---
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

```python
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.