Instructions to use krahets/Diffuman4D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use krahets/Diffuman4D with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krahets/Diffuman4D", 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
Research Collaboration: Scaling Educational Video AI (Access to AIRAWAT Supercompute)
Hi Krahets,
I’ve been a huge fan of Hello-Algo—it’s the gold standard for how algorithms should be taught.
I recently came across your work on Diffuman4D and realized you are the perfect person for what we are building at Zulense.
We are building a generative video model specifically for Mathematics Education (Class 8-10). Our goal is to solve the "temporal consistency" problem in educational videos so AI tutors can explain concepts without distortion.
Why this might interest you:
Compute: We have access to the AIRAWAT Supercomputer and are ready to train large-scale diffusion models.
Domain: We are applying your two passions—Algo Education and 4D/Video Generation—into a single product.
I know you are likely focused on research, but I would love to discuss a potential collaboration, advisory role, or technical lead position.
Best, Manish kumar Founder, Zulense