Develop NLP code using openAI GPT-3/ BERT, Transformers, and NLP models for summarizing Investor information memorandums -- 2

Use Case: Develop NLP code using openAI GPT-3/ BERT, Transformers, and NLP models for summarizing Investor information memorandums; Summarize Company information in 1-2 page based on Investor information memorandums (50-60 page documents) Key Requirements/ Deliverables: 1. Develop code that leverages NLP models such as BERT, GPT-3,RoBERTa T5 or XLNet to summarize information from the IM 2. Preprocess and prepare dataset for fine-tuning the model using OpenAI API or the Hugging Face's Transformers library 3. Developing API using frameworks such as Flask or FastAPI and deploy API using AWS Lambda or Google 4. Provide a fully functional application that takes input and provides output as described above: 5. Develop a basic UI that can be used to upload the Information Memorandum (IM) document Input: Investor Information Memorandum (IM), which is a 50-80 slide powerpoint/ word document describing a company in significant details) Output: 1-2 page word document that summarizes information in IM as available: Basic Summary - Industry, Revenue, EBITDA, employees, locations Products - Product sales broken down by key segments or products Growth - Growth % and growth drivers Number of employees - Employee breakdown by categories, if available Major Initiatives and expenditures, if available Other Information as available - IT systems Next Phase Use Cases (developed after above use case is complete and will be priced separately) Customize engagement letters based on company profile ChatGPT type question-answering in