Qwen
/

QwQ-32B-GGUF

@@ -19,6 +19,10 @@ tags:
 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 in the GGUF Format**, which has the following features:
 - Type: Causal Language Models
 - Training Stage: Pretraining & Post-training (Supervised Finetuning and Reinforcement Learning)
@@ -32,6 +36,8 @@ QwQ is the reasoning model of the Qwen series. Compared with conventional instru
 **Note:** For the best experience, please review the [usage guidelines](#usage-guidelines) before deploying QwQ models.
 For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwq-32b/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/).
 ## Requirements
@@ -103,7 +109,7 @@ If you find our work helpful, feel free to give us a cite.
 ```
 @misc{qwq32b,
-    title = {Qwen2.5: A Party of Foundation Models},
     url = {https://qwenlm.github.io/blog/qwq-32b/},
     author = {Qwen Team},
     month = {March},

 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.
+<p align="center">
+  <img width="100%" src="figures/benchmark.jpg">
+</p>
 **This repo contains the QwQ 32B model in the GGUF Format**, which has the following features:
 - Type: Causal Language Models
 - Training Stage: Pretraining & Post-training (Supervised Finetuning and Reinforcement Learning)
 **Note:** For the best experience, please review the [usage guidelines](#usage-guidelines) before deploying QwQ models.
+You can try our [demo](https://huggingface.co/spaces/Qwen/QwQ-32B-Demo) or access QwQ models via [QwenChat](https://chat.qwen.ai).
 For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwq-32b/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/).
 ## Requirements
 ```
 @misc{qwq32b,
+    title = {QwQ-32B: The Power of Scaling RL},
     url = {https://qwenlm.github.io/blog/qwq-32b/},
     author = {Qwen Team},
     month = {March},

figures/benchmark.jpg ADDED Viewed