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Learn how to fine-tune the DeepSeek R1 large language model with this comprehensive step-by-step tutorial that covers the entire process from environment setup to cloud GPU usage, training, and inference. Discover what DeepSeek-R1 is and its various model sizes ranging from 1.5B to 671B parameters. Understand the hardware requirements needed for training, including GPU, CPU, RAM, and storage specifications. Follow guidance on selecting an affordable cloud GPU provider with specific focus on ThunderCompute. Master the process of creating a remote GPU instance, setting up a Python virtual environment, and installing necessary deep learning libraries. Learn to download the DeepSeek-R1 7B model from Hugging Face and implement PEFT and LoRA techniques for efficient fine-tuning. The tutorial also covers uploading and running training scripts on remote servers and downloading your trained model locally to run inference.
