Instructions to use francsharma/chini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use francsharma/chini 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("francsharma/chini") prompt = "head shot portrait photo of a beautiful 20yo woman, lacey white shirt, smiling <lora:beauty_standard1:0.85>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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beauty_standard1.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4b3a56c0e6eac854bdc033c862c978c9b86f992f5c690fbf4f5480459d1a472a
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size 153271560
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images/00315-3060916687-esrgan4x.png
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Git LFS Details
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