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Merge pull request #178 from ausimian/feat/expr-compiler-livebooks-rename
Rename notebooks/ → livebooks/
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README.md

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Bumblebee inference works with no further configuration once the
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backend is installed — see the conformance suites under
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`test/emily/conformance/` for worked DistilBERT, Qwen3, ViT, and
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Whisper pipelines, and the Notebooks section of the HexDocs nav for
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Whisper pipelines, and the Livebooks section of the HexDocs nav for
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runnable Livebooks.
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The low-level tensor API (`Emily.from_binary/3`, `to_binary/1`,
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`shape/1`, `dtype/1`, `eval/1`) remains available for diagnostics
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and direct MLX round-trips, but most users should go through Nx.
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## Notebooks
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## Livebooks
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End-to-end Livebooks under `notebooks/`. Each one declares its own
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End-to-end Livebooks under `livebooks/`. Each one declares its own
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`Mix.install/2` block and pins `Emily.Backend` as the default Nx
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backend, so they're self-contained — open in Livebook and run.
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process wraps the call in `Emily.Stream.with_stream/2` and whether
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you run one serving or many.
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See `Emily.Stream` for the API and the `qwen3_quantized` notebook
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under Notebooks for a worked multi-stream example.
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See `Emily.Stream` for the API and the `qwen3_quantized` livebook
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under Livebooks for a worked multi-stream example.
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## Observability
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## Documentation
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* [HexDocs](https://hexdocs.pm/emily) — per-module API docs and
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runnable notebooks.
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runnable livebooks.
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* [`ARCHITECTURE.md`](ARCHITECTURE.md) — current shape of the
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library: layer boundaries, design decisions, concurrency and
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memory model, observability surface.

ROADMAP.md

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* `CHANGELOG.md` accumulated across releases (it is, since 0.3.0).
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* `MAINTAINING.md` reflects the precompiled-NIF release flow (it
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does, since 0.3.0).
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* Worked Bumblebee + quantized-Qwen3 examples in `notebooks/`
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(present and grouped in the HexDocs Notebooks section).
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* Worked Bumblebee + quantized-Qwen3 examples in `livebooks/`
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(present and grouped in the HexDocs Livebooks section).
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## Overview
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The other notebooks in this repo run pretrained models forward. This
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The other livebooks in this repo run pretrained models forward. This
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one trains from scratch — a small Axon MLP on MNIST, lowered through
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`Emily.Compiler` so every step of the backward pass dispatches to
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MLX. It's the end-to-end exercise of the `Nx.Defn.grad` chain that
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