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GitHub / ray-project / ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-project%2Fray

Stars: 30,888
Forks: 5,218
Open Issues: 3,623

License: apache-2.0
Language: Python
Repo Size: 375 MB
Dependencies: 3,401

Created: over 7 years ago
Updated: 4 days ago
Last pushed: 22 days ago
Last synced: 22 days ago

Commit Stats

Commits: 20389
Authors: 1004
Mean commits per author: 20.31
Development Distribution Score: 0.935
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/ray-project/ray

Topics: automl, data-science, deep-learning, deployment, distributed, hyperparameter-optimization, hyperparameter-search, java, llm-serving, machine-learning, model-selection, optimization, parallel, python, pytorch, ray, reinforcement-learning, rllib, serving, tensorflow

Files
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    Readme
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    Dependencies
    • gym [accept-rom-license]
    • gymnasium [accept-rom-license, atari]==0.26.3
    • ray [rllib]==2.5.0
    • gym [accept-rom-license]
    • gymnasium [accept-rom-license, atari]==0.26.3
    • ray [rllib]==2.5.0