t5-mic / docs /source-cards /fixture.md
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Consolidate MIC usage, slim weights and reviewed framework expectations
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metadata
tags:
  - mic
  - test-artifact
base_model: google-t5/t5-small

Slim fixture: mic-t5-slim

A 2.2M-parameter fixture for the t5 MIC, covering google-t5/t5-small. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.

  • Fixture key c5306fc18451. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
  • Same architecture, smaller config: T5ForConditionalGeneration, shrunk by the generic rule in sweep.py (num_layers 2, num_decoder_layers 2).
  • Processor files copied byte for byte from google-t5/t5-small: generation_config.json, spiece.model, tokenizer.json, tokenizer_config.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, 1.28), so no training was needed.
  • Same tensor names as the real checkpoint. The real checkpoint has every parameter, and so does the fixture.
  • Saved in float32, the dtype google-t5/t5-small 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. The source repository commits only README.md and build.json; rebuild the other files with python example/build_fixtures.py --fixture mic-t5-slim.