Build a basic text classification model using any framework(PyTorch, Keras, etc..) and deploy via a REST API
- Fork or clone this repo
- Maintain the directory structure given for the project
- Use Python 3.7+
- If you need additional imports specify them in
requirements.txt
- Model should be trained on the given dataset.
- Create a model artifact and save it under
/models
. - Report accuracy on
sampled_test
.
- Serve the model as a REST API using FastAPI
- Be able to use CURL to send in text input and return the prediction.
The dataset you will be using contains hate speech from an online forum. You need to train basic text classification model which will classify given text into hate
noHate
categories. You can find the dataset and details data format and labels can be found here
Dataset contains two splits sampled_train
and sampled_test
.
Note: The text in this dataset might contain offensive language.
Timebox this challenge to 4-8 hours. After completing the assignment, please compress whole repo and send it.