Update app.py

app.py

@@ -75,7 +75,7 @@ def train_stock_model(stock_symbol, start_date, end_date, feature_range=(10, 100
     target_tensors = [t[0] for t in target]
 
     device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-    model = StockLlamaForForecasting.from_pretrained("StockLlama/StockLlama").to(device)
+    model = StockLlamaForForecasting.from_pretrained("StockLlama/StockLlama-base-v1").to(device)
     config = LoraConfig(
         r=64,
         lora_alpha=32,
@@ -88,7 +88,7 @@ def train_stock_model(stock_symbol, start_date, end_date, feature_range=(10, 100
 
     dct = {"input_ids": seq_tensors, "label": target_tensors}
     dataset = Dataset.from_dict(dct)
-    dataset.push_to_hub(repo_id)
+    dataset.push_to_hub(f"StockLlama/{stock_symbol}-{start_date}_{end_date}")
     trainer = Trainer(
         model=model,
         train_dataset=dataset,