luke-base-mic

Slim model weights, executable usage and framework expectations in one repository.

• Contract manifest
• Transformers usage
• Transformers expectations
• Fixture provenance
• How the fixture was shrunk

Contract

LUKE masked language modeling

Runnable usage and the framework expectations directory are linked above.

Slim model

Slim fixture: luke-base-mic

A 10.2M-parameter fixture for the LUKE MIC, covering studio-ousia/luke-base. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.

• Fixture key c9b636bf3b64. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
• Same architecture, smaller config: LukeForMaskedLM, shrunk by the generic rule in sweep.py (num_hidden_layers 2).
• Processor files copied byte for byte from studio-ousia/luke-base: added_tokens.json, entity_vocab.json, merges.txt, special_tokens_map.json, tokenizer_config.json, vocab.json.
• Random weights (seed 17). They passed the input-sensitivity gate: every perturbation of the contract's inputs moved the logits by at least 0.001 (weakest: attention_mask:all_ones, 0.00396), so no training was needed.
• Same tensor names as the real checkpoint. The real checkpoint lacks lm_head.decoder.weight, so the fixture omits it too, and loading initializes it as it does for users.
• Saved in float32, the dtype studio-ousia/luke-base loads in by default.
• Finite in float32, bfloat16, and float16 (forward, loss, gradients).

Built by build_fixtures.py; build.json records the pinned sources, gate results, and file hashes. This repository includes the slim weights, usage and framework expectations; rebuild the other files with python example/build_fixtures.py --fixture luke-base-mic.