updates to README.md

README.md

@@ -11,14 +11,24 @@ pinned: false
 
 # Finetuning Language Models - Toxic Tweets
 
-## Milestone 1:
+[![Sync to Hugging Face hub](https://github.com/jjmakes/cs482-project/actions/workflows/sync_to_hf.yml/badge.svg)](https://github.com/jjmakes/cs482-project/actions/workflows/sync_to_hf.yml)
+
+## [See the deployed App on HuggingFace](https://huggingface.co/spaces/jjmakes/cs482-toxic-tweets)
+
+CS 482 Project - [Instructions](https://pantelis.github.io/data-mining/aiml-common/projects/nlp/finetuning-language-models-tweets/index.html)
+
+## Milestone 1 - Development Environment
 
 ## OS Version
 
+This project was created in Ubuntu 20.04. Thus, steps for installing and developing in Windows are not included.
+
+```
 Distributor ID: Ubuntu
 Description: Ubuntu 20.04.6 LTS
 Release: 20.04
 Codename: focal
+```
 
 ## Docker Installation
 
@@ -47,20 +57,13 @@ sudo apt install docker-ce
 sudo systemctl status docker
 
 ## Add sudo docker permissions to current user
-sudo usermod -aG docker ${USER}
-
-## Apply the user membership
-su - ${USER}
-
-## Check if the user has the docker group added
-groups
-```
+sudo usermod -aG docker ${USER}[![Sync to Hugging Face hub](https://github.com/jjmakes/cs482-project/actions/workflows/sync_to_hf.yml/badge.svg)](https://github.com/jjmakes/cs482-project/actions/workflows/sync_to_hf.yml)
 
 ## VS Code Installation
 
 The instructions below will help install VS Code on Ubuntu version 20.04.6
 
-(Download the VS Code .deb package (64 bit))[https://code.visualstudio.com/download]
+[Download the VS Code .deb package (64 bit)](https://code.visualstudio.com/download)
 
 ```
 ## Navigate to downloads folder
@@ -83,3 +86,24 @@ Some notable images worth using are:
 - Python3: Container for developing Python 3 Applications
 
 ![](./milestone-1.png)
+
+
+## Milestone 2
+
+App is deployed to [HuggingFace](https://huggingface.co/spaces/jjmakes/cs482-toxic-tweets) via GitHub actions following [instructions provided in this tutorial](https://www.youtube.com/watch?v=8hOzsFETm4I). HuggingFace provides documentation for performing [sentiment analysis with python](https://huggingface.co/blog/sentiment-analysis-python).
+
+### Testing with Streamlit Locally
+
+To test with streamlit, install the project dependencies locally with:
+```
+pip3 install -r requirements.txt
+```
+
+To run the project, use:
+```
+streamlit run app.py --server.port 8888
+```
+
+The page can be set to hot-reload by selecting `Always Rerun` after a change is made.
+
+Models used are pretrained and provided by [HuggingFace](https://huggingface.co/models?pipeline_tag=text-classification&sort=likes&search=sentiment).