Instructions to use codyreading/custom_diffusion-noprior with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codyreading/custom_diffusion-noprior with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("codyreading/custom_diffusion-noprior", dtype=torch.bfloat16, device_map="cuda") prompt = "None" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 662 Bytes
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---
license: creativeml-openrail-m
base_model: runwayml/stable-diffusion-v1-5
instance_prompt: None
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- custom-diffusion
inference: true
---
# Custom Diffusion - codyreading/custom_diffusion-noprior
These are Custom Diffusion adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on None using [Custom Diffusion](https://www.cs.cmu.edu/~custom-diffusion). You can find some example images in the following.
For more details on the training, please follow [this link](https://github.com/huggingface/diffusers/blob/main/examples/custom_diffusion).
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