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omniRecsysLLM_semanticIDsmodality
zjkarina/omniRecsysLLM_semanticIDsmodality
omniRecsysLLM_semanticIDsmodality is a machine learning model from zjkarina. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Recommendation model with semantic IDs for Amazon Fashion.
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At a glance
- License
- mit
- Model type
- semantic_recommendation
- Access
- Public
- Created
- Sep 16, 2025
- Updated
- Sep 16, 2025
- SHA
- 4bfa0cb2
Base models
Model card
From the Hugging Face model README
zjkarina/omniRecsysLLM_semanticIDsmodality
Recommendation model with semantic IDs for Amazon Fashion.
Description
This model uses VQ-VAE to create semantic item IDs, enabling a more accurate understanding of semantic relationships between products.
Architecture
- Base model: Qwen2.5-Omni-7B
- Item vocabulary size: 709,036
- ID embedding dimension: 512
- VQ-VAE codebook size: 10,000
- VQ-VAE codebook dimension: 256
- Dataset: Amazon Fashion 2023 Full
Usage
from any2any_trainer.models.recommendation import SemanticIDRecommendationModel
# Load model
model = SemanticIDRecommendationModel.from_pretrained("zjkarina/omniRecsysLLM_semanticIDsmodality")
# Generate recommendations with semantic IDs
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,
use_semantic_ids=True
)
Training
The model was trained on the Amazon Fashion 2023 dataset using semantic IDs generated via VQ-VAE.
- Type
- semantic_recommendation
- License
- mit
- Languages
- en
- Created
- Sep 16, 2025
- Updated
- Sep 16, 2025