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 text_encoder_2/model.safetensors from ModelsLab/Obj-base: direct link, hf CLI and curl.
- Browser
- Download file 1.39 GB
-
https://huggingface.co/ModelsLab/Obj-base/resolve/main/text_encoder_2/model.safetensors
- Command line
-
hf download hf://ModelsLab/Obj-base/text_encoder_2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ModelsLab/Obj-base/resolve/main/text_encoder_2/model.safetensors
1.39 GB
- Xet hash:
- 4492fc5e4a399bef9de0a2bc105359b4f0ca0fac7800a9258a5c53aac9c8b114
- Size of remote file:
- 1.39 GB
- SHA256:
- ec310df2af79c318e24d20511b601a591ca8cd4f1fce1d8dff822a356bcdb1f4
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