PEFT
qlora
sft
trl
qwen3
tmf921
intent-based-networking
network-slicing
rtx-6000-ada
ml-intern
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# Core training stack
# Tested API targets: TRL v1.3+, Transformers v5.5+/v5.6+, PEFT v0.19+, Datasets v4.8+
torch>=2.6
transformers>=5.5.0
trl[peft]>=1.3.0
peft>=0.19.0
accelerate>=1.12.0
datasets>=4.8.0
bitsandbytes>=0.48.0
safetensors>=0.5.0
huggingface_hub>=1.0.0
trackio>=0.8.0

# Evaluation / utilities
pandas>=2.2.0
numpy>=2.0.0
tqdm>=4.66.0
jsonschema>=4.23.0
scikit-learn>=1.5.0
pyyaml>=6.0.2
rich>=13.7.0

# Optional but recommended on RTX 6000 Ada for packing/throughput.
# Install separately if your CUDA/PyTorch build supports it:
# pip install flash-attn --no-build-isolation