Text-to-Image
Diffusers
Safetensors
PyTorch
StableDiffusionPipeline
stable-diffusion
latent-diffusion
medical-imaging
brain-mri
multiple-sclerosis
dataset-conditioning
Instructions to use benetraco/latent_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use benetraco/latent_finetuning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("benetraco/latent_finetuning", 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:
- c6fbaf0bda4c0e1107942d43873aa0c6103897b58dc24a81561393f72cf69cde
- Size of remote file:
- 3.44 GB
- SHA256:
- f4eb318e746e112e2888847a845e9ef8267cacffc99330ff1553066c61093a72
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