Instructions to use RamonGuthrie/z_image_base-nvfp8-mixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RamonGuthrie/z_image_base-nvfp8-mixed with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RamonGuthrie/z_image_base-nvfp8-mixed", 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 Settings
- Draw Things
- DiffusionBee
Upload z_image_base-nvfp8-mixed_MAX.safetensors
Browse filesLayers optimised to be as close to the full FP32 base model as possible, 74.41% size reduction, so this can run on 8GB Vram or less very easily!
z_image_base-nvfp8-mixed_MAX.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2ae25a3aec79901de2022032c2308de1fd85ec43c77eab685ba127620114e5c7
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size 6293653344
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