Starred repositories
Tokenize the Stock Price and then apply Generative LLM.
A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 and reasoning techniques.
Python Backtesting library for trading strategies
🥜 A Self-Compiling C Transpiler Targeting Human-Readable POSIX Shell
Library for fast text representation and classification.
The official evaluation suite and dynamic data release for MixEval.
An educational resource to help anyone learn deep reinforcement learning.
The simplest, fastest repository for training/finetuning medium-sized GPTs.
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
A barebones transactional in-memory key: value store with a REPL [For educational purposes]
A one-stop data processing system to make data higher-quality, juicier, and more digestible for (multimodal) LLMs! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷为大模型提供更高质量、更丰富、更易”消化“的数据！
Explorations into some recent techniques surrounding speculative decoding
GPT-Fathom is an open-source and reproducible LLM evaluation suite, benchmarking 10+ leading open-source and closed-source LLMs as well as OpenAI's earlier models on 20+ curated benchmarks under al…
screenshots leetcode editorials and problems
Awesome LLM compression research papers and tools.
Asynchronous event I/O driven quantitative trading framework.
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
A large-scale 7B pretraining language model developed by BaiChuan-Inc.
Fast and memory-efficient exact attention
A collection of phenomenons observed during the scaling of big foundation models, which may be developed into consensus, principles, or laws in the future
Implementation of MEGABYTE, Predicting Million-byte Sequences with Multiscale Transformers, in Pytorch
Best Practices on Recommendation Systems
Adam1679 / backtesting.py
Forked from kernc/backtesting.py🔎 📈 🐍 💰 Backtest trading strategies in Python.
Streamlit — A faster way to build and share data apps.
24 Lessons, 12 Weeks, Get Started as a Web Developer
Best Practices on Recommendation Systems
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all