Text-to-Image
Diffusers
ONNX
Safetensors
GGUF
English
art
agent
image-generation
video-generation
text-to-video
style-transfer
image-editing
tts
local-inference
Instructions to use atMrMattV/Visione with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use atMrMattV/Visione with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("atMrMattV/Visione", 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

- Xet hash:
- 533989d7c4fd278347afe110555308cc2ff59a7af1c81301f3ef15adc5f373fc
- Size of remote file:
- 1.83 MB
- SHA256:
- dc87387d00f8891fa4190f936c61459a6868e1d11e4d353979aba2e4085597d0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.