Update README.md

README.md

@@ -10,6 +10,42 @@ base_model: FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-Flash-32B-Preview
 This model was converted to GGUF format from [`FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-Flash-32B-Preview`](https://huggingface.co/FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-Flash-32B-Preview) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-Flash-32B-Preview) for more details on the model.
 
+---
+FuseO1-Preview
+ is our initial endeavor to enhance the System-II reasoning capabilities
+ of large language models (LLMs) through innovative model fusion 
+techniques. By employing our advanced SCE
+ merging methodologies, we integrate multiple open-source o1-like LLMs 
+into a unified model. Our goal is to incorporate the distinct knowledge 
+and strengths from different reasoning LLMs into a single, unified model
+ with strong System-II reasoning abilities, particularly in mathematics,
+ coding, and science domains.
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+     
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+To achieve this, we conduct two types of model merging:
+
+
+Long-Long Reasoning Merging: This approach involves
+ model fusion across LLMs that utilize long-CoT reasoning, with the goal
+ of enhancing long-CoT reasoning capabilities. The resulted FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-32B-Preview achieves a Pass@1 accuracy of 74.0 on AIME24,
+  demonstrating significant performance improvements compared to the 
+OpenAI o1-preview (44.6) and OpenAI o1-mini (63.4), even approaching 
+OpenAI o1 (79.2).
+Long-Short Reasoning Merging: This approach 
+involves model fusion between long-CoT and short-CoT LLMs, aiming to 
+improve reasoning capabilities in both long and short reasoning 
+processes. The resulted FuseAI/FuseO1-DeepSeekR1-Qwen2.5-Instruct-32B-Preview and FuseAI/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-Preview
+ is capable of utilizing both long and short reasoning processes and 
+demonstrates relatively strong performance in long reasoning tasks.
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)