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https://huggingface.co/ | The Home of Machine Learning
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https://huggingface.co/google | ALBERT release
The ALBERT release was done in two steps, over 4 checkpoints of different sizes each time. The first version is noted as "v1", the second as "v2". |
https://huggingface.co/Intel | Intel and Hugging Face are building powerful optimization tools to accelerate training and inference with Transformers. |
https://huggingface.co/microsoft | Research interests
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Collections 1
SpeechT5
The SpeechT5 framework consists of a shared seq2seq and six modal-specific (speech/text) pre/post-nets that can address a few audio-related tasks.
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
Paper • 2110.07205 • Publis... |
https://huggingface.co/grammarly | Research interests
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models 6
grammarly/coedit-large
Text2Text Generation • Updated 14 days ago • 21.1k • 26
grammarly/pseudonymization-seq2seq
Text2Text Generation • Updated Aug 31 • 4
grammarly/coedit-xxl
Text2Text Generation • Updated Aug 19 • 157 • 10
grammarly/coedit-xl-composite
Text2Text Gene... |
https://huggingface.co/Writer | Writer is a generative AI platform focused on advancing AI technology by solving the problems faced by businesses. We are making LLMs accessible to everyone with the availability of our Palmyra LLMs on Hugging Face and our API. You can run these models in your own, secure environment and fine-tune them for your needs w... |
https://huggingface.co/docs/transformers | 🤗 Transformers
State-of-the-art Machine Learning for PyTorch, TensorFlow, and JAX.
🤗 Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a mo... |
https://huggingface.co/docs/safetensors | You are viewing main version, which requires
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Safetensors
Safetensors is a new simple format for storing tensors safely (as opposed to pickle) and that is still fast (zero-copy). Safetensors is really fast 🚀.
I... |
https://huggingface.co/docs/diffusers | Diffusers
🤗 Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you’re looking for a simple inference solution or want to train your own diffusion model, 🤗 Diffusers is a modular toolbox that supports both. Our lib... |
https://huggingface.co/docs/huggingface_hub | 🤗 Hub client library
The huggingface_hub library allows you to interact with the Hugging Face Hub, a machine learning platform for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the hundreds of machine learning apps hosted on the Hub. You can also create and share y... |
https://huggingface.co/docs/tokenizers | Tokenizers
Fast State-of-the-art tokenizers, optimized for both research and production
🤗 Tokenizers provides an implementation of today’s most used tokenizers, with a focus on performance and versatility. These tokenizers are also used in 🤗 Transformers.
Main features:
Train new vocabularies and tokenize, using to... |
https://huggingface.co/docs/transformers.js | Transformers.js
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
Transformers.js is designed to be functionally equivalent to Hugging Face’s transformers python library, meaning you can run the same pretrained models using a very similar API. These ... |
https://huggingface.co/docs/timm | timm
timm is a library containing SOTA computer vision models, layers, utilities, optimizers, schedulers, data-loaders, augmentations, and training/evaluation scripts.
It comes packaged with >700 pretrained models, and is designed to be flexible and easy to use.
Read the quick start guide to get up and running with the... |
https://huggingface.co/docs/peft | PEFT
🤗 PEFT, or Parameter-Efficient Fine-Tuning (PEFT), is a library for efficiently adapting pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model’s parameters. PEFT methods only fine-tune a small number of (extra) model parameters, significantly decreasing computatio... |
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https://huggingface.co/support | Thomas Wolf, creator of Transformers
Ross Wightman, creator of timm (SOTA computer vision)
Colin Raffel, first author of T5 from Google
Morgan Funtowicz, contributor to ONNX
Abhishek Thakur, worldwide expert on auto-ML
Victor Sanh, author of DistilBERT
Anthony Moi, creator of Tokenizers
Julien Simon, author of “Learn ... |
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https://huggingface.co/learn | Hugging Face
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https://huggingface.co/blog | Ethics and Society Newsletter #5: Hugging Face Goes To Washington and Other Summer 2023 Musings
By September 29, 2023
Finetune Stable Diffusion Models with DDPO via TRL
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Non-engineers guide: Train a LLaMA 2 chatbot
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Llama 2 on Amazon SageMaker a Benchmark
By Septemb... |
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https://huggingface.co/datasets | Edit Datasets filters
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Depth Estimation Image Classification Object Detection Image Segmentation Image-to-Image Unconditional Image Generation Video Classi... |
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The HF Hub is the central place to explore, experiment, collaborate and build technology with Machine Learning.
Join the open source Machine Learning movemen... |
https://huggingface.co/monster-labs/control_v1p_sd15_qrcode_monster | Controlnet QR Code Monster v2 For SD-1.5
Model Description
This model is made to generate creative QR codes that still scan. Keep in mind that not all generated codes might be readable, but you can try different parameters and prompts to get the desired results.
NEW VERSION
Introducing the upgraded version of our mod... |
https://huggingface.co/mistralai/Mistral-7B-v0.1 | 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 Llama 2 13B on all benchmarks we tested.
For full details of this model please read our Release blog post
Model Architecture
Mistral-7B-v0.1 is a t... |
https://huggingface.co/spaces/AP123/IllusionDiffusion | App Files Files
Community
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https://huggingface.co/spaces/Shopify/background-replacement | App Files Files
Community
3 |
https://huggingface.co/spaces/jbilcke-hf/ai-comic-factory | App Files Files
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225 |
https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0 | SD-XL 1.0-base Model Card
Model
SDXL consists of an ensemble of experts pipeline for latent diffusion: In a first step, the base model is used to generate (noisy) latents, which are then further processed with a refinement model (available here: https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0/) spe... |
https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 | 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 generative text model using a variety of publicly available conversation datasets.
For full details of this model please read our release blog post
Instruction format ... |
https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GGUF | Mistral 7B Instruct v0.1 - GGUF
Model creator: Mistral AI
Original model: Mistral 7B Instruct v0.1
Description
This repo contains GGUF format model files for Mistral AI's Mistral 7B Instruct v0.1.
About GGUF
GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, whic... |
https://huggingface.co/spaces/facebook/MusicGen | App Files Files
Community
51 |
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard | App Files Files
Community
303 |
https://huggingface.co/datasets/lmsys/lmsys-chat-1m | You need to agree to share your contact information to access this dataset
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
Log in or Sign Up to review the conditions and access this dataset content.
NOTE: We are currently conducting a final review of the ... |
https://huggingface.co/datasets/vikp/textbook_quality_programming | Dataset Card for "textbook_quality_programming"
Synthetic programming textbooks generated with GPT-3.5 and retrieval. Very high quality, aimed at being used in a phi replication.
Generated using the textbook_quality repo.
Downloads last month262
Models trained or fine-tuned on vikp/textbook_quality_programming |
https://huggingface.co/enterprise | Enterprise Hub:
Build AI through secure collaboration
Give your team the most advanced platform to build AI with enterprise-grade security, access controls and dedicated support.
Join leading AI organizations already using Enterprise Hub
A Complete Platform for Machine Learning
Hugging Face’s complete ecosystem com... |
https://huggingface.co/datasets/fka/awesome-chatgpt-prompts | I want you to act as a linux terminal. I will type commands and you will reply with what the terminal should show. I want you to only reply with the terminal output inside one unique code block, and nothing else. do not write explanations. do not type commands unless I instruct you to do so. when i need to tell you som... |
https://huggingface.co/datasets/Open-Orca/OpenOrca | 🐋 The OpenOrca Dataset! 🐋
We are thrilled to announce the release of the OpenOrca dataset! This rich collection of augmented FLAN data aligns, as best as possible, with the distributions outlined in the Orca paper. It has been instrumental in generating high-performing model checkpoints and serves as a valuable resou... |
https://huggingface.co/docs/sagemaker | Hugging Face on Amazon SageMaker
Deep Learning Containers
Deep Learning Containers (DLCs) are Docker images pre-installed with deep learning frameworks and libraries such as 🤗 Transformers, 🤗 Datasets, and 🤗 Tokenizers. The DLCs allow you to start training models immediately, skipping the complicated process of bu... |
https://huggingface.co/amazon/sm-hackathon-actionability-9-multi-outputs-setfit-all-distilroberta-model-v0.2 | amazon/sm-hackathon-actionability-9-multi-outputs-setfit-all-distilroberta-model-v0.2
This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
Fine-tuning a Sentence Transformer with contrastive learning.
Training a classi... |
https://huggingface.co/allenai | Research interests
AI for the Common Good
models 203
datasets 62 |
https://huggingface.co/datasets/emrgnt-cmplxty/sciphi-textbooks-are-all-you-need | Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: Imagine you are a prolific author tasked with writing a textbook. You are working on writing a textbook chapter titled "Marine Biology: Unveiling the Ocean's Depths - A Detailed Study of Marine Bio... |
https://huggingface.co/amazon/sm-hackathon-actionability-9-multi-outputs-setfit-all-distilroberta-model-v0.1 | amazon/sm-hackathon-actionability-9-multi-outputs-setfit-all-distilroberta-model-v0.1
This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
Fine-tuning a Sentence Transformer with contrastive learning.
Training a classi... |
https://huggingface.co/amazon/sm-hackathon-actionability-9-multi-outputs-setfit-model-v0.1 | amazon/sm-hackathon-actionability-9-multi-outputs-setfit-model-v0.1
This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
Fine-tuning a Sentence Transformer with contrastive learning.
Training a classification head with... |
https://huggingface.co/amazon/sm-hackathon-setfit-model | amazon/sm-hackathon-setfit-model
This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
Fine-tuning a Sentence Transformer with contrastive learning.
Training a classification head with features from the fine-tuned Sente... |
https://huggingface.co/amazon/FalconLite | FalconLite Model
FalconLite is a quantized version of the Falcon 40B SFT OASST-TOP1 model, capable of processing long (i.e. 11K tokens) input sequences while consuming 4x less GPU memory. By utilizing 4-bit GPTQ quantization and adapted dynamic NTK RotaryEmbedding, FalconLite achieves a balance between latency, accura... |
https://huggingface.co/amazon/sm-hackathon-actionability-9-multi-outputs-setfit-all-roberta-large-model-v0.1 | amazon/sm-hackathon-actionability-9-multi-outputs-setfit-all-roberta-large-model-v0.1
This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
Fine-tuning a Sentence Transformer with contrastive learning.
Training a classi... |
https://huggingface.co/amazon/LightGPT | LightGPT-instruct-6B Model
LightGPT-instruct is a language model based on GPT-J 6B. It was instruction fine-tuned on the high quality, Apache-2.0 licensed OIG-small-chip2 instruction dataset with ~200K training examples.
Model Details
Developed by: AWS Contributors
Model type: Transformer-based Language Model
Langua... |
https://huggingface.co/amazon/bort | ⚠️ Disclaimer ⚠️
This model is community-contributed, and not supported by Amazon, Inc.
BORT
Amazon's BORT
BORT is a highly compressed version of bert-large that is up to 10 times faster at inference. The model is an optimal sub-architecture of bert-large that was found using neural architecture search.
Paper
Abstrac... |
https://huggingface.co/cfarcas | C
cfarcas
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https://huggingface.co/mikegchambers | Mike Chambers
mikegchambers
mikegchambers
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https://huggingface.co/engincanmeydan | 1
Engincan Meydan
engincanmeydan
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https://huggingface.co/flash9001 | 3
flash9001
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BioMedLM
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https://huggingface.co/aastha6 | Aastha Varma
aastha6
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LLM: quantization, fine tuning, optimizations | NLP | Deep Learning
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https://huggingface.co/vvaaee | Vladimir Eremichev
vvaaee
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https://huggingface.co/berardin | Nick Berardi
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https://huggingface.co/nehanejh | Neha Jha
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nehanejh/demo
Updated Feb 1
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https://huggingface.co/sding | S Ding
sding
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https://huggingface.co/xingniu | Xing Niu
xingniu
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https://huggingface.co/solpatel | Sol Patel
solpatel
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https://huggingface.co/memopenaws | Luis Pena
memopenaws
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https://huggingface.co/haywse | Wooseok Ha
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hphu
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https://huggingface.co/jianfeili | Jeff Li
jianfeili
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https://huggingface.co/hasandemirkiran | Hasan Demirkiran
hasandemirkiran
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Computer Vision Graph Clustering Causal Inference Anomaly Detection
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https://huggingface.co/swarooprs | Swaroop Ramarao Satish
swarooprs
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https://huggingface.co/leonidp | Leonid Pishchulin
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https://huggingface.co/KannUN | Yunfang Guan
KannUN
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https://huggingface.co/crecaido | Charles
crecaido
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https://huggingface.co/wanghaod | 2
tony wang
wanghaod
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https://huggingface.co/redfiche | Robert Fisher
redfiche
SaRedfiche
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https://huggingface.co/robcost | 5
Rob Costello PRO
robcost
https://robcost.github.io/
robcost
robcost
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https://huggingface.co/cmlott | 2
Chris Lott
cmlott
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https://huggingface.co/dineshmane | 3
Dinesh Mane
dineshmane
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models 1
dineshmane/bert-finetuned-mrpc
Text Classification • Updated May 1, 2022 • 3
datasets
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https://huggingface.co/docs/hub/organizations-cards | Organization cards
You can create an organization card to help users learn more about what your organization is working on and how users can use your libraries, models, datasets, and Spaces.
An organization card is displayed on an organization’s profile:
If you’re a member of an organization, you’ll see a button to cre... |
https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face | Look at these smiles!
Today, we announce a strategic partnership between Hugging Face and Amazon to make it easier for companies to leverage State of the Art Machine Learning models, and ship cutting-edge NLP features faster.
Through this partnership, Hugging Face is leveraging Amazon Web Services as its Preferred Clou... |
https://huggingface.co/johnyi | John
johnyi
jyidiego
jyidiego
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https://huggingface.co/mkamp | Mariano Kamp
mkamp
mkamp
marianokamp
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models 1
mkamp/distilbert-base-uncased-finetuned-emotion
Updated Jan 22, 2022
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https://huggingface.co/portisto | 2
Luka Riester
portisto
portisto
portisto
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https://huggingface.co/facebook | Research interests
None defined yet.
Collections 1
SeamlessM4T
SeamlessM4T is designed to provide high quality translation, allowing people from different linguistic communities to communicate effortlessly.
Running ona100
683
📞
Seamless M4T
facebook/seamless-m4t-large
Updated 18 days ago • 427
facebook/seamless-m4t... |
https://huggingface.co/shulindt | 1
Lei Shu
shulindt
https://leishu02.github.io/
leishu02
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Language Model, NLP, Multi-modal Pretrained Model
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https://huggingface.co/sunbc0120 | Baichuan Sun
sunbc0120
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Generative AI, Computer Vision, LLMs/NLP, Reinforcement Learning
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https://huggingface.co/rafidka | Rafid Al-Humaimidi
rafidka
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Natural Language Processing, Computer Vision
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https://huggingface.co/rppth | Raj Pathak
rppth
Research interests
Named Entity Recognition Document Classification Text Generation
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https://huggingface.co/5cp | Scott Perry
5cp
5cp
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models 1
5cp/whisper-small-hi
Updated Dec 7, 2022
datasets
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https://huggingface.co/tomofi | Tomofumi Inoue
tomofi
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TensorFlow Certified Developer
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spaces 13
models 1 |
https://huggingface.co/Sa-m | 1 15
samarth
Sa-m
samarth70
Research interests
Deep Learning, NLP
Organizations
spaces 11
pinned
Runtime error
3
📈
Manifesto Explainer
Building
👁
Flask App Trial
Runtime error
2
👀
Political Party Symbol Detector V1
Runtime error
3
🐠
Vehicles Detection Custom YoloV7
🐨
Brand Logo Classification
1
🌖
YOLO V7 Cus... |
https://huggingface.co/tapas | Tapas Agarwal
tapas
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Deep Learning | Computer Vision | NLP | Multimodal Learning
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https://huggingface.co/pronoyc | Pronoy Chopra
pronoyc
https://pronoy.in
DarkSector
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IoT + AI/ML
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https://huggingface.co/sermolin | 2
Sergey Ermolin
sermolin
sermolin
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ML practice on AWS and other clouds
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