Python modules and jupyter notebook examples for the paper Arbitrage-free Neural-SDE Market Models.

Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.

Distributed Reinforcement Learning accelerated by Lightning Fabric

Building a fast matching engine in Rust for efficient processing of an ITCH order book.

JAX-accelerated Meta-Reinforcement Learning Environments Inspired by XLand and MiniGrid 🏎️

Awesome Aleo mining and development resources maintained by MinerDAO community.

LaVie: High-Quality Video Generation with Cascaded Latent Diffusion Models

Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）

Machine Learning Engineering Open Book

Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

3D Visualization of an GPT-style LLM

📖A curated list of Awesome LLM Inference Paper with codes, TensorRT-LLM, vLLM, streaming-llm, AWQ, SmoothQuant, WINT8/4, Continuous Batching, FlashAttention, PagedAttention etc.

MIDI / symbolic music tokenizers for Deep Learning models 🎶

Efficient baselines for autocurricula in JAX.

A step-by-step tutorial of QuantumFlow, using the MNIST sub-dataset {3,6} and the 16-2-2 neural network as an example.

Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.

Multi-Agent Reinforcement Learning with JAX

https://acl2023-retrieval-lm.github.io/

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…

Robust recipes to align language models with human and AI preferences

Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with …

Create LLM agents with long-term memory and custom tools 📚🦙

F3RM: Feature Fields for Robotic Manipulation. Official repo for the paper "Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation" (CoRL 2023).

《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新，English version ongoing

Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.

Distilled variant of Whisper for speech recognition. 6x faster, 50% smaller, within 1% word error rate.

Adding guardrails to large language models.

Single Image to 3D using Cross-Domain Diffusion for 3D Generation