---
tags:
  - mic
  - test-artifact
base_model: microsoft/mpnet-base
---

# mpnet-base-mic

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

- [Contract manifest](integration.json)
- [Transformers usage](integrations/transformers/usage.md)
- [Transformers expectations](integrations/transformers/expectations)
- [Fixture provenance](build.json)
- [How the fixture was shrunk](https://huggingface-mic-mic-coverage.static.hf.space/shrink/mpnet-base-mic.html)

## Contract

### MPNet fill-mask

Runnable usage and the framework expectations directory are linked above.

## Slim model

### Slim fixture: mpnet-base-mic

A 2.1M-parameter fixture for the [MPNet MIC](https://huggingface.co/huggingface-mic/mpnet-base-mic), covering [`microsoft/mpnet-base`](https://huggingface.co/microsoft/mpnet-base). It is a test artifact, not a usable model, tagged `test-artifact` to keep it out of candidate-model search.

- **Fixture key `f651cf653329`.** It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
- **Same architecture, smaller config:** `MPNetForMaskedLM`, shrunk by the generic rule in [`sweep.py`](https://github.com/huggingface/transformers-mic/blob/main/experiments/sweep.py) (num_hidden_layers 2).
- **Processor files copied byte for byte** from `microsoft/mpnet-base`: `tokenizer.json`, `tokenizer_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: `attention_mask:all_ones`, 0.00388), 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 `microsoft/mpnet-base` loads in by default.
- **Finite in float32, bfloat16, and float16** (forward, loss, gradients).

Built by [`build_fixtures.py`](https://github.com/huggingface/transformers-mic/blob/main/example/build_fixtures.py); [`build.json`](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 mpnet-base-mic`.