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docs: add fine-tuned model section

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  1. README.md +6 -0
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@@ -27,6 +27,12 @@ ROCmPort AI orchestrates a migration loop:
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  Complex kernels can fail conversion due to architecture assumptions, undefined behavior, inline PTX, or handcrafted memory logic. The value is reduced migration time and faster debug loops.
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  ## Dataset
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  Training data: [tazwarrrr/cuda-to-rocm-wavefront-bugs](https://huggingface.co/datasets/tazwarrrr/cuda-to-rocm-wavefront-bugs)
 
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  Complex kernels can fail conversion due to architecture assumptions, undefined behavior, inline PTX, or handcrafted memory logic. The value is reduced migration time and faster debug loops.
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+ ## Fine-tuned Model
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+ [tazwarrrr/rocmport-qwen-wavefront-finetuned](https://huggingface.co/tazwarrrr/rocmport-qwen-wavefront-finetuned)
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+ Qwen2.5-Coder-7B-Instruct fine-tuned on 153 CUDA→ROCm wavefront-64 bug examples.
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+ Trained on AMD Instinct MI300X (gfx942) with ROCm 6.2 in 79 seconds.
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  ## Dataset
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  Training data: [tazwarrrr/cuda-to-rocm-wavefront-bugs](https://huggingface.co/datasets/tazwarrrr/cuda-to-rocm-wavefront-bugs)