Instructions to use pixologyds/xpriyam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pixologyds/xpriyam 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("pixologyds/xpriyam") prompt = "wide and low angle, cinematic, fashion photography. xpriyam sitting on floor wearing a full size white t-shirt with big letters \\\"Priyamani\\\" logo text, green jeans, colored high heels and a gracious look on her face. The background is a color gradient, her face is lit with cool white light, studio setting <lora:xpriyam_lora:1>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Priyamani

- Prompt
- wide and low angle, cinematic, fashion photography. xpriyam sitting on floor wearing a full size white t-shirt with big letters \"Priyamani\" logo text, green jeans, colored high heels and a gracious look on her face. The background is a color gradient, her face is lit with cool white light, studio setting <lora:xpriyam_lora:1>
Trigger words
You should use xpriyam 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 pixologyds/xpriyam
Base model
black-forest-labs/FLUX.1-dev