Insight
Project Insight is designed to create NLP as a service with code base for both front end GUI (streamlit) and backend server (FastAPI) the usage of ...
fastapi huggingface transformers pytorch streamlit transfer-learning docker named-entity-recognition sentiment-analysis text-summarization natural-language-processing bert attention api code

Project Insight is designed to create NLP as a service with code base for both front end GUI (streamlit) and backend server (FastApi) the usage of transformers models on various downstream NLP task. The downstream NLP tasks covered:

  1. News Classification
  2. Entity Recognition
  3. Sentiment Analysis
  4. Summarization
  5. Information Extraction (To Do)

The user can select different models from the drop down to run the inference. The users can also directly use the backend fastapi server to have a command line inference.

Features of the solution

Python Code Base: Built using Fastapi and Streamlit making the complete code base in Python.

Expandable: The backend is desinged in a way that it can be expanded with more Transformer based models and it will be available in the front end app automatically.

Don't forget to tag @abhimishra91 in your comment, otherwise they may not be notified.

Authors original post
Eat, Sleep, Pray, and Code * An Operations Innovation Lead at IHS Markit during working hours. * Love to read manga and cook new cuisines.
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