GitHub / LambdaLabsML / distributed-training-guide
Best practices & guides on how to write distributed pytorch training code
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LambdaLabsML%2Fdistributed-training-guide
PURL: pkg:github/LambdaLabsML/distributed-training-guide
Stars: 425
Forks: 34
Open issues: 2
License: mit
Language: Python
Size: 429 KB
Dependencies parsed at: Pending
Created at: 11 months ago
Updated at: 27 days ago
Pushed at: 4 months ago
Last synced at: 26 days ago
Commit Stats
Commits: 227
Authors: 4
Mean commits per author: 56.75
Development Distribution Score: 0.172
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/LambdaLabsML/distributed-training-guide
Topics: cluster, cuda, deepspeed, distributed-training, fsdp, gpu, gpu-cluster, kuberentes, lambdalabs, mpi, nccl, pytorch, sharding, slurm