renauddahou / resume_parser_using_deep_learning

Resume parser with ner using state of art in deep learning with transformers specifically bert.

Resume_parser_using_deep_learning

Resume parser with ner using state of art in deep learning with transformers specifically roberta.

The link for trained model is link to model .I did not added it on github because size was exceeding github size parameter.

There are seven types of entity possible for a given set of words:

1. Job title : This entity represents the the type of job which users wants
2. skill : This represents the importants skills which users possess
3. experience : This represents the job of the user in previous company and it timeline
4. org : This represents the set of companies ehich user has worked previously or working now.
5. tool : This represents the software tools used by user
6. Degree : This represents which degree user has taken for example B.Tech,M.tech,MBA etc
7. Educ : This represents the college in which user studied.

Deployment

• Create virtual envinronment with python version==3.7.13
• Then download the generated_model folder(Link is given above) in Deployment folder
• Then in command line use pip3 install pip install -r requirements.txt
• Then run python3 main.py
• And on this url link you can upload your resume and then the model will give parsed output after sometime so that you will be able to see important keyword in the resume.

Demo Gif of the Application