Instructions to use fingerprinted/hellohello with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fingerprinted/hellohello with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("digiplay/hellopure_v2.23", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fingerprinted/hellohello") prompt = "hellohello" 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: hellohello
parameters:
negative_prompt: hellohello
output:
url: images/mz.svg
base_model: digiplay/hellopure_v2.23
instance_prompt: hello
license: bigscience-bloom-rail-1.0
hellohello
- Prompt
- hellohello
- Negative Prompt
- hellohello
Model description
hello
Trigger words
You should use hello to trigger the image generation.
Download model
Download them in the Files & versions tab.