TL;DR — Fine-Tuning Platform

Design a platform that enables users to fine-tune foundation models on their custom datasets. The system manages the full lifecycle: dataset upload and validation, training job configuration, distributed training on GPU clusters, evaluation against benchmarks, and model deployment. Key features: Upload and validate training datasets (JSONL, CSV, Parquet). Configure fine-tuning jobs with model, method, and hyperparameters.