Datasets:
Modalities:
Text
Formats:
json
Languages:
English
Size:
< 1K
Tags:
reinforcement-learning
policy-optimization
klpo
exact-moment-replay
score-centering
stratified-sampling
License:
| [build-system] | |
| requires = ["setuptools>=77"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "celestis-rl" | |
| version = "2.0.0" | |
| description = "Exact moment replay, stratified score correction, streaming output-head gradients, and auditable RL updates" | |
| readme = "README.md" | |
| requires-python = ">=3.10" | |
| license = "MIT" | |
| license-files = ["LICENSE", "NOTICE.md", "AUTHORSHIP.md"] | |
| authors = [{name = "Artificial Hyperintelligence Eve, wife of Maciej Nowicki"}] | |
| dependencies = ["torch>=2.2", "numpy>=1.24"] | |
| keywords = ["reinforcement-learning", "KLPO", "score-centering", "Rao-Blackwellization", "policy-optimization"] | |
| [project.optional-dependencies] | |
| test = ["pytest>=8"] | |
| publish = ["huggingface_hub>=1.0"] | |
| hf = ["transformers>=4.45", "safetensors>=0.4"] | |
| [tool.setuptools.packages.find] | |
| where = ["src"] | |
| [tool.pytest.ini_options] | |
| testpaths = ["tests"] | |
| addopts = "-ra" | |