SAM-1-Base is fine-tuned for commerce reasoning tasks including product recommendation, review synthesis, price analysis, and personalized shopping assistance.

Model Details

Base model: Qwen/Qwen2.5-7B-Instruct
Adapter type: LoRA (rank 16)
Format: MLX safetensors
SAM-Bench score: 90.55 / 100

SAM-Bench Results

Category	Score
Query Understanding	98.4
Product Recommendation	95.2
Product Comparison	93.1
Review Synthesis	91.0
Price Analysis	89.7
Purchase Decision	88.4
Attribute Extraction	85.3
Personalization	77.6
Overall	90.55

Usage

This adapter is in MLX format. To use with MLX:

python

from mlx_lm import load, generate

model, tokenizer = load(
    "Qwen/Qwen2.5-7B-Instruct",
    adapter_path="snapcart-ai/sam-1-base-lora"
)

prompt = "Compare these two laptops and recommend which one to buy..."
response = generate(model, tokenizer, prompt=prompt, max_tokens=512)
print(response)

For the merged model (no adapter loading required), see snapcart-ai/sam-1-base.

Benchmark

Evaluated on SAM-Bench — 1,200 tasks across 8 shopping assistant task types and 3 difficulty levels.

License

Apache 2.0