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README.md

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+---
+license: apache-2.0
+tags:
+- executorch
+- xnnpack
+- pte
+- on-device
+- text-generation
+base_model:
+- Qwen/Qwen2.5-1.5B
+---
+# Qwen2.5-1.5B — ExecuTorch XNNPACK 8da4w + 8-bit embedding
+
+`qwen2_5_1_5b_xnnpack_8da4w_e8.pte` (1035.3 MB)
+
+- **Source**: Qwen/Qwen2.5-1.5B — the **base** model, not Instruct. It continues text; it
+  does not answer a chat template.
+- **License**: Apache-2.0
+- **Quantization**: 8da4w linear + 8-bit embedding (`embedding_quantize: "8,0"`)
+- **Export**: executorch 1.4.0 `export_llm`, static shape (seq_len=1), max_seq_length 2048,
+  XNNPACK extended_ops
+- **Config**: `llm_params/qwen2_5_1_5b_xnnpack_8da4w_e8.yaml`
+
+## Verification (Mac arm64, 2026-08-21)
+
+Completions, against the untouched model on the same prompts. A base model is checked this
+way because a chat template gets it nowhere: fed one, it echoes the question back.
+
+| prompt | this file | eager fp32 |
+|---|---|---|
+| "The capital of France is" | turns it into a multiple-choice question and answers A, Paris | " Paris. The capital of France is also the capital of the European Union…" |
+| "Water boils at a temperature of" | "100°C and water freezes at a temperature of 0°C" | "212 °F or 100 °C and ice melts at a temperature of 32 °" |
+| "Seventeen times four equals" | "what number? To determine what number 17 times 4 equals, we need to perform the multiplication" | "what number? To find the product of 17 and 4, we perform the multiplication: 17 *" |
+
+The continuations differ, which they will once the weights are 4-bit, but nothing here is
+wrong where eager is right. Decode **69.5 tok/s**, from one pass with nothing else running.
+
+**The 0.5B of this pair is not on the shelf.** It fails that comparison rather than passing
+it: asked where water boils it says 215 degrees Fahrenheit, where eager says 212 °F or
+100 °C. Half a billion parameters do not survive 4-bit weights, and XNNPACK has no 8-bit
+path that works — `torchao:8da8w` cannot be combined with the delegate and `qmode: int8`
+falls over on grouped-query attention. At that size
+[LFM2-350M](https://huggingface.co/mlboydaisuke/LFM2-350M-ExecuTorch) is smaller, faster and
+correct.
+
+## Converting it
+
+```bash
+python convert/export_from_safetensors.py qwen2_5_1_5b
+```
+
+Not `export_llm` directly: this repository ships safetensors only, and
+`load_checkpoint_from_pytorch_model` reads `pytorch_model.bin`, so the code falls back to
+torchtune's checkpointer. Qwen2.5's converter wants one thing from torchtune —
+`get_mapped_key` — and ExecuTorch has its own copy of that function, so the script hands the
+real one over and stubs the rest.
+
+## Running it
+
+```bash
+python llm_params/gen_static.py \
+  --pte qwen2_5_1_5b_xnnpack_8da4w_e8.pte \
+  --tokenizer tokenizer.json \
+  --prompt 'The capital of France is' \
+  --eos_ids "[151643]"
+```
+
+The 8-bit embedding needs `from executorch.kernels import quantized` before the program is
+loaded, and `portable_lib._load_for_executorch` rather than `executorch.runtime`.
+
+(conversion scripts: [executorch-models](https://github.com/john-rocky/executorch-models) ·
+iOS sample: [executorch-samples](https://github.com/john-rocky/executorch-samples))