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millid-tiny-v1.5

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Replaces the PyTorch-only snippet with a Use it section:

• Python: pip install millid, then MillID.from_pretrained(...), predict and identify_document, plus the millid predict command.
• JavaScript: @baobabtech/millid, for Node (onnxruntime-node) and browsers (onnxruntime-web).
• PyTorch: millid.py, labelled as the training code.
• The ONNX graph: its inputs and outputs.

All of it runs the model in-process from onnx/model.onnx, with no server and no PyTorch.

Everything described here is implemented and tested in https://github.com/baobab-tech/millid/pull/1:

• Python and JavaScript are tested against the same fixtures: every encoded id equal, and probabilities within 1e-4.
• Headless Chrome gave the same answers.

Merge after that PR. The install line points at its main branch, so these instructions only work once it is merged.