amul_mascot_girl_flux1_dev_lora_v2_fp16

Description

This is Text-to-Image Model Finetuned on top of Flux-Dev Model on a Dataset of Amul mascot girl Images

Amul Mascot girl - Lora-fp16-v2

Model trained with AI Toolkit by Ostris <Gallery />

Trigger words

You should use amul girl to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Scripts for preprocessing , inferencing and finetuning the most popular amul mascot girl

• Used flux 1.1 dev model with lora (low rank adaption) for finetuning text to image generation

preprocessing

https://github.com/sanjay7178/amul-mascot-girl-flux-t2i/blob/main/amul_mascot_girl_preprocess.ipynb

dataset

https://huggingface.co/datasets/sanjay7178/amul-mascot-girl

configuration

Install conda-forge or mamba-forge create virtual environment

conda create -n amul python=3.10 
conda activate amul     # change current env to amul

Linux:

git clone https://github.com/ostris/ai-toolkit.git
cd ai-toolkit
git submodule update --init --recursive
python3 -m venv venv
source venv/bin/activate
# .\venv\Scripts\activate on windows
# install torch first
pip3 install torch
pip3 install -r requirements.txt

Windows:

git clone https://github.com/ostris/ai-toolkit.git
cd ai-toolkit
git submodule update --init --recursive
python -m venv venv
.\venv\Scripts\activate
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121
pip install -r requirements.txt

finetuning

Before fine tuning change dataset path and some required vram hyperparameters according to your system requirements from config.yml in files

python run.py /<relative path>/config.yml

inference (gradio demo)

https://github.com/sanjay7178/amul-mascot-girl-flux-t2i/tree/main/lora-gradio-demo

results

Loss Plot

<a href="url"><img src="https://github.com/user-attachments/assets/59177225-78cc-4963-9698-798aa5fdadfc" align="left" height="400" width="500" ></a>