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ProdocAI
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EndConvo-health-1b-GGUF-v1

PyTorch
Safetensors
GGUF
multilingual
llama
conversational
healthcare
conversation-ending
LLM
Inference Endpoints
Model card Files Community
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EndConvo-health-1b-GGUF-v1 / README.md
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metadata
license: mit
language: multilingual
tags:
  - conversational
  - healthcare
  - conversation-ending
  - LLM

ProdocAI/EndConvo-health-1b-GGUF-v1

EndConvo-health-1b-GGUF-v1 is a fine-tuned version of the Llama3.2-1B model, trained on a dataset of healthcare-related conversations with the purpose of identifying whether a conversation has ended. This model helps to avoid unnecessary responses from larger language models by detecting closing statements.

Model Details

  • Model Name: EndConvo-health-1b-GGUF-v1
  • Base Model: Llama3.2-1B
  • Number of Parameters: 1 Billion
  • Dataset: Custom dataset of 4,000 rows focused on healthcare conversations
  • Training Data Statistics:
    • Total Conversations: 11,798
    • Chat Count: 94,472
    • Average Chats per Conversation: ~8
    • Languages: Includes en, mr, te, hi, bn, among others (detailed in Language Map section)

Model Objective

The model identifies if a healthcare-related conversation has reached a natural conclusion to prevent unnecessary responses from a larger LLM. The model is trained to output:

  • True: Conversation has ended.
  • False: Conversation is still active.

Dataset Overview

This healthcare-focused conversational dataset includes 11,798 unique conversations, with an average of 8 messages per conversation. The dataset consists of conversations in a variety of languages with the following breakdown:

  • English (en): 78,404 messages
  • Marathi (mr): 2,092 messages
  • Hindi (hi): 2,857 messages
  • ... and others as per the Language Map section.

Example Input Format

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

"Below is the conversation between the bot and user:

user: Please send me one bottle
bot: Hi, I am Vaidushi and how can I help you today regarding your interest to buy Madhavprash?
bot: Here is the link to purchase your Madhavprash https://madhavprash.store

user: 👆COD not possible here
bot: Currently, we do not support Cash on Delivery (COD) for purchases. You can complete your purchase using other available payment methods on our website.

bot: Thanks for your order, it will be delivered to you within 2-3 working days. Dosage Guidelines...
user: Thanks 🙏🤝 madam..... Kailas Varsekar ..."