SAM-1-Base (Shopping Agent Model) is a 7.6B parameter language model fine-tuned for commerce reasoning tasks, developed by SnapCart AI. Built on Qwen2.5-7B-Instruct via LoRA adaptation, SAM-1-Base achieves 90.55/100 on SAM-Bench, a comprehensive benchmark spanning 8 shopping assistant task types. This is the fully merged model (LoRA weights fused into the base) — ready for direct inference with no adapter loading required. SAM-1-Base is evaluated on SAM-Bench v0.1.0 — a benchmark of 1,200 programmatically generated tasks across 8 shopping assistant capabilities and 3 difficulty levels. Evaluation uses the 60% test split (719 tasks) with difficulty-weighted composite scoring (easy=1.0x, medium=1.5x, hard=2.0x). — Ranking tasks (Recommendation, Personalization): NDCG@5 + Relevance F1 — Classification tasks (Price Analysis, Purchase Decision): Accuracy metrics — Generation tasks (Review Synthesis): ROUGE-L + Sentiment Accuracy — Extraction tasks (Attribute Extraction, Query Understanding): Precision, Recall, F1 The composite task score is the arithmetic mean of all applicable metrics, scaled to [0, 100]. The overall benchmark score is the difficulty-weighted average across all tasks.…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: snapcart-ai
Теги: mlx, qwen2, shopping, e-commerce, commerce, recommendation, lora, conversational
Лайков: 3 | Загрузок: 26
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
