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junchenfu/diger-rqvae-yelp
diger-rqvae-yelp is a feature extraction model from junchenfu. Use it when you need embeddings to search or compare text. The card lists the license as mit.
This repository provides the pretrained RQ-VAE checkpoint for yelp used in the paper:
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Updated Aug 30, 2026
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From the Hugging Face model README
This repository provides the pretrained RQ-VAE checkpoint for yelp used in the paper:
DIGER: Differentiable Semantic IDs for Generative Recommendation
This artifact is associated with the DIGER paper page:
https://huggingface.co/papers/2601.19711
best_collision_model.pth: released checkpoint from the DIGER RQ-VAE pretraining pipeline.Download with huggingface_hub:
from huggingface_hub import hf_hub_download
ckpt_path = hf_hub_download(
repo_id="junchenfu/diger-rqvae-yelp",
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.
LLaMA embeddings used by DIGER should be generated following the procedure described in:
https://github.com/honghuibao2000/letter
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.
If you use this checkpoint, please cite the DIGER paper.