--- base_model: unsloth/Llama-3.2-1B language: - en - fi license: llama3.2 tags: - text-generation-inference - transformers - unsloth - llama - trl datasets: - wikimedia/wikipedia --- Here's a "continued pre-trained" model using [Finnish Wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset. I still don't understand why no one in Finland has figured out that they could just do continued pre-training on existing models that are already supported by every frontend.. I've seen Japanese models perform pretty well with that kind of continued pre-training, yet Finnish models are still done from scratch which means they suck ass. If you compare them to Llama 3 or Gemma 2 they just suck so much. They can't even match Mistral 7B a model from last year. Just stop wasting money on training models from scratch, use these better models as base and train it on all your closed-source data I don't have access to. Thank you. Merged model: [mpasila/Llama-3.2-Finnish-Wikipedia-1B](https://huggingface.co/mpasila/Llama-3.2-Finnish-Wikipedia-1B) Trained with regular LoRA (not quantized/QLoRA) and LoRA rank was 128 and Alpha set to 32. Trained for 1 epoch using RTX 4090 for about 12,5 hours. # Uploaded Llama-3.2-Finnish-Wikipedia-LoRA-1B model - **Developed by:** mpasila - **License:** Llama 3.2 Community License Agreement - **Finetuned from model :** unsloth/Llama-3.2-1B This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [](https://github.com/unslothai/unsloth)