Instructions to use ModelsLab/Obj-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/Obj-base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ModelsLab/Obj-base", 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 unet/diffusion_pytorch_model.safetensors from ModelsLab/Obj-base: direct link, hf CLI and curl.
- Browser
- Download file 5.14 GB
-
https://huggingface.co/ModelsLab/Obj-base/resolve/main/unet/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://ModelsLab/Obj-base/unet/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/ModelsLab/Obj-base/resolve/main/unet/diffusion_pytorch_model.safetensors
5.14 GB
- Xet hash:
- 6309ef64c2196bec5dec3e5faae18f21368582afb2a3e1470cb928a1b6668da5
- Size of remote file:
- 5.14 GB
- SHA256:
- 1463cc6b5784b6199dcfa3068003573d7eb0fe5b0d4793bf6c8b740d8908540e
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