Slim fixture: mic-llava-slim

A 4.3M-parameter fixture for the llava MIC, covering llava-hf/llava-1.5-7b-hf. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.

  • Fixture key 232603d3d5e9. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
  • Same architecture, smaller config: LlavaForConditionalGeneration, shrunk by the generic rule in sweep.py (vision num_hidden_layers 2, text num_hidden_layers 2).
  • Processor files copied byte for byte from llava-hf/llava-1.5-7b-hf: added_tokens.json, chat_template.jinja, chat_template.json, generation_config.json, preprocessor_config.json, processor_config.json, special_tokens_map.json, tokenizer.json, tokenizer.model, tokenizer_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:halve, 0.035), 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 float16, the dtype llava-hf/llava-1.5-7b-hf 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. The source repository commits only README.md and build.json; rebuild the other files with python example/build_fixtures.py --fixture mic-llava-slim.

Downloads last month
27
Safetensors
Model size
4.34M params
Tensor type
F16
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support