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_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use benetraco/latent_finetuning_encoder 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_encoder", 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
- Xet hash:
- 775e6b310b9d8f45cb9848667748f29e5b4fc0c38819a5d9d40b609cda3d7c82
- Size of remote file:
- 492 MB
- SHA256:
- ec2a717e0d6368168ade5deda23970b4441441e18c36eec7fcc95666e755afe3
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