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🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
500 AI Machine learning Deep learning Computer vision NLP Projects with code
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
🦭 Video/Audio Downloader for Android, based on yt-dlp, designed with Material You
Python library for portfolio optimization built on top of scikit-learn
The PyTorch-based audio source separation toolkit for researchers
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Learn Low Level Design (LLD) and prepare for interviews using free resources.
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Notebooks using the Hugging Face libraries 🤗
Jupyter notebooks for the Natural Language Processing with Transformers book
This repository contains demos I made with the Transformers library by HuggingFace.
The fastai book, published as Jupyter Notebooks
手把手带你实战 Huggingface Transformers 课程视频同步更新在B站与YouTube
A multi-platform desktop application to evaluate and compare LLM models, written in Rust and React.
CodeGen is a family of open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.
OpenCodeInterpreter is a suite of open-source code generation systems aimed at bridging the gap between large language models and sophisticated proprietary systems like the GPT-4 Code Interpreter. …
DeepSeek Coder: Let the Code Write Itself
Your Next SaaS Template or Boilerplate ! A magic trip start with `bun create saasfly` . The more stars, the more surprises
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Get up and running with Llama 3.1, Mistral, Gemma 2, and other large language models.
SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.47% of bugs in the SWE-bench evaluation set and takes just 1 minute to run.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Learn System Design concepts and prepare for interviews using free resources.