Instructions to use KamCastle/meticulous with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KamCastle/meticulous with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KamCastle/meticulous", 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 vae/diffusion_pytorch_model.bin from KamCastle/meticulous: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/KamCastle/meticulous/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://KamCastle/meticulous/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/KamCastle/meticulous/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 1c4839ac24c44a9d241652aef3878bd00f630d71e9f5e17dd1c295b71359d71a
- Size of remote file:
- 335 MB
- SHA256:
- c693d974604faea22ff0d3f99eb71973bbcff8a9a6e9645c81058a4706df21af
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