Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use CompVis/stable-diffusion-v1-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CompVis/stable-diffusion-v1-4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") prompt = "A high tech solarpunk utopia in the Amazon rainforest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
AttributeError: 'AutoencoderKLOutput' object has no attribute 'sample'
#53
by ArchaeonSeq - opened
Started getting this error suddenly even though I have been using the code with no issues for some time
Hi @ArchaeonSeq , there were breaking changes in the scheduler outputs of diffusers version 0.3.0: https://github.com/huggingface/diffusers/releases/tag/v0.3.0.
In this case, I think you can use the following instead:
init_latents = self.vae.encode(init_image.to(self.device)).latent_dist.sample()
or:
init_latents = self.vae.encode(init_image.to(self.device))[0].sample()
