DeepSeek R1 Distill Llama 70B FP8 dynamic Model Overview Model Architecture: LlamaForCausalLM Input: Text Output: Text Model Optimizations: Weight quantization: FP8 Activation quantization: FP8 Release Date: 2/1/2025 Version: 1.0 Model Developers: Neural Magic Quantized version of DeepSeek R1 Distill Llama 70B. Model Optimizations This model was obtained by quantizing the weights and activations of DeepSeek R1 Distill Llama 70B to FP8 data type. This optimization reduces the number of bits per parameter from 16 to 8, reducing the disk size and GPU memory requirements by approximately 50%. Only the weights and activations of the linear operators within transformers blocks are quantized. Weights are quantized using a symmetric per channel scheme, whereas quantizations are quantized using a symmetric per token scheme. LLM Compressor is used for quantization. Use with vLLM This model can be deployed efficiently using the vLLM backend, as shown in the example below. vLLM also supports OpenAI compatible serving. See the documentation for more details. Creation This model was created with llm compressor by running the code snippet below. Evaluation The model was evaluated on OpenLLM Leade…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy