Text Classification use case using BERT base architecture and fine tunning the model with the help of ktrain. Dataset used - 20newsgroups dataset.
git clone <repository_url>
Execute below commands in git bash. (Note - Must have conda installed and path defined of conda in system environments)
If using git bash then use below command
source activate base
Else for cmd use
conda activate base
To Create Conda Enviroment and activate it
conda create -n <envName> python=3.7 -y
conda env list
activate <envName>
Conda command to create virtual env inside current directly
conda create --prefix ./env python=3.7 -y && conda activate ./env
pip install -r requirements.txt
conda list
Step 4 : To save your version of code. Create new git repository & then execute below commands only once to push change first time.
git add .
git status
git commit -m "commit message"
git remote add origin 'your_repository_url'
git branch -m master main
git push -u origin main
git add .
git commit -m "commit message"
git push
pip freeze>requirements.txt