Update README.md

README.md

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 This model was converted to GGUF format from [`Skywork/Skywork-o1-Open-Llama-3.1-8B`](https://huggingface.co/Skywork/Skywork-o1-Open-Llama-3.1-8B) 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/Skywork/Skywork-o1-Open-Llama-3.1-8B) for more details on the model.
 
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+Model details:
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+We are excited to announce the release of the Skywork o1 Open model series, developed by the Skywork team at Kunlun Inc. This groundbreaking release introduces a series of models that incorporate o1-like slow thinking and reasoning capabilities. The Skywork o1 Open model series includes three advanced models:
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+    Skywork o1 Open-Llama-3.1-8B: A robust chat model trained on Llama-3.1-8B, enhanced significantly with "o1-style" data to improve reasoning skills.
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+    Skywork o1 Open-PRM-Qwen-2.5-1.5B: A specialized model designed to enhance reasoning capability through incremental process rewards, ideal for complex problem solving at a smaller scale.
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+    Skywork o1 Open-PRM-Qwen-2.5-7B: Extends the capabilities of the 1.5B model by scaling up to handle more demanding reasoning tasks, pushing the boundaries of AI reasoning.
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+Different from mere reproductions of the OpenAI o1 model, the Skywork o1 Open model series not only exhibits innate thinking, planning, and reflecting capabilities in its outputs, but also shows significant improvements in reasoning skills on standard benchmarks. This series represents a strategic advancement in AI capabilities, moving a previously weaker base model towards the state-of-the-art (SOTA) in reasoning tasks.
+Methods
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+The Skywork o1 Open series' remarkable cognitive abilities are developed through a three-stage training scheme:
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+    Reflective Reasoning Training: Utilizing a proprietary multi-agent system to generate high-quality, diverse data for long-thinking tasks, followed by continuous pre-training and supervised fine-tuning.
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+    Reinforcement Learning for Reasoning Capabilities: Introduction of the Skywork o1 Process Reward Model (PRM), tailored to enhance step-by-step reasoning. Our experiments confirm that the Skywork-PRM effectively captures the influence of intermediate reasoning steps on final outcomes, combined with proprietary reasoning reinforcement algorithms.
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+    Reasoning Planning: Deploying Tiangong's proprietary Q* online reasoning algorithm alongside model-based thinking, searching for optimal reasoning paths. This marks the first implementation and public release of a Q* algorithm, significantly boosting the model's online reasoning capabilities.
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 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)