Xuechen Li (lxuechen)

lxuechen

Geek Repo

Company:Stanford University

Home Page:www.lxuechen.com

Twitter:@lxuechen

Github PK Tool:Github PK Tool


Organizations
lxuechen-org
stanford-crfm
stanfordnlp
VectorInstitute

Xuechen Li's repositories

ml-swissknife

An ML research codebase built with friends :)

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LLM-Training-Puzzles

What would you do with 1000 H100s...

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minRLHF

A minimal PyTorch re-implementation of RLHF

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accelerate

🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

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awesome-ai-agents

A list of AI autonomous agents

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bitsandbytes

8-bit CUDA functions for PyTorch

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build-your-own-x

Master programming by recreating your favorite technologies from scratch.

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codegpt

VSCode extension that allows you to use GPT3 inside the IDE

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FastChat

An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.

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flash-attention

Fast and memory-efficient exact attention

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label-studio-ml-backend

Configs and boilerplates for Label Studio's Machine Learning backend

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levanter

Legibile, Scalable, Reproducible Foundation Models with Named Tensors and Jax

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Megatron-LM

Ongoing research training transformer models at scale

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open_flamingo

An open-source framework for training large multimodal models.

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peft

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

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RL4LMs-lxuechen

A modular RL library to fine-tune language models to human preferences

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self-instruct

Aligning pretrained language models with instruction data generated by themselves.

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shap

A game theoretic approach to explain the output of any machine learning model.

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summarize-from-feedback

Code for "Learning to summarize from human feedback"

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tensor_parallel

Automatically split your PyTorch models on multiple GPUs for training & inference

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thesis

my thesis

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transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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trl-lxuechen

Train transformer language models with reinforcement learning.

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vllm

A high-throughput and memory-efficient inference and serving engine for LLMs

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