Qwen2.5 7B Instruct FP8 dynamic Model Overview Model Architecture: Qwen2 Input: Text Output: Text Model Optimizations: Activation quantization: FP8 Weight quantization: FP8 Intended Use Cases: Intended for commercial and research use multiple languages. Similarly to Qwen2.5 7B, this models is intended for assistant like chat. Out of scope: Use in any manner that violates applicable laws or regulations (including trade compliance laws). Release Date: 11/27/2024 Version: 1.0 Validated on: RHOAI 2.20, RHAIIS 3.0, RHELAI 1.5 License(s): apache 2.0 Model Developers: Neural Magic Model Optimizations This model was obtained by quantizing activations and weights of Qwen2.5 7B Instruct to FP8 data type. This optimization reduces the number of bits used to represent weights and activations from 16 to 8, reducing GPU memory requirements (by approximately 50%) and increasing matrix multiply compute throughput (by approximately 2x). Weight quantization also reduces disk size requirements by approximately 50%. Only weights and activations of the linear operators within transformers blocks are quantized. Weights are quantized with a symmetric static per channel scheme, whereas activations are qua…
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