hf-internal-testing/mic-SmolLM-slim

Slim fixture: proto-SmolLM-slim

A 3.2M-parameter fixture for the SmolLM MIC, covering HuggingFaceTB/SmolLM-135M, HuggingFaceTB/SmolLM-360M. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.

• Fixture key a186080c7a70. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
• Same architecture, smaller config: LlamaForCausalLM, shrunk by the generic rule in sweep.py (num_hidden_layers 2).
• Processor files copied byte for byte from HuggingFaceTB/SmolLM-135M: generation_config.json, merges.txt, special_tokens_map.json, tokenizer.json, tokenizer_config.json, vocab.json.
• Overfit to the contract's training step (80 steps), although random weights passed the input-sensitivity gate: random weights generate the same tokens for every prompt, so generated_tokens cannot tell the prompts apart. The training rows share 'The capital of' and then name four countries, so ln 4 at that position (about 0.2 per token) cannot be learned: target_loss 0.3.
• Same tensor names as the real checkpoint. The real checkpoint has every parameter, and so does the fixture.
• Saved in bfloat16, the dtype HuggingFaceTB/SmolLM-135M 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 proto-SmolLM-slim.