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 Settings
- Draw Things
- DiffusionBee
Download added_tokens.json from benetraco/latent_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 57 Bytes
-
https://huggingface.co/benetraco/latent_finetuning/resolve/main/added_tokens.json
- Command line
-
hf download hf://benetraco/latent_finetuning/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/benetraco/latent_finetuning/resolve/main/added_tokens.json
57 Bytes
| { | |
| "SHIFTS": 49408, | |
| "VH": 49409, | |
| "WMH2017": 49410 | |
| } | |