-
huggingface
- Brussels
-
18:20
(UTC -12:00) - @ben_burtenshaw
- in/ben-burtenshaw
- https://huggingface.co/burtenshaw
Stars
A simple, in-browser, markdown-driven slideshow tool.
π¦ CLI tool for making HTML presentations with Remark.js using Markdown
A macOS app that provides an MCP server to your Messages, Contacts, Reminders and more
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
"LightRAG: Simple and Fast Retrieval-Augmented Generation"
This package contains the original 2012 AlexNet code.
MCP Server to Use HuggingFace spaces, easy configuration and Claude Desktop mode.
Finetune Qwen3, Llama 4, TTS, DeepSeek-R1 & Gemma 3 LLMs 2x faster with 70% less memory! π¦₯
State-of-the-art Machine Learning for the web. Run π€ Transformers directly in your browser, with no need for a server!
Fully open reproduction of DeepSeek-R1
π Accelerate inference and training of π€ Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools
π A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
π€ PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
π€ The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
π€ Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
π€ Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
The python library for real-time communication
The package used to build the documentation of our Hugging Face repos
This repository contains the Hugging Face Agents Course.
The official Python client for the Huggingface Hub.
A course on aligning smol models.
π€ smolagents: a barebones library for agents that think in python code.
π€ LeRobot: Making AI for Robotics more accessible with end-to-end learning
A library for working with prompt templates locally or on the Hugging Face Hub.
Build datasets using natural language