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Dashboard: multi-model support (Stories110M + Qwen3-0.6B) with GQA-aware text generation and KV cache. Weights & Biases logging (--wandb flag) for loss, timing, power, and checkpoint events. Top-k=50 sampling to eliminate garbage tokens from untrained vocab entries. Tokenizer reads any vocab size. train.m: only save checkpoint when loss improves (best_loss tracking).