chinese-clip-vit-base-patch16-mic

Slim model weights, executable usage and framework expectations in one repository.

Contract

ChineseCLIP image-text retrieval

Runnable usage and the framework expectations directory are linked above.

Slim model

Slim fixture: chinese-clip-vit-base-patch16-mic

A 1.6M-parameter fixture for the ChineseCLIP MIC, covering OFA-Sys/chinese-clip-vit-base-patch16. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.

  • Fixture key 0f427f71401d. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
  • Same architecture, smaller config: ChineseCLIPModel, shrunk by the generic rule in sweep.py (text num_hidden_layers 2, vision num_hidden_layers 2).
  • Processor files copied byte for byte from OFA-Sys/chinese-clip-vit-base-patch16: festival.jpg, preprocessor_config.json, vocab.txt.
  • 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:halve, 0.00862), 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 OFA-Sys/chinese-clip-vit-base-patch16 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. This repository includes the slim weights, usage and framework expectations; rebuild the other files with python example/build_fixtures.py --fixture chinese-clip-vit-base-patch16-mic.

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