Instructions to use Akalabeth12/Text-to-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Akalabeth12/Text-to-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Akalabeth12/Text-to-Image", 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
Ctrl+K
- ANIMA LORAS
- ANIMA
- CHROMA LORAS
- CHROMA
- CLIP
- CONTROLNET
- DETAILERS
- FLUX CONTROL
- FLUX LORAS
- FLUX
- IDEOGRAM 4 LORAS
- IDEOGRAM 4
- ILLUSTRIOUS LORAS
- ILLUSTRIOUS
- KREA 2 LORAS
- KREA 2
- KREA LORAS
- KREA
- LUMINA
- NOOBAI LORAS
- NOOBAI
- PONY LORAS
- PONY
- PREPROCESSORS
- SD1.5 EMBEDDINGS
- SD1.5 LORAS
- SDXL II
- SDXL LORAS
- SDXL
- Stable Diffusion 1.5
- TEXT ENCODERS
- UPSCALERS
- VAE APPROX
- VAE
- Z IMAGE BASE LORAS
- Z IMAGE BASE
- Z IMAGE TURBO LORAS
- Z IMAGE TURBO
- 51.9 kB