Delete model.py

model.py

@@ -1,55 +0,0 @@
-# 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-V-2_6",
-    trust_remote_code=True,
-    attn_implementation="sdpa",
-    torch_dtype=torch.bfloat16,
-)
-model = model.to(device=device)
-tokenizer = AutoTokenizer.from_pretrained(
-    "openbmb/MiniCPM-V-2_6", 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": [image, question]}]
-
-    # Generate the answer
-    res = model.chat(
-        image=None,
-        msgs=msgs,
-        tokenizer=tokenizer,
-        sampling=True,
-        stream=True,
-        top_p=0.8,
-        top_k=100,
-        temperature=0.7,
-        repetition_penalty=1.05,
-        max_new_tokens=2048,
-        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)