Bitext - Customer Service 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 Customer Support sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-customer-support-llm-chatbot-training-dataset.

LLM Dataset - Prompts and Generated Texts

The dataset contains prompts and texts generated by the Large Language Models (LLMs) in 32 different languages. The prompts are short sentences or phrases for the model to generate text. The texts generated by the LLM are responses to these prompts and can vary in length and complexity. Researchers and developers can use this dataset to train and fine-tune their own language models for multilingual applications. The dataset provides a rich… See the full description on the dataset page: https://huggingface.co/datasets/TrainingDataPro/llm-dataset.

llama-instruct

This dataset was used to finetune Llama-2-7B-32K-Instruct. We follow the distillation paradigm that is used by Alpaca, Vicuna, WizardLM, Orca — producing instructions by querying a powerful LLM, which in our case, is the Llama-2-70B-Chat model released by Meta. To build Llama-2-7B-32K-Instruct, we collect instructions from 19K human inputs extracted from ShareGPT-90K (only using human inputs, not ChatGPT outputs). The actual script handles multi-turn conversations… See the full description on the dataset page: https://huggingface.co/datasets/togethercomputer/llama-instruct.