CARE: A QLoRA-Fine Tuned Multi-Domain Chatbot With Fast Learning On Minimal Hardware

Fuente: arXiv
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Hauptverfasser: Dutta, Ankit, Ghosh, Nabarup, Chatterjee, Ankush
Format: Preprint
Veröffentlicht: 2025
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author Dutta, Ankit
Ghosh, Nabarup
Chatterjee, Ankush
author_facet Dutta, Ankit
Ghosh, Nabarup
Chatterjee, Ankush
contents Large Language models have demonstrated excellent domain-specific question-answering capabilities when finetuned with a particular dataset of that specific domain. However, fine-tuning the models requires a significant amount of training time and a considerable amount of hardware. In this work, we propose CARE (Customer Assistance and Response Engine), a lightweight model made by fine-tuning Phi3.5-mini on very minimal hardware and data, designed to handle queries primarily across three domains: telecommunications support, medical support, and banking support. For telecommunications and banking, the chatbot addresses issues and problems faced by customers regularly in the above-mentioned domains. In the medical domain, CARE provides preliminary support by offering basic diagnoses and medical suggestions that a user might take before consulting a healthcare professional. Since CARE is built on Phi3.5-mini, it can be used even on mobile devices, increasing its usability. Our research also shows that CARE performs relatively well on various medical benchmarks, indicating that it can be used to make basic medical suggestions.
format Preprint
id arxiv_https___arxiv_org_abs_2503_14136
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle CARE: A QLoRA-Fine Tuned Multi-Domain Chatbot With Fast Learning On Minimal Hardware
Dutta, Ankit
Ghosh, Nabarup
Chatterjee, Ankush
Computation and Language
Artificial Intelligence
Large Language models have demonstrated excellent domain-specific question-answering capabilities when finetuned with a particular dataset of that specific domain. However, fine-tuning the models requires a significant amount of training time and a considerable amount of hardware. In this work, we propose CARE (Customer Assistance and Response Engine), a lightweight model made by fine-tuning Phi3.5-mini on very minimal hardware and data, designed to handle queries primarily across three domains: telecommunications support, medical support, and banking support. For telecommunications and banking, the chatbot addresses issues and problems faced by customers regularly in the above-mentioned domains. In the medical domain, CARE provides preliminary support by offering basic diagnoses and medical suggestions that a user might take before consulting a healthcare professional. Since CARE is built on Phi3.5-mini, it can be used even on mobile devices, increasing its usability. Our research also shows that CARE performs relatively well on various medical benchmarks, indicating that it can be used to make basic medical suggestions.
title CARE: A QLoRA-Fine Tuned Multi-Domain Chatbot With Fast Learning On Minimal Hardware
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2503.14136