LoRA trained with text-generation-webui in 4-bit using LumiOpen/Viking-7B as the base model for 1 epoch. Dataset used with the LoRA is mpasila/Alpacazord-V1.

It uses Alpaca format like so:

{
    "instruction,output": "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n%instruction%\n\n### Response:\n%output%",
    "instruction,input,output": "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n%instruction%\n\n### Input:\n%input%\n\n### Response:\n%output%"
}

Merged using this Colab notebook. It might not be the best way to merge a quantized LoRA on to a float16 model but I just wanted to quickly do something. You can try merging it better if you want.

Evaluation

Model	Size	Type	FIN-bench (score)
mpasila/Alpacazord-Viking-7B	7B	Instruct
mpasila/Finnish-Viking-Alpaca-V1-7B	7B	Instruct	0.3943
mpasila/NordicAlpaca-Finnish-V1-7B	7B	Instruct	0.3891
Finnish-NLP/llama-7b-finnish-instruct-v0.1	7B	Instruct	0.4365
Finnish-NLP/llama-7b-finnish-instruct-v0.2	7B	Instruct	0.3993
Finnish-NLP/llama-7b-finnish	7B	Base	0.2350
LumiOpen/Viking-7B (1000B)	7B	Base	0.3721
HPLT/gpt-7b-nordic-prerelease	7B	Base	0.3169

Source

FIN-bench scores:

Will add later. And possibly other evals?????

Framework versions

PEFT 0.8.2

mpasila/Alpacazord-Viking-7B-exl2-4bpw

Original Model card:

Model Card for Alpacazord-Viking-7B

Evaluation

FIN-bench scores:

Framework versions

mpasila/
Alpacazord-Viking-7B-exl2-4bpw