What's included

• Code for AI model and Workflow

  If the work requires a machine learning model, whether custom-trained or downloaded from HuggingFace, I'll include all the code for training and/or retrieving the model.

• Performance Benchmarking Results

  This is the numerical indicators of how well the ML pipeline performs, either on your data, a dataset that resembles your data, or an academic benchmark. If the latter, this will also include how other competing open and closed-source tools may perform on the same benchmark.

• Deployment Instructions

  This will include the instructions for deploying the AI model or workflow to a web app or mobile app or a cloud service (AWS, GCP, Azure, Lambda, etc.)

• The repository containing the other deliverables

  All the results described above will be delivered in your choice of a GitHub Repo, a GitLab repo, a BitBucket Repo, or a password-protected compressed archive.