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Using real-world user data from a previous farmer assistant chatbot service and additional curated datasets (prioritizing sustainable regenerative organic farming practices,) Gemma 2B and Mistral 7B LLMs were iteratively fine-tuned and tested against eachother as well as basic benchmarking, whereby the Gemma 2B fine-tune emerged victorious. LORA adapters were saved for each model.

V3 here scored better in agriculture-focused prelim testing than V1 or V2 of the Mistral series of fine-tunes for the selected dataset.

This mistral model was trained with Unsloth and Huggingface's TRL library.

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