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
- Draw Things
- DiffusionBee
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]mem-model Dreambooth model trained by ktkeller with Hugging Face Dreambooth Training Space with the v1-5 base model
You run your new concept via diffusers Colab Notebook for Inference. Don't forget to use the concept prompts!
Sample pictures of:
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