Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -40,7 +40,7 @@ masterpiece, newest, absurdres
|
|
40 |
torch.backends.cudnn.deterministic = True
|
41 |
torch.backends.cudnn.benchmark = False
|
42 |
|
43 |
-
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
44 |
|
45 |
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
|
46 |
if randomize_seed:
|
@@ -72,6 +72,20 @@ def get_scheduler(scheduler_config: Dict, name: str) -> Optional[Callable]:
|
|
72 |
}
|
73 |
return scheduler_factory_map.get(name, lambda: None)()
|
74 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
75 |
@spaces.GPU(enable_queue=False)
|
76 |
def generate(
|
77 |
prompt: str,
|
@@ -81,9 +95,10 @@ def generate(
|
|
81 |
height: int = 1024,
|
82 |
guidance_scale: float = 5.0,
|
83 |
num_inference_steps: int = 26,
|
84 |
-
sampler: str = "
|
85 |
clip_skip: int = 1,
|
86 |
):
|
|
|
87 |
if torch.cuda.is_available():
|
88 |
pipe = StableDiffusionXLPipeline.from_pretrained(
|
89 |
MODEL,
|
@@ -94,6 +109,7 @@ def generate(
|
|
94 |
add_watermarker=False,
|
95 |
use_auth_token=HF_TOKEN
|
96 |
)
|
|
|
97 |
|
98 |
generator = seed_everything(seed)
|
99 |
pipe.scheduler = get_scheduler(pipe.scheduler.config, sampler)
|
|
|
40 |
torch.backends.cudnn.deterministic = True
|
41 |
torch.backends.cudnn.benchmark = False
|
42 |
|
43 |
+
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
|
44 |
|
45 |
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
|
46 |
if randomize_seed:
|
|
|
72 |
}
|
73 |
return scheduler_factory_map.get(name, lambda: None)()
|
74 |
|
75 |
+
def load_pipeline(model_name):
|
76 |
+
if torch.cuda.is_available():
|
77 |
+
pipe = StableDiffusionXLPipeline.from_pretrained(
|
78 |
+
model_name,
|
79 |
+
torch_dtype=torch.float16,
|
80 |
+
custom_pipeline="lpw_stable_diffusion_xl",
|
81 |
+
safety_checker=None,
|
82 |
+
use_safetensors=True,
|
83 |
+
add_watermarker=False,
|
84 |
+
use_auth_token=HF_TOKEN
|
85 |
+
)
|
86 |
+
pipe.to(device)
|
87 |
+
return pipe
|
88 |
+
|
89 |
@spaces.GPU(enable_queue=False)
|
90 |
def generate(
|
91 |
prompt: str,
|
|
|
95 |
height: int = 1024,
|
96 |
guidance_scale: float = 5.0,
|
97 |
num_inference_steps: int = 26,
|
98 |
+
sampler: str = "Eul""er a",
|
99 |
clip_skip: int = 1,
|
100 |
):
|
101 |
+
"""
|
102 |
if torch.cuda.is_available():
|
103 |
pipe = StableDiffusionXLPipeline.from_pretrained(
|
104 |
MODEL,
|
|
|
109 |
add_watermarker=False,
|
110 |
use_auth_token=HF_TOKEN
|
111 |
)
|
112 |
+
"""
|
113 |
|
114 |
generator = seed_everything(seed)
|
115 |
pipe.scheduler = get_scheduler(pipe.scheduler.config, sampler)
|