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.gitattributes

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README.md

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+---
+license: cc-by-4.0
+language:
+- en
+- de
+- es
+- fr
+pipeline_tag: automatic-speech-recognition
+tags:
+- automatic-speech-recognition
+- onnx
+- directml
+- nemo
+- canary
+base_model:
+- nvidia/canary-1b-v2
+---
+
+# NVIDIA canary-1b-v2 — DirectML-safe ONNX
+
+ONNX export of [nvidia/canary-1b-v2](https://huggingface.co/nvidia/canary-1b-v2) whose **encoder is re-exported
+in the TorchScript idiom** (`torch.onnx.export(dynamo=False)`), so the model runs on the ONNX Runtime
+**DirectML EP** (and every other EP).
+
+## Why
+
+istupakov's `canary-1b-v2-onnx` encoder is a torch-**dynamo** export. On the DirectML EP it is a two-sided
+trap (isolated by graph bisection): dynamic shapes crash the Reshape/attention kernels
+(`MLOperatorAuthorImpl.cpp:2597`, then a D3D12 device-removal `887A0020`), and forcing static shapes
+fails session creation in `InferAndVerifyOutputSizes` (`:2853`) — both unfixed ORT-DML defects around
+the dynamo `view` idiom (upstream onnxruntime #26826 / #26944; the DML EP is in maintenance mode).
+NVIDIA's Parakeet FastConformer, exported via TorchScript, runs fine on DML — so this repo re-exports
+the **same encoder** the same way.
+
+## What changed
+
+- `encoder-model.onnx` (+ `encoder-model.int8.onnx`): re-exported from the `nvidia/canary-1b-v2` NeMo
+  checkpoint via `torch.onnx.export(dynamo=False, opset=17)`, same I/O contract as istupakov
+  (`audio_signal[B,128,T]`, `length[B]` → `encoder_embeddings[B,S,1024]`, `encoder_mask[B,S]`).
+  Numerically identical to istupakov's encoder on CPU (max|Δ| ≈ 4e-6 — export-tracer float noise).
+- `decoder-model.onnx` / `decoder-model.int8.onnx` / `config.json` / `vocab.txt`: **unchanged** from
+  [istupakov/canary-1b-v2-onnx](https://huggingface.co/istupakov/canary-1b-v2-onnx) — the DML crash was
+  encoder-only; the AED decoder is byte-for-byte the same.
+
+Produced by [WinSTT](https://github.com/dahshury/WinSTT)'s `canary_encoder_export.py`.

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encoder-model.onnx.data

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