Consolidate MIC usage, slim weights and reviewed framework expectations

44b77c4 verified 1 day ago

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---
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](https://huggingface.co/hf-internal-testing/table_transformer-integration), covering [`microsoft/table-transformer-detection`](https://huggingface.co/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`](https://github.com/huggingface/model-integration-contracts/blob/main/experiments/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`](https://github.com/huggingface/transformers-mic/blob/main/example/build_fixtures.py); [`build.json`](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`.

	---
	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](https://huggingface.co/hf-internal-testing/table_transformer-integration), covering [`microsoft/table-transformer-detection`](https://huggingface.co/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`](https://github.com/huggingface/model-integration-contracts/blob/main/experiments/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`](https://github.com/huggingface/transformers-mic/blob/main/example/build_fixtures.py); [`build.json`](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`.