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:
- 02f38a439e1b3fe5cb98108a64af84d1ad1722c432fb0bed2e43f1573195f0c1
- Size of remote file:
- 10 GB
- SHA256:
- 8171a25dd356525379573429c35eb610d79989d7e52f9129f1dfb9ea82f6e5e6
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