Instructions to use rootlocalghost/Z-Image-Turbo-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rootlocalghost/Z-Image-Turbo-FP8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rootlocalghost/Z-Image-Turbo-FP8", 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
- Local Apps
- Draw Things
- DiffusionBee
Upload FP8 quantized transformer/diffusion_pytorch_model-00002-of-00003.safetensors
Browse files
transformer/diffusion_pytorch_model-00002-of-00003.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5b4933627a2d690dbc55ef215edf499dbfbae504dceea9f9654a624bfd1c0a13
|
| 3 |
+
size 2493446176
|