Instructions to use MJ-Bench/DiffusionDPO-alignment-claude3-opus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MJ-Bench/DiffusionDPO-alignment-claude3-opus with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MJ-Bench/DiffusionDPO-alignment-claude3-opus", torch_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
- Xet hash:
- c0fa53cbb1247d69d7a31076189d2d5927493b77fc2cec56730e9cc16e87488b
- Size of remote file:
- 3.44 GB
- SHA256:
- 380e7045f6aaeb531461f4be9be69f368eac62e78c2917dcfaf7186a4621c6e5
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