Instructions to use Texttra/Cityscape_Studio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Texttra/Cityscape_Studio with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Texttra/Cityscape_Studio") prompt = "c1t3, close up of severed head of a black woman with a fluorescent orange bob haircut with bangs and wearing amber square sunglasses, being held to the side, harsh fill in flash lighting, dark spooky forest background " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update handler.py
Browse files- handler.py +12 -7
handler.py
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@@ -2,14 +2,19 @@ from diffusers import DiffusionPipeline
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import torch
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class EndpointHandler:
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def __init__(self, path=""):
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print("Loading pipeline...")
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def __call__(self, data):
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inputs = data.pop("inputs", data)
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import torch
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class EndpointHandler:
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def __init__(self, path="Texttra/Cityscape_Studio"):
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print("Loading pipeline...")
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try:
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self.pipe = DiffusionPipeline.from_pretrained(
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path,
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torch_dtype=torch.float16,
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revision="fp16",
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use_safetensors=True
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).to("cuda")
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print("Pipeline loaded successfully.")
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except Exception as e:
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print(f"Error loading model: {e}")
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raise
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def __call__(self, data):
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inputs = data.pop("inputs", data)
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