Add README with usage and quality info

README.md

@@ -0,0 +1,51 @@
+---
+license: apache-2.0
+tags:
+- directml
+- onnx
+- embedding
+- qwen3
+- sentence-transformers
+- feature-extraction
+pipeline_tag: feature-extraction
+---
+
+# Octen-Embedding-0.6B — DirectML ONNX
+
+Patched ONNX export of [Octen/Octen-Embedding-0.6B](https://huggingface.co/Octen/Octen-Embedding-0.6B) that runs on **DirectML** (Windows GPU via ONNX Runtime).
+
+## What was fixed
+
+The original `torch.onnx.export` (dynamo) produces `val_41 = [-1]` used in Reshape shapes for multi-head attention (GQA: 16 Q heads, 8 KV heads). DirectML's execution provider cannot resolve symbolic `-1` at graph-capture time.
+
+**Fix**: Replace `[-1]` with four concrete head-count constants (16 for Q, 8 for K, 8 for V, 2048 for attention output) and reconnect 84 Reshape consumer nodes.
+
+See `fix_octen_dml.py` for the full patch script.
+
+## Files
+
+- `model.fp16.onnx` — ONNX graph proto (4 MB)
+- `model.fp16.onnx.data` — external weights (1.1 GB, fp16)
+- `tokenizer.json` — Qwen2 tokenizer
+- `config.json` — model config (max_position_embeddings=32768)
+- `fix_octen_dml.py` — reproduction script
+
+## Usage
+
+```python
+import onnxruntime as ort
+
+session = ort.InferenceSession(
+    "model.fp16.onnx",
+    providers=["DmlExecutionProvider"],
+)
+```
+
+## Quality
+
+| Dataset | R@5 | R@10 | MRR |
+|---------|-----|------|-----|
+| esp32 (smoke) | 0.930 | 0.950 | 0.810 |
+| autosar | 0.678 | 0.774 | 0.552 |
+
+Identical to CPU fp16 reference — patch preserves quality exactly.