Instructions to use ChandrilBasu/Borse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ChandrilBasu/Borse 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("ChandrilBasu/Borse") prompt = "UNICODE\u0000\u0000c\u0000i\u0000n\u0000e\u0000m\u0000a\u0000t\u0000i\u0000c\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000 \u0000o\u0000f\u0000 \u0000b\u0000o\u0000r\u0000s\u0000e\u0000 \u0000 \u0000a\u0000n\u0000 \u0000a\u0000c\u0000t\u0000r\u0000e\u0000s\u0000s\u0000,\u0000 \u0000f\u0000a\u0000c\u0000e\u0000 \u0000c\u0000l\u0000o\u0000s\u0000e\u0000u\u0000p\u0000 \u0000f\u0000r\u0000o\u0000n\u0000t\u0000,\u0000 \u0000o\u0000u\u0000t\u0000s\u0000i\u0000d\u0000e\u0000 \u0000n\u0000i\u0000g\u0000h\u0000t\u0000,\u0000 \u0000s\u0000i\u0000t\u0000t\u0000i\u0000n\u0000g\u0000,\u0000 \u0000r\u0000e\u0000d\u0000 \u0000l\u0000e\u0000a\u0000t\u0000h\u0000e\u0000r\u0000 \u0000j\u0000a\u0000c\u0000k\u0000e\u0000t\u0000 \u0000w\u0000i\u0000t\u0000h\u0000 \u0000w\u0000h\u0000i\u0000t\u0000e\u0000 \u0000a\u0000c\u0000c\u0000e\u0000n\u0000t\u0000s\u0000 \u0000b\u0000l\u0000a\u0000c\u0000k\u0000 \u0000u\u0000n\u0000d\u0000e\u0000r\u0000 \u0000d\u0000e\u0000n\u0000i\u0000m\u0000 \u0000j\u0000e\u0000a\u0000n\u0000s\u0000 \u0000b\u0000r\u0000o\u0000w\u0000n\u0000 \u0000b\u0000o\u0000o\u0000t\u0000s\u0000 \u0000b\u0000l\u0000a\u0000c\u0000k\u0000 \u0000f\u0000i\u0000n\u0000g\u0000e\u0000r\u0000l\u0000e\u0000s\u0000s\u0000 \u0000g\u0000l\u0000o\u0000v\u0000e\u0000s\u0000 \u0000h\u0000o\u0000l\u0000s\u0000t\u0000e\u0000r\u0000 \u0000a\u0000m\u0000m\u0000u\u0000n\u0000i\u0000t\u0000i\u0000o\u0000n\u0000 \u0000p\u0000o\u0000u\u0000c\u0000h\u0000e\u0000s\u0000 \u0000.\u00003\u00005\u0000m\u0000m\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000g\u0000r\u0000a\u0000p\u0000h\u0000,\u0000 \u0000f\u0000i\u0000l\u0000m\u0000,\u0000 \u0000b\u0000o\u0000k\u0000e\u0000h\u0000,\u0000 \u0000p\u0000r\u0000o\u0000f\u0000e\u0000s\u0000s\u0000i\u0000o\u0000n\u0000a\u0000l\u0000,\u0000 \u00004\u0000k\u0000,\u0000 \u0000h\u0000i\u0000g\u0000h\u0000l\u0000y\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000e\u0000d\u0000 \u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000b\u0000h\u0000a\u0000g\u0000y\u0000a\u0000s\u0000h\u0000r\u0000i\u0000-\u0000b\u0000o\u0000r\u0000s\u0000e\u0000-\u00000\u00000\u00000\u00000\u00000\u00008\u0000:\u00000\u0000.\u00009\u0000>\u0000 \u0000" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Borse
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- Prompt
- UNICODEcinematic photo of borse an actress, face closeup front, outside night, sitting, red leather jacket with white accents black under denim jeans brown boots black fingerless gloves holster ammunition pouches .35mm photograph, film, bokeh, professional, 4k, highly detailed <lora:bhagyashri-borse-000008:0.9>
Trigger words
You should use borse 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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