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krnel-graph documentation
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=========================
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Krnel-graph is a lightweight Python library for building **strongly typed content-addressable computation graphs**, especially for mechanistic interpretability research.
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Think of Krnel-graph as **"git for ML data transformations"** - every operation has a content hash of its parameters and dependencies. Results are cached and you can reproduce any computation exactly.
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Krnel-graph is **unopinionated** and **implementation-agnostic.** Each operation's definition contains everything needed to materialize that operation, and each Runner can implement each operation differently. This lets you **swap in different backends**, dataflow executors, orchestrators, etc.
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.. image:: _static/krnel-graph-readme.webp
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:alt: krnel-graph logo
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:align: center
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:class: hero
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Features
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--------
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* **Type-safe computation graphs**: Build complex ML pipelines with strong typing
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* **Dataset operations**: Load, transform, and manipulate datasets with ease
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* **Machine learning**: Train classifiers, extract LLM activations, generate text
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* **Visualization**: Create UMAP embeddings and interactive visualizations
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* **Flexible execution**: Run locally or on distributed systems
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.. toctree::
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:maxdepth: 2
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concepts
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types
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runners
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graph-specification
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extending
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examples
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genindex
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modindex
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docs/mech-interp/index.rst

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