Instructions to use fangqi/world_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fangqi/world_checkpoints with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fangqi/world_checkpoints", 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
Add files using upload-large-folder tool
Browse files
aol_online_only_low_nft/ema/checkpoint-2900/transformer/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9028b17232393c33df597de8894b62a20af7688bc795e42d86ed8bfa97a77ede
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size 34231948208
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