Instructions to use kaneyxx/bento with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kaneyxx/bento with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kaneyxx/bento") 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 checkpoint-2000/optimizer.bin from kaneyxx/bento: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/kaneyxx/bento/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://kaneyxx/bento/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/kaneyxx/bento/resolve/main/checkpoint-2000/optimizer.bin
6.85 MB
- Xet hash:
- ec19310cd1204eed9e1a84fe35d25ff4ac2575cc0370b460ad89b3fd99c00de9
- Size of remote file:
- 6.85 MB
- SHA256:
- 4f1b3a60e503bc3560286d252ea89018ee71fa87c1e532d83c39c646cab7c504
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