license: apache-2.0
language:
- en
pipeline_tag: text-generation
tags:
- mistral
- instruct
- finetune
- chatml
- gpt4
- synthetic data
- distillation
- conversational
- text-generation-inference
base_model: teknium/OpenHermes-2.5-Mistral-7B
inference: false
OpenHermes-2.5-Mistral-7B-GGUF
- GGUF quantized versions for OpenHermes-2.5-Mistral-7B
- Created using llama.cpp
Model description
OpenHermes 2.5 Mistral 7B is a state of the art Mistral Fine-tune, a continuation of OpenHermes 2 model, which trained on additional code datasets.
Potentially the most interesting finding from training on a good ratio (est. of around 7-14% of the total dataset) of code instruction was that it has boosted several non-code benchmarks, including TruthfulQA, AGIEval, and GPT4All suite. It did however reduce BigBench benchmark score, but the net gain overall is significant.
The code it trained on also improved it's humaneval score (benchmarking done by Glaive team) from 43% @ Pass 1 with Open Herms 2 to 50.7% @ Pass 1 with Open Hermes 2.5.
OpenHermes was trained on 1,000,000 entries of primarily GPT-4 generated data, as well as other high quality data from open datasets across the AI landscape. [More details soon]
Filtering was extensive of these public datasets, as well as conversion of all formats to ShareGPT, which was then further transformed by axolotl to use ChatML.