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:
- 6390528b41e77ad00617ea24c32ac837b35d1ab8e821b3f68ff31b8f481d8911
- Size of remote file:
- 2.13 GB
- SHA256:
- a5d435d9d2cb78865e931150b286f9676fb8b7d9aa684aca314faad70cd8d999
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