Instructions to use Solshine/Gemma2B-NaturalFarmerV3_HF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Solshine/Gemma2B-NaturalFarmerV3_HF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Solshine/Gemma2B-NaturalFarmerV3_HF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded model
- Developed by: Solshine
- License: apache-2.0
- Finetuned from model : unsloth/gemma-2b-it-bnb-4bit
Background: 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. Following this, the Gemma version was released.
Updates for this model: We then revisited the data, adding four additional months of real-world in-field data from hundreds of users which was then editted by a domain expert in regenerative farming and natural farming (approximately 2,000 instruct examples.) This was combined with a small portion of synthetic datasets and semisynthetic datasets related to regenerative agriculture and natural farming, including some non-english language samples
This gemma model was trained with Unsloth and Huggingface's TRL library.
Model tree for Solshine/Gemma2B-NaturalFarmerV3_HF
Base model
unsloth/gemma-2b-it-bnb-4bit