Text-to-Image
Diffusers
Safetensors
MLX
English
ZImagePipeline
apple-silicon
quantized
4-bit precision
Instructions to use Giniiki/Z-Image-Turbo-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Giniiki/Z-Image-Turbo-mlx-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("Giniiki/Z-Image-Turbo-mlx-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 Giniiki/Z-Image-Turbo-mlx-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Z-Image-Turbo-mlx-4bit Giniiki/Z-Image-Turbo-mlx-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Draw Things
- DiffusionBee
- Atomic Chat
File size: 239 Bytes
3356ea2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"bos_token_id": 151643,
"do_sample": true,
"eos_token_id": [
151645,
151643
],
"pad_token_id": 151643,
"temperature": 0.6,
"top_k": 20,
"top_p": 0.95,
"transformers_version": "4.51.0"
} |