Instructions to use EnD-Diffusers/lineart-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/lineart-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/lineart-model", dtype=torch.bfloat16, device_map="cuda") prompt = "mchozn" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 1,010 Bytes
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license: creativeml-openrail-m
tags:
- text-to-image
widget:
- text: mchozn
---
### Line Art Model Dreambooth model trained by Duskfallcrew with [Hugging Face Dreambooth Training Space](https://huggingface.co/spaces/multimodalart/dreambooth-training) with the v1-5 base model
You run your new concept via `diffusers` [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb). Don't forget to use the concept prompts!
Testing to happen asap, just did this on the fly for kicks.
DO NOT: RESELL THE TRAINING DATA
Why? Cause my art is crap. and you should feel bad XD
What you can do:
Merge this model, host this model
What you still can't do: Sell the model, use it to make nasty things.
What's the copyright on this: It's my own art, thought some of it's fan art on a whime, it's probably crap - so i guess go ahead with the selling of generated images at your own risk?
mchozn (use that on your prompt)
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