Instructions to use xin0920/trained-sd3-sae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xin0920/trained-sd3-sae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xin0920/trained-sd3-sae", 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
Download pytorch_sae_weights.safetensors from xin0920/trained-sd3-sae: direct link, hf CLI and curl.
- Browser
- Download file 267 MB
-
https://huggingface.co/xin0920/trained-sd3-sae/resolve/main/pytorch_sae_weights.safetensors
- Command line
-
hf download hf://xin0920/trained-sd3-sae/pytorch_sae_weights.safetensors
-
curl -L -o pytorch_sae_weights.safetensors https://huggingface.co/xin0920/trained-sd3-sae/resolve/main/pytorch_sae_weights.safetensors
267 MB
- Xet hash:
- 40678fa3be9e31e77d79f070cd068b2336ee98ef0c3e342716fe310fdee13bd7
- Size of remote file:
- 267 MB
- SHA256:
- 901c35ebb8a1b66c263daf5af637c4016353563d02c6d034a95206c0c84c0eb4
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