Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
diffusion
concept-erasure
stable-diffusion
esdx
chainsaw
Instructions to use DiffusionConceptErasure/esdx_chainsaw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DiffusionConceptErasure/esdx_chainsaw with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DiffusionConceptErasure/esdx_chainsaw", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| license: mit | |
| tags: | |
| - diffusion | |
| - concept-erasure | |
| - stable-diffusion | |
| - esdx | |
| - chainsaw | |
| datasets: | |
| - imagenet | |
| language: | |
| - en | |
| pipeline_tag: text-to-image | |
| # esdx_chainsaw | |
| This is a concept-erased Stable Diffusion model using the **Exact Source Distillation (ESD-X)** method to remove the concept **"Chainsaw"**. | |
| ## Method | |
| Exact Source Distillation (ESD-X) erases concepts by distilling knowledge while excluding specific concept representations. | |
| ## Usage | |
| ```python | |
| from diffusers import StableDiffusionPipeline | |
| import torch | |
| pipe = StableDiffusionPipeline.from_pretrained("ErasureResearch/esdx_chainsaw", torch_dtype=torch.float16).to("cuda") | |
| prompt = "a photo of a chainsaw" | |
| image = pipe(prompt).images[0] | |
| image.save("erased_chainsaw.png") | |
| ``` | |
| ## Citation | |
| If you use this model in your research, please cite: | |
| ```bibtex | |
| @article{concept_erasure_2024, | |
| title={Concept Erasure in Diffusion Models}, | |
| author={ErasureResearch Team}, | |
| journal={Proceedings of...}, | |
| year={2024} | |
| } | |
| ``` | |