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
- Draw Things
- DiffusionBee
Update handler.py
Browse files- handler.py +2 -2
handler.py
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@@ -15,7 +15,7 @@ class EndpointHandler:
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print("Loading LoRA weights from: Texttra/Cityscape_Studio")
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self.pipe.load_lora_weights("Texttra/Cityscape_Studio", weight_name="c1t3_v1.safetensors")
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self.pipe.fuse_lora(lora_scale=
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self.pipe.to("cuda" if torch.cuda.is_available() else "cpu")
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print("Model initialized successfully.")
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@@ -32,7 +32,7 @@ class EndpointHandler:
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image = self.pipe(
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prompt,
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num_inference_steps=
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guidance_scale=4.5
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).images[0]
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print("Image generated.")
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print("Loading LoRA weights from: Texttra/Cityscape_Studio")
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self.pipe.load_lora_weights("Texttra/Cityscape_Studio", weight_name="c1t3_v1.safetensors")
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self.pipe.fuse_lora(lora_scale=0.9)
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self.pipe.to("cuda" if torch.cuda.is_available() else "cpu")
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print("Model initialized successfully.")
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image = self.pipe(
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prompt,
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num_inference_steps=50,
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guidance_scale=4.5
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).images[0]
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print("Image generated.")
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