clip-vit-base-patch32-mic

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

Contract

MIC: CLIP zero-shot image classification

Model integration contract (MIC) for one usage path, across the checkpoints that share it. This repository holds the contract code and the manifest; each framework keeps its own expected results and pins this repository by revision. The model repositories are unchanged. It is a test artifact, not a model: exclude it from model search.

Usage path: CLIPProcessor + CLIPModel, image-caption matching, batched.

File What it is
integration.json Manifest: checkpoints, which fixture covers each, frameworks, entry points, variants, unsupported targets, comparison rules
integrations/transformers/usage.md Transformers contract, written as doc-builder runnable markdown: the same blocks are documentation and test

Checked outputs: image_to_text, text_to_image, logits_per_image, text_kwargs_input_ids, image_processor_config_keys, training.loss, training.gradients, training.updated.

A fixture pass and a real-checkpoint pass have different scopes; either establishes agreement on fixed inputs and a recorded runtime, not correctness on arbitrary inputs.

Slim model

Slim fixture: proto-clip-vit-base-patch32-slim

A 3.5M-parameter fixture for the CLIP MIC, covering openai/clip-vit-base-patch32. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.

  • Fixture key b50917f048e5. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
  • Same architecture, smaller config: CLIPModel, 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 openai/clip-vit-base-patch32: merges.txt, preprocessor_config.json, special_tokens_map.json, tokenizer.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: pixel_values:halve, 0.00487), so no training was needed.
  • Same tensor names as the real checkpoint. The real checkpoint has every parameter, and so does the fixture.
  • 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 proto-clip-vit-base-patch32-slim.

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