Instructions to use Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3 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 Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3 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 Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3", max_seq_length=2048, )
Uploaded model
- Developed by: Caleb DeLeeuw; Copyleft Cultivars, a nonprofit
- License: Hippocratic 3.0 CL-Eco-Extr
https://firstdonoharm.dev/version/3/0/cl-eco-extr.html
- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-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.
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.
Model tree for Solshine/LORA-Adapters-Mistral7B-NaturalFarmerV3
Base model
unsloth/mistral-7b-instruct-v0.2-bnb-4bit