Mistral NeMo, Ollama & CSV support

Unsloth has made significant updates to its offerings, particularly with the release of Mistral NeMo, a 12 billion parameter multilingual model that fits within a free Google Colab GPU instance for fine-tuning. The company has addressed several issues in NeMo, including the erroneous addition of an EOS token and dimension mismatches in the model's architecture, ensuring improved performance and VRAM efficiency. Additionally, Unsloth now supports CSV/Excel files with multicolumn datasets for fine-tuning, offers model deployment to Ollama, and has introduced a new documentation page. The platform has also enhanced long-context support across models such as Gemma 2 and Qwen2, and facilitates faster downloads from Hugging Face, alongside supporting Torch 2.5, Triton 3, and preparing for Flex Attention. These advancements underscore Unsloth's commitment to making fine-tuning more accessible and efficient.

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