QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks, especially hard problems. QwQ-32B is the medium-sized reasoning model, which is capable of achieving competitive performance against state-of-the-art reasoning models, e.g., DeepSeek-R1, o1-mini. This repo contains the QwQ 32B model, which has the following features: — Type: Causal Language Models — Training Stage: Pretraining & Post-training (Supervised Finetuning and Reinforcement Learning) — Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias — Number of Parameters: 32.5B — Number of Paramaters (Non-Embedding): 31.0B — Number of Layers: 64 — Number of Attention Heads (GQA): 40 for Q and 8 for KV — Context Length: Full 131,072 tokens For mo QwQ is based on Qwen2.5, whose code has been in the latest Hugging face transformers. We advise you to use the latest version of transformers. Here provides a code snippet with applychattemplate to show you how to load the tokenizer and…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: dillonroach
Теги: qwen2, chat, conversational, en, exl2
Лайков: 4 | Загрузок: 13
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
