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[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.

LLMs-from-scratch项目中文翻译

中文翻译的 Hands-On-Large-Language-Models (hands-on-llms)，动手学习大模型

A library for debugging/inspecting machine learning classifiers and explaining their predictions

We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！

Benchmarking large language models' complex reasoning ability with chain-of-thought prompting

Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads

Model API for GALACTICA

机器学习、深度学习的学习路径及知识总结

Practice to LLM.

FMA: A Dataset For Music Analysis

Jupyter extensions that help you write code faster: Context aware AI Chat, Autocomplete, and Spreadsheet

Machine Learning in Finance: From Theory to Practice Book

The /llms.txt file, helping language models use your website

Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.

Algorithms for outlier, adversarial and drift detection

动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor.

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

Code and Slides

Doing simple retrieval from LLM models at various context lengths to measure accuracy

Mastering Applied AI, One Concept at a Time

Machine Learning Journal for Intermediate to Advanced Topics.

Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.

This is a workshop designed for Amazon Bedrock a foundational model service.

Repository containing notebooks of my posts on Medium