Instructions to use XLabs-AI/flux-RealismLora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XLabs-AI/flux-RealismLora 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("XLabs-AI/flux-RealismLora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update README.md
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by arteivissa - opened
README.md
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@@ -50,6 +50,15 @@ A .json file contains "caption" field with a text prompt.
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python3 demo_lora_inference.py \
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--checkpoint lora.safetensors \
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--prompt " handsome girl in a suit covered with bold tattoos and holding a pistol. Animatrix illustration style, fantasy style, natural photo cinematic"
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```
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python3 demo_lora_inference.py \
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--checkpoint lora.safetensors \
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--prompt " handsome girl in a suit covered with bold tattoos and holding a pistol. Animatrix illustration style, fantasy style, natural photo cinematic"
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# Cargar el LoRA con un peso ajustable
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def load_lora_weights(pipe, lora_path, scale=0.75):
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lora_weights = torch.load(lora_path)
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# Aplicar el peso del LoRA (influencia)
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pipe.unet.load_attn_procs(lora_weights, scale=scale)
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# Generar la imagen con LoRA ajustado
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image = pipe(prompt, num_inference_steps=50).images[0]
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image.show()
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```
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