Instructions to use zz001/001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zz001/001 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("h94/IP-Adapter-FaceID", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("zz001/001") prompt = "1" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: '1'
parameters:
negative_prompt: '1'
output:
url: images/XbpD1BVwv8.png
base_model: h94/IP-Adapter-FaceID
instance_prompt: '11'
license: apache-2.0
111

- Prompt
- 1
- Negative Prompt
- 1
Model description
111
Trigger words
You should use 11 to trigger the image generation.
Download model
Download them in the Files & versions tab.