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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
t5-large | 2023-04-06T13:42:27.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"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:1808.09121",
"arxi... | translation | null | null | null | t5-large | 109 | 311,081 | 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 Large
![model image](https://camo.githubusercontent.com/623b4dea0b653f2ad3f36c71ebfe749a677ac0a1/68747470733a2f2f6d69726f2e6d656469756d2e636f6d2f6d61782f343030362f312a44304a... | 8,473 | [
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facebook/dpr-ctx_encoder-single-nq-base | 2022-12-21T15:16:53.000Z | [
"transformers",
"pytorch",
"tf",
"dpr",
"en",
"dataset:nq_open",
"arxiv:2004.04906",
"arxiv:1702.08734",
"arxiv:1910.09700",
"license:cc-by-nc-4.0",
"has_space",
"region:us"
] | null | facebook | null | null | facebook/dpr-ctx_encoder-single-nq-base | 15 | 310,231 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: cc-by-nc-4.0
tags:
- dpr
datasets:
- nq_open
inference: false
---
# `dpr-ctx_encoder-single-nq-base`
## 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-limit... | 8,189 | [
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gpt2-large | 2023-06-30T02:33:40.000Z | [
"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-large | 172 | 309,768 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: mit
---
# GPT-2 Large
## 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)
- [Envir... | 12,346 | [
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google/bert_uncased_L-8_H-768_A-12 | 2021-05-19T17:36:32.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | google | null | null | google/bert_uncased_L-8_H-768_A-12 | 0 | 309,303 | 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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-0.00190... |
sentence-transformers/paraphrase-MiniLM-L6-v2 | 2022-06-15T18:39:43.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:1908.10084",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | sentence-transformers | null | null | sentence-transformers/paraphrase-MiniLM-L6-v2 | 55 | 309,178 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/paraphrase-MiniLM-L6-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dens... | 3,693 | [
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0.01005554199... |
stabilityai/stable-diffusion-2 | 2023-07-05T16:19:01.000Z | [
"diffusers",
"stable-diffusion",
"text-to-image",
"arxiv:2202.00512",
"arxiv:2112.10752",
"arxiv:1910.09700",
"license:openrail++",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | stabilityai | null | null | stabilityai/stable-diffusion-2 | 1,661 | 308,733 | diffusers | 2022-11-23T11:54:34 | ---
license: openrail++
tags:
- stable-diffusion
- text-to-image
---
# Stable Diffusion v2 Model Card
This model card focuses on the model associated with the Stable Diffusion v2 model, available [here](https://github.com/Stability-AI/stablediffusion).
This `stable-diffusion-2` model is resumed from [stable-diffusion... | 12,303 | [
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papluca/xlm-roberta-base-language-detection | 2022-11-05T18:20:13.000Z | [
"transformers",
"pytorch",
"tf",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"multilingual",
"ar",
"bg",
"de",
"el",
"en",
"es",
"fr",
"hi",
"it",
"ja",
"nl",
"pl",
"pt",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh",
"arxiv:1911.02116",
"licens... | text-classification | papluca | null | null | papluca/xlm-roberta-base-language-detection | 144 | 304,235 | transformers | 2022-03-02T23:29:05 | ---
language:
- multilingual
- ar
- bg
- de
- el
- en
- es
- fr
- hi
- it
- ja
- nl
- pl
- pt
- ru
- sw
- th
- tr
- ur
- vi
- zh
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-language-detection
results: []
---
# xlm-roberta-base-language-detection
This mo... | 5,932 | [
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mistralai/Mistral-7B-v0.1 | 2023-10-12T17:52:53.000Z | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"pretrained",
"en",
"arxiv:2310.06825",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | mistralai | null | null | mistralai/Mistral-7B-v0.1 | 1,701 | 302,166 | transformers | 2023-09-20T13:03:50 | ---
license: apache-2.0
pipeline_tag: text-generation
language:
- en
tags:
- pretrained
inference:
parameters:
temperature: 0.7
---
# Model Card for Mistral-7B-v0.1
The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters.
Mistral-7B-v0.1 outperforms Llam... | 1,390 | [
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facebook/wav2vec2-large-robust-ft-swbd-300h | 2022-04-05T16:42:51.000Z | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"speech",
"audio",
"en",
"dataset:libri_light",
"dataset:common_voice",
"dataset:switchboard",
"dataset:fisher",
"arxiv:2104.01027",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | facebook | null | null | facebook/wav2vec2-large-robust-ft-swbd-300h | 14 | 299,457 | transformers | 2022-03-02T23:29:05 | ---
language: en
datasets:
- libri_light
- common_voice
- switchboard
- fisher
tags:
- speech
- audio
- automatic-speech-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.huggingfac... | 3,747 | [
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philschmid/bart-large-cnn-samsum | 2022-12-23T19:48:57.000Z | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"sagemaker",
"summarization",
"en",
"dataset:samsum",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | summarization | philschmid | null | null | philschmid/bart-large-cnn-samsum | 206 | 297,961 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: mit
tags:
- sagemaker
- bart
- summarization
datasets:
- samsum
widget:
- text: "Jeff: Can I train a \U0001F917 Transformers model on Amazon SageMaker? \n\
Philipp: Sure you can use the new Hugging Face Deep Learning Container. \nJeff:\
\ ok.\nJeff: and how can I get started? \nJeff: w... | 5,698 | [
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facebook/detr-resnet-50 | 2023-10-17T17:18:59.000Z | [
"transformers",
"pytorch",
"detr",
"object-detection",
"vision",
"dataset:coco",
"arxiv:2005.12872",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | object-detection | facebook | null | null | facebook/detr-resnet-50 | 325 | 297,878 | transformers | 2022-03-02T23:29:05 | ---
license: apache-2.0
tags:
- object-detection
- vision
datasets:
- coco
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
- s... | 5,891 | [
[
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Jean-Baptiste/camembert-ner | 2023-06-01T01:32:51.000Z | [
"transformers",
"pytorch",
"onnx",
"safetensors",
"camembert",
"token-classification",
"fr",
"dataset:Jean-Baptiste/wikiner_fr",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | Jean-Baptiste | null | null | Jean-Baptiste/camembert-ner | 81 | 294,793 | transformers | 2022-03-02T23:29:04 | ---
language: fr
datasets:
- Jean-Baptiste/wikiner_fr
widget:
- text: "Je m'appelle jean-baptiste et je vis à montréal"
- text: "george washington est allé à washington"
license: mit
---
# camembert-ner: model fine-tuned from camemBERT for NER task.
## Introduction
[camembert-ner] is a NER model that was fine-tuned ... | 3,111 | [
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google/flan-t5-xl | 2023-07-17T12:48:53.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"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",
"dataset:aqua_rat",
... | text2text-generation | google | null | null | google/flan-t5-xl | 367 | 294,765 | transformers | 2022-10-21T15:43:52 | ---
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... | 10,745 | [
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microsoft/trocr-base-handwritten | 2023-01-26T12:56:57.000Z | [
"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-base-handwritten | 104 | 293,715 | transformers | 2022-03-02T23:29:05 | ---
tags:
- trocr
- image-to-text
widget:
- src: https://fki.tic.heia-fr.ch/static/img/a01-122-02.jpg
example_title: Note 1
- src: https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSoolxi9yWGAT5SLZShv8vVd0bz47UWRzQC19fDTeE8GmGv_Rn-PCF1pP1rrUx8kOjA4gg&usqp=CAU
example_title: Note 2
- src: https://encrypted-tbn0.... | 2,972 | [
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madhurjindal/autonlp-Gibberish-Detector-492513457 | 2023-10-02T08:32:14.000Z | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"autonlp",
"en",
"dataset:madhurjindal/autonlp-data-Gibberish-Detector",
"co2_eq_emissions",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | madhurjindal | null | null | madhurjindal/autonlp-Gibberish-Detector-492513457 | 25 | 289,872 | transformers | 2022-03-02T23:29:05 | ---
tags: [autonlp]
language: en
widget:
- text: "I love Machine Learning!"
datasets:
- madhurjindal/autonlp-data-Gibberish-Detector
co2_eq_emissions: 5.527544460835904
---
# Problem Description
The ability to process and understand user input is crucial for various applications, such as chatbots or downstream tasks. ... | 4,935 | [
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cross-encoder/nli-deberta-base | 2021-08-05T08:40:53.000Z | [
"transformers",
"pytorch",
"deberta",
"text-classification",
"deberta-base-base",
"zero-shot-classification",
"en",
"dataset:multi_nli",
"dataset:snli",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | zero-shot-classification | cross-encoder | null | null | cross-encoder/nli-deberta-base | 13 | 289,216 | transformers | 2022-03-02T23:29:05 | ---
language: en
pipeline_tag: zero-shot-classification
tags:
- deberta-base-base
datasets:
- multi_nli
- snli
metrics:
- accuracy
license: apache-2.0
---
# Cross-Encoder for Natural Language Inference
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples... | 2,564 | [
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stabilityai/stable-diffusion-2-base | 2023-07-05T16:19:03.000Z | [
"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-base | 299 | 287,950 | diffusers | 2022-11-23T17:41:31 | ---
license: openrail++
tags:
- stable-diffusion
- text-to-image
---
# Stable Diffusion v2-base Model Card
This model card focuses on the model associated with the Stable Diffusion v2-base model, available [here](https://github.com/Stability-AI/stablediffusion).
The model is trained from scratch 550k steps at resolut... | 12,566 | [
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0.032440185546875,
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... |
dccuchile/bert-base-spanish-wwm-cased | 2022-05-31T15:01:30.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"masked-lm",
"es",
"arxiv:1904.09077",
"arxiv:1906.01502",
"arxiv:1812.10464",
"arxiv:1901.07291",
"arxiv:1904.02099",
"arxiv:1906.01569",
"arxiv:1908.11828",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
... | fill-mask | dccuchile | null | null | dccuchile/bert-base-spanish-wwm-cased | 37 | 284,677 | transformers | 2022-03-02T23:29:05 | ---
language:
- es
tags:
- masked-lm
---
# BETO: Spanish BERT
BETO is a [BERT model](https://github.com/google-research/bert) trained on a [big Spanish corpus](https://github.com/josecannete/spanish-corpora). BETO is of size similar to a BERT-Base and was trained with the Whole Word Masking technique. Below yo... | 5,906 | [
[
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... |
google/electra-small-discriminator | 2021-04-29T15:24:16.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"electra",
"pretraining",
"en",
"arxiv:1406.2661",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | google | null | null | google/electra-small-discriminator | 19 | 284,178 | 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... | 2,211 | [
[
-0.035308837890625,
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-0.0192413330078125,
-0.0134124755859375,
0.0301055908203125,
0.033050537109375,
-0.0261077880859375,
-0.01493072509765625,
-0.03802490234375,... |
hellomyoh/llama2-2b-s117755-v2 | 2023-09-26T05:11:12.000Z | [
"peft",
"region:us"
] | null | hellomyoh | null | null | hellomyoh/llama2-2b-s117755-v2 | 0 | 282,983 | peft | 2023-09-26T05:10:43 | ---
library_name: peft
---
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weig... | 863 | [
[
-0.049713134765625,
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0.03436279296875,
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0.026763916015625,
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-0.01548004150390625,
-0.037811279296875,
... |
prithivida/parrot_adequacy_model | 2022-05-27T02:47:22.000Z | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | prithivida | null | null | prithivida/parrot_adequacy_model | 6 | 275,343 | transformers | 2022-05-27T02:04:37 | ---
license: apache-2.0
---
Parrot
THIS IS AN ANCILLARY MODEL FOR PARROT PARAPHRASER
1. What is Parrot?
Parrot is a paraphrase-based utterance augmentation framework purpose-built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model. Please refer to the GitHub page or The mo... | 364 | [
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... |
SG161222/Realistic_Vision_V5.1_noVAE | 2023-07-31T06:32:01.000Z | [
"diffusers",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | SG161222 | null | null | SG161222/Realistic_Vision_V5.1_noVAE | 98 | 274,981 | diffusers | 2023-07-31T05:20:51 | ---
license: creativeml-openrail-m
---
<b>Please read this!</b><br>
For version 5.1 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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0.0083084... |
THUDM/chatglm2-6b | 2023-10-09T08:19:27.000Z | [
"transformers",
"pytorch",
"chatglm",
"glm",
"thudm",
"custom_code",
"zh",
"en",
"arxiv:2103.10360",
"arxiv:2210.02414",
"arxiv:1911.02150",
"endpoints_compatible",
"has_space",
"region:us"
] | null | THUDM | null | null | THUDM/chatglm2-6b | 1,882 | 274,059 | transformers | 2023-06-24T16:26:27 | ---
language:
- zh
- en
tags:
- glm
- chatglm
- thudm
---
# ChatGLM2-6B
<p align="center">
💻 <a href="https://github.com/THUDM/ChatGLM2-6B" target="_blank">Github Repo</a> • 🐦 <a href="https://twitter.com/thukeg" target="_blank">Twitter</a> • 📃 <a href="https://arxiv.org/abs/2103.10360" target="_blank">[GLM@ACL 22... | 6,205 | [
[
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0.01255035400390625,
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-0.... |
michellejieli/emotion_text_classifier | 2023-05-03T00:39:47.000Z | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"distilroberta",
"sentiment",
"emotion",
"twitter",
"reddit",
"en",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | michellejieli | null | null | michellejieli/emotion_text_classifier | 24 | 272,386 | transformers | 2022-10-22T22:44:07 | ---
language: "en"
tags:
- distilroberta
- sentiment
- emotion
- twitter
- reddit
widget:
- text: "Oh my God, he's lost it. He's totally lost it."
- text: "What?"
- text: "Wow, congratulations! So excited for you!"
---
# Fine-tuned DistilRoBERTa-base for Emotion Classification 🤬🤢😀😐😭😲
# Model Description
Dis... | 2,333 | [
[
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0.031280517578125,
-0.025421142578125,
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0.0276641845703125,
0.0020904541015625,
-0.05120849609375,
-0.04583740234375,
-0.0643310546875,
... |
openai/whisper-large-v2 | 2023-09-08T12:54:49.000Z | [
"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-v2 | 1,383 | 270,529 | transformers | 2022-12-05T18:42:20 | ---
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
... | 18,955 | [
[
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0.0155181884765625,
0.034423828125,
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-0.043792724609375,
-0.05792236328125,
... |
facebook/blenderbot-400M-distill | 2023-03-30T16:12:30.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"blenderbot",
"text2text-generation",
"convAI",
"conversational",
"facebook",
"en",
"dataset:blended_skill_talk",
"arxiv:2004.13637",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | conversational | facebook | null | null | facebook/blenderbot-400M-distill | 283 | 268,295 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
thumbnail:
tags:
- convAI
- conversational
- facebook
license: apache-2.0
datasets:
- blended_skill_talk
metrics:
- perplexity
---
## Model description
+ Paper: [Recipes for building an open-domain chatbot]( https://arxiv.org/abs/2004.13637)
+ [Original PARLAI Code](https://parl.ai/projects/recipe... | 1,451 | [
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0.0501708984375,
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-0.0194244384765625,
-0.057098388671875,
... |
indolem/indobert-base-uncased | 2023-08-09T13:07:37.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"fill-mask",
"indobert",
"indolem",
"id",
"arxiv:2011.00677",
"license:mit",
"autotrain_compatible",
"has_space",
"region:us"
] | fill-mask | indolem | null | null | indolem/indobert-base-uncased | 23 | 266,655 | transformers | 2022-03-02T23:29:05 | ---
language: id
tags:
- indobert
- indolem
license: mit
inference: False
---
## About
[IndoBERT](https://arxiv.org/pdf/2011.00677.pdf) is the Indonesian version of BERT model. We train the model using over 220M words, aggregated from three main sources:
* Indonesian Wikipedia (74M words)
* news articles from Kompas... | 2,373 | [
[
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0.01076507568359375,
0.0194244384765625,
-0.0140228271484375,
-0.0294036865234375,
-0.049652099609375... |
mrm8488/bert-spanish-cased-finetuned-ner | 2021-05-20T00:35:25.000Z | [
"transformers",
"pytorch",
"jax",
"bert",
"token-classification",
"es",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | mrm8488 | null | null | mrm8488/bert-spanish-cased-finetuned-ner | 18 | 266,332 | transformers | 2022-03-02T23:29:05 | ---
language: es
thumbnail: https://i.imgur.com/jgBdimh.png
---
# Spanish BERT (BETO) + NER
This model is a fine-tuned on [NER-C](https://www.kaggle.com/nltkdata/conll-corpora) version of the Spanish BERT cased [(BETO)](https://github.com/dccuchile/beto) for **NER** downstream task.
## Details of the downstream task... | 2,716 | [
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0.0176... |
bert-large-uncased-whole-word-masking | 2023-04-06T13:39:50.000Z | [
"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-whole-word-masking | 10 | 264,753 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT large model (uncased) whole word masking
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]... | 9,763 | [
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-0.06246948242187... |
jbetker/wav2vec2-large-robust-ft-libritts-voxpopuli | 2022-02-25T19:07:57.000Z | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"endpoints_compatible",
"has_space",
"region:us"
] | automatic-speech-recognition | jbetker | null | null | jbetker/wav2vec2-large-robust-ft-libritts-voxpopuli | 7 | 264,486 | transformers | 2022-03-02T23:29:05 | This checkpoint is a wav2vec2-large model that is useful for generating transcriptions with punctuation. It is intended for use in building transcriptions for TTS models, where punctuation is very important for prosody.
This model was created by fine-tuning the `facebook/wav2vec2-large-robust-ft-libri-960h` checkpoint... | 1,085 | [
[
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... |
deepset/bert-base-cased-squad2 | 2023-05-05T07:00:52.000Z | [
"transformers",
"pytorch",
"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-base-cased-squad2 | 17 | 263,105 | transformers | 2022-03-02T23:29:05 | ---
language: en
license: cc-by-4.0
datasets:
- squad_v2
model-index:
- name: deepset/bert-base-cased-squad2
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validation
metrics:
- type: e... | 1,045 | [
[
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0.000019311904907226562,
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... |
naver/splade-cocondenser-ensembledistil | 2022-05-11T08:05:37.000Z | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"splade",
"query-expansion",
"document-expansion",
"bag-of-words",
"passage-retrieval",
"knowledge-distillation",
"en",
"dataset:ms_marco",
"arxiv:2205.04733",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"... | fill-mask | naver | null | null | naver/splade-cocondenser-ensembledistil | 17 | 260,595 | transformers | 2022-05-09T13:18:41 | ---
license: cc-by-nc-sa-4.0
language: "en"
tags:
- splade
- query-expansion
- document-expansion
- bag-of-words
- passage-retrieval
- knowledge-distillation
datasets:
- ms_marco
---
## SPLADE CoCondenser EnsembleDistil
SPLADE model for passage retrieval. For additional details, please visit:
* paper: https://arxiv.o... | 1,203 | [
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0.02166748046875,
0.0164031982421875,
-0.02130126953125,
-0.040863037109375,
-0.053985595703125,
0.015... |
damo-vilab/text-to-video-ms-1.7b | 2023-05-15T22:44:20.000Z | [
"diffusers",
"text-to-video",
"license:cc-by-nc-4.0",
"has_space",
"diffusers:TextToVideoSDPipeline",
"region:us"
] | text-to-video | damo-vilab | null | null | damo-vilab/text-to-video-ms-1.7b | 338 | 258,876 | diffusers | 2023-03-22T13:23:33 | ---
license: cc-by-nc-4.0
tags:
- text-to-video
duplicated_from: diffusers/text-to-video-ms-1.7b
---
# Text-to-video-synthesis Model in Open Domain
This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only... | 6,580 | [
[
-0.039520263671875,
-0.06671142578125,
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0.0030517578125,
0.0313720703125,
-0.0494384765625,
-0.036712646484375,
-0.06292724609375,
-... |
hfl/chinese-bert-wwm-ext | 2021-05-19T19:06:39.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"arxiv:1906.08101",
"arxiv:2004.13922",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | hfl | null | null | hfl/chinese-bert-wwm-ext | 122 | 258,307 | transformers | 2022-03-02T23:29:05 | ---
language:
- zh
license: "apache-2.0"
---
## Chinese BERT with Whole Word Masking
For further accelerating Chinese natural language processing, we provide **Chinese pre-trained BERT with Whole Word Masking**.
**[Pre-Training with Whole Word Masking for Chinese BERT](https://arxiv.org/abs/1906.08101)**
Yiming Cu... | 1,993 | [
[
-0.0305633544921875,
-0.054412841796875,
0.0236053466796875,
0.042236328125,
-0.0304107666015625,
-0.0091400146484375,
-0.042999267578125,
-0.053985595703125,
0.0261383056640625,
0.034332275390625,
-0.03448486328125,
-0.034637451171875,
-0.04266357421875,
-0... |
prithivida/parrot_paraphraser_on_T5 | 2021-05-18T07:53:27.000Z | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text2text-generation | prithivida | null | null | prithivida/parrot_paraphraser_on_T5 | 119 | 256,559 | transformers | 2022-03-02T23:29:05 | # Parrot
## 1. What is Parrot?
Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model. For more details on the library and usage please refer to the [github page](https://github.com/PrithivirajDamodar... | 6,361 | [
[
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0.0126495361328125,
0.03863525390625,
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-0.00905609130859375,
-0.0230712890625,
0.026168823242187... |
laion/CLIP-ViT-bigG-14-laion2B-39B-b160k | 2023-04-18T18:35:30.000Z | [
"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-bigG-14-laion2B-39B-b160k | 130 | 256,043 | open_clip | 2023-01-23T07:12:35 | ---
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-bigG/14 - LAION-2B
#... | 8,652 | [
[
-0.0220489501953125,
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0.034393310546875,
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-0.0435791015625,
-0.048583984375,
-0... |
PlanTL-GOB-ES/roberta-base-bne | 2023-01-31T13:59:59.000Z | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"national library of spain",
"spanish",
"bne",
"roberta-base-bne",
"es",
"dataset:bne",
"arxiv:1907.11692",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | PlanTL-GOB-ES | null | null | PlanTL-GOB-ES/roberta-base-bne | 20 | 255,041 | transformers | 2022-03-02T23:29:04 | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
- "roberta-base-bne"
datasets:
- "bne"
metrics:
- "ppl"
widget:
- text: "Por la ventanilla del coche vi la Giralda y pensé que bonita que es la ciudad de <mask>."
- text: "Más vale <mask> que lamentar."
- text: ... | 11,565 | [
[
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-0.06622314453125,
-0.062255859375,
0.01... |
NousResearch/Llama-2-7b-chat-hf | 2023-07-18T20:57:56.000Z | [
"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-2-7b-chat-hf | 46 | 253,823 | transformers | 2023-07-18T19:45:53 | ---
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... | 10,136 | [
[
-0.0165863037109375,
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0.023590087890625,
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-0.043182373046875,
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0... |
intfloat/e5-large-v2 | 2023-08-07T05:01:43.000Z | [
"sentence-transformers",
"pytorch",
"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-large-v2 | 142 | 250,017 | sentence-transformers | 2023-05-19T07:23:33 | ---
tags:
- mteb
- Sentence Transformers
- sentence-similarity
- sentence-transformers
model-index:
- name: e5-large-v2
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
re... | 67,842 | [
[
-0.00958251953125,
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0.019561767578125,
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... |
flair/ner-english-ontonotes-large | 2021-05-08T15:35:21.000Z | [
"flair",
"pytorch",
"token-classification",
"sequence-tagger-model",
"en",
"dataset:ontonotes",
"arxiv:2011.06993",
"has_space",
"region:us"
] | token-classification | flair | null | null | flair/ner-english-ontonotes-large | 69 | 249,800 | flair | 2022-03-02T23:29:05 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- ontonotes
widget:
- text: "On September 1st George won 1 dollar while watching Game of Thrones."
---
## English NER in Flair (Ontonotes large model)
This is the large 18-class NER model for English that ships with [Flair](https:... | 4,828 | [
[
-0.025146484375,
-0.0379638671875,
0.01103973388671875,
0.00644683837890625,
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-0.01529693603515625,
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0.0426025390625,
0.032257080078125,
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-0.0411376953125,
-0.042388916015625,
0.0... |
microsoft/deberta-v3-base | 2022-09-22T12:34:19.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"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-base | 124 | 249,697 | 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... | 3,472 | [
[
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BAAI/llm-embedder | 2023-11-03T06:29:15.000Z | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"arxiv:2310.07554",
"arxiv:2309.07597",
"license:mit",
"endpoints_compatible",
"region:us"
] | feature-extraction | BAAI | null | null | BAAI/llm-embedder | 43 | 247,724 | transformers | 2023-10-09T09:46:10 | ---
license: mit
---
<h1 align="center">FlagEmbedding</h1>
<h4 align="center">
<p>
<a href=#model-list>Model List</a> |
<a href=#frequently-asked-questions>FAQ</a> |
<a href=#usage>Usage</a> |
<a href="#evaluation">Evaluation</a> |
<a href="#train">Train</a> |
<... | 28,287 | [
[
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rizvandwiki/gender-classification-2 | 2023-05-18T11:17:43.000Z | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"huggingpics",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | rizvandwiki | null | null | rizvandwiki/gender-classification-2 | 15 | 245,474 | transformers | 2022-12-12T03:13:20 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: gender-classification-2
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9910714030265808
---
# gender-cla... | 743 | [
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... |
mistralai/Mistral-7B-Instruct-v0.1 | 2023-10-11T12:31:14.000Z | [
"transformers",
"pytorch",
"mistral",
"text-generation",
"finetuned",
"arxiv:2310.06825",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | mistralai | null | null | mistralai/Mistral-7B-Instruct-v0.1 | 958 | 243,608 | transformers | 2023-09-27T14:31:52 | ---
license: apache-2.0
pipeline_tag: text-generation
tags:
- finetuned
inference:
parameters:
temperature: 0.7
---
# Model Card for Mistral-7B-Instruct-v0.1
The Mistral-7B-Instruct-v0.1 Large Language Model (LLM) is a instruct fine-tuned version of the [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral... | 3,848 | [
[
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0.02935791015625,
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... |
thenlper/gte-base | 2023-10-12T02:06:40.000Z | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"bert",
"mteb",
"sentence-similarity",
"Sentence Transformers",
"en",
"arxiv:2308.03281",
"license:mit",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | thenlper | null | null | thenlper/gte-base | 44 | 240,050 | sentence-transformers | 2023-07-27T03:21:20 | ---
tags:
- mteb
- sentence-similarity
- sentence-transformers
- Sentence Transformers
model-index:
- name: gte-base
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revi... | 68,118 | [
[
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stabilityai/stable-diffusion-x4-upscaler | 2023-07-05T16:19:13.000Z | [
"diffusers",
"stable-diffusion",
"arxiv:2112.10752",
"arxiv:2202.00512",
"arxiv:1910.09700",
"license:openrail++",
"has_space",
"diffusers:StableDiffusionUpscalePipeline",
"region:us"
] | null | stabilityai | null | null | stabilityai/stable-diffusion-x4-upscaler | 502 | 233,214 | diffusers | 2022-11-23T17:42:04 | ---
license: openrail++
tags:
- stable-diffusion
inference: false
---
# Stable Diffusion x4 upscaler model card
This model card focuses on the model associated with the Stable Diffusion Upscaler, available [here](https://github.com/Stability-AI/stablediffusion).
This model is trained for 1.25M steps on a 10M subset of... | 12,601 | [
[
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... |
google/flan-t5-xxl | 2023-07-27T11:42:14.000Z | [
"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-xxl | 967 | 231,423 | transformers | 2022-10-21T15:54:59 | ---
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... | 10,304 | [
[
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0... |
monster-labs/control_v1p_sd15_qrcode_monster | 2023-07-21T11:35:31.000Z | [
"diffusers",
"stable-diffusion",
"controlnet",
"qrcode",
"en",
"license:openrail++",
"has_space",
"diffusers:ControlNetModel",
"region:us"
] | null | monster-labs | null | null | monster-labs/control_v1p_sd15_qrcode_monster | 1,051 | 230,519 | diffusers | 2023-06-24T15:07:20 | ---
tags:
- stable-diffusion
- controlnet
- qrcode
license: openrail++
language:
- en
---
# Controlnet QR Code Monster v2 For SD-1.5
## Model Description
This model is made to generate creative QR codes that still scan.
Keep... | 2,721 | [
[
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hustvl/yolos-tiny | 2023-06-05T11:57:44.000Z | [
"transformers",
"pytorch",
"safetensors",
"yolos",
"object-detection",
"vision",
"dataset:coco",
"arxiv:2106.00666",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | object-detection | hustvl | null | null | hustvl/yolos-tiny | 146 | 230,156 | transformers | 2022-04-26T09:28:47 | ---
license: apache-2.0
tags:
- object-detection
- vision
datasets:
- coco
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
- s... | 4,618 | [
[
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0.0343017578125,
-0.03692626953125,
-0.032867431640625,
-0.0419921875,
0... |
flair/ner-english-ontonotes | 2023-04-07T09:23:02.000Z | [
"flair",
"pytorch",
"token-classification",
"sequence-tagger-model",
"en",
"dataset:ontonotes",
"region:us"
] | token-classification | flair | null | null | flair/ner-english-ontonotes | 15 | 228,076 | flair | 2022-03-02T23:29:05 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- ontonotes
widget:
- text: "On September 1st George Washington won 1 dollar."
---
## English NER in Flair (Ontonotes default model)
This is the 18-class NER model for English that ships with [Flair](https://github.com/flairNLP/fl... | 4,414 | [
[
-0.0222625732421875,
-0.042022705078125,
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0.050506591796875,
0.0244598388671875,
-0.0289459228515625,
-0.04071044921875,
-0.03814697265625,
... |
Babelscape/rebel-large | 2023-06-20T10:17:00.000Z | [
"transformers",
"pytorch",
"safetensors",
"bart",
"text2text-generation",
"seq2seq",
"relation-extraction",
"en",
"dataset:Babelscape/rebel-dataset",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | text2text-generation | Babelscape | null | null | Babelscape/rebel-large | 140 | 226,519 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
widget:
- text: "Punta Cana is a resort town in the municipality of Higuey, in La Altagracia Province, the eastern most province of the Dominican Republic"
tags:
- seq2seq
- relation-extraction
datasets:
- Babelscape/rebel-dataset
model-index:
- name: REBEL
results:
- task:
name: Relation E... | 9,210 | [
[
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microsoft/wavlm-large | 2022-02-02T21:21:50.000Z | [
"transformers",
"pytorch",
"wavlm",
"feature-extraction",
"speech",
"en",
"arxiv:1912.07875",
"arxiv:2106.06909",
"arxiv:2101.00390",
"arxiv:2110.13900",
"has_space",
"region:us"
] | feature-extraction | microsoft | null | null | microsoft/wavlm-large | 37 | 226,095 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
tags:
- speech
inference: false
---
# WavLM-Large
[Microsoft's WavLM](https://github.com/microsoft/unilm/tree/master/wavlm)
The large model pretrained on 16kHz sampled speech audio. When using the model, make sure that your speech input is also sampled at 16kHz.
**Note**: This model does not hav... | 3,891 | [
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TheBloke/Llama-2-7B-32K-Instruct-GPTQ | 2023-09-27T12:45:53.000Z | [
"transformers",
"safetensors",
"llama",
"text-generation",
"custom_code",
"en",
"dataset:togethercomputer/llama-instruct",
"arxiv:2307.03172",
"license:llama2",
"text-generation-inference",
"region:us"
] | text-generation | TheBloke | null | null | TheBloke/Llama-2-7B-32K-Instruct-GPTQ | 21 | 225,318 | transformers | 2023-08-21T12:18:32 | ---
language:
- en
license: llama2
library_name: transformers
datasets:
- togethercomputer/llama-instruct
model_name: Llama2 7B 32K Instruct
base_model: togethercomputer/Llama-2-7B-32K-Instruct
inference: false
model_creator: Together
model_type: llama
prompt_template: '[INST]
{prompt}
[\INST]
'
quantized_by: ... | 21,548 | [
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xlnet-base-cased | 2023-01-24T14:50:31.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"xlnet",
"text-generation",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1906.08237",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | text-generation | null | null | null | xlnet-base-cased | 48 | 224,522 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: mit
datasets:
- bookcorpus
- wikipedia
---
# XLNet (base-sized model)
XLNet model pre-trained on English language. It was introduced in the paper [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://arxiv.org/abs/1906.08237) by Yang et al. and first released in... | 2,696 | [
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siebert/sentiment-roberta-large-english | 2023-04-02T16:25:45.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"sentiment",
"twitter",
"reviews",
"siebert",
"en",
"arxiv:1907.11692",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | siebert | null | null | siebert/sentiment-roberta-large-english | 83 | 222,812 | transformers | 2022-03-02T23:29:05 | ---
language: "en"
tags:
- sentiment
- twitter
- reviews
- siebert
---
## SiEBERT - English-Language Sentiment Classification
# Overview
This model ("SiEBERT", prefix for "Sentiment in English") is a fine-tuned checkpoint of [RoBERTa-large](https://huggingface.co/roberta-large) ([Liu et al. 2019](https://arxiv.org/pd... | 5,181 | [
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THUDM/chatglm2-6b-int4 | 2023-10-09T08:23:08.000Z | [
"transformers",
"pytorch",
"chatglm",
"glm",
"thudm",
"custom_code",
"zh",
"en",
"arxiv:2103.10360",
"arxiv:2210.02414",
"arxiv:1911.02150",
"endpoints_compatible",
"has_space",
"region:us"
] | null | THUDM | null | null | THUDM/chatglm2-6b-int4 | 207 | 214,817 | transformers | 2023-06-25T12:46:22 | ---
language:
- zh
- en
tags:
- glm
- chatglm
- thudm
---
# ChatGLM2-6B
<p align="center">
💻 <a href="https://github.com/THUDM/ChatGLM2-6B" target="_blank">Github Repo</a> • 🐦 <a href="https://twitter.com/thukeg" target="_blank">Twitter</a> • 📃 <a href="https://arxiv.org/abs/2103.10360" target="_blank">[GLM@ACL 22... | 5,783 | [
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facebook/opt-350m | 2023-09-15T13:09:50.000Z | [
"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-350m | 77 | 214,166 | transformers | 2022-05-11T08:25:39 | ---
language: en
inference: false
tags:
- text-generation
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://github... | 8,772 | [
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Rakib/roberta-base-on-cuad | 2023-01-18T12:18:53.000Z | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"legal-contract-review",
"cuad",
"en",
"dataset:cuad",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | question-answering | Rakib | null | null | Rakib/roberta-base-on-cuad | 4 | 214,054 | transformers | 2022-03-02T23:29:04 | ---
language:
- en
license: mit
datasets:
- cuad
pipeline_tag: question-answering
tags:
- legal-contract-review
- roberta
- cuad
library_name: transformers
---
# Model Card for roberta-base-on-cuad
# Model Details
## Model Description
- **Developed by:** Mohammed Rakib
- **Shared by [Optional]:** More informatio... | 5,001 | [
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tsmatz/xlm-roberta-ner-japanese | 2023-09-12T00:26:01.000Z | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"ner",
"bert",
"ja",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | tsmatz | null | null | tsmatz/xlm-roberta-ner-japanese | 7 | 212,817 | transformers | 2022-10-24T02:08:37 | ---
language:
- ja
license: mit
tags:
- generated_from_trainer
- ner
- bert
metrics:
- f1
widget:
- text: 鈴木は4月の陽気の良い日に、鈴をつけて熊本県の阿蘇山に登った
- text: 中国では、中国共産党による一党統治が続く
base_model: xlm-roberta-base
model-index:
- name: xlm-roberta-ner-ja
results: []
---
<!-- This model card has been generated automatically according to... | 2,616 | [
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0.00... |
stabilityai/stable-diffusion-2-depth | 2023-07-05T16:19:06.000Z | [
"diffusers",
"stable-diffusion",
"arxiv:2112.10752",
"arxiv:2202.00512",
"arxiv:1910.09700",
"license:openrail++",
"has_space",
"diffusers:StableDiffusionDepth2ImgPipeline",
"region:us"
] | null | stabilityai | null | null | stabilityai/stable-diffusion-2-depth | 353 | 211,554 | diffusers | 2022-11-23T17:41:46 | ---
license: openrail++
tags:
- stable-diffusion
inference: false
---
# Stable Diffusion v2 Model Card
This model card focuses on the model associated with the Stable Diffusion v2 model, available [here](https://github.com/Stability-AI/stablediffusion).
This `stable-diffusion-2-depth` model is resumed from [stable-di... | 12,412 | [
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Jean-Baptiste/roberta-large-ner-english | 2023-03-22T02:19:36.000Z | [
"transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"roberta",
"token-classification",
"en",
"dataset:conll2003",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | Jean-Baptiste | null | null | Jean-Baptiste/roberta-large-ner-english | 53 | 211,184 | transformers | 2022-03-02T23:29:04 | ---
language: en
datasets:
- conll2003
widget:
- text: "My name is jean-baptiste and I live in montreal"
- text: "My name is clara and I live in berkeley, california."
- text: "My name is wolfgang and I live in berlin"
train-eval-index:
- config: conll2003
task: token-classification
task_id: entity_extraction
spl... | 3,545 | [
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neuralmind/bert-base-portuguese-cased | 2022-06-14T14:37:09.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"pt",
"dataset:brWaC",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | neuralmind | null | null | neuralmind/bert-base-portuguese-cased | 94 | 210,757 | transformers | 2022-03-02T23:29:05 | ---
language: pt
license: mit
tags:
- bert
- pytorch
datasets:
- brWaC
---
# BERTimbau Base (aka "bert-base-portuguese-cased")
## Introduction
BERTimbau Base is a pretrained BERT model for Brazilian Portuguese that achieves state-of-the-art performance... | 3,598 | [
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cointegrated/LaBSE-en-ru | 2023-11-04T11:49:30.000Z | [
"transformers",
"pytorch",
"tf",
"safetensors",
"bert",
"pretraining",
"feature-extraction",
"embeddings",
"sentence-similarity",
"ru",
"en",
"arxiv:2007.01852",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | cointegrated | null | null | cointegrated/LaBSE-en-ru | 25 | 210,077 | transformers | 2022-03-02T23:29:05 | ---
language: ["ru", "en"]
tags:
- feature-extraction
- embeddings
- sentence-similarity
---
# LaBSE for English and Russian
This is a truncated version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE), which is, in turn, a port of [LaBSE](https://tfhub.dev/google/LaBSE/1) by Google.... | 1,705 | [
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google/flan-t5-small | 2023-10-10T18:01:54.000Z | [
"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-small | 136 | 208,387 | transformers | 2022-10-21T09:59:24 | ---
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... | 10,818 | [
[
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microsoft/deberta-v2-xlarge | 2022-09-26T08:59:06.000Z | [
"transformers",
"pytorch",
"tf",
"deberta-v2",
"deberta",
"fill-mask",
"en",
"arxiv:2006.03654",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | microsoft | null | null | microsoft/deberta-v2-xlarge | 18 | 206,776 | transformers | 2022-03-02T23:29:05 | ---
language: en
tags:
- deberta
- 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 mask... | 3,910 | [
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sentence-transformers/nli-mpnet-base-v2 | 2022-06-15T20:14:17.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"mpnet",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:1908.10084",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | sentence-transformers | null | null | sentence-transformers/nli-mpnet-base-v2 | 7 | 206,550 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/nli-mpnet-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vect... | 3,663 | [
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0.0... |
Meina/MeinaMix_V10 | 2023-05-25T11:22:20.000Z | [
"diffusers",
"art",
"anime",
"stable diffusion",
"text-to-image",
"en",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | Meina | null | null | Meina/MeinaMix_V10 | 27 | 203,911 | diffusers | 2023-05-24T04:44:20 | ---
license: creativeml-openrail-m
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
tags:
- art
- anime
- stable diffusion
---
MeinaMix Objective is to be able to do good art with little prompting.
For examples and prompts, please checkout: https://civitai.com/models/7240/meinamix
I have a discord s... | 1,445 | [
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0.014091491... |
rizvandwiki/gender-classification | 2023-05-18T11:16:33.000Z | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"huggingpics",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | image-classification | rizvandwiki | null | null | rizvandwiki/gender-classification | 4 | 201,226 | transformers | 2022-12-06T08:53:43 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: gender-classification
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9244444370269775
---
# gender-class... | 739 | [
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allenai/wmt19-de-en-6-6-big | 2023-01-24T16:28:51.000Z | [
"transformers",
"pytorch",
"fsmt",
"text2text-generation",
"translation",
"wmt19",
"allenai",
"de",
"en",
"dataset:wmt19",
"arxiv:2006.10369",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | translation | allenai | null | null | allenai/wmt19-de-en-6-6-big | 3 | 200,429 | transformers | 2022-03-02T23:29:05 |
---
language:
- de
- en
thumbnail:
tags:
- translation
- wmt19
- allenai
license: apache-2.0
datasets:
- wmt19
metrics:
- bleu
---
# FSMT
## Model description
This is a ported version of fairseq-based [wmt19 transformer](https://github.com/jungokasai/deep-shallow/) for de-en.
For more details, please, see [Deep E... | 2,667 | [
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-0.047607421875,
-0.0206451416015625,
-0.066162109375,
0.... |
microsoft/layoutxlm-base | 2022-09-16T03:41:38.000Z | [
"transformers",
"pytorch",
"layoutlmv2",
"arxiv:2104.08836",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | microsoft | null | null | microsoft/layoutxlm-base | 47 | 198,564 | transformers | 2022-03-02T23:29:05 | ---
license: cc-by-nc-sa-4.0
---
# LayoutXLM
**Multimodal (text + layout/format + image) pre-training for document AI**
LayoutXLM is a multilingual variant of LayoutLMv2.
The documentation of this model in the Transformers library can be found [here](https://huggingface.co/docs/transformers/model_doc/layoutxlm).
[... | 1,038 | [
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0.031219482421875,
-0.0516357421875,
-0.045562744140625,
-0.038604736328125,
... |
busecarik/berturk-sunlp-ner-turkish | 2023-01-09T19:38:54.000Z | [
"transformers",
"pytorch",
"tf",
"bert",
"token-classification",
"tr",
"dataset:SUNLP-NER-Twitter",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | busecarik | null | null | busecarik/berturk-sunlp-ner-turkish | 3 | 198,294 | transformers | 2022-08-26T12:34:48 | ---
language: tr
datasets:
- SUNLP-NER-Twitter
---
# berturk-sunlp-ner-turkish
## Introduction
[berturk-sunlp-ner-turkish] is a NER model that was fine-tuned from the BERTurk-cased model on the SUNLP-NER-Twitter dataset.
## Training data
The model was trained on the SUNLP-NER-Twitter dataset (5000 tweets). The datas... | 1,794 | [
[
-0.033477783203125,
-0.0469970703125,
0.00559234619140625,
0.01456451416015625,
-0.02862548828125,
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-0.0180816650390625,
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0.03790283203125,
0.02301025390625,
-0.041229248046875,
-0.043670654296875,
-0.05194091796875,
0... |
kk08/CryptoBERT | 2023-09-12T06:37:34.000Z | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"crypto",
"sentiment",
"analysis",
"en",
"endpoints_compatible",
"region:us"
] | text-classification | kk08 | null | null | kk08/CryptoBERT | 7 | 193,483 | transformers | 2023-04-13T17:52:32 | ---
language:
- en
tags:
- generated_from_trainer
- crypto
- sentiment
- analysis
pipeline_tag: text-classification
base_model: ProsusAI/finbert
model-index:
- name: CryptoBERT
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should pro... | 2,753 | [
[
-0.036865234375,
-0.039154052734375,
0.0006775856018066406,
0.004154205322265625,
-0.0283660888671875,
-0.006473541259765625,
-0.00926971435546875,
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0.02301025390625,
0.02886962890625,
-0.045379638671875,
-0.058074951171875,
-0.05581665039062... |
nlpaueb/legal-bert-base-uncased | 2022-04-28T14:42:50.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"pretraining",
"legal",
"fill-mask",
"en",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | fill-mask | nlpaueb | null | null | nlpaueb/legal-bert-base-uncased | 84 | 192,891 | transformers | 2022-03-02T23:29:05 | ---
language: en
pipeline_tag: fill-mask
license: cc-by-sa-4.0
thumbnail: https://i.ibb.co/p3kQ7Rw/Screenshot-2020-10-06-at-12-16-36-PM.png
tags:
- legal
widget:
- text: "The applicant submitted that her husband was subjected to treatment amounting to [MASK] whilst in the custody of police."
---
# LEGAL-BERT: The Mupp... | 11,567 | [
[
-0.020599365234375,
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0.048583984375,
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-0.03997802734375,
-0.039337158203125,
-0.00905... |
Helsinki-NLP/opus-mt-ar-en | 2023-08-16T11:25:35.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"ar",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-ar-en | 18 | 190,964 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ar-en
* source languages: ar
* target languages: en
* OPUS readme: [ar-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ar-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 818 | [
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-0.049102783203125,
... |
laion/CLIP-ViT-L-14-DataComp.XL-s13B-b90K | 2023-05-16T16:59:39.000Z | [
"open_clip",
"pytorch",
"clip",
"zero-shot-image-classification",
"dataset:mlfoundations/datacomp_pools",
"arxiv:2304.14108",
"license:mit",
"has_space",
"region:us"
] | zero-shot-image-classification | laion | null | null | laion/CLIP-ViT-L-14-DataComp.XL-s13B-b90K | 89 | 190,462 | open_clip | 2023-04-26T01:41:18 | ---
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
datasets:
- mlfoundations/datacomp_pools
pipeline_tag: zero-shot-image-classification
---
# Mode... | 7,405 | [
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-0... |
hiiamsid/sentence_similarity_spanish_es | 2023-08-02T12:43:34.000Z | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"es",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | hiiamsid | null | null | hiiamsid/sentence_similarity_spanish_es | 30 | 189,946 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
language:
- es
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
license: apache-2.0
---
# hiiamsid/sentence_similarity_spanish_es
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensi... | 4,509 | [
[
-0.0211334228515625,
-0.06268310546875,
0.02130126953125,
0.031463623046875,
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-0.0243377685546875,
-0.00705718994140625,
0.0269775390625,
0.022674560546875,
-0.05108642578125,
-0.053802490234375,
-0.05072021484375,
0.0102... |
stabilityai/sd-vae-ft-mse | 2023-06-06T11:39:15.000Z | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"license:mit",
"has_space",
"diffusers:AutoencoderKL",
"region:us"
] | null | stabilityai | null | null | stabilityai/sd-vae-ft-mse | 214 | 189,411 | diffusers | 2022-10-13T12:50:55 | ---
license: mit
tags:
- stable-diffusion
- stable-diffusion-diffusers
inference: false
---
# Improved Autoencoders
## Utilizing
These weights are intended to be used with the [🧨 diffusers library](https://github.com/huggingface/diffusers). If you are looking for the model to use with the original [CompVis Stable Dif... | 6,838 | [
[
-0.054443359375,
-0.02984619140625,
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0.0176239013671875,
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0.039764404296875,
0.0184326171875,
-0.025787353515625,
-0.0325927734375,
-0.045623779296875,
... |
openai/whisper-tiny | 2023-09-08T13:08:03.000Z | [
"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-tiny | 117 | 189,229 | transformers | 2022-09-26T06:50:30 | ---
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
... | 19,750 | [
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0.03216552734375,
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0.0162811279296875,
0.032684326171875,
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-0.... |
hpcai-tech/Colossal-LLaMA-2-7b-base | 2023-10-10T06:21:00.000Z | [
"transformers",
"pytorch",
"llama",
"text-generation",
"zh",
"en",
"arxiv:2307.09288",
"license:llama2",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | text-generation | hpcai-tech | null | null | hpcai-tech/Colossal-LLaMA-2-7b-base | 67 | 188,722 | transformers | 2023-09-18T07:51:31 | ---
license: llama2
language:
- zh
- en
---
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<div align="center">
<h1>
Colossal-LLaMA-2-7B
</h1>
</div>
<div align="center">
🎉 We released Colossal-LLaMA-2-7B-base based on LLaMA-2 !!
</div>
<div align="center">
｜<a href="https://gi... | 16,966 | [
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MCG-NJU/videomae-base-finetuned-kinetics | 2023-04-22T11:30:54.000Z | [
"transformers",
"pytorch",
"videomae",
"video-classification",
"vision",
"arxiv:2203.12602",
"arxiv:2111.06377",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | video-classification | MCG-NJU | null | null | MCG-NJU/videomae-base-finetuned-kinetics | 10 | 185,265 | transformers | 2022-07-08T15:01:34 | ---
license: "cc-by-nc-4.0"
tags:
- vision
- video-classification
---
# VideoMAE (base-sized model, fine-tuned on Kinetics-400)
VideoMAE model pre-trained for 1600 epochs in a self-supervised way and fine-tuned in a supervised way on Kinetics-400. It was introduced in the paper [VideoMAE: Masked Autoencoders are Dat... | 3,584 | [
[
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... |
distilbert-base-cased-distilled-squad | 2023-04-12T12:06:44.000Z | [
"transformers",
"pytorch",
"tf",
"rust",
"safetensors",
"openvino",
"distilbert",
"question-answering",
"en",
"dataset:squad",
"arxiv:1910.01108",
"arxiv:1910.09700",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | question-answering | null | null | null | distilbert-base-cased-distilled-squad | 141 | 184,739 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- squad
metrics:
- squad
model-index:
- name: distilbert-base-cased-distilled-squad
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad
type: squad
config: plain_text
split: validation
metr... | 9,515 | [
[
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0.0118865966796875,
-0.061004638671875,
-0.022796630859375,
-0.055206298828125... |
hkunlp/instructor-large | 2023-04-21T06:04:33.000Z | [
"sentence-transformers",
"pytorch",
"t5",
"text-embedding",
"embeddings",
"information-retrieval",
"beir",
"text-classification",
"language-model",
"text-clustering",
"text-semantic-similarity",
"text-evaluation",
"prompt-retrieval",
"text-reranking",
"feature-extraction",
"sentence-si... | sentence-similarity | hkunlp | null | null | hkunlp/instructor-large | 328 | 182,758 | sentence-transformers | 2022-12-20T05:31:06 | ---
pipeline_tag: sentence-similarity
tags:
- text-embedding
- embeddings
- information-retrieval
- beir
- text-classification
- language-model
- text-clustering
- text-semantic-similarity
- text-evaluation
- prompt-retrieval
- text-reranking
- sentence-transformers
- feature-extraction
- sentence-similarity
- transfor... | 66,300 | [
[
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0.021240234375,
0.0200653076171875,
-0.0175018310546875,
-0.06201171875,
-0.0350341796875,
... |
sentence-transformers/paraphrase-multilingual-mpnet-base-v2 | 2023-11-02T09:45:42.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"xlm-roberta",
"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/paraphrase-multilingual-mpnet-base-v2 | 148 | 180,114 | 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
- ... | 4,102 | [
[
-0.016876220703125,
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0.031707763671875,
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0.037017822265625,
-0.02899169921875,
-0.0236663818359375,
-0.055999755859375,
... |
Helsinki-NLP/opus-mt-it-en | 2023-08-16T11:58:49.000Z | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"it",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | translation | Helsinki-NLP | null | null | Helsinki-NLP/opus-mt-it-en | 8 | 179,643 | transformers | 2022-03-02T23:29:04 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-it-en
* source languages: it
* target languages: en
* OPUS readme: [it-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/it-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | 901 | [
[
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0.0008111000061035156,
0.0290679931640625,
-0.046478271484375,
-0.046844482421875,
-0.042816162109375,... |
MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli | 2023-03-20T08:27:01.000Z | [
"transformers",
"pytorch",
"safetensors",
"deberta-v2",
"text-classification",
"zero-shot-classification",
"en",
"dataset:multi_nli",
"dataset:anli",
"dataset:fever",
"dataset:lingnli",
"dataset:alisawuffles/WANLI",
"arxiv:2104.07179",
"arxiv:2111.09543",
"license:mit",
"model-index",
... | zero-shot-classification | MoritzLaurer | null | null | MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli | 61 | 179,353 | transformers | 2022-06-06T18:28:10 | ---
language:
- en
tags:
- text-classification
- zero-shot-classification
license: mit
metrics:
- accuracy
datasets:
- multi_nli
- anli
- fever
- lingnli
- alisawuffles/WANLI
pipeline_tag: zero-shot-classification
#- text-classification
#widget:
#- text: "I first thought that I really liked the movie, but upon second ... | 11,394 | [
[
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... |
stabilityai/stable-diffusion-2-inpainting | 2023-07-05T16:19:10.000Z | [
"diffusers",
"stable-diffusion",
"arxiv:2112.10752",
"arxiv:2202.00512",
"arxiv:1910.09700",
"license:openrail++",
"has_space",
"diffusers:StableDiffusionInpaintPipeline",
"region:us"
] | null | stabilityai | null | null | stabilityai/stable-diffusion-2-inpainting | 371 | 177,563 | diffusers | 2022-11-23T17:41:55 | ---
license: openrail++
tags:
- stable-diffusion
inference: false
---
# Stable Diffusion v2 Model Card
This model card focuses on the model associated with the Stable Diffusion v2, available [here](https://github.com/Stability-AI/stablediffusion).
This `stable-diffusion-2-inpainting` model is resumed from [stable-dif... | 13,062 | [
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-0.044891357421875,
-0.0080... |
bert-large-uncased-whole-word-masking-finetuned-squad | 2023-04-06T13:42:50.000Z | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"question-answering",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | question-answering | null | null | null | bert-large-uncased-whole-word-masking-finetuned-squad | 97 | 177,375 | transformers | 2022-03-02T23:29:04 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT large model (uncased) whole word masking finetuned on SQuAD
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 i... | 6,240 | [
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0.0091400... |
meta-llama/Llama-2-70b-hf | 2023-08-09T15:30:59.000Z | [
"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-hf | 650 | 177,169 | transformers | 2023-07-11T08:56:34 | ---
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... | 10,360 | [
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0.022735595703125,
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-0.050811767578125,
0.0051116... |
sentence-transformers/multi-qa-mpnet-base-dot-v1 | 2023-11-02T09:30:37.000Z | [
"sentence-transformers",
"pytorch",
"mpnet",
"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",
"data... | sentence-similarity | sentence-transformers | null | null | sentence-transformers/multi-qa-mpnet-base-dot-v1 | 115 | 175,312 | 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... | 8,664 | [
[
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... |
microsoft/deberta-xlarge-mnli | 2022-06-27T15:47:33.000Z | [
"transformers",
"pytorch",
"tf",
"deberta",
"text-classification",
"deberta-v1",
"deberta-mnli",
"en",
"arxiv:2006.03654",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
] | text-classification | microsoft | null | null | microsoft/deberta-xlarge-mnli | 15 | 174,741 | 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... | 3,909 | [
[
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0.0212860107421875,
0.01309967041015625,
-0.06243896484375,
-0.0254058837890625,
-0.0687255859375,
... |
sentence-transformers/clip-ViT-B-32-multilingual-v1 | 2022-06-15T20:17:26.000Z | [
"sentence-transformers",
"pytorch",
"tf",
"distilbert",
"feature-extraction",
"sentence-similarity",
"transformers",
"multilingual",
"arxiv:2004.09813",
"arxiv:1908.10084",
"license:apache-2.0",
"endpoints_compatible",
"has_space",
"region:us"
] | sentence-similarity | sentence-transformers | null | null | sentence-transformers/clip-ViT-B-32-multilingual-v1 | 56 | 173,720 | sentence-transformers | 2022-03-02T23:29:05 | ---
pipeline_tag: sentence-similarity
language: multilingual
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
license: apache-2.0
---
# sentence-transformers/clip-ViT-B-32-multilingual-v1
This is a multi-lingual version of the OpenAI CLIP-ViT-B32 model. You can map text (in 50+ ... | 5,626 | [
[
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-0.052001953125,
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-0.02685546875,
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0.0159759521484375,
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-0.042266845703125,
-0.039215087890625,
0.0273895263671... |
obi/deid_roberta_i2b2 | 2022-08-22T13:28:26.000Z | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"deidentification",
"medical notes",
"ehr",
"phi",
"en",
"dataset:I2B2",
"arxiv:1907.11692",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | token-classification | obi | null | null | obi/deid_roberta_i2b2 | 7 | 172,479 | transformers | 2022-03-02T23:29:05 | ---
language:
- en
thumbnail: "https://www.onebraveidea.org/wp-content/uploads/2019/07/OBI-Logo-Website.png"
tags:
- deidentification
- medical notes
- ehr
- phi
datasets:
- I2B2
metrics:
- F1
- Recall
- Precision
widget:
- text: "Physician Discharge Summary Admit date: 10/12/1982 Discharge date: 10/22/1982 Patient I... | 5,280 | [
[
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0.0179443359375,
0.042816162109375,
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-0.0625,
-0.051605224609375,
-0.000939846038... |
cross-encoder/ms-marco-TinyBERT-L-2-v2 | 2021-08-05T08:39:45.000Z | [
"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-TinyBERT-L-2-v2 | 9 | 171,523 | 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 | [
[
-0.03228759765625,
-0.043670654296875,
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-0.051055908203125,
-0.058013916015625,
... |
BAAI/bge-small-en-v1.5 | 2023-11-02T10:47:51.000Z | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"mteb",
"en",
"arxiv:2310.07554",
"arxiv:2309.07597",
"license:mit",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | feature-extraction | BAAI | null | null | BAAI/bge-small-en-v1.5 | 37 | 170,376 | sentence-transformers | 2023-09-12T05:20:55 | ---
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- mteb
model-index:
- name: bge-small-en-v1.5
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
sp... | 89,841 | [
[
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0.0292816162109375,
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0.028350830078125,
-0.0260467529296875,
-0.0654296875,
-0.036102294921875,
-0.0... |
timm/convnext_small.fb_in22k | 2023-03-31T22:34:14.000Z | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"dataset:imagenet-22k",
"arxiv:2201.03545",
"license:apache-2.0",
"region:us"
] | image-classification | timm | null | null | timm/convnext_small.fb_in22k | 0 | 169,191 | timm | 2022-12-13T07:13:23 | ---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
datasets:
- imagenet-22k
---
# Model card for convnext_small.fb_in22k
A ConvNeXt image classification model. Pretrained on ImageNet-22k by paper authors.
## Model Details
- **Model Type:** Image classification / feature backbone
- **Model ... | 15,600 | [
[
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-0.03302001953125,
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0.065673828125,
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-0.04345703125,
-0.04144287109375,
-0.050506591796875,
-0.002... |
cross-encoder/ms-marco-MiniLM-L-4-v2 | 2021-08-05T08:39:32.000Z | [
"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-4-v2 | 1 | 164,634 | 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 | [
[
-0.03228759765625,
-0.043670654296875,
0.0250396728515625,
0.01168060302734375,
-0.0127105712890625,
0.01073455810546875,
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0.025146484375,
0.0255889892578125,
-0.041229248046875,
-0.051055908203125,
-0.058013916015625,
... |
google/pix2struct-textcaps-base | 2023-09-07T18:57:01.000Z | [
"transformers",
"pytorch",
"safetensors",
"pix2struct",
"text2text-generation",
"image-to-text",
"en",
"fr",
"ro",
"de",
"multilingual",
"arxiv:2210.03347",
"license:apache-2.0",
"autotrain_compatible",
"has_space",
"region:us"
] | image-to-text | google | null | null | google/pix2struct-textcaps-base | 23 | 163,798 | transformers | 2023-03-01T09:07:41 | ---
language:
- en
- fr
- ro
- de
- multilingual
pipeline_tag: image-to-text
inference: false
license: apache-2.0
---
# Model card for Pix2Struct - Finetuned on TextCaps
# Table of Contents
0. [... | 7,674 | [
[
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0.035797119140625,
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0.0195465087890625,
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microsoft/trocr-large-stage1 | 2023-03-31T18:38:51.000Z | [
"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-stage1 | 10 | 163,433 | transformers | 2022-03-02T23:29:05 | ---
tags:
- trocr
- image-to-text
---
# TrOCR (large-sized model, pre-trained only)
TrOCR pre-trained only model. It was introduced in the paper [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://arxiv.org/abs/2109.10282) by Li et al. and first released in [this repository](http... | 2,520 | [
[
-0.0203094482421875,
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-0.0284271240234375,
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-0.0016317367553710938,
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-0.0306549072265625,
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liuhaotian/llava-v1.5-13b | 2023-10-16T21:53:56.000Z | [
"transformers",
"pytorch",
"llava",
"text-generation",
"has_space",
"region:us"
] | text-generation | liuhaotian | null | null | liuhaotian/llava-v1.5-13b | 257 | 163,328 | transformers | 2023-10-05T18:27:40 | ---
inference: false
---
<br>
<br>
# LLaVA Model Card
## Model details
**Model type:**
LLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
It is an auto-regressive language model, based on the transformer architecture.
**Model date:**
LLaVA-v1... | 1,365 | [
[
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facebook/maskformer-swin-large-ade | 2023-02-27T15:08:57.000Z | [
"transformers",
"pytorch",
"maskformer",
"vision",
"image-segmentation",
"dataset:scene_parse_150",
"arxiv:2107.06278",
"license:other",
"endpoints_compatible",
"has_space",
"region:us"
] | image-segmentation | facebook | null | null | facebook/maskformer-swin-large-ade | 38 | 163,031 | transformers | 2022-03-02T23:29:05 | ---
license: other
tags:
- vision
- image-segmentation
datasets:
- scene_parse_150
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_0... | 2,804 | [
[
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0.005405426025390625,
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0.0462646484375,
-0.06842041015625,
-0.048004150390625,
-0.057403564453125,
-0.018... |
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