Instructions to use ktkeller/mem-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ktkeller/mem-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ktkeller/mem-model", dtype=torch.bfloat16, device_map="cuda") prompt = "This is the Mem logo" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c46f9445bbcaf195ada31c1a4f70b137bc7dabcb8f83ccae10b4cfb551382be2
- Size of remote file:
- 492 MB
- SHA256:
- 6ea8a4263b7f9ec7d7d8af79295b44e0c8afa5d0abfb900c64f600216bc59641
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