Instructions to use nebulette/mossad-2b-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nebulette/mossad-2b-encoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nebulette/mossad-2b-encoder", 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
This is an alpha release, which will remain so until stated otherwise.
The direct continuation of Moqs for the MOSSad finetune.
- JSON layout support (without the text field)
- 400 art genres and techniques
- reference names as either "style of [name]" or @name
The layout editor has been used to define the pose.
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