Instructions to use Akalabeth12/Text-to-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Akalabeth12/Text-to-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Akalabeth12/Text-to-Image", 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
Upload z_image_base_fp32.safetensors
Browse files
Z IMAGE BASE/z_image_base_fp32.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:69c6b4f3521a55981337048fbcdb82bcd57f3b8b83ca34014969ac80ced70f82
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