Dataset · Hugging Face

bitext/Bitext-retail-ecommerce-llm-chatbot-training-dataset

Name: Bitext-retail-ecommerce-llm-chatbot-training-dataset
Creator: bitext
License: cdla-sharing-1.0
Keywords: task_categories:question-answering, task_categories:table-question-answering, language:en, license:cdla-sharing-1.0, size_categories:10K<n<100K, format:csv, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, region:us, question-answering, llm, chatbot

Bitext - Retail (eCommerce) Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Retail (eCommerce)] sector can be easily achieved using our two-step approach to… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-retail-ecommerce-llm-chatbot-training-d

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Author / organization	bitext
License (as declared)	cdla-sharing-1.0
Downloads	2.5K (as reported by Hugging Face)
Likes	20
Created	5 August 2024
Last updated at source	5 August 2024

question-answeringllmchatbotretailecommerceconversational-aigenerative-ainatural-language-understandingfine-tuning

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16 Oct 2026 Description: Bitext - Retail (eCommerce) Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated u → Bitext - Retail (eCommerce) Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated u

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Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.