Jin Chi He's repositories
aider
aider is AI pair programming in your terminal
Awesome-LLM
Awesome-LLM: a curated list of Large Language Model
AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
awesome-ai-agents
A list of AI autonomous agents
ChatGLM2-6B
ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
cloud-provider-plugins
Location of cloud provider plugins for LSF Resource Connector
DeepSpeed-MII
MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.
DeepSpeedExamples
Example models using DeepSpeed
getting-started
Getting Started Material
h2o-llmstudio
H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://h2oai.github.io/h2o-llmstudio/
langchain
⚡ Building applications with LLMs through composability ⚡
Langchain-Chatchat
Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM) QA app with langchain | 基于 Langchain 与 ChatGLM 等语言模型的本地知识库问答
litellm
Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
llama_index
LlamaIndex is a data framework for your LLM applications
MetaGPT
🌟 The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo
pr-agent
🚀CodiumAI PR-Agent: An AI-Powered 🤖 Tool for Automated Pull Request Analysis, Feedback, Suggestions and More! 💻🔍
ragflow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
scaphandre
⚡ Energy consumption metrology agent. Let "scaph" dive and bring back the metrics that will help you make your systems and applications more sustainable !
SWE-agent
SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.29% of bugs in the SWE-bench evaluation set and takes just 1.5 minutes to run.
training-operator
Training operators on Kubernetes.
Working
The repo is to public some document or code for kubeflow from my investigation.