Instructions to use Lonuhbow/beth3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lonuhbow/beth3 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("Lonuhbow/beth3") prompt = "A cinematic, wide shot of Beth3 as a futuristic cybernetic explorer standing on the neon-lit crystalline plains of a distant purple planet." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from Lonuhbow/beth3: direct link, hf CLI and curl.
- Browser
- Download file 195 MB
-
https://huggingface.co/Lonuhbow/beth3/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://Lonuhbow/beth3/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Lonuhbow/beth3/resolve/main/checkpoint-2000/optimizer.bin
195 MB
- Xet hash:
- 802aed0e836e39ec32dd2c9621920c189ec0a0284563bfb32d0dc5fd43526007
- Size of remote file:
- 195 MB
- SHA256:
- 097ac39c7b859f431fb93340291d435e7c7f3eeaa59b785a38f1ca48dbdb2fd4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.