Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-GGUF

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🌟 Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled 🔥 Update (April 5): I’ve released the complete training notebook, codebase, and a comprehensive PDF guide to help beginners and enthusiasts understand and reproduce this model's fine-tuning process. ❤️ Special thanks to the Unsloth open-source library and @KyleHessling1 for their support. 📚 Resources & Guides 👉 GitHub Repository: Jackrong-llm-finetuning-guide Visit the repo to dive into the codebase and reproduce the results locally or on Colab. 📥 Core Technical Document 🔗 Qwopus3.5-27b Complete Fine-Tuning Guide (PDF) The Full Pipeline: A step-by-step walkthrough—from downloading the base model and unifying heterogeneous data, to configuring trainer hyperparameters and publishing to Hugging Face. Beginner Friendly: Includes an introductory guide to getting started with Google Colab and Unsloth. Feedback welcome! If you spot any areas for improvement, please let me know and I will update it promptly.* A Note: My goal isn't just to detail a workflow, but to demystify LLM training. Beyond the social media hype, fine-tuning isn't an unattainable ritual—often, all you need is a Google account, a standard laptop, and relentless curiosity. No one starts as an expert, but every expert was once brave enough to begin. All training and testing for this project were self-funded. If you find this model or guide helpful, a Star ⭐️ on GitHub …