Instructions to use h1t/oms_l_mixclip_xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use h1t/oms_l_mixclip_xl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("h1t/oms_l_mixclip_xl", 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:
- 701459798c2ff6cbed426181328df7f004371f97b26a2eec8a92833dfdb3282c
- Size of remote file:
- 5.09 GB
- SHA256:
- 74fd9e2da1cc1cb5e6b6ea293ccf070766ae1ea094b40aae1814307b902ee14c
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