owlvit-base-patch32-mic
Slim model weights, executable usage and framework expectations in one repository.
Contract
OWL-ViT open-vocabulary object detection
Runnable usage and the framework expectations directory are linked above.
Slim model
Slim fixture: owlvit-base-patch32-mic
A 3.6M-parameter fixture for the OWL-ViT MIC, covering google/owlvit-base-patch32. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.
- Fixture key
1e4ee370dc3d. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking. - Same architecture, smaller config:
OwlViTForObjectDetection, shrunk by the generic rule insweep.py(text num_hidden_layers 2, vision num_hidden_layers 2). - Processor files copied byte for byte from
google/owlvit-base-patch32:merges.txt,preprocessor_config.json,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:
input_ids:roll_batch, 0.194), 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/owlvit-base-patch32loads 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 owlvit-base-patch32-mic.
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Base model
google/owlvit-base-patch32