1.rohitg00 / ai-engineering-from-scratch
Learn AI Engineering! Learn it. Build it. Ship it for others.
Ranked by Attention Score: stars gained over the last 30 complete days
30 repositories by Attention Score · Oct 4, 2026 – Nov 2, 2026 (UTC)
Learn AI Engineering! Learn it. Build it. Ship it for others.
21 Lessons, Get Started Building with Generative AI
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Machine Learning Engineering Open Book
Turn any LLM into a Jev-style decision model: typed decisions, real probabilities, no training. (continue updating, welcome any issue and PR request)
Ongoing research training transformer models at scale
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
Open source real-time translation app for Android that runs locally
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Open-source offline translation library written in Python
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
CVPR 2026 论文和开源项目合集
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
A PyTorch-based Speech Toolkit
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
This repository contains demos I made with the Transformers library by HuggingFace.
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, DeepSeek, Mixtral, Gemma, Phi, MiniCPM, Qwen-VL, MiniCPM-V, etc.) on Intel XPU (e.g., local PC with iGPU and NPU, discrete GPU such as Arc, Flex and Max); seamlessly integrate with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, vLLM, DeepSpeed, Axolotl, etc.
Superduper: End-to-end framework for building custom AI applications and agents.
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
Seamlessly integrate LLMs into scikit-learn.
State of the Art Natural Language Processing
🦖 𝗟𝗲𝗮𝗿𝗻 about 𝗟𝗟𝗠𝘀, 𝗟𝗟𝗠𝗢𝗽𝘀, and 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀 for free by designing, training, and deploying a real-time financial advisor LLM system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 𝘷𝘪𝘥𝘦𝘰 & 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴
Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.