Instructions to use nachomartinezl/nacho with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nachomartinezl/nacho with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SY573M404/f222-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("nachomartinezl/nacho") prompt = "a photo of 7766c9e50f2b person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
LoRA DreamBooth - nachomartinezl/nacho
These are LoRA adaption weights for SY573M404/f222-diffusers. The weights were trained on a photo of 7766c9e50f2b person using DreamBooth. You can find some example images in the following.
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Model tree for nachomartinezl/nacho
Base model
SY573M404/f222-diffusers


