metadata
license: mit
datasets:
- seniichev/amazon-fashion-2023-full
language:
- en
base_model:
- Qwen/Qwen2.5-7B-Instruct
zjkarina/omniRecsysLLM_idmodality
Recommendation model based on ID modality for Amazon Fashion.
Description
This model uses item ID embeddings to generate recommendations based on users’ purchase history.
Architecture
- Base model: Qwen2.5-Omni-7B
- Item vocabulary size: 709,036
- ID embedding dimension: 512
- Fusion head dimension: 1024
- Dataset: Amazon Fashion 2023 Full
Использование
from any2any_trainer.models.recommendation import RecommendationModel
# Load model
model = RecommendationModel.from_pretrained("zjkarina/omniRecsysLLM_idmodality")
# Generate recommendations
recommendations = model.predict_next_item(
text="The user bought jeans and a t-shirt",
id_ids=[12345, 67890], # Item IDs from purchase history
top_k=5
)
Training
The model was trained on the Amazon Fashion 2023 dataset using the ID modality.