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--- |
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library_name: transformers |
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license: mit |
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language: |
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- en |
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--- |
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### Model Description |
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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. |
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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- **Developed by:** Anupam Wagle |
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- **Model type:** Text Generation |
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- **Language(s) (NLP):** PyTorch |
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- **License:** MIT |
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- **Finetuned from model:** Microsoft Phi-2 |
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## Uses |
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Use to generate the message based on the previous ones. |
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## Bias, Risks, and Limitations |
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For better results, increase the size of the dataset and the training epochs. |
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## Training Details |
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### Training Data |
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The format of the dataset used for finetuning is as follows: |
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[{ |
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"input_email": "Hello Adam,\n\nCan you come to the party tonight after 6 PM?\nBest,\nSubash", |
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"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" |
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}, |
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...] |
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## Technical Specifications |
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This model was finetuned on Google colab's Tesla t4 GPU for a total of 2 epochs. |
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### Model Architecture and Objective |
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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. |
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