2 个仓库
Awesome GitHub RepositoriesLLM Format Converters
Tools for transforming large language models into formats optimized for local hardware.
Distinct from Model Conversion: Specializes in LLM-specific conversions rather than general model format transformations
Explore 2 awesome GitHub repositories matching devops & infrastructure · LLM Format Converters. Refine with filters or upvote what's useful.
Awesome LLM Format Converters GitHub Repositories
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- microsoft/vscode-copilot-chat
microsoft/vscode-copilot-chat
9,493在 GitHub 上查看This project is an AI-powered IDE extension and LLM coding assistant that provides a conversational interface for generating, refactoring, and debugging code. It functions as an AI agent framework and a Model Context Protocol client, connecting AI models to external data sources and tools to automate complex development tasks. The system is distinguished by its use of autonomous AI agents capable of multi-step task execution, including the ability to read files, modify code, and run terminal commands iteratively. It supports recursive agent orchestration through subagent delegation and employ
Transforms large language models for local use by leveraging local GPU resources.
TypeScript - b4rtaz/distributed-llama
b4rtaz/distributed-llama
2,837在 GitHub 上查看Distributed-llama is a distributed inference engine and command line tool for running large language models across multiple networked machines. It functions as a compute cluster manager that coordinates worker nodes to share the computational load of a single model. The system utilizes tensor parallelism to shard model weights across different hosts, allowing the execution of models that exceed the memory capacity of a single piece of hardware. It includes a dedicated format converter to transform standard model files into a compatible binary layout optimized for distributed loading. The eng
Transforms large language models into specialized formats optimized for distributed inference on private hardware.
C++distributed-computingdistributed-llmllama2
