| {"node":{"id":"urn:cid:bafkr4ieqv4gkv6vvpb3twx2qdrg3p76evukyhgbtc6zyqo4cmktx6fj56q","properties":{"registeredBy":"did:key:z6MkutbV1GPZLLquVDwfVrkHcJezwvvCp92RmL1MGdvN4J5P","timestamp":"2024-01-18T04:36:05Z","nodeType":"data","dataRegistrationJcs":"urn:cid:baga6yaq6ebhgvoqqmvtq635kgbbwoo4r67mnqx62sj6fjugl6tiauijrihzji"}},"enrichments":{"asset_hub":{"asset_id":149,"asset_name":"AppTek's RLHF Climate Feedback/Training Data","owning_project":"EQTY ClimateGPT","asset_description":"AppTek's RLHF (Reinforcement Learning from Human Feedback) Climate Feedback/Training Data is a meticulously curated dataset designed for improving the performance and responsiveness of ClimateGPT-40B. Leveraging a policy optimizer for human feedback, this dataset captures a wide spectrum of human-climate interactions, feedback loops, and decision-making nuances related to climate change. The RLHF approach ensures that the model's responses are aligned with human values and provides better, more relevant, and context-aware outputs.","asset_format":"Dataset (CSV, JSON, etc.)","asset_type":"Code","asset_blob_type":"","source_location_url":"","contact_info":"Via AppTek community or associated paper authors","license":"Custom License - Refer to the official site for terms.","license_link":"https://apptek.com/rlhf-climate-feedback-license","registered_date":"2024-01-18T04:49:09.582926Z","last_modified_date":"2024-01-18T04:49:09.582926Z"}}} |