Update app.py

app.py

@@ -3,42 +3,15 @@ from PIL import Image
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# # Set default device to CUDA for GPU acceleration
-# device = 'cuda' if torch.cuda.is_available() else "cpu"
 torch.set_default_device("cuda")
 
 # Initialize the model and tokenizer
-model = AutoModelForCausalLM.from_pretrained("ManishThota/Sparrow",  torch_dtype=torch.float16, 
-    device_map="auto",
-    trust_remote_code=True).to(device)
+model = AutoModelForCausalLM.from_pretrained("ManishThota/Sparrow",
+                                             torch_dtype=torch.float16, 
+                                             device_map="auto",
+                                             trust_remote_code=True)
 tokenizer = AutoTokenizer.from_pretrained("ManishThota/Sparrow", trust_remote_code=True)
 
-# def predict_answer(image, question):
-#     # Convert PIL image to RGB if not already
-#     image = image.convert("RGB")
-    
-#     # # Format the text input for the model
-#     # text = f"A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>\n{question} ASSISTANT:"
-    
-#     # Tokenize the text input
-#     encoding = tokenizer(image, question, return_tensors='pt').to(device)
-
-#     out = model.generate(**encoding)
-#     # Preprocess the image for the model
-#     generated_text = tokenizer.decode(out[0], skip_special_tokens=True)
-    
-#     # # Generate the answer
-#     # output_ids = model.generate(
-#     #     input_ids,
-#     #     max_new_tokens=100,
-#     #     images=image_tensor,
-#     #     use_cache=True)[0]
-    
-#     # # Decode the generated tokens to get the answer
-#     # answer = tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True).strip()
-    
-#     return generated_text
-
 def predict_answer(image, question, max_tokens):
     #Set inputs
     text = f"A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>\n{question}? ASSISTANT:"