Instructions to use funseshon/faju with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use funseshon/faju with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("funseshon/faju") prompt = "A cinematic shot of a futuristic FAJU robot tending to a glowing neon garden in a floating cyberpunk city." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1000/optimizer.bin from funseshon/faju: direct link, hf CLI and curl.
- Browser
- Download file 195 MB
-
https://huggingface.co/funseshon/faju/resolve/main/checkpoint-1000/optimizer.bin
- Command line
-
hf download hf://funseshon/faju/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/funseshon/faju/resolve/main/checkpoint-1000/optimizer.bin
195 MB
- Xet hash:
- ce0cf5fa82146ef3cea4a575f2fb3f8e5d74382b6abaf007fc8f074a1d311fdb
- Size of remote file:
- 195 MB
- SHA256:
- 8df11600cf0e235633d03d630bc8018f059e23d209969d06e708cade6d6503bd
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