Llama-3.2-1B-Instruct-onnx-ryzenai-npu

Llama-3.2-1B-Instruct-onnx-ryzenai-npu

• Introduction

  This model was created using Quark Quantization, followed by OGA Model Builder, and finalized with post-processing for NPU deployment.

• Quantization Strategy

  • AWQ / Group 128 / Asymmetric / BFP16 activations / UINT4 Weights

• Quick Start

  For quickstart, refer to Ryzen AI documentation

Evaluation scores

• The perplexity measurement is run on the wikitext-2-raw-v1 (raw data) dataset provided by Hugging Face. Perplexity score measured for prompt length 2k is 14.9164.

• The average MMLU scores are astronomy - 46.05, philosophy - 49.2 and management - 56.31.

License

Modifications copyright(c) 2024 Advanced Micro Devices,Inc. All rights reserved.

MIT License

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