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tarekziade HF Staff
Consolidate MIC usage, slim weights and reviewed framework expectations
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metadata
tags:
  - mic
  - test-artifact
base_model: microsoft/table-transformer-detection

Slim fixture: mic-table_transformer-slim

A 11.4M-parameter fixture for the table_transformer MIC, covering microsoft/table-transformer-detection. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.

  • Fixture key 39c20ea7dc73. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
  • Same architecture, smaller config: TableTransformerForObjectDetection, shrunk by the generic rule in sweep.py (encoder_layers 2, decoder_layers 2).
  • Processor files copied byte for byte from microsoft/table-transformer-detection: preprocessor_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: pixel_values:reverse, 0.00502), 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 microsoft/table-transformer-detection 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-table_transformer-slim.