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Llama-3.1-8B-awq-g128-int4-asym-bf16-onnx-ryzen-strix

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uday610 commited on Oct 2, 2024

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 - ## Introduction
   This model was created by applying [Quark](https://quark.docs.amd.com/latest/index.html) with calibration samples from Pile dataset, and applying [onnxruntime-genai model builder](https://github.com/microsoft/onnxruntime-genai/tree/main/src/python/py/models) to convert to ONNX.
 - ## Quantization Strategy
-  - ***Quantized Layers***: TBD
-  - ***Weight***: TBD
 - ## Quick Start
 For quickstart, refer to AMD [RyzenAI-SW-EA](https://account.amd.com/en/member/ryzenai-sw-ea.html)

 - ## Introduction
   This model was created by applying [Quark](https://quark.docs.amd.com/latest/index.html) with calibration samples from Pile dataset, and applying [onnxruntime-genai model builder](https://github.com/microsoft/onnxruntime-genai/tree/main/src/python/py/models) to convert to ONNX.
 - ## Quantization Strategy
+  - AWQ / Group 128 / Asymmetric / FP32 activations
 - ## Quick Start
 For quickstart, refer to AMD [RyzenAI-SW-EA](https://account.amd.com/en/member/ryzenai-sw-ea.html)