Update app.py

app.py

@@ -1,5 +1,6 @@
 import os
 os.system('git clone https://github.com/tencent-ailab/IP-Adapter.git')
+os.system('wget https://huggingface.co/h94/IP-Adapter/resolve/main/models/ip-adapter_sd15.bin')
 os.system('mv IP-Adapter IP_Adapter')
 os.system('ls IP_Adapter/ip_adapter')
 import gradio as gr
@@ -16,7 +17,7 @@ base_model_path = "stable-diffusion-v1-5/stable-diffusion-v1-5"
 vae_model_path = "stabilityai/sd-vae-ft-mse"
 image_encoder_repo="InvokeAI/ip_adapter_sd_image_encoder"
 image_encoder_path = "IP_Adapter/ip_adapter/models/image_encoder/"
-ip_ckpt = "https://huggingface.co/h94/IP-Adapter/resolve/main/models/ip-adapter_sd15.bin"
+ip_ckpt = "ip-adapter_sd15.bin"
 device = "cpu"  # or "cuda" if using GPU
 
 # VAE and scheduler
@@ -46,7 +47,7 @@ def generate_variations(upload_img):
         vae=vae,
         feature_extractor=None,
         safety_checker=None,
-        torch_dtype=torch.float16
+        #torch_dtype=torch.float16
     )
     ip_model = IPAdapter(pipe, image_encoder_repo, ip_ckpt, device)
     images = ip_model.generate(pil_image=upload_img, num_samples=4, num_inference_steps=50, seed=42)
@@ -55,7 +56,7 @@ def generate_variations(upload_img):
 def generate_img2img(base_img, guide_img):
     pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
         base_model_path,
-        torch_dtype=torch.float16,
+        #torch_dtype=torch.float16,
         scheduler=noise_scheduler,
         vae=vae,
         feature_extractor=None,
@@ -68,7 +69,7 @@ def generate_img2img(base_img, guide_img):
 def generate_inpaint(input_img, masked_img, mask_img):
     pipe = StableDiffusionInpaintPipelineLegacy.from_pretrained(
         base_model_path,
-        torch_dtype=torch.float16,
+        #torch_dtype=torch.float16,
         scheduler=noise_scheduler,
         vae=vae,
         feature_extractor=None,