Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
code
stable-diffusion
scheduler
text_encoder
tokenizer
unet
vae
Instructions to use samim2024/text-to-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use samim2024/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("samim2024/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
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
-
Update README.md
Verified signaturea20edc7 -
Update README.md
Verified signature03c603a -
Update README.md
Verified signature85721f8 -
Update README.md
Verified signaturee213f37 -
Update README.md
Verified signature86c0030 -
Upload 5.jpeg
Verified signature8cb07a0 -
Update README.md
Verified signature318580d -
Update README.md
Verified signature123a578 -
Upload 4.jpeg
Verified signatureff8039f -
Update README.md
Verified signature26cdf46 -
Upload diffusion_pytorch_model.bin
Verified signaturecd06151 -
Upload diffusion_pytorch_model.bin
Verified signatureb9922a2 -
Upload pytorch_model.bin
Verified signature0434ee9 -
Update README.md
Verified signature388a546 -
Upload 10 files
Verified signature18be3c9 -
Upload 4 files
Verified signature6aa7149 -
Create README.md
Verified signature6297eb3 -
initial commit
Verified signature5083e19