Instructions to use fortbonnitar/Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fortbonnitar/Model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fortbonnitar/Model", 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
Download checkpoint-1000/optimizer.bin from fortbonnitar/Model: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/fortbonnitar/Model/resolve/main/checkpoint-1000/optimizer.bin
- Command line
-
hf download hf://fortbonnitar/Model/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/fortbonnitar/Model/resolve/main/checkpoint-1000/optimizer.bin
910 MB
- Xet hash:
- ac1fe5cab9021ce77f5cd020c914d24c63b5a7c69a57f8599a058839d0329e16
- Size of remote file:
- 910 MB
- SHA256:
- 8e2a1798ebed9ce410066f5298df17e812328ab38e6c5754322b9a9e7779a880
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