files for inference generation

app.py

@@ -4,6 +4,7 @@ from PIL import Image
 import torchvision.transforms as transforms
 import torch
 from model import load_model
+import os
 
 # Initialize FastAPI
 app = FastAPI()

model.py

@@ -1,10 +1,21 @@
 import os
+
+
+
+# Set cache directory to a writable location within your app's directory
+os.environ["TRANSFORMERS_CACHE"] = "./cache"
+os.makedirs("./cache", exist_ok=True)
+
+
+
 import torch
 import torch.nn as nn
 from transformers import ViTModel, T5ForConditionalGeneration, T5Tokenizer
 from transformers.modeling_outputs import BaseModelOutput
 import requests
 
+
+
 class ViTT5(nn.Module):
     def __init__(self, vit_encoder, t5_decoder):
         super(ViTT5, self).__init__()