Update app.py

app.py

@@ -12,7 +12,8 @@ dataseteCQM = load_dataset("awacke1/eCQM-Code-Value-Semantic-Set.csv")
 # map using autotokenizer
 from transformers import AutoTokenizer
 tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
-dataset = dataset.map(lambda datasetLOINC : tokenizer(datasetLOINC["Description"]), batched=True)
+dataset = datasetLOINC.map(lambda examples: tokenizer(examples["Description"]), batched=True)
+JSONOBJ=dataset[0]
 
 print(datasetLOINC)
 print(datasetSNOMED)
@@ -33,7 +34,7 @@ import gradio as gr
 
 HF_TOKEN = os.environ.get("HF_TOKEN")
 CHOICES = ["SNOMED", "LOINC", "CQM"]
-JSONOBJ = """{"items":{"item":[{"id": "0001","type": null,"is_good": false,"ppu": 0.55,"batters":{"batter":[{ "id": "1001", "type": "Regular" },{ "id": "1002", "type": "Chocolate" },{ "id": "1003", "type": "Blueberry" },{ "id": "1004", "type": "Devil's Food" }]},"topping":[{ "id": "5001", "type": "None" },{ "id": "5002", "type": "Glazed" },{ "id": "5005", "type": "Sugar" },{ "id": "5007", "type": "Powdered Sugar" },{ "id": "5006", "type": "Chocolate with Sprinkles" },{ "id": "5003", "type": "Chocolate" },{ "id": "5004", "type": "Maple" }]}]}}"""
+#JSONOBJ = """{"items":{"item":[{"id": "0001","type": null,"is_good": false,"ppu": 0.55,"batters":{"batter":[{ "id": "1001", "type": "Regular" },{ "id": "1002", "type": "Chocolate" },{ "id": "1003", "type": "Blueberry" },{ "id": "1004", "type": "Devil's Food" }]},"topping":[{ "id": "5001", "type": "None" },{ "id": "5002", "type": "Glazed" },{ "id": "5005", "type": "Sugar" },{ "id": "5007", "type": "Powdered Sugar" },{ "id": "5006", "type": "Chocolate with Sprinkles" },{ "id": "5003", "type": "Chocolate" },{ "id": "5004", "type": "Maple" }]}]}}"""
 
 
 def profile_dataset(dataset=datasetSNOMED, username="awacke1", token=HF_TOKEN, dataset_name="awacke1/SNOMED-CT-Code-Value-Semantic-Set.csv"):