Instructions to use SeanZheng/Distill-WAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SeanZheng/Distill-WAM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SeanZheng/Distill-WAM", 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
galaxea-a1-kitchen-no-memory-flashwam-nochunk-step114: weights
Browse files
galaxea-a1-kitchen-no-memory-flashwam-nochunk-step114/transformer/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6c66f830a6340bd39f952ba3d216fc3ea725117fa6d679ad5a3973b81fba3bd6
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size 19997351340
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