Instructions to use AlexanderLab/BGZPRSN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlexanderLab/BGZPRSN with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AlexanderLab/BGZPRSN") prompt = "BGZPRSN" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- baa8c44b509fab3c354baa3bb4681cd6f24c6e4546b26afe25057b3d6062443c
- Size of remote file:
- 344 MB
- SHA256:
- d46a0b0693af4cee2338403c0b46b9432975829e65a214b4e91b04e05a05e60b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.