Private OpenMed development export of deepgrove/maple-preview revision ac1ddd79d2b5cb4406f5d2bebdf95406ce505a07 for a compatible ONNX Runtime Web/WebGPU integration. The expert matrices use symmetric 4-bit, 128-value blocks through the fused com.microsoft.QMoE operator; cache and logit I/O use FP16. The included openmed-maple-onnx-export.json records file hashes, source provenance, the exact toolchain, and validation gates. The complete 24-layer graph passed ONNX checker and OpenMed’s graph contract. On ONNX Runtime 1.25.1 CPU it completed a real one-token prefill and cached decode with finite logits and correct KV growth. Physical browser WebGPU execution, source-logit parity, useful generation, direct-identifier recall, critical-leakage, peak memory, and latency remain release gates. This custom Maple graph is not a stock Transformers.js model. The browser demo requires an audited, same-origin adapter with compatible QMoE support. See docs/maple-on-device.md and the standalone demo in docs/demo/web/. Notes and generated outputs must not be persisted in browser storage, and PHI workflows must not use cloud fallback. Maple Preview is a research model, not a medical device. It must…
Модальности:
Генерация текста
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Задача: Генерация текста
Автор: OpenMed
Теги: onnxruntime, onnx, onnxruntime-web, webgpu, browser, maple, mixture-of-experts, quantized
Лайков: 3 | Загрузок: 0
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
