Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use ManuD/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ManuD/trained_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ManuD/trained_model", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of Julia" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 36a2633fd4c657cfc6e0da76e6b86584e1df4220357924cf6db7116de7d54054
- Size of remote file:
- 1 kB
- SHA256:
- 65115106fbd9463fa6c7133b543dece71c31fcba363ff15b8c73f8c7eb0739c5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.