Instructions to use ChandrilBasu/Ashi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ChandrilBasu/Ashi 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/Ashi") prompt = "UNICODE\u0000\u0000r\u0000e\u0000a\u0000l\u0000i\u0000s\u0000t\u0000i\u0000c\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000 \u0000o\u0000f\u0000 \u0000a\u0000 \u0000w\u0000o\u0000m\u0000a\u0000n\u0000" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from ChandrilBasu/Ashi: direct link, hf CLI and curl.
- Browser
- Download file 601 Bytes
-
https://huggingface.co/ChandrilBasu/Ashi/resolve/main/README.md
- Command line
-
hf download hf://ChandrilBasu/Ashi/README.md
-
curl -L -o README.md https://huggingface.co/ChandrilBasu/Ashi/resolve/main/README.md
601 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: "UNICODE\0\0r\0e\0a\0l\0i\0s\0t\0i\0c\0 \0p\0h\0o\0t\0o\0 \0o\0f\0 \0a\0 \0w\0o\0m\0a\0n\0"
output:
url: images/11e5eea2-9fae-4fb3-95f8-8984aeba7570.jpeg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Palestinian woman
Ashi

- Prompt
- UNICODErealistic photo of a woman
Trigger words
You should use Palestinian woman to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.