— Model Architecture: DeepSeek-R1-Distill-Qwen-32B — Input: Text / Image — Output: Text — Model Optimizations: — Weight quantization: FP4 — Activation quantization: FP4 — Release Date: 7/30/25 — Version: 1.0 — Model Developers: RedHatAI This model is a quantized version of DeepSeek-R1-Distill-Qwen-32B. It was evaluated on a several tasks to assess the its quality in comparison to the unquatized model. This model was obtained by quantizing the weights and activations of DeepSeek-R1-Distill-Qwen-32B to FP4 data type, ready for inference with vLLM>=0.9.1 This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 75%. Only the weights of the linear operators within transformers blocks are quantized using LLM Compressor. This model can be deployed efficiently using the vLLM backend, as shown in the example below. Model Usage Code vLLM aslo supports OpenAI-compatible serving. See the documentation for more details. This model was created by applying LLM Compressor with calibration samples from neuralmagic/calibration dataset, as presented in the code snipet below. This model was evaluated on the…
Модальности:
Генерация текста
Области применения:
Диалог / чат Логика и рассуждение
Задача: Генерация текста
Автор: nm-testing
Теги: qwen2, fp4, vllm, conversational, en, de, fr, it
Лайков: 3 | Загрузок: 280
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
