update dataset refs for models

model_1h.py

@@ -214,7 +214,7 @@ def get_data():
 
         
     # Pull in data
-    data = load_dataset("boomsss/SPX_full_30min", split='train')
+    data = load_dataset("boomsss/spx_intra", split='train')
 
     rows = [d['text'] for d in data]
     rows = [x.split(',') for x in rows]

model_30m.py

@@ -210,7 +210,7 @@ def get_data():
     spx = yf.Ticker('^GSPC')
 
     # Pull in data
-    data = load_dataset("boomsss/SPX_full_30min", split='train')
+    data = load_dataset("boomsss/spx_intra", split='train')
 
     rows = [d['text'] for d in data]
     rows = [x.split(',') for x in rows]

model_90m.py

@@ -214,7 +214,7 @@ def get_data():
 
         
     # Pull in data
-    data = load_dataset("boomsss/SPX_full_30min", split='train')
+    data = load_dataset("boomsss/spx_intra", split='train')
 
     rows = [d['text'] for d in data]
     rows = [x.split(',') for x in rows]

model_day.py

@@ -18,7 +18,7 @@ from pandas.tseries.offsets import BDay
 from datasets import load_dataset
 
 # If the dataset is gated/private, make sure you have run huggingface-cli login
-dataset = load_dataset("boomsss/SPX_full_30min", split="train")
+dataset = load_dataset("boomsss/spx_intra", split="train")
 
 def walk_forward_validation(df, target_column, num_training_rows, num_periods):
     

research_hod_lod.ipynb

@@ -26,7 +26,7 @@
     "\n",
     "raw_data, df_final, final_date = get_data()\n",
     "\n",
-    "data = load_dataset(\"boomsss/SPX_full_30min\", split='train')\n",
+    "data = load_dataset(\"boomsss/spx_intra\", split='train')\n",
     "\n",
     "rows = [d['text'] for d in data]\n",
     "rows = [x.split(',') for x in rows]\n",