Instructions to use diffusers-internal-dev/tiny-minimax-h3-modular-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-internal-dev/tiny-minimax-h3-modular-pipe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-internal-dev/tiny-minimax-h3-modular-pipe", 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
- Xet hash:
- 6e9b2263cdf9c3d3e0767ea863ce3867b82447a077e0bcd4703a6813be7a7104
- Size of remote file:
- 91 kB
- SHA256:
- 5b713e1a4d05d24615a9675c67c91df06f0db7e0c28c583ec0df595b5353a405
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.