Instructions to use MLXCreator/MLXCreator-ACEStep-1.5-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MLXCreator/MLXCreator-ACEStep-1.5-4bit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MLXCreator/MLXCreator-ACEStep-1.5-4bit", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - MLX
How to use MLXCreator/MLXCreator-ACEStep-1.5-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MLXCreator-ACEStep-1.5-4bit MLXCreator/MLXCreator-ACEStep-1.5-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 25f1dc0fa1e323c9f5f9f25b769b730ad7f9fac282231c494e49ffbbc48f6674
- Size of remote file:
- 675 MB
- SHA256:
- c84ac17576b1c5b0a4da2af9ee165401cd1e9e76cbc7d85cf606a3bb0f4bbbf1
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