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shubhbali/customer-support-llm

sourceHugging Faceotherupdated 3mo agoView on Hugging Face

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Model Card

Customer Support LLM

LoRA fine-tune of Qwen/Qwen2-0.5B-Instruct trained with Hugging Face AutoTrain on rjac/e-commerce-customer-support-qa.

This prototype explores whether a small open-source language model can be adapted for e-commerce customer-support workflows relevant to SMEs.

Training Details

—Base model: Qwen/Qwen2-0.5B-Instruct
—Dataset: rjac/e-commerce-customer-support-qa
—Training column: conversation
—Method: LoRA / PEFT
—Platform: Hugging Face AutoTrain
—Examples: 1,000
—Epochs: 1
—Max sequence length: 1024
—Runtime: about 4 minutes on Nvidia T4

Intended Use

—customer-support response drafting
—e-commerce support workflow automation
—SME AI adoption prototype
—lightweight domain adaptation experiment

Example Use Case

A small e-commerce business could use a lightweight adapted model to draft first-pass support replies, help triage customer issues, and support customer-service workflows without relying only on closed frontier models.

Example Prompt

text

Customer: I ordered a phone case last week and the tracking page still says pending. Can you help?

Agent: