A simple, traceable workspace methodology and setup tool for AI research projects, shared data, runs, and checkpoints.
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Updated
Jul 16, 2026 - Python
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checkpoint-management
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ML training orchestration for the Crucible ecosystem. Distributed training, hyperparameter optimization, checkpointing, model versioning, metrics collection, early stopping, LR scheduling, gradient accumulation, and mixed precision training with Nx/Scholar integration.
machine-learning elixir phoenix research ai deep-learning metrics neural-networks hyperparameter-optimization gradient-descent nx model-training distributed-training scholar mlops ml-ops experiment-tracking training-framework nshkr-crucible checkpoint-management
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Updated
Jul 16, 2026 - Elixir
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