base_model: teknium/OpenHermes-2.5-Mistral-7B
tags:
- mistral
- instruct
- finetune
- chatml
- gpt4
- synthetic data
- distillation
- dpo
- rlhf
license: apache-2.0
language:
- en
datasets:
- mlabonne/chatml_dpo_pairs
quantized_by: bartowski
pipeline_tag: text-generation
Exllama v2 Quantizations of NeuralHermes-2.5-Mistral-7B
Using turboderp's ExLlamaV2 v0.0.10 for quantization.
Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
Conversion was done using VMWareOpenInstruct.parquet as calibration dataset.
Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.
Original model: https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B
Download instructions
With git:
git clone --single-branch --branch 4_0 https://huggingface.co/bartowski/NeuralHermes-2.5-Mistral-7B-exl2
With huggingface hub (credit to TheBloke for instructions):
pip3 install huggingface-hub
To download the main (only useful if you only care about measurement.json) branch to a folder called NeuralHermes-2.5-Mistral-7B-exl2:
mkdir NeuralHermes-2.5-Mistral-7B-exl2
huggingface-cli download bartowski/NeuralHermes-2.5-Mistral-7B-exl2 --local-dir NeuralHermes-2.5-Mistral-7B-exl2 --local-dir-use-symlinks False
To download from a different branch, add the --revision parameter:
mkdir NeuralHermes-2.5-Mistral-7B-exl2
huggingface-cli download bartowski/NeuralHermes-2.5-Mistral-7B-exl2 --revision 4_0 --local-dir NeuralHermes-2.5-Mistral-7B-exl2 --local-dir-use-symlinks False