metadata

license: mit
language: multilingual
base_model: unsloth/Llama-3.2-1B-Instruct
quantized_by: prodoc.ai
tags:
  - classification
  - intent
  - healthcare
  - conversational
  - LLM
widget:
  - text: I want to book an appointment for my child.
  - text: Can you help me with lab test results?

ProdocAI/HealthIntent-Classifier-1b-GGUF-v1

HealthIntent-Classifier-1b-GGUF-v1 is a fine-tuned version of the Llama3.2-1B model, trained to classify healthcare-related queries into predefined intents. This model is designed to streamline user interactions by identifying their specific healthcare-related needs efficiently.

Ollama Integration

Leverage seamless integration with Ollama, where the model is fully hosted and ready to run. Simply execute the command ollama run Prodoc/intent-classification-1b to start utilizing the model's intent classification capabilities. Transform your healthcare conversational systems with precision and ease.

Model Details

Model Name: Intent-classification-1b-GGUF-v1
Base Model: Llama3.2-1B
Number of Parameters: 1 Billion
Dataset: Custom dataset of healthcare-related conversation
Training Data Statistics:
- Languages: Includes en, mr, te, hi, bn, among others (detailed in Language Map section)

Model Objective

The model identifies the intent behind healthcare-related queries and classifies them into one of the predefined categories. This allows for better routing and handling of user requests in healthcare systems.

Supported Intents

Appointment Booking
Surgery Enquiry
Emergency Assistance
Lab Test Results Inquiry
Symptom Consultation
Hospital Services Enquiry
Job or Internship Enquiry
Complaint or Feedback
Health Check-Up Packages
Health Insurance Enquiry
Irrelevant Query

Dataset Overview

The dataset includes 3,000 unique conversations mapped to the above intents. Conversations are provided in multiple languages to support diverse user bases.

Example Input Format

Input to the model should be provided in the following format:

"Below is the conversation between the bot and user

user: Hello
bot: Hello! I am Aisha, a Health-Care Executive at Madhavbaug. How can I assist you today with your health concern?

user: Is my appointment confirmed for tomorrow
bot: I can help you with that. Can you please provide me with your name and contact number so I can check the appointment status for you?

user: 👆
bot: I can help you check the status of your appointment. Please provide me with your name and contact number.

user: Krishnan Iyer
9323195487
bot: Current location, city name, or postal code is required to book an appointment, please provide your location details so I can assist you further

user: Booking is already done for tomorrow 10 am
bot: It seems that your message does not include information about your location. Could you please provide your current city name or postal code? This will help me assist you better in booking an appointment.

user: Thane
bot: Oh great! We have found 20 expert doctors in your area. Could you please let us know your exact location in Thane?

user: Majiwada Thane West
bot: Clinic list Sent

user: ✅ Your appointment has been successfully booked!

*Appointment Details:*

*Clinic Name:*
Kolshet Road (Thane W )

*Date & Time:*
19-Oct-2024 10:00

*Clinic Address:*
Shop no.102, First floor, Krishna towers, above Sanman hotel kolshet road, kapurbawdi,Thane West, Thane, MAHARASHTRA - 400607

Thank you for booking appointment with us!

We shall call you shortly to confirm your appointment.
bot: Your appointment has been successfully booked at Kolshet Road (Thane W) clinic on 19-Oct-2024 at 10:00. The clinic address is Shop no.102, First floor, Krishna towers, above Sanman hotel kolshet road, kapurbawdi, Thane West, Thane, MAHARASHTRA - 400607. Thank you for booking the appointment!

user: Hope it is confirmed
bot: Yes, your appointment at Kolshet Road (Thane W) clinic on 19-Oct-2024 at 10:00 is confirmed. Thank you for booking the appointment!

user: Thanks"