Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
General purpose
Photorealistic
3D artworks
Anime
Pixar
CGI
nitrosocke
PromptSharingSamaritan
artificialguybr
stable-diffusion
stable-diffusion-1.5
stable-diffusion-diffusers
Instructions to use Yntec/Shift with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Shift with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/Shift", 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 Settings
- Draw Things
- DiffusionBee
File size: 465 Bytes
d4ff7d3 b2522f3 d4ff7d3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- General purpose
- Photorealistic
- 3D artworks
- Anime
- Pixar
- CGI
- nitrosocke
- PromptSharingSamaritan
- artificialguybr
- stable-diffusion
- stable-diffusion-1.5
- stable-diffusion-diffusers
- text-to-image
- diffusers
base_model:
- nitrosocke/redshift-diffusion
- Yntec/LiberteRedmond
- Yntec/Shiny3DCartoon
base_model_relation: merge
---
Work in progress. |