# Deps for the lora-finetune step, installed into its venv by command.sh on first run.
# torch==2.12.0: PyPI Linux wheel bundles CUDA 13.0 (GPU); macOS wheel is CPU/MPS.
torch==2.12.0
# >=4.56: run.py uses from_pretrained(dtype=), added in 4.56 (crashes on 4.55.x). <5: avoid major bump.
transformers>=4.56,<5
# trl 0.25+ computes the MoE aux loss unconditionally, crashing on zero-expert configs;
# run.py guards it by zeroing router_aux_loss_coef (see the guard in main()).
trl>=0.25
peft>=0.13
datasets
accelerate
# sentencepiece + protobuf: needed to load the Granite tokenizer (transformers won't pull them).
sentencepiece
protobuf
