Nvalchemi Fine Tuning
NVIDIA/nvalchemi-toolkit/.claude/skills/nvalchemi-fine-tuning
ai-mlOfficial
Official Provider SkillView repo
How to fine-tune nvalchemi-compatible models with FineTuningStrategy, pretrained checkpoint initialization, module patches, trainable-parameter filters, conservative optimizer defaults, validation, restart checkpoints, and model-agnostic MACE, AIMNet2, custom BaseModelMixin, or PyTorch inputs. Use when adapting a pretrained MLIP (e.g. MACE-MP) to new reference data, freezing or patching submodules during training, or resuming an interrupted fine-tune from a checkpoint.
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Skill details
Versionv1.0.0
AuthorNVIDIA
Categoryai-ml
Skill IDNVIDIA/nvalchemi-toolkit/.claude/skills/nvalchemi-fine-tuning
Related skills
Nvalchemi Data StorageHow to write, read, compose, and load atomic data using nvalchemi's composable Zarr-backed storage pipeline (Writer, Reader, Dataset, MultiDataset, DataLoader). Use when saving simulation outputs or trajectories to disk, converting structures (e.g. ASE / extxyz) into Zarr stores, assembling datasets for training or inference, or wiring a DataLoader to stream batches to the GPU.Nvalchemi Data StructuresHow to use AtomicData and Batch, the core graph-based data structures for representing atomic systems and batching them for GPU computation. Use when building systems from positions, cells, and atomic numbers, converting from ASE Atoms, batching or unbatching structures, reading per-atom vs per-graph tensors, or debugging shape, dtype, or device errors in model inputs.Nvalchemi Dynamics ApiHow to configure and run dynamics simulations, compose multi-stage pipelines (FusedStage, DistributedPipeline), use inflight batching, and manage data sinks. Use when writing any simulation script — molecular dynamics (NVE/NVT), structure relaxation or geometry optimization (e.g. FIRE), equation-of-state or adsorption scans — or orchestrating many structures through a batched GPU pipeline.Nvalchemi Dynamics HooksHow to use and write dynamics hooks — callbacks that observe or modify batch state at specific points during each simulation step. Use when a simulation needs neighbor-list rebuilds, convergence checks or early stopping, temperature control, per-step logging or trajectory capture, or any custom per-step behavior attached to a dynamics run.Nvalchemi Dynamics ImplementationHow to implement a dynamics integrator by subclassing BaseDynamics and overriding pre_update() and post_update() methods. Use when creating a custom integrator, optimizer, or sampler that the built-in stages do not provide; for configuring existing dynamics, see nvalchemi-dynamics-api.Nvalchemi Loss ApiHow to use built-in loss functions and implement custom losses using the BaseLossFunction template-method pattern — residual types, per-atom normalization, masking, and graph-balanced reductions. Use when choosing or weighting energy, force, or stress objectives for training or fine-tuning, masking atoms or graphs out of the loss, or writing a custom loss term.