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GPU Cloud
Fine-Tuning
Fine-tuning adapts a pre-trained model to a specific task using domain-specific data.
Definition
Fine-tuning is the process of taking a pre-trained foundation model and adapting it to a specific task or domain using a smaller, specialized dataset. Techniques include: (1) Full fine-tuning — updating all model weights, (2) LoRA (Low-Rank Adaptation) — training small adapter layers, (3) QLoRA — quantized LoRA for memory efficiency, (4) RLHF — Reinforcement Learning from Human Feedback. Harch Corp provides GPU cloud infrastructure optimized for fine-tuning, with pre-built environments for PEFT, LoRA, and QLoRA on H100/H200 GPUs.
Related Keywords
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Related Terms
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