policy
criteriaforreward
Mukullight · PyTorch
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Overview
Name
criteriaforreward
Author
Mukullight
Framework
PyTorch
License
MIT
Skill type
manipulation
Evidence level
untested
Task description
the following repository contains the code for finetuning the reward models using ranked human preference it helps stream line the process by which the human feedback can be easily integrated into the rl based fine tuning for llm alignment
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
3+17 mentioned but not in catalog yetCompatible environments
0No environments list criteriaforreward yet.
Datasets that reference this policy
0No datasets reference criteriaforreward yet.