pegasus-xsum-mic
Slim model weights, executable usage and framework expectations in one repository.
- Contract manifest
- Transformers usage
- Transformers expectations
- Fixture provenance
- How the fixture was shrunk
Contract
Pegasus summarization
Runnable usage and the framework expectations directory are linked above.
Slim model
Slim fixture: pegasus-xsum-mic
A 6.4M-parameter fixture for the Pegasus MIC, covering google/pegasus-xsum. It is a test artifact, not a usable model, tagged test-artifact to keep it out of candidate-model search.
- Fixture key
d407756b9dfb. It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking. - Same architecture, smaller config:
PegasusForConditionalGeneration, shrunk by the generic rule insweep.py(encoder_layers 2, decoder_layers 2). - Processor files copied byte for byte from
google/pegasus-xsum:generation_config.json,special_tokens_map.json,spiece.model,tokenizer.json,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:
input_ids:reverse, 0.00311), so no training was needed. - Same tensor names as the real checkpoint. The real checkpoint lacks
model.decoder.embed_positions.weight,model.encoder.embed_positions.weight, so the fixture omits it too, and loading initializes it as it does for users. - Saved in float32, the dtype
google/pegasus-xsumloads 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 pegasus-xsum-mic.
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Base model
google/pegasus-xsum