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 Settings
- Draw Things
- DiffusionBee
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Download README.md from francsharma/chini: direct link, hf CLI and curl.
- Browser
- Download file 457 Bytes
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https://huggingface.co/francsharma/chini/resolve/main/README.md
- Command line
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hf download hf://francsharma/chini/README.md
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curl -L -o README.md https://huggingface.co/francsharma/chini/resolve/main/README.md
457 Bytes
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/00315-3060916687-esrgan4x.png | |
| text: >- | |
| head shot portrait photo of a beautiful 20yo woman, lacey white shirt, | |
| smiling <lora:beauty_standard1:0.85> | |
| base_model: black-forest-labs/FLUX.1-dev | |
| instance_prompt: null | |
| # chini | |
| <Gallery /> | |
| ## Download model | |
| [Download](/francsharma/chini/tree/main) them in the Files & versions tab. | |