phi2_qlora_emailGen_bitsandbytes

Model Description

This model is used to generate the template based on the body of any emails or messages. It uses Microsoft's Phi-2 as the base model and was finetuned for 2 epochs on Google Colab's Tesla T4 GPU.

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

• Developed by: Anupam Wagle
• Model type: Text Generation
• Language(s) (NLP): PyTorch
• License: MIT
• Finetuned from model: Microsoft Phi-2

Uses

Use to generate the message based on the previous ones.

Bias, Risks, and Limitations

For better results, increase the size of the dataset and the training epochs.

Training Details

Training Data

The format of the dataset used for finetuning is as follows: [{ "input_email": "Hello Adam,\n\nCan you come to the party tonight after 6 PM?\nBest,\nSubash", "generated_email": "Hi Eve,\n\nThank you for the invitation. I'd love to come to the party tonight after 6 PM. Looking forward to it!\n\nBest,\nAdam" }, ...]

Technical Specifications

This model was finetuned on Google colab's Tesla t4 GPU for a total of 2 epochs.

Model Architecture and Objective

The base model for this was the Microsoft's Phi-2 which was quantized using Bits and Bytes. It's primray objective is to generate messages based on previous messages.