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RahulPi
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Email_Text_Formatter

Feature Extraction
Transformers
Safetensors
English
llama
text-generation
text-generation-inference
unsloth
phi-4
information-extraction
text-embeddings-inference
4-bit precision
bitsandbytes
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xet
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Phi-4 Finetuned for Business Asset Extraction

  • Developed by: RahulPi
  • License: apache-2.0
  • Finetuned from model: unsloth/phi-4-unsloth-bnb-4bit
  • Primary Task: Information Extraction / Structured Output Generation

Model Description

This model has been specifically fine-tuned to automate business workflows by processing unstructured email communications. It is designed to read through incoming business emails, identify key business assets mentioned within the text, and reliably convert that information into a clean, structured format for downstream use.

Dataset

The model was trained on a custom dataset built for a specific business case scenario:

  • Input: Unstructured, natural language text mimicking standard business emails containing asset details.
  • Output: A structured format mapping out the identified business assets for easy database entry and automation.

Training Details

This model was trained 2x faster with Unsloth and Hugging Face's TRL library.

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