Instructions to use alaub/10Eros-Max-fl2va-diffusers-transformer-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alaub/10Eros-Max-fl2va-diffusers-transformer-int8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alaub/10Eros-Max-fl2va-diffusers-transformer-int8", 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
- Xet hash:
- 3cb995b798efa90381b4c8626f6185d680c354db282642e05dd95f2076ad9ccf
- Size of remote file:
- 9.81 GB
- SHA256:
- 079a492cafbd3e1e69d330a23ceda3e764fc13c6b4f30c1a7f6ffc833d46ac9b
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