Why They Return

Problem: about one in four online clothing orders comes back, and size and fit is the top reason (Coresight Research, 2023). The reasons are already in the reviews, but nobody reads 300 reviews per product. User: fashion sellers and rental shops who need to know which items to fix first and what to change on the listing. What it does: Gemma 3 12B runs on an AMD Radeon PRO W7900D with ROCm and PyTorch. Pass one reads every review and returns the fit direction (runs small, runs large, true to size), other causes (length, fabric, colour vs photo, comfort, zipper), the exact customer quote and a one-line fix. Code counts the shares per product. Pass two sees only those counts and quotes and writes the size note, the description sentence and the photo to add. The seller gets items ranked by fit-return risk, a report per item, copy-ready text and a money estimate. A live notebook runs it on the AMD GPU: 30 reviews of a new item in 27.8 s. Proof: Rent the Runway renters label every review fit, small or large. We hid the label and compared with the keyword rules a seller would write. 900 reviews: macro-F1 0.737 vs 0.606; Gemma finds 64% of "runs large" reviews, rules 40%. 40 products drawn after the prompt was fixed, run once: Gemma ranks items that run large at Spearman 0.87 vs 0.72; on items that run small rules are level (0.84 vs 0.88). The README shows the full history, including a prompt that over-counted and how it was fixed. Why AMD and open weights: one 48 GB Radeon card holds the model in bf16 and the customer text never leaves the seller's GPU. Next: vLLM on AMD Instinct, Shopify imports, A/B test of the size note against return rate.