sentiment-engine/sentiment_engine/training/requirements-lora.txt

# Minimal requirements for LoRA pipeline (CPU-friendly)
torch==2.3.0 --index-url https://download.pytorch.org/whl/cpu
transformers==4.44.0
peft==0.12.0
datasets==2.20.0
accelerate==0.33.0
scikit-learn==1.5.0
numpy==1.26.0
feat(training): LoRA pipeline with human-in-the-loop verification - PEFT/LoRA fine-tuning (r=8, alpha=16) — only 1.2% params trainable - Data augmentation: templates + crypto slang (5x from 177→885 samples) - Human-in-the-loop CLI verification with persistent JSONL log - Disk-conscious: save_total_limit=1, ~6MB adapter size - CPU-friendly, single-file deployment - Tested: 1 epoch in ~4min on CPU, 6MB adapter 2026-09-26 18:54:41 +02:00			`# Minimal requirements for LoRA pipeline (CPU-friendly)`
			`torch==2.3.0 --index-url https://download.pytorch.org/whl/cpu`
			`transformers==4.44.0`
			`peft==0.12.0`
			`datasets==2.20.0`
			`accelerate==0.33.0`
			`scikit-learn==1.5.0`
			`numpy==1.26.0`