Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
|
@@ -16,7 +16,6 @@ with open('loras.json', 'r') as f:
|
|
| 16 |
# Initialize the base model
|
| 17 |
base_model = "black-forest-labs/FLUX.1-dev"
|
| 18 |
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
|
| 19 |
-
pipe.to("cuda")
|
| 20 |
|
| 21 |
MAX_SEED = 2**32-1
|
| 22 |
|
|
@@ -50,6 +49,7 @@ def update_selection(evt: gr.SelectData):
|
|
| 50 |
|
| 51 |
@spaces.GPU(duration=80)
|
| 52 |
def generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress):
|
|
|
|
| 53 |
|
| 54 |
generator = torch.Generator(device="cuda").manual_seed(seed)
|
| 55 |
|
|
@@ -87,7 +87,7 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
|
|
| 87 |
seed = random.randint(0, MAX_SEED)
|
| 88 |
|
| 89 |
image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress)
|
| 90 |
-
|
| 91 |
pipe.unload_lora_weights()
|
| 92 |
return image, seed
|
| 93 |
|
|
|
|
| 16 |
# Initialize the base model
|
| 17 |
base_model = "black-forest-labs/FLUX.1-dev"
|
| 18 |
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
|
|
|
|
| 19 |
|
| 20 |
MAX_SEED = 2**32-1
|
| 21 |
|
|
|
|
| 49 |
|
| 50 |
@spaces.GPU(duration=80)
|
| 51 |
def generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress):
|
| 52 |
+
pipe.to("cuda")
|
| 53 |
|
| 54 |
generator = torch.Generator(device="cuda").manual_seed(seed)
|
| 55 |
|
|
|
|
| 87 |
seed = random.randint(0, MAX_SEED)
|
| 88 |
|
| 89 |
image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress)
|
| 90 |
+
pipe.to("cpu")
|
| 91 |
pipe.unload_lora_weights()
|
| 92 |
return image, seed
|
| 93 |
|