Add dataset card

README.md

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+---
+tags:
+- recommendation
+- generative-recommendation
+- semantic-id
+- diger
+- rq-vae
+- llama-embeddings
+pretty_name: DIGER Processed Data and Embeddings
+---
+
+# DIGER Processed Data and Embeddings
+
+This dataset repository contains the processed artifacts used by **DIGER: Differentiable Semantic IDs for Generative Recommendation**.
+
+The files are provided to make reproduction easier, since small differences in preprocessing or embedding generation may lead to different semantic IDs and recommendation results.
+
+## Contents
+
+The repository contains processed files for three datasets:
+
+- `beauty/`
+- `instruments/`
+- `yelp/`
+
+Each dataset directory contains:
+
+- `*.train.jsonl`, `*.valid.jsonl`, `*.test.jsonl`: processed interaction splits used by DIGER.
+- `*.emb_map.json`: mapping between processed item ids and embedding rows.
+- `*.emb-llama.npy`: LLaMA-based item embeddings used for RQ-VAE checkpoint training and DIGER experiments.
+- `*_stats.json` when available: summary statistics for the processed split.
+
+## LLaMA Embeddings
+
+The LLaMA embeddings follow the generation procedure described in:
+
+https://github.com/honghuibao2000/letter
+
+We include the processed embeddings here so that downstream users can reproduce the released DIGER artifacts without depending on small preprocessing or embedding-generation differences.
+
+## Models
+
+The corresponding released RQ-VAE checkpoints are available at:
+
+- Beauty: https://huggingface.co/junchenfu/diger-rqvae-beauty
+- Instruments: https://huggingface.co/junchenfu/diger-rqvae-instruments
+- Yelp: https://huggingface.co/junchenfu/diger-rqvae-yelp
+
+## Source Dataset Note
+
+The underlying recommendation datasets are public datasets from their original sources. This repository hosts the processed DIGER artifacts and embeddings for reproducibility; it is not intended to replace or relicense the original datasets.
+
+Please consult the original dataset sources and their terms before using these files.
+
+## Loading
+
+The split files can be read as JSON Lines. For example:
+
+```python
+import json
+import numpy as np
+
+with open("beauty/beauty.train.jsonl") as f:
+    first = json.loads(next(f))
+
+emb = np.load("beauty/Beauty.emb-llama.npy")
+```
+
+You can download files with `huggingface_hub`:
+
+```python
+from huggingface_hub import hf_hub_download
+
+path = hf_hub_download(
+    repo_id="junchenfu/diger-processed-data",
+    repo_type="dataset",
+    filename="beauty/Beauty.emb-llama.npy",
+)
+```
+
+## Citation
+
+If you use these processed artifacts, please cite the DIGER paper and the original dataset sources.