Instructions to use kashansean/Virat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kashansean/Virat 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("kashansean/Virat") prompt = "n3v4r0 , Ultra-HD, realistic, ((close portrait photo)), Shirt" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Virat

- Prompt
- n3v4r0 , Ultra-HD, realistic, ((close portrait photo)), Shirt
Trigger words
You should use n3v4r0 to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for kashansean/Virat
Base model
black-forest-labs/FLUX.1-dev