OpenHermes 7B is the first fine tune of the Hermes dataset that has a fully open source dataset!
What is unique about this 7B model is that it used sample packing, which speeds up training by many multiples if the dataset token averages arent near the max sequence length.
OpenHermes was trained on 242,000 entries of primarily GPT-4 generated data, from open datasets across the AI landscape, including:
GPTeacher - General Instruct, Roleplay v1, Roleplay v2, and Code Instruct Datasets, by Teknium
WizardLM (v1, evol_instruct 70k), by WizardLM Team/nlpxucan
Airoboros GPT-4 (v1.0), by JonDurbin
Camel-AI's domain expert datasets, by the Camel-AI Team
CodeAlpaca, by Sahil2801
GPT4-LLM and Unnatural Instructions, by Microsoft
Filtering included removal of OpenAI refusals, disclaimers, and "As an AI" type examples and more
The base dataset mix the model was trained on is identical to Nous-Hermes', minus the Nous-Instruct and PDACTL datasets which were private datasets.
Huge thank you to main_horse for compute access and a16z for sponsoring my work, and all the dataset creators and other people who's work has contributed to this project!
