base_model, language, license, tags, datasets

base_model	language	license	tags	datasets
LumiOpen/Viking-7B	en fi sv no da is nn	apache-2.0	text-generation-inference transformers unsloth llama trl sft	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

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 and Huggingface's TRL library.