Spaces:
Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
@@ -60,27 +60,27 @@ def generate(
|
|
60 |
|
61 |
if not use_img2img:
|
62 |
pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch.float16)
|
63 |
-
pipe.
|
64 |
pipe.unet.set_default_attn_processor()
|
65 |
pipe.enable_vae_slicing()
|
66 |
|
67 |
if use_vae:
|
68 |
vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
|
69 |
pipe = DiffusionPipeline.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
|
70 |
-
pipe.
|
71 |
pipe.unet.set_default_attn_processor()
|
72 |
pipe.enable_vae_slicing()
|
73 |
|
74 |
if use_img2img:
|
75 |
pipe = AutoPipelineForImage2Image.from_pretrained(model, torch_dtype=torch.float16)
|
76 |
-
pipe.
|
77 |
pipe.unet.set_default_attn_processor()
|
78 |
pipe.enable_vae_slicing()
|
79 |
|
80 |
if use_vae:
|
81 |
vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
|
82 |
pipe = AutoPipelineForImage2Image.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
|
83 |
-
pipe.
|
84 |
pipe.unet.set_default_attn_processor()
|
85 |
pipe.enable_vae_slicing()
|
86 |
|
|
|
60 |
|
61 |
if not use_img2img:
|
62 |
pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch.float16)
|
63 |
+
pipe.enable_sequential_cpu_offload()
|
64 |
pipe.unet.set_default_attn_processor()
|
65 |
pipe.enable_vae_slicing()
|
66 |
|
67 |
if use_vae:
|
68 |
vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
|
69 |
pipe = DiffusionPipeline.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
|
70 |
+
pipe.enable_sequential_cpu_offload()
|
71 |
pipe.unet.set_default_attn_processor()
|
72 |
pipe.enable_vae_slicing()
|
73 |
|
74 |
if use_img2img:
|
75 |
pipe = AutoPipelineForImage2Image.from_pretrained(model, torch_dtype=torch.float16)
|
76 |
+
pipe.enable_sequential_cpu_offload()
|
77 |
pipe.unet.set_default_attn_processor()
|
78 |
pipe.enable_vae_slicing()
|
79 |
|
80 |
if use_vae:
|
81 |
vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
|
82 |
pipe = AutoPipelineForImage2Image.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
|
83 |
+
pipe.enable_sequential_cpu_offload()
|
84 |
pipe.unet.set_default_attn_processor()
|
85 |
pipe.enable_vae_slicing()
|
86 |
|