Instructions to use huggingface-meta/concorde with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use huggingface-meta/concorde 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-schnell", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("huggingface-meta/concorde") prompt = "Nikon Photography of a silver chrome concorde flying with the orange moon in the background, night shot, clouds, 90s picture" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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## Credit
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Thanks to the AI Toolkit by [Ostris](https://github.com/ostris/ai-toolkit) for help with training.
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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## WIP
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An interface that let people use this HuggingFace space to collaboratively generate images of the Concorde, and curate the best images with an external model.
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## Credit
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Thanks to the AI Toolkit by [Ostris](https://github.com/ostris/ai-toolkit) for help with training.
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