Instructions to use CopyleftCultivars/Gemma2B-NaturalFarmerV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CopyleftCultivars/Gemma2B-NaturalFarmerV1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CopyleftCultivars/Gemma2B-NaturalFarmerV1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use CopyleftCultivars/Gemma2B-NaturalFarmerV1 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CopyleftCultivars/Gemma2B-NaturalFarmerV1 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CopyleftCultivars/Gemma2B-NaturalFarmerV1 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CopyleftCultivars/Gemma2B-NaturalFarmerV1 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="CopyleftCultivars/Gemma2B-NaturalFarmerV1", max_seq_length=2048, )
Gemma 2B Natural Farmer V1 by Copyleft Cultivars
- Developed by: Caleb DeLeeuw, Copyleft Cultivars (a nonprofit, protecting and preserving vulnerable plants)
- License: MIT
- Finetuned from model : unsloth/gemma-2b-it-bnb-4bit
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. The Natural Farming Gemma 2B was then loaded onto Hugging Face Hub in hopes it will help farmers everywhere and inspire future works.
Shout out to roger j (bhugxer) for help with the dataset and training framework.
Testing and further compiling to integrate into on-device app interfaces are ongoing. This project was created by Copyleft Cultivars, a nonprofit, in partnership with Open Nutrient Project and Evergreen State College. This project serves to democratize access to farming knowledge and support the protection of vulnerable plants.
This is V1 beta. It runs locally on Ollama with some expirimental configuring so you can use it off the grid and places where internet is not accessible (ie most farms I've been on.)
This Gemma model was trained with Unsloth and Huggingface's TRL library.
Model tree for CopyleftCultivars/Gemma2B-NaturalFarmerV1
Base model
unsloth/gemma-2b-it-bnb-4bit
