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README
License: apache-2.0Model Details
- Developed by: brimbim (using Adaption Labs AutoScientist)
- Model type: LoRA adapter (PEFT)
- Base model: mistralai/Mixtral-8x7B-Instruct-v0.1
- Language(s): English
- License: Apache 2.0
- Finetuned from: mistralai/Mixtral-8x7B-Instruct-v0.1
Capabilities
- Precise diagnosis from text descriptions of symptoms
- Practical treatment recommendations (strong emphasis on organic & low-cost options)
- Region-aware and climate-resilient advice
- Confidence scores, risk flags, and safety warnings
- Simple, farmer-friendly language
Training Details
- Dataset: ~20,000 high-quality instruction-completion pairs (PlantVillage + synthetic diverse examples)
- Method: LoRA (rank 64, alpha 128)
- Win Rate: 92% (adapted vs base model)
- Quality Score: 9.8/10 (Grade A)
Quick Start
python
from transformers import AutoModelForCausalLM, AutoTokenizerimport torchmodel_name = "brimbim/agriculture-crop-disease-model-v2"tokenizer = AutoTokenizer.from_pretrained(model_name)model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype=torch.bfloat16)prompt = """You are an expert agronomist helping smallholder farmers.A farmer in East Africa reports yellow spots with white centers on tomato leaves after heavy rain."""inputs = tokenizer(prompt, return_tensors="pt").to(model.device)outputs = model.generate(**inputs, max_new_tokens=400, temperature=0.7, top_p=0.9)print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Uses
Intended Use:
Helping smallholder farmers and agronomists with crop disease diagnosis and management.
Out-of-Scope:
Medical advice for humans/animals, large-scale commercial farming systems, or any high-stakes legal/financial decisions.
Bias, Risks, and Limitations
- Model performance is strongest on common crops (tomato, maize, potato, etc.)
- May have reduced accuracy on rare diseases or crops not well-represented in training data
- Always verify critical recommendations with local agricultural extension services
Citation
If you use this model, please cite:bibtex
@misc{agriculture-crop-disease-advisor-v2, author = {brimbim}, title = {Agriculture Crop Disease Advisor v2}, year = {2026}, publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/brimbim/agriculture-crop-disease-model-v2}} }
Model provider
brimbim
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Base
mistralai/Mixtral-8x7B-Instruct-v0.1
Adapter
this model
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