This repository is a curated list of open-source alternatives to ChatGPT, focusing on models fine-tuned for instruction following and chat. It targets developers and researchers seeking to replicate or build upon conversational AI capabilities without relying on proprietary solutions. The primary benefit is providing a centralized resource for discovering and evaluating truly open alternatives.

How It Works

The list categorizes projects based on their openness and completeness, using tags like "Bare" (code only), "Standard" (data, weights, API chat), "Full" (data, weights, UI), and "Complicated" (partially open or closed models). This classification helps users quickly assess the suitability of each project for their needs, from basic model experimentation to full-fledged chatbot deployment.

Quick Start & Requirements

• Installation and usage vary significantly per project. Refer to individual project READMEs for specific commands and dependencies.
• Many projects require substantial GPU resources (e.g., 6GB+ VRAM for quantized models like ChatGLM-6B), specific Python versions, and potentially large datasets for fine-tuning.
• Links to official documentation, demos, and Hugging Face model pages are often provided within the list.

Highlighted Details

• Comprehensive coverage of LLaMA-derived projects, including fine-tuning methods (LoRA) and CPU inference ports (llama.cpp).
• Includes projects focused on specific languages (e.g., BELLE for Chinese) and architectures (e.g., ChatRWKV using RNNs).
• Features projects with integrated chat systems (TUI/GUI) and those focused solely on model weights and APIs.
• Highlights models explicitly licensed for commercial use (e.g., Databricks Dolly v2).

Maintenance & Community

• The list is maintained by nichtdax and includes contributions from various research institutions and companies (e.g., LAION-AI, Stability AI, Databricks, THUDM).
• Community interaction points like Reddit (r/OpenAssistant) and specific project Discord/Slack channels are sometimes linked.

Licensing & Compatibility

• Licenses vary widely, from permissive Apache 2.0 (Cerebras-GPT) to more restrictive ones. Some projects are based on LLaMA, whose original license had non-commercial restrictions.
• Commercial use compatibility depends heavily on the specific project's licensing and the base model's license. Projects like Dolly v2 are explicitly noted as commercially usable.

Limitations & Caveats

• The "Complicated" tag indicates projects that may not be fully open-source or rely on closed-source components, requiring careful vetting.
• Many projects are research-oriented and may require significant technical expertise for setup, fine-tuning, and deployment.
• Performance and quality can vary greatly between listed alternatives.