Claude Prompt for Fine-tuning & Model Adaptation
End-to-end SFT dataset construction: collection, labeling, cleaning, dedup, contamination check for code refactoring suggestions.
More prompts for Fine-tuning & Model Adaptation.
Full fine-tuning recipe: LoRA on Qwen 2.5 32B via DeepSpeed, targeting 4x A100 40GB, with data mix and eval plan.
Rigorous evaluation harness comparing the fine-tuned model against Gemma 2 27B base, closed-source frontier, and previous checkpoint.
Rigorous evaluation harness comparing the fine-tuned model against Llama 3.3 70B base, closed-source frontier, and previous checkpoint.
Rigorous evaluation harness comparing the fine-tuned model against Mixtral 8x7B base, closed-source frontier, and previous checkpoint.
Full fine-tuning recipe: LoRA on Phi-4 via DeepSpeed, targeting 2x RTX 4090, with data mix and eval plan.
Full fine-tuning recipe: DPO on Gemma 2 9B via FSDP, targeting 8x H100, with data mix and eval plan.
Replace the bracketed placeholders with your own context before running the prompt:
[{ "input": "...", "output": "..." }]— fill in your specific { "input": "...", "output": "..." }.