junchenfu/diger-rqvae-instruments

DIGER RQ-VAE Checkpoint (instruments)

This repository provides the pretrained RQ-VAE checkpoint for instruments used in the paper:

DIGER: Differentiable Semantic IDs for Generative Recommendation

Paper

This artifact is associated with the DIGER paper page:

https://huggingface.co/papers/2601.19711

Files

• best_collision_model.pth: released checkpoint from the DIGER RQ-VAE pretraining pipeline.

Usage

Download with huggingface_hub:

from huggingface_hub import hf_hub_download

ckpt_path = hf_hub_download(
    repo_id="junchenfu/diger-rqvae-instruments",
    filename="best_collision_model.pth",
)

The checkpoint can be loaded with the RQ-VAE implementation in the DIGER GitHub repository:

https://github.com/junchen-fu/DIGER

Please refer to the repository README for the full training configuration and commands.

Embeddings

LLaMA embeddings used by DIGER should be generated following the procedure described in:

https://github.com/honghuibao2000/letter

Dataset Note

The underlying recommendation datasets are publicly available from their original sources. Processed interaction data are not hosted in this model repository; they can be regenerated following the DIGER codebase.

Citation

If you use this checkpoint, please cite the DIGER paper.