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Model: mpasila/Viking-Magnum-v0.1-7B Source: Original Platform
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README.md
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---
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base_model: LumiOpen/Viking-7B
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language:
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- en
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- fi
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- sv
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- 'no'
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- da
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- is
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- nn
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- trl
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- sft
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datasets:
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- mpasila/Magnum-V2-Mix
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- anthracite-org/Stheno-Data-Filtered
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- anthracite-org/kalo-opus-instruct-22k-no-refusal
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- anthracite-org/nopm_claude_writing_fixed
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---
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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.
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Prompt format is: ChatML
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LoRA: [mpasila/Viking-Magnum-v0.1-LoRA-7B](https://huggingface.co/mpasila/Viking-Magnum-v0.1-LoRA-7B)
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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.
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LoRA rank was 128 and Alpha set to the same. Trained for 1 epoch.
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# Uploaded model
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- **Developed by:** mpasila
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- **License:** apache-2.0
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- **Finetuned from model :** LumiOpen/Viking-7B
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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