Instructions to use Alexvp/latina21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Alexvp/latina21 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Alexvp/latina21") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Alexvp/latina21: direct link, hf CLI and curl.
- Browser
- Download file 396 Bytes
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https://huggingface.co/Alexvp/latina21/resolve/main/README.md
- Command line
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hf download hf://Alexvp/latina21/README.md
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curl -L -o README.md https://huggingface.co/Alexvp/latina21/resolve/main/README.md
396 Bytes
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/1231.png | |
| text: '-' | |
| base_model: Tongyi-MAI/Z-Image-Turbo | |
| instance_prompt: latina | |
| # latina12 | |
| <Gallery /> | |
| ## Trigger words | |
| You should use `latina` to trigger the image generation. | |
| ## Download model | |
| [Download](/Alexvp/latina21/tree/main) them in the Files & versions tab. | |