
This is the pretrained model presented in [SciBERT: A Pretrained Language Model for Scientific Text](https://www.aclweb.org/anthology/D19-1371/), which is a BERT model trained on scientific text.
The training corpus was papers taken from [Semantic Scholar](https://www.semanticscholar.or... | 1,135 | [
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0.0141... |
microsoft/deberta-large-mnli | 2021-05-21T20:07:51.000Z | [
"transformers",
"pytorch",
"deberta",
"text-classification",
"deberta-v1",
"deberta-mnli",
"en",
"arxiv:2006.03654",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | microsoft | null | null | microsoft/deberta-large-mnli | 8 | 535,174 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- deberta-v1
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
widget:
- text: "[CLS] I love you. [SEP] I like you. [SEP]"
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) impro... | 3,907 | [
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yiyanghkust/finbert-tone | 2022-10-17T00:35:39.000Z | [
"transformers",
"pytorch",
"tf",
"text-classification",
"financial-sentiment-analysis",
"sentiment-analysis",
"en",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | yiyanghkust | null | null | yiyanghkust/finbert-tone | 106 | 527,473 | transformers | 2022-03-02T23:29:05 | ---
language: "en"
tags:
- financial-sentiment-analysis
- sentiment-analysis
widget:
- text: "growth is strong and we have plenty of liquidity"
---
`FinBERT` is a BERT model pre-trained on financial communication text. The purpose is to enhance financial NLP research and practice. It is trained on the following three ... | 1,943 | [
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prajjwal1/bert-tiny | 2021-10-27T18:29:01.000Z | [
"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-tiny | 69 | 516,915 | 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 ... | 2,560 | [
[
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... |
openai/whisper-large | 2023-09-08T13:08:10.000Z | [
"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-large | 373 | 514,146 | transformers | 2022-09-26T06:56:04 | ---
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
... | 20,556 | [
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TheBloke/CodeLlama-34B-Instruct-GPTQ | 2023-09-27T12:46:12.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-2",
"custom_code",
"code",
"arxiv:2308.12950",
"license:llama2",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/CodeLlama-34B-Instruct-GPTQ | 54 | 512,405 | transformers | 2023-08-25T07:43:45 | ---
language:
- code
license: llama2
tags:
- llama-2
model_name: CodeLlama 34B Instruct
base_model: codellama/CodeLlama-34b-instruct-hf
inference: false
model_creator: Meta
model_type: llama
pipeline_tag: text-generation
prompt_template: '[INST] Write code to solve the following coding problem that obeys
the constrai... | 21,180 | [
[
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-0.0240478515625,
-0.0... |
sentence-transformers/multi-qa-MiniLM-L6-cos-v1 | 2023-11-02T09:30:12.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"dataset:flax-sentence-embeddings/stackexchange_xml",
"dataset:ms_marco",
"dataset:gooaq",
"dataset:yahoo_answers_topics",
"dataset:search_qa",
"dataset:eli5",
"dataset:natural_questions",
... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/multi-qa-MiniLM-L6-cos-v1 | 79 | 507,525 | sentence-transformers | 2022-03-02T23:29:05 | ---
language:
- en
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
datasets:
- flax-sentence-embeddings/stackexchange_xml
- ms_marco
- gooaq
- yahoo_answers_topics
- search_qa
- eli5
- natural_questions
- trivia_qa
- embedding-data/QQP
- embedding-data/PAQ_pair... | 11,535 | [
[
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-0.043304443359375,
-0.04888916015625,
... |
lmsys/fastchat-t5-3b-v1.0 | 2023-06-29T22:39:04.000Z | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"license:apache-2.0",
"autotrain_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text2text-generation | lmsys | null | null | lmsys/fastchat-t5-3b-v1.0 | 294 | 505,155 | transformers | 2023-04-27T23:48:43 | ---
license: apache-2.0
inference: false
---
# FastChat-T5 Model Card
## Model details
**Model type:**
FastChat-T5 is an open-source chatbot trained by fine-tuning Flan-t5-xl (3B parameters) on user-shared conversations collected from ShareGPT.
It is based on an encoder-decoder transformer architecture, and can auto... | 1,984 | [
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Helsinki-NLP/opus-mt-ru-en | 2023-08-16T12:03:22.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"ru",
"en",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-ru-en | 40 | 503,201 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: cc-by-4.0
---
### opus-mt-ru-en
## 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 Sta... | 3,157 | [
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meta-llama/Llama-2-7b-hf | 2023-08-09T15:31:23.000Z | [
"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-2-7b-hf | 772 | 499,862 | transformers | 2023-07-13T16:16:13 | ---
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... | 10,358 | [
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microsoft/table-transformer-detection | 2023-09-06T14:49:09.000Z | [
"transformers",
"pytorch",
"safetensors",
"table-transformer",
"object-detection",
"arxiv:2110.00061",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | object-detection | microsoft | null | null | microsoft/table-transformer-detection | 73 | 497,212 | transformers | 2022-10-14T09:14:13 | ---
license: mit
widget:
- src: https://www.invoicesimple.com/wp-content/uploads/2018/06/Sample-Invoice-printable.png
example_title: Invoice
---
# Table Transformer (fine-tuned for Table Detection)
Table Transformer (DETR) model trained on PubTables1M. It was introduced in the paper [PubTables-1M: Towards Comprehe... | 1,174 | [
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-0.044464111328125,
0.... |
ntu-spml/distilhubert | 2023-07-24T18:30:45.000Z | [
"transformers",
"pytorch",
"safetensors",
"hubert",
"feature-extraction",
"speech",
"en",
"dataset:librispeech_asr",
"arxiv:2110.01900",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | ntu-spml | null | null | ntu-spml/distilhubert | 16 | 497,141 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- librispeech_asr
tags:
- speech
license: apache-2.0
---
# DistilHuBERT
[DistilHuBERT by NTU Speech Processing & Machine Learning Lab](https://github.com/s3prl/s3prl/tree/master/s3prl/upstream/distiller)
The base model pretrained on 16kHz sampled speech audio. When using the model make sur... | 2,053 | [
[
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csebuetnlp/banglabert | 2022-12-23T18:49:36.000Z | [
"transformers",
"pytorch",
"electra",
"pretraining",
"bn",
"endpoints_compatible",
"region:us"
] | null | csebuetnlp | null | null | csebuetnlp/banglabert | 12 | 487,834 | transformers | 2022-03-02T23:29:05 | ---
language:
- bn
licenses:
- cc-by-nc-sa-4.0
---
# BanglaBERT
This repository contains the pretrained discriminator checkpoint of the model **BanglaBERT**. This is an [ELECTRA](https://openreview.net/pdf?id=r1xMH1BtvB) discriminator model pretrained with the Replaced Token Detection (RTD) objective. Finetuned mode... | 8,345 | [
[
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sentence-transformers/all-distilroberta-v1 | 2022-07-11T21:04:19.000Z | [
"sentence-transformers",
"pytorch",
"rust",
"roberta",
"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_q... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/all-distilroberta-v1 | 14 | 486,985 | 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... | 10,291 | [
[
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0.0266265869140625,
0.012939453125,
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-0.04400634765625,
-0.0513916015625,
0.01... |
emilyalsentzer/Bio_ClinicalBERT | 2023-03-31T21:00:42.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"en",
"arxiv:1904.03323",
"arxiv:1901.08746",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | emilyalsentzer | null | null | emilyalsentzer/Bio_ClinicalBERT | 179 | 477,848 | transformers | 2022-03-02T23:29:05 | ---
language: "en"
tags:
- fill-mask
license: mit
---
# ClinicalBERT - Bio + Clinical BERT Model
The [Publicly Available Clinical BERT Embeddings](https://arxiv.org/abs/1904.03323) paper contains four unique clinicalBERT models: initialized with BERT-Base (`cased_L-12_H-768_A-12`) or BioBERT (`BioBERT-Base v1.0 + Pu... | 2,669 | [
[
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Helsinki-NLP/opus-mt-es-en | 2023-08-16T11:32:34.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"es",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-es-en | 34 | 473,921 | transformers | 2022-03-02T23:29:04 | ---
language:
- es
- en
tags:
- translation
license: apache-2.0
---
### spa-eng
* source group: Spanish
* target group: English
* OPUS readme: [spa-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-eng/README.md)
* model: transformer
* source language(s): spa
* target language(s): ... | 2,427 | [
[
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0.0272... |
sentence-transformers/distiluse-base-multilingual-cased-v2 | 2023-11-02T09:41:26.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"distilbert",
"feature-extraction",
"sentence-similarity",
"transformers",
"multilingual",
"ar",
"bg",
"ca",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"fi",
"fr",
"gl",
"gu",
"he",
"hi",
"hr",
"hu",
"hy",
"id",
... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/distiluse-base-multilingual-cased-v2 | 90 | 468,432 | sentence-transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- ar
- bg
- ca
- cs
- da
- de
- el
- en
- es
- et
- fa
- fi
- fr
- gl
- gu
- he
- hi
- hr
- hu
- hy
- id
- it
- ja
- ka
- ko
- ku
- lt
- lv
- mk
- mn
- mr
- ms
- my
- nb
- nl
- pl
- pt
- ro
- ru
- sk
- sl
- sq
- sr
- sv
- th
- tr
- uk
- ur
- vi
language_bcp47:
- fr-ca
- pt-br
- ... | 2,685 | [
[
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0.02825927734375,
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-0.035858154296875,
-0.050262451171875,
0.012... |
timbrooks/instruct-pix2pix | 2023-07-05T16:19:25.000Z | [
"diffusers",
"image-to-image",
"license:mit",
"has_space",
"diffusers:StableDiffusionInstructPix2PixPipeline",
"region:us"
] | image-to-image | timbrooks | null | null | timbrooks/instruct-pix2pix | 715 | 461,743 | diffusers | 2023-01-20T04:27:06 | ---
license: mit
tags:
- image-to-image
---
# InstructPix2Pix: Learning to Follow Image Editing Instructions
GitHub: https://github.com/timothybrooks/instruct-pix2pix
<img src='https://instruct-pix2pix.timothybrooks.com/teaser.jpg'/>
## Example
To use `InstructPix2Pix`, install `diffusers` using `main` for now. Th... | 1,291 | [
[
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0.0235748291015625,
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-0... |
prompthero/openjourney | 2023-05-15T22:39:37.000Z | [
"diffusers",
"safetensors",
"stable-diffusion",
"text-to-image",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | prompthero | null | null | prompthero/openjourney | 2,941 | 456,603 | diffusers | 2022-11-08T09:44:58 | ---
inference: true
language:
- en
tags:
- stable-diffusion
- text-to-image
license: creativeml-openrail-m
---
# Openjourney is an open source Stable Diffusion fine tuned model on Midjourney images, by [PromptHero](https://prompthero.com/poolsuite-diffusion-prompts?utm_source=huggingface&utm_medium=referral)
Inc... | 2,722 | [
[
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0.03692626953125,
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-0.042633056640625,
-0.0291900634765625,
... |
microsoft/layoutlmv2-base-uncased | 2022-09-16T03:40:56.000Z | [
"transformers",
"pytorch",
"layoutlmv2",
"en",
"arxiv:2012.14740",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | microsoft | null | null | microsoft/layoutlmv2-base-uncased | 38 | 449,251 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: cc-by-nc-sa-4.0
---
# LayoutLMv2
**Multimodal (text + layout/format + image) pre-training for document AI**
The documentation of this model in the Transformers library can be found [here](https://huggingface.co/docs/transformers/model_doc/layoutlmv2).
[Microsoft Document AI](https://www.mi... | 1,219 | [
[
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0.00957489013671875,
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... |
cross-encoder/ms-marco-MiniLM-L-12-v2 | 2021-08-05T08:39:01.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"text-classification",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | cross-encoder | null | null | cross-encoder/ms-marco-MiniLM-L-12-v2 | 35 | 446,472 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
---
# Cross-Encoder for MS Marco
This model was trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch).... | 3,233 | [
[
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0.0251617431640625,
0.02557373046875,
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-0.05108642578125,
-0.0579833984375,
0.0030... |
databricks/dolly-v2-3b | 2023-06-30T18:33:24.000Z | [
"transformers",
"pytorch",
"gpt_neox",
"text-generation",
"en",
"dataset:databricks/databricks-dolly-15k",
"license:mit",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | databricks | null | null | databricks/dolly-v2-3b | 239 | 445,213 | transformers | 2023-04-13T05:20:15 | ---
license: mit
language:
- en
library_name: transformers
inference: false
datasets:
- databricks/databricks-dolly-15k
---
# dolly-v2-3b Model Card
## Summary
Databricks' `dolly-v2-3b`, an instruction-following large language model trained on the Databricks machine learning platform
that is licensed for commercial u... | 10,624 | [
[
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0.0006227493286132812,
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0.0032329559326171875,
0.0352783203125,
-0.0369873046875,
-0.037139892578125,
-0.049591064... |
GanjinZero/UMLSBert_ENG | 2023-04-04T07:46:34.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"feature-extraction",
"biomedical",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | feature-extraction | GanjinZero | null | null | GanjinZero/UMLSBert_ENG | 6 | 440,103 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
license: apache-2.0
tags:
- bert
- biomedical
---
CODER: Knowledge infused cross-lingual medical term embedding for term normalization.
English Version. Old name. This model is not UMLSBert!!!
Github Link: https://github.com/GanjinZero/CODER
```
@article{YUAN2022103983,
title = {CODER: Knowled... | 853 | [
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0.00... |
Helsinki-NLP/opus-mt-zh-en | 2023-08-16T12:09:10.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"zh",
"en",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-zh-en | 278 | 438,690 | transformers | 2022-03-02T23:29:04 | ---
language:
- zh
- en
tags:
- translation
license: cc-by-4.0
---
### zho-eng
## 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)
... | 3,172 | [
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... |
google/bert_uncased_L-12_H-768_A-12 | 2021-05-19T17:27:43.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | google | null | null | google/bert_uncased_L-12_H-768_A-12 | 6 | 438,015 | transformers | 2022-03-02T23:29:05 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... | 4,617 | [
[
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-0.030670166015625,
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-... |
SZTAKI-HLT/hubert-base-cc | 2021-05-19T11:29:35.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"hu",
"dataset:common_crawl",
"dataset:wikipedia",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | SZTAKI-HLT | null | null | SZTAKI-HLT/hubert-base-cc | 10 | 423,929 | transformers | 2022-03-02T23:29:04 | ---
language: hu
license: apache-2.0
datasets:
- common_crawl
- wikipedia
---
# huBERT base model (cased)
## Model description
Cased BERT model for Hungarian, trained on the (filtered, deduplicated) Hungarian subset of the Common Crawl and a snapshot of the Hungarian Wikipedia.
## Intended uses & limitations
The m... | 2,011 | [
[
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0.031707763671875,
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-0.047943115234375,
-0.05035400390625,
0.02243... |
google/electra-large-discriminator | 2021-04-30T07:38:14.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"electra",
"pretraining",
"en",
"arxiv:1406.2661",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | google | null | null | google/electra-large-discriminator | 6 | 423,201 | 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... | 2,201 | [
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0.034576416015625,
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-0.016021728515625,
-0.038726806640625,
0.0307617... |
gpt2-medium | 2023-06-30T02:23:32.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"onnx",
"safetensors",
"gpt2",
"text-generation",
"en",
"arxiv:1910.09700",
"license:mit",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | null | null | null | gpt2-medium | 86 | 416,470 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: mit
---
# GPT-2 Medium
## Model Details
**Model Description:** GPT-2 Medium is the **355M parameter** version of GPT-2, a transformer-based language model created and released by OpenAI. The model is a pretrained model on English language using a causal language modeling (CLM) objective.
... | 11,888 | [
[
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0.0347900390625,
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... |
kandinsky-community/kandinsky-2-2-decoder | 2023-10-09T11:32:52.000Z | [
"diffusers",
"text-to-image",
"kandinsky",
"license:apache-2.0",
"has_space",
"diffusers:KandinskyV22Pipeline",
"region:us"
] | text-to-image | kandinsky-community | null | null | kandinsky-community/kandinsky-2-2-decoder | 34 | 410,625 | diffusers | 2023-06-09T11:17:35 | ---
license: apache-2.0
prior:
- kandinsky-community/kandinsky-2-2-prior
tags:
- text-to-image
- kandinsky
inference: false
---
# Kandinsky 2.2
Kandinsky inherits best practices from Dall-E 2 and Latent diffusion while introducing some new ideas.
It uses the CLIP model as a text and image encoder, and diffusion im... | 7,339 | [
[
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-0.027099609375,
-0.00861358642578125,
-0.0028896331787109375,
-0.020294189453125,
-0.003849029541015625,
0.0301971435546875,
-0.02838134765625,
-0.0364990234375,
-0.044586181640625,
... |
flair/ner-english | 2021-03-02T22:11:28.000Z | [
"flair",
"pytorch",
"token-classification",
"sequence-tagger-model",
"en",
"dataset:conll2003",
"has_space",
"region:us"
] | token-classification | flair | null | null | flair/ner-english | 21 | 409,631 | flair | 2022-03-02T23:29:05 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- conll2003
widget:
- text: "George Washington went to Washington"
---
## English NER in Flair (default model)
This is the standard 4-class NER model for English that ships with [Flair](https://github.com/flairNLP/flair/).
F1-Sco... | 3,486 | [
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Riiid/sheep-duck-llama-2 | 2023-10-13T00:59:55.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"Riiid",
"llama-2",
"en",
"arxiv:2306.02707",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | Riiid | null | null | Riiid/sheep-duck-llama-2 | 32 | 407,184 | transformers | 2023-09-06T01:16:43 | ---
thumbnail: >-
https://cdn-uploads.huggingface.co/production/uploads/62fb1ef7e8c9c532aa7d19e4/NswB5XPkkOljeRh1xbMmR.png
pipeline_tag: text-generation
license: llama2
language:
- en
library_name: transformers
tags:
- Riiid
- llama-2
---
# sheep-duck-llama-2
<img src = "https://cdn-uploads.huggingface.co/productio... | 4,147 | [
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-... |
kandinsky-community/kandinsky-2-2-prior | 2023-10-09T11:33:28.000Z | [
"diffusers",
"text-to-image",
"kandinsky",
"license:apache-2.0",
"has_space",
"diffusers:KandinskyV22PriorPipeline",
"region:us"
] | text-to-image | kandinsky-community | null | null | kandinsky-community/kandinsky-2-2-prior | 37 | 405,183 | diffusers | 2023-06-09T13:37:11 | ---
license: apache-2.0
tags:
- text-to-image
- kandinsky
inference: false
---
# Kandinsky 2.2
Kandinsky inherits best practices from Dall-E 2 and Latent diffusion while introducing some new ideas.
It uses the CLIP model as a text and image encoder, and diffusion image prior (mapping) between latent spaces of CLIP ... | 14,440 | [
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microsoft/trocr-large-printed | 2023-01-24T16:57:36.000Z | [
"transformers",
"pytorch",
"vision-encoder-decoder",
"trocr",
"image-to-text",
"arxiv:2109.10282",
"endpoints_compatible",
"has_space",
"region:us"
] | image-to-text | microsoft | null | null | microsoft/trocr-large-printed | 41 | 399,834 | transformers | 2022-03-02T23:29:05 | ---
tags:
- trocr
- image-to-text
widget:
- src: https://layoutlm.blob.core.windows.net/trocr/dataset/SROIE2019Task2Crop/train/X00016469612_1.jpg
example_title: Printed 1
- src: https://layoutlm.blob.core.windows.net/trocr/dataset/SROIE2019Task2Crop/train/X51005255805_7.jpg
example_title: Printed 2
- src: https://l... | 2,979 | [
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-0.0275421142578125,
-0.0274505615234375,
-0.046691894... |
Helsinki-NLP/opus-mt-fr-en | 2023-08-16T11:36:20.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"marian",
"text2text-generation",
"translation",
"fr",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-fr-en | 24 | 399,029 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-fr-en
* source languages: fr
* target languages: en
* OPUS readme: [fr-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fr-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 1,250 | [
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0.0163... |
Hello-SimpleAI/chatgpt-detector-roberta | 2023-01-19T11:03:04.000Z | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"chatgpt",
"en",
"dataset:Hello-SimpleAI/HC3",
"arxiv:2301.07597",
"doi:10.57967/hf/1203",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | Hello-SimpleAI | null | null | Hello-SimpleAI/chatgpt-detector-roberta | 35 | 396,803 | transformers | 2023-01-18T16:38:53 | ---
datasets:
- Hello-SimpleAI/HC3
language:
- en
pipeline_tag: text-classification
tags:
- chatgpt
---
# Model Card for `Hello-SimpleAI/chatgpt-detector-roberta`
This model is trained on **the mix of full-text and splitted sentences** of `answer`s from [Hello-SimpleAI/HC3](https://huggingface.co/datasets/Hello-Simpl... | 1,325 | [
[
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0.025238037109375,
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... |
microsoft/table-transformer-structure-recognition | 2023-09-06T14:50:49.000Z | [
"transformers",
"pytorch",
"safetensors",
"table-transformer",
"object-detection",
"arxiv:2110.00061",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | object-detection | microsoft | null | null | microsoft/table-transformer-structure-recognition | 95 | 396,299 | transformers | 2022-10-14T09:19:57 | ---
license: mit
widget:
- src: https://documentation.tricentis.com/tosca/1420/en/content/tbox/images/table.png
example_title: Table
---
# Table Transformer (fine-tuned for Table Structure Recognition)
Table Transformer (DETR) model trained on PubTables1M. It was introduced in the paper [PubTables-1M: Towards Comp... | 1,203 | [
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0.0361328125,
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-0.0305938720703125,
-0.038726806640625,
0.013389587402... |
facebook/encodec_24khz | 2023-07-25T11:28:04.000Z | [
"transformers",
"pytorch",
"safetensors",
"encodec",
"feature-extraction",
"arxiv:2210.13438",
"has_space",
"region:us"
] | feature-extraction | facebook | null | null | facebook/encodec_24khz | 10 | 381,541 | transformers | 2023-06-12T16:10:36 | ---
inference: false
---
# Model Card for EnCodec
This model card provides details and information about EnCodec, a state-of-the-art real-time audio codec developed by Meta AI.
## Model Details... | 8,280 | [
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0... |
oliverguhr/fullstop-punctuation-multilang-large | 2023-08-05T19:01:38.000Z | [
"transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"xlm-roberta",
"token-classification",
"punctuation prediction",
"punctuation",
"en",
"de",
"fr",
"it",
"multilingual",
"dataset:wmt/europarl",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"r... | token-classification | oliverguhr | null | null | oliverguhr/fullstop-punctuation-multilang-large | 91 | 381,520 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
- de
- fr
- it
- multilingual
tags:
- punctuation prediction
- punctuation
datasets: wmt/europarl
license: mit
widget:
- text: "Ho sentito che ti sei laureata il che mi fa molto piacere"
example_title: "Italian"
- text: "Tous les matins vers quatre heures mon père ouvrait la porte de ma chambre"
... | 5,955 | [
[
-0.01317596435546875,
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-0.040985107421875,
... |
deepset/bert-large-uncased-whole-word-masking-squad2 | 2023-09-26T08:52:18.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"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/bert-large-uncased-whole-word-masking-squad2 | 25 | 377,535 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: cc-by-4.0
datasets:
- squad_v2
model-index:
- name: deepset/bert-large-uncased-whole-word-masking-squad2
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validation
... | 6,626 | [
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0.000... |
allenai/specter2_base | 2023-10-17T21:43:53.000Z | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"en",
"dataset:allenai/scirepeval",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | allenai | null | null | allenai/specter2_base | 25 | 375,149 | transformers | 2023-02-16T21:25:53 | ---
license: apache-2.0
datasets:
- allenai/scirepeval
language:
- en
---
<!-- Provide a quick summary of what the model is/does. -->
# SPECTER2 Base
**Aug 2023 Update:**
1. **The SPECTER2 Base and proximity adapter models have been renamed in Hugging Face based upon usage patterns as follows:**
|Old Name|New Name... | 8,946 | [
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cross-encoder/ms-marco-MiniLM-L-6-v2 | 2021-08-05T08:39:38.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"text-classification",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | cross-encoder | null | null | cross-encoder/ms-marco-MiniLM-L-6-v2 | 28 | 374,384 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
---
# Cross-Encoder for MS Marco
This model was trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch).... | 3,233 | [
[
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0.025177001953125,
0.0255584716796875,
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-0.05108642578125,
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0... |
jonatasgrosman/wav2vec2-large-xlsr-53-arabic | 2022-12-14T01:57:28.000Z | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"ar",
"dataset:common_voice",
"dataset:arabic_speech_corpus",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | jonatasgrosman | null | null | jonatasgrosman/wav2vec2-large-xlsr-53-arabic | 15 | 372,037 | transformers | 2022-03-02T23:29:05 | ---
language: ar
datasets:
- common_voice
- arabic_speech_corpus
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Arabic by Jonatas Grosman
results:
- task:
name: Speech Recognition
type: automatic-... | 7,629 | [
[
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google/vit-base-patch16-384 | 2023-09-11T20:46:00.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"vit",
"image-classification",
"vision",
"dataset:imagenet",
"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-patch16-384 | 18 | 369,206 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet
- imagenet-21k
---
# Vision Transformer (base-sized model)
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000 ... | 5,473 | [
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0.01064300537109375,
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-0.01934814453125,
-0.0567626953125,
... |
google/bert_uncased_L-10_H-768_A-12 | 2021-05-19T17:24:59.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | google | null | null | google/bert_uncased_L-10_H-768_A-12 | 0 | 368,929 | transformers | 2022-03-02T23:29:05 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... | 4,617 | [
[
-0.053558349609375,
-0.03546142578125,
0.0239410400390625,
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-0.031219482421875,
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-0.006107330322265625,
-0.06103515625,
-0.030670166015625,
-0.052093505859375,
-0.... |
finiteautomata/beto-sentiment-analysis | 2023-02-25T14:23:57.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"text-classification",
"sentiment-analysis",
"es",
"arxiv:2106.09462",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | finiteautomata | null | null | finiteautomata/beto-sentiment-analysis | 21 | 351,782 | transformers | 2022-03-02T23:29:05 | ---
language:
- es
tags:
- sentiment-analysis
---
# Sentiment Analysis in Spanish
## beto-sentiment-analysis
**NOTE: this model will be removed soon -- use [pysentimiento/robertuito-sentiment-analysis](https://huggingface.co/pysentimiento/robertuito-sentiment-analysis) instead**
Repository: [https://github.com/... | 1,670 | [
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0.0... |
facebook/esm2_t12_35M_UR50D | 2023-03-21T15:04:57.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"esm",
"fill-mask",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | facebook | null | null | facebook/esm2_t12_35M_UR50D | 4 | 346,220 | transformers | 2022-09-27T14:30:05 | ---
license: mit
widget:
- text: "MQIFVKTLTGKTITLEVEPS<mask>TIENVKAKIQDKEGIPPDQQRLIFAGKQLEDGRTLSDYNIQKESTLHLVLRLRGG"
---
## ESM-2
ESM-2 is a state-of-the-art protein model trained on a masked language modelling objective. It is suitable for fine-tuning on a wide range of tasks that take protein sequences as input. F... | 1,705 | [
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0.0285186767578125,
-0.056793212890625,
-0.03656005859375,
-0.064208984375,
0.0057334899902... |
speechbrain/spkrec-ecapa-voxceleb | 2022-06-26T23:15:06.000Z | [
"speechbrain",
"embeddings",
"Speaker",
"Verification",
"Identification",
"pytorch",
"ECAPA",
"TDNN",
"en",
"dataset:voxceleb",
"arxiv:2106.04624",
"license:apache-2.0",
"has_space",
"region:us"
] | null | speechbrain | null | null | speechbrain/spkrec-ecapa-voxceleb | 95 | 345,936 | speechbrain | 2022-03-02T23:29:05 | ---
language: "en"
thumbnail:
tags:
- speechbrain
- embeddings
- Speaker
- Verification
- Identification
- pytorch
- ECAPA
- TDNN
license: "apache-2.0"
datasets:
- voxceleb
metrics:
- EER
widget:
- example_title: VoxCeleb Speaker id10003
src: https://cdn-media.huggingface.co/speech_samples/VoxCeleb1_00003.wav
- examp... | 5,315 | [
[
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0.001721... |
valhalla/t5-base-e2e-qg | 2021-06-23T14:40:07.000Z | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"question-generation",
"dataset:squad",
"arxiv:1910.10683",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text2text-generation | valhalla | null | null | valhalla/t5-base-e2e-qg | 23 | 345,380 | transformers | 2022-03-02T23:29:05 | ---
datasets:
- squad
tags:
- question-generation
widget:
- text: "Python is a programming language. It is developed by Guido Van Rossum and released in 1991. </s>"
license: mit
---
## T5 for question-generation
This is [t5-base](https://arxiv.org/abs/1910.10683) model trained for end-to-end question generation task. ... | 1,339 | [
[
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0.0438232421875,
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-0.024200439453125,
-0.0167236328125,
0.0236968... |
runwayml/stable-diffusion-inpainting | 2023-07-05T01:09:17.000Z | [
"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",
"has_space",
"diffusers:StableDiffusionInpaintPipeline",
"region:us"
] | text-to-image | runwayml | null | null | runwayml/stable-diffusion-inpainting | 1,342 | 340,858 | diffusers | 2022-10-17T02:48:32 | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
inference: false
library_name: diffusers
extra_gated_prompt: |-
One more step before getting this model.
This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying ri... | 15,791 | [
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meta-llama/Llama-2-13b-chat-hf | 2023-10-12T16:15:39.000Z | [
"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-2-13b-chat-hf | 670 | 339,521 | transformers | 2023-07-13T15:11:20 | ---
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... | 10,397 | [
[
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0.02294921875,
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-0.0504150390625,
0.00530624389... |
jackaduma/SecBERT | 2023-06-26T05:54:48.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"fill-mask",
"exbert",
"security",
"cybersecurity",
"cyber security",
"threat hunting",
"threat intelligence",
"en",
"dataset:APTnotes",
"dataset:Stucco-Data",
"dataset:CASIE",
"license:apache-2.0",
"autotrain_compatible",
"endpoint... | fill-mask | jackaduma | null | null | jackaduma/SecBERT | 18 | 333,638 | transformers | 2022-03-02T23:29:05 | ---
language: en
thumbnail: https://github.com/jackaduma
tags:
- exbert
- security
- cybersecurity
- cyber security
- threat hunting
- threat intelligence
license: apache-2.0
datasets:
- APTnotes
- Stucco-Data
- CASIE
---
# SecBERT
This is the pretrained model presented in [SecBERT: A Pretrained Language Model for C... | 1,934 | [
[
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-0.05322265625,
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mtg-upf/discogs-maest-30s-pw-73e-ts | 2023-11-06T10:29:46.000Z | [
"transformers",
"pytorch",
"audio-spectrogram-transformer",
"audio-classification",
"arxiv:2309.16418",
"arxiv:1910.09700",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us"
] | audio-classification | mtg-upf | null | null | mtg-upf/discogs-maest-30s-pw-73e-ts | 1 | 332,217 | transformers | 2023-09-27T12:50:18 | ---
license: cc-by-nc-sa-4.0
metrics:
- roc_auc
library_name: transformers
pipeline_tag: audio-classification
---
# Model Card for discogs-maest-30s-pw-73e-ts
## Model Details
MAEST is a family of Transformer models based on [PASST](https://github.com/kkoutini/PaSST) and
focused on music analysis applications.
The MA... | 7,573 | [
[
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... |
openai/whisper-medium | 2023-09-08T13:08:09.000Z | [
"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-medium | 128 | 331,016 | transformers | 2022-09-26T06:52:52 | ---
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
... | 19,770 | [
[
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google/owlvit-base-patch16 | 2023-10-23T09:19:45.000Z | [
"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-patch16 | 6 | 325,377 | transformers | 2022-07-05T07:12:33 | ---
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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0.02262... |
sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 | 2023-11-02T09:46:44.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"multilingual",
"ar",
"bg",
"ca",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"fi",
"fr",
"gl",
"gu",
"he",
"hi",
"hr",
"hu",
"hy",
"id",
"it",... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 | 277 | 321,161 | sentence-transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- ar
- bg
- ca
- cs
- da
- de
- el
- en
- es
- et
- fa
- fi
- fr
- gl
- gu
- he
- hi
- hr
- hu
- hy
- id
- it
- ja
- ka
- ko
- ku
- lt
- lv
- mk
- mn
- mr
- ms
- my
- nb
- nl
- pl
- pt
- ro
- ru
- sk
- sl
- sq
- sr
- sv
- th
- tr
- uk
- ur
- vi
language_bcp47:
- fr-ca
- pt-br
- ... | 4,094 | [
[
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... |
SG161222/Realistic_Vision_V5.0_noVAE | 2023-07-25T05:05:03.000Z | [
"diffusers",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | SG161222 | null | null | SG161222/Realistic_Vision_V5.0_noVAE | 26 | 319,809 | diffusers | 2023-07-23T15:41:10 | ---
license: creativeml-openrail-m
---
<b>Please read this!</b><br>
For version 5.0 it is recommended to use with VAE (to improve generation quality and get rid of artifacts): https://huggingface.co/stabilityai/sd-vae-ft-mse-original<br>
<hr/>
<b>The recommended negative prompt:</b>
(deformed iris, deformed pupils, ... | 1,332 | [
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... |
facebook/m2m100_418M | 2023-08-11T11:43:56.000Z | [
"transformers",
"pytorch",
"rust",
"m2m_100",
"text2text-generation",
"multilingual",
"af",
"am",
"ar",
"ast",
"az",
"ba",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"ceb",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"ff",
"fi",
"fr",
"fy",
"ga",
... | text2text-generation | facebook | null | null | facebook/m2m100_418M | 150 | 315,967 | transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- af
- am
- ar
- ast
- az
- ba
- be
- bg
- bn
- br
- bs
- ca
- ceb
- cs
- cy
- da
- de
- el
- en
- es
- et
- fa
- ff
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- ht
- hu
- hy
- id
- ig
- ilo
- is
- it
- ja
- jv
- ka
- kk
- km
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- ko
- lb
- lg
- ln
- lo
- lt
- lv
- mg
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- ... | 4,532 | [
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... |
facebook/opt-125m | 2023-09-15T13:10:03.000Z | [
"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-125m | 86 | 313,778 | transformers | 2022-05-11T08:25:17 | ---
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... | 7,095 | [
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vinai/phobert-base-v2 | 2023-08-05T08:20:06.000Z | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | vinai | null | null | vinai/phobert-base-v2 | 11 | 312,325 | transformers | 2023-04-24T10:53:35 |
#### Table of contents
1. [Introduction](#introduction)
2. [Using PhoBERT with `transformers`](#transformers)
- [Installation](#install2)
- [Pre-trained models](#models2)
- [Example usage](#usage2)
3. [Using PhoBERT with `fairseq`](#fairseq)
4. [Notes](#vncorenlp)
# <a name="introduction"></a> PhoBERT: Pre-trained... | 5,980 | [
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0.019... |
flair/ner-english-fast | 2021-02-26T15:39:34.000Z | [
"flair",
"pytorch",
"token-classification",
"sequence-tagger-model",
"en",
"dataset:conll2003",
"has_space",
"region:us"
] | token-classification | flair | null | null | flair/ner-english-fast | 16 | 311,468 | flair | 2022-03-02T23:29:05 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- conll2003
widget:
- text: "George Washington went to Washington"
---
## English NER in Flair (fast model)
This is the fast 4-class NER model for English that ships with [Flair](https://github.com/flairNLP/flair/).
F1-Score: **9... | 3,493 | [
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