Instructions to use Vijish/Samudra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Vijish/Samudra 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("Vijish/Samudra") prompt = "samudra9595" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 54c69ea88b05d3f4b335441e785dcdc5a41f0fee1901ee4d0b87032704659c59
- Size of remote file:
- 89.7 MB
- SHA256:
- ba016b175d8b6042363133d0943f93415c0626428387d66d1023e97745d21be0
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