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Des workflows originaux pour sites web, images, présentations et animations.

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Rapid MLX benchmark comparison
Tarif non précisé
Tests et sécurité

Rapid MLX Performance Workflow

Investigate Rapid MLX performance, prototype changes, benchmark results, and prepare reviewed improvements.

4,1 kÉtoiles441Forks
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Ponytail code reuse example
Gratuit
Tests et sécurité

Ponytail: Benchmark Scoreboard

Display Ponytail’s recorded benchmark results for code size, cost and execution speed.

189,4 kÉtoiles10,5 kForks
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Field-tested methodology and concrete recipes for training and operating large-scale LLM/VLM/multi-modal models end to end - choosing and benchmarking accelerators, storage and network; SLURM/Kubernetes orchestration; maximizing training throughput and fitting models in memory; diagnosing and surviving training instabilities, NaN/Inf, and hardware/job failures; checkpointing and fault tolerance; inference…

  • machine-learning
  • development
19,7 kÉtoiles1,3 kForks
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Apply practical large-model training and operations guidance, and evaluate GPU cluster performance and readiness.

  • machine-learning
  • benchmarking
19,7 kÉtoiles1,3 kForks
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Evaluates an ML GPU cluster for a cloud trial or acceptance test: environment dump, isolated newest PyTorch, matmul FLOPS (MAMF/MSMF) on every GPU while the others compute, intra-node all-reduce bandwidth and per-call latency of every collective, the same inter-node on every node you were given (omit those sections if there is only one node), fio on local disk and shared FS, dated markdown report.

  • benchmarking
  • machine-learning
19,7 kÉtoiles1,3 kForks
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Une petite bibliothèque créée avec soin. D’autres skills arrivent bientôt.