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@@ -34,7 +34,7 @@ Visit the repo to dive into the codebase and reproduce the results locally or on
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  **🔗 [Qwopus3.5-27b Complete Fine-Tuning Guide (PDF)](https://github.com/R6410418/Jackrong-llm-finetuning-guide/blob/main/guidePDF/Qwopus3-5-27b-Colab_complete_guide_to_llm_finetuning.pdf)**
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  * **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.
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  * **Beginner Friendly:** Includes an introductory guide to getting started with Google Colab and Unsloth.
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- * *Feedback welcome! If you spot any areas for improvement, please let me know and I will update it promptly.*
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  > **A Note:**
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  > 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.
 
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  **🔗 [Qwopus3.5-27b Complete Fine-Tuning Guide (PDF)](https://github.com/R6410418/Jackrong-llm-finetuning-guide/blob/main/guidePDF/Qwopus3-5-27b-Colab_complete_guide_to_llm_finetuning.pdf)**
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  * **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.
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  * **Beginner Friendly:** Includes an introductory guide to getting started with Google Colab and Unsloth.
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+ * *Feedback welcome. If you spot any areas for improvement, please let me know and I will update it promptly.*
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  > **A Note:**
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  > 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.