---
base_model: LumiOpen/Viking-7B
language:
- en
- fi
- sv
- 'no'
- da
- is
- nn
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
datasets:
- mpasila/Magnum-V2-Mix
- anthracite-org/Stheno-Data-Filtered
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- anthracite-org/nopm_claude_writing_fixed
---
It seems fine but I should probably add some instruction prompts to the dataset or train it with a instruct dataset first and then train it with the RP stuff to make it better.

Prompt format is: ChatML

LoRA: [mpasila/Viking-Magnum-v0.1-LoRA-7B](https://huggingface.co/mpasila/Viking-Magnum-v0.1-LoRA-7B)

Another thing to note is this was trained with regular LoRA (not quantized/QLoRA) so it should improve the quality a bit. This model's context length is only 4096 so it's trained on that too but I think you can use RoPE with it.

LoRA rank was 128 and Alpha set to the same. Trained for 1 epoch.

# Uploaded  model

- **Developed by:** mpasila
- **License:** apache-2.0
- **Finetuned from model :** LumiOpen/Viking-7B

This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
