Instructions to use microsoft/vq-diffusion-ithq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use microsoft/vq-diffusion-ithq with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("microsoft/vq-diffusion-ithq", 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
metadata
license: mit
VQ Diffusion
Authors: Shuyang Gu, Dong Chen, et al.
#!pip install diffusers[torch] transformers
import torch
from diffusers import VQDiffusionPipeline
pipeline = VQDiffusionPipeline.from_pretrained("microsoft/vq-diffusion-ithq", torch_dtype=torch.float16)
pipeline = pipeline.to("cuda")
output = pipeline("teddy bear playing in the pool", truncation_rate=1.0)
image = output.images[0]
image.save("./teddy_bear.png")
Contribution: This model was contribution by williamberman in VQ-diffusion.
