File size: 1,365 Bytes
d778850 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 |
---
base_model: "Qwen/Qwen2-VL-7B-Instruct"
library_name: peft
model_name: "AgriAssist"
tags:
- vision-language
- agriculture
- crop-detection
- pest-detection
- weed-detection
- fine-tuning
- sft
- lora
- transformers
license: apache-2.0
pipeline_tag: text-generation
---
# AgriAssist: Domain-Specific Vision-Language Model for Indian Agriculture
AgriAssist is a fine-tuned vision-language model (VLM) built on **Qwen2-VL-7B-Instruct**, designed specifically for Indian agricultural applications. It is trained on curated datasets covering major **crops, weeds, pests, and diseases**, enabling robust recognition and basic reasoning over agricultural images.
## Features
- Domain-specific fine-tuning for Indian agriculture
- Recognition of crops, weeds, and pests
- Instruction-tuned for multimodal reasoning
- Trained on multiple public datasets: MH-Weed16, PlantVillage, AgroBench
- Ready for integration in applications requiring agricultural image understanding
## Usage
```python
from transformers import AutoProcessor, AutoModelForCausalLM
processor = AutoProcessor.from_pretrained("your-username/AgriAssist")
model = AutoModelForCausalLM.from_pretrained("your-username/AgriAssist")
# Example usage
inputs = processor(images=image_list, text="Identify the pest in the image", return_tensors="pt")
outputs = model.generate(**inputs)
|