Diffusers
ophthalmology
OCT
fundus
medical-imaging
diffusion
stable-diffusion-3
segmentation
instruction-tuning
Instructions to use MaybeRichard/OCTFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MaybeRichard/OCTFlow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MaybeRichard/OCTFlow", 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
OCTFlow v1 (2026-06-21): 13 weights (core+downstream) + S0-S7 report + experiment log; public release
941b719 verified - Xet hash:
- 71eeb79757d87b3c26e6e6410416bde51c11370f102c8acdb950efd23367cebe
- Size of remote file:
- 8.34 GB
- SHA256:
- 8d917cce08bd25c3c80866c0e08f8f7aff0a3a8418d7d1dcd059158d78f989ff
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