Feat/pr2 ports nanogpt minimind - #22
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Add examples/nanoGPT/ and examples/MiniMind/ — end-to-end lighttrain ports of two well-known training repos. nanoGPT (Karpathy): model.py: @register("model","nano_gpt") — identical arch (optional-bias LayerNorm, c_attn/c_proj naming, Flash Attn, from_pretrained for GPT-2 weights, estimate_mfu, weight-decay split optimizer) components.py: @register BinaryMemmapDataset("memmap_bin") + StackCollator configs/: train_shakespeare_char / train_gpt2 / finetune_shakespeare data/: shakespeare_char + shakespeare (BPE) + openwebtext prepare scripts sample.py: standalone generation from lighttrain checkpoint or gpt2* MiniMind (jingyaogong): model/: model_minimind.py (verbatim) + model_adapter.py (@register "minimind" + @register("tokenizer","hf_auto")) + model_lora.py tokenizer: vocab_size=6400 custom tokenizer dataset/lm_dataset.py: @register minimind_pretrain/sft/dpo/rlaif datasets + minimind_pad collator trainer/trainer_utils.py + rollout_engine.py (adapted/verbatim) configs/: pretrain / sft / lora / dpo / grpo / ppo / distillation (7 total) scripts/: chat_api / web_demo / serve_openai_api / eval_toolcall / convert_model (verbatim + sys.path adapted) All gates green: ruff clean, mypy 575 files 0 errors, pytest 4491 passed. Verbatim copies (model_minimind, model_lora, rollout_engine, prepare.py) carry # ruff: noqa to preserve upstream style. CanGeng
…OWN_ISSUES CanGeng
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