Instructions to use glif-loradex-trainer/AP123_flux_dev_gpu_poor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use glif-loradex-trainer/AP123_flux_dev_gpu_poor 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("glif-loradex-trainer/AP123_flux_dev_gpu_poor") prompt = "wounded centaur, mythical creature gr4ph1c-4rt" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update metadata with huggingface_hub
Browse files
README.md
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- lora
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widget:
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- output:
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url: samples/1726950578835__000003000_0.jpg
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text: wounded centaur, mythical creature
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- output:
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url: samples/1726950603508__000003000_1.jpg
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text: ruins of athens, snake
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- output:
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url: samples/1726950628175__000003000_2.jpg
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text: silver vampire sword
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trigger: gr4ph1c-4rt
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---
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# flux_dev_gpu_poor
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- lora
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widget:
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url: https://huggingface.co/glif-loradex-trainer/AP123_flux_dev_gpu_poor/resolve/main/samples/1726950578835__000003000_0.jpg
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text: wounded centaur, mythical creature gr4ph1c-4rt
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- output:
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url: https://huggingface.co/glif-loradex-trainer/AP123_flux_dev_gpu_poor/resolve/main/samples/1726950603508__000003000_1.jpg
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text: ruins of athens, snake gr4ph1c-4rt
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- output:
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url: https://huggingface.co/glif-loradex-trainer/AP123_flux_dev_gpu_poor/resolve/main/samples/1726950628175__000003000_2.jpg
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text: silver vampire sword gr4ph1c-4rt
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trigger: gr4ph1c-4rt
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---
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# flux_dev_gpu_poor
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