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AI conversational assistant for answering questions, writing, and coding help
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Open-source chat assistant built through collaborative human feedback
A completed open-source project that created a chat-based large language model assistant through crowdsourced data collection and reinforcement learning from human feedback (RLHF).
Open Assistant was a community-driven initiative to democratize access to advanced conversational AI by building a chat-based large language model through open collaboration. The project has now concluded, with its final dataset (oasst2) publicly available on HuggingFace.
The project followed a three-phase methodology inspired by InstructGPT: collecting high-quality human-generated instruction-response pairs through crowdsourcing, ranking multiple completions to train a reward model, and applying reinforcement learning from human feedback (RLHF). Contributors participated through dedicated web interfaces for data collection, prompt submission, response ranking, and quality labeling.
Built with Python and TypeScript, Open Assistant aimed to create more than a ChatGPT alternative—the vision encompassed an extensible assistant capable of API integration, dynamic research, and personalization. While the project is complete, it demonstrated how collaborative open-source efforts can produce valuable AI resources. The resulting dataset and learnings continue to benefit the broader AI community, embodying the belief that shared knowledge advances innovation in natural language processing.
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Training Data for Custom Assistants
Leverage the oasst2 dataset to fine-tune or evaluate custom conversational models with human-ranked responses
RLHF Research and Experimentation
Study and replicate the three-phase InstructGPT-inspired methodology for academic or commercial research
Open-Source AI Benchmarking
Use the dataset and model artifacts as baselines for comparing new conversational AI approaches
Educational AI Development
Learn collaborative AI development practices by exploring the codebase, documentation, and contribution patterns
No, the project is completed and no longer under active development. The team has published the final oasst2 dataset on HuggingFace for community use.
The local setup is designed for development contributions, not end-user chatbot deployment. Running inference locally requires technical expertise and is not intended as a consumer-ready solution.
The final oasst2 dataset is publicly available on HuggingFace at OpenAssistant/oasst2 under the Apache-2.0 license.
The project used crowdsourced prompt submission, response generation, and multi-user ranking with quality controls to build training data, following a three-phase RLHF approach inspired by InstructGPT.
Since the project is completed, new contributions are not being accepted. However, the codebase and dataset remain available for forking, adaptation, and research under the Apache-2.0 license.
Project at a glance
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