Upload model.py

model.py

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+# Importing the requirements
+import torch
+from transformers import AutoModel, AutoTokenizer
+import spaces
+
+
+# Device for the model
+device = "cuda"
+
+# Load the model and tokenizer
+model = AutoModel.from_pretrained(
+    "openbmb/MiniCPM-Llama3-V-2_5", trust_remote_code=True, torch_dtype=torch.float16
+)
+model = model.to(device=device)
+tokenizer = AutoTokenizer.from_pretrained(
+    "openbmb/MiniCPM-Llama3-V-2_5", trust_remote_code=True
+)
+model.eval()
+
+
+@spaces.GPU(duration=120)
+def answer_question(image, question):
+    """
+    Generates an answer to a given question based on the provided image and question.
+    Args:
+        image (str): The path to the image file.
+        question (str): The question text.
+    Returns:
+        str: The generated answer to the question.
+    """
+
+    # Message format for the model
+    msgs = [{"role": "user", "content": question}]
+
+    # Generate the answer
+    res = model.chat(
+        image=image,
+        msgs=msgs,
+        tokenizer=tokenizer,
+        sampling=True,
+        temperature=0.7,
+        stream=True,
+        system_prompt="You are an AI assistant specialized in visual content analysis. Given an image and a related question, analyze the image thoroughly and provide a precise and informative answer based on the visible content. Ensure your response is clear, accurate, and directly addresses the question.",
+    )
+
+    # Return the answer
+    return "".join(res)