SAM-1-Base LoRA Adapter

LoRA adapter weights for SAM-1-Base, a shopping assistant model built on Qwen2.5-7B-Instruct.

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:

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 โ€” 1,200 tasks across 8 shopping assistant task types and 3 difficulty levels.

License

Apache 2.0

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