Use dataset variable for embedding loading example

README.md

@@ -62,13 +62,19 @@ import json
 import numpy as np
 
 repo_id = "junchenfu/diger-processed-data"
-dataset = "beauty"
+dataset = "beauty"  # choose from: "beauty", "instruments", "yelp"
+
+embedding_files = {
+    "beauty": "Beauty.emb-llama.npy",
+    "instruments": "Instruments.emb-llama.npy",
+    "yelp": "Yelp.emb-llama.npy",
+}
 
 train_path = hf_hub_download(repo_id=repo_id, repo_type="dataset", filename=f"{dataset}/{dataset}.train.jsonl")
 valid_path = hf_hub_download(repo_id=repo_id, repo_type="dataset", filename=f"{dataset}/{dataset}.valid.jsonl")
 test_path = hf_hub_download(repo_id=repo_id, repo_type="dataset", filename=f"{dataset}/{dataset}.test.jsonl")
 map_path = hf_hub_download(repo_id=repo_id, repo_type="dataset", filename=f"{dataset}/{dataset}.emb_map.json")
-emb_path = hf_hub_download(repo_id=repo_id, repo_type="dataset", filename="beauty/Beauty.emb-llama.npy")
+emb_path = hf_hub_download(repo_id=repo_id, repo_type="dataset", filename=f"{dataset}/{embedding_files[dataset]}")
 
 with open(train_path, encoding="utf-8") as f:
     first_train = json.loads(next(f))