docs/source-cards/fixture.md

---
tags:
  - mic
  - test-artifact
base_model: stepfun-ai/GOT-OCR-2.0-hf
---

# Slim fixture: mic-got_ocr2-slim

A 13.0M-parameter fixture for the [got_ocr2 MIC](https://huggingface.co/hf-internal-testing/got_ocr2-integration), covering [`stepfun-ai/GOT-OCR-2.0-hf`](https://huggingface.co/stepfun-ai/GOT-OCR-2.0-hf). It is a test artifact, not a usable model, tagged `test-artifact` to keep it out of candidate-model search.

- **Fixture key `6141fa8be862`.** It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
- **Same architecture, smaller config:** `GotOcr2ForConditionalGeneration`, shrunk by the generic rule in [`sweep.py`](https://github.com/huggingface/model-integration-contracts/blob/main/experiments/sweep.py) (vision num_hidden_layers 2, text num_hidden_layers 2).
- **Processor files copied byte for byte** from `stepfun-ai/GOT-OCR-2.0-hf`: `generation_config.json`, `preprocessor_config.json`, `special_tokens_map.json`, `tokenizer.json`, `tokenizer_config.json`.
- **Overfit to the contract's training step** (250 steps). Random weights failed the input-sensitivity gate: `pixel_values:roll_batch` moved the logits by only 0 (threshold 0.001).
- **Same tensor names as the real checkpoint.** The real checkpoint has every parameter, and so does the fixture.
- **Saved in bfloat16**, the dtype `stepfun-ai/GOT-OCR-2.0-hf` 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-got_ocr2-slim`.