Instructions to use pimpilikipilapi1/Facesitting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pimpilikipilapi1/Facesitting 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("pimpilikipilapi1/Facesitting") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add 2 files
Browse files- Facesitting FLUXDV1.safetensors +3 -0
- images/2.png +3 -0
Facesitting FLUXDV1.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ffe952267529b4264e0f8759b48113f77bf39524430a5ec23654e5af04b914b2
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size 171969424
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images/2.png
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Git LFS Details
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