MAKOTO's repositories
accelerate
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
Chinese-LLaMA-Alpaca-2
中文LLaMA-2 & Alpaca-2大模型二期项目 + 64K超长上下文模型 (Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models)
Chinese-LLaMA-Alpaca-3
中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3
Chinese-Mixtral
中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs）
codellama
Inference code for CodeLlama models
DongwuLLM
This is the codebase for pre-training, compressing, extending, and distilling LLMs with Megatron-LM.
FastChat
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
grok-1
Grok open release
llama-moe
⛷️ LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training
llama.go
llama.go is like llama.cpp in pure Golang!
LLM-Pruner
[NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support LLaMA, Llama-2, BLOOM, Vicuna, Baichuan, etc.
LLM-Shearing
[ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
Megatron-LM
Ongoing research training transformer models at scale
Open-Sora
Open-Sora: Democratizing Efficient Video Production for All
promptulate_new
A large language model automation and Autonomous Language Agents development framework. Build your LLM Agent Application in a pythonic way!
Pruning-LLMs
The framework to prune LLMs to any size and any config.
k8s-vgpu-scheduler
OpenAIOS vGPU device plugin for Kubernetes is originated from the OpenAIOS project to virtualize GPU device memory, in order to allow applications to access larger memory space than its physical capacity. It is designed for ease of use of extended device memory for AI workloads.
Llama2-Code-Interpreter
Make Llama2 use Code Execution, Debug, Save Code, Reuse it, Access to Internet
LLaVA-pp
🔥🔥 LLaVA++: Extending LLaVA with Phi-3 and LLaMA-3 (LLaVA LLaMA-3, LLaVA Phi-3)
mixture-of-experts
PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538
MS-DOS
The original sources of MS-DOS 1.25, 2.0, and 4.0 for reference purposes
xllm
🦖 X—LLM: Cutting Edge & Easy LLM Finetuning