Update app.py

app.py

@@ -1,3 +1,5 @@
+import warnings
+from transformers.utils import logging as transformers_logging
 import torch
 import yfinance as yf
 import matplotlib.pyplot as plt
@@ -7,6 +9,12 @@ import gradio as gr
 import logging
 from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
 
+# Suppress specific FutureWarnings from transformers library
+warnings.filterwarnings("ignore", category=FutureWarning, message=".*vocab_size.*")
+
+# Optionally, configure the transformers logging to avoid clutter
+transformers_logging.set_verbosity_error()
+
 # Configure logging to write to a file
 logging.basicConfig(filename='debug.log', level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
 
@@ -15,7 +23,7 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 logging.info(f"CUDA Available: {torch.cuda.is_available()}")
 logging.info(f"Device: {device}")
 
-# Load the model and processor
+# Load the ChartGemma model and processor
 model = PaliGemmaForConditionalGeneration.from_pretrained("ahmed-masry/chartgemma", torch_dtype=torch.float16).to(device)
 processor = AutoProcessor.from_pretrained("ahmed-masry/chartgemma")