First public release.
compile_hf_bundleandsave_hf_bundlenow writegeneration_config.json(pad token aliased to eos), sogenerate()andpipeline()run without an explicitpad_token_id.
compile_to_hfandcompile_hf_bundlenow default to the typedCompileProfile.PHI3contract: SwiGLU, biasless projections, RMSNorm, and a stockPhi3ForCausalLMbundle with no remote code.- The former custom classes were renamed to
TorchwrightCustomConfig,TorchwrightCustomModel, andTorchwrightCustomForCausalLM; their modules are nowconfiguration_torchwright_custom.pyandmodeling_torchwright_custom.py. - The custom tokenizer is now
TorchwrightCustomTokenizerintokenization_torchwright_custom.py. - Custom model generation requires the explicit
architecture="custom"profile andtrust_remote_code=Truewhen loading a published bundle. - The ONNX-to-HF converter,
save_bundle(onnx_path, ...), andread_vocabwere removed. Recompile source graphs directly to HF. - The obsolete
calculator_v2compatibility name was removed; useexamples.calculator_simple. - HF bundle builders now stage and validate a complete bundle before replacing the destination. A failed compile leaves an existing published bundle untouched, and successful recompilation removes stale files.
- Token compilation now requires exactly one
Embeddingreachable from the output and verifies that it is the same node supplied to the HF API. - Schedule metadata distinguishes the emitted schedule and its certified optimality from the independent CP-SAT attempt that proposed a candidate.
compile_hf_bundlereturns an immutableHFBundleReportcontaining the published output directory, layer count, and typed selected-schedule provenance.
There are intentionally no compatibility aliases. Pin an older release to load historical Python APIs, or recompile the source graph with the current compiler.