— Model Architecture: DeepSeek-R1-Distill-Llama-70B — Input: Text — Output: Text — Model Optimizations: — Weight quantization: FP8 — Activation quantization: FP8 — Release Date: 3/1/2025 — Version: 1.0 — Model Developers: Neural Magic Quantized version of DeepSeek-R1-Distill-Llama-70B. It achieves an average score of 76.52 on the OpenLLM benchmark (version 1), whereas the unquantized model achieves 76.49. This model was obtained by quantizing the weights and activations to FP8 data type, ready for inference with vLLM. 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. 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. This model was created with llm-compressor by running the code snippet below. The model was evaluated on OpenLLM Leaderboard V1 and V2, using the following commands: Results on Math-Hard, GPQA, and MUSR are not considred for accuracy recovery…
Модальности:
Генерация текста
Области применения:
Диалог / чат Логика и рассуждение
Задача: Генерация текста
Автор: nm-testing
Теги: llama, deepseek, fp8, vllm, conversational, en, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 53
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
