| | --- |
| | license: apache-2.0 |
| | language: |
| | - en |
| | - fr |
| | - es |
| | - pt |
| | - sw |
| | - ja |
| | - ar |
| | base_model: Qwen/Qwen2-0.5B-Instruct |
| | tags: |
| | - agriculture |
| | - multilingual |
| | - chatbot |
| | - crop-diseases |
| | - farming |
| | - west-africa |
| | pipeline_tag: text-generation |
| | --- |
| | |
| | # AgriChat Multilingual - Agricultural Assistant |
| |
|
| | A multilingual chatbot fine-tuned for agricultural assistance, specifically designed for farmers in West Africa and beyond. |
| |
|
| | ## Model Description |
| |
|
| | - **Base Model:** Qwen/Qwen2-0.5B-Instruct |
| | - **Fine-tuning Method:** LoRA (Low-Rank Adaptation) |
| | - **Languages:** English, French, Spanish, Portuguese, Swahili, Japanese, Arabic |
| | - **Domain:** Agricultural crop diseases, farming practices, pest management |
| | - **License:** Apache 2.0 |
| |
|
| | ## Supported Languages |
| |
|
| | | Language | Code | Coverage | |
| | |----------|------|----------| |
| | | English | en | Full | |
| | | French | fr | Full | |
| | | Spanish | es | Full | |
| | | Portuguese | pt | Full | |
| | | Swahili | sw | Full | |
| | | Japanese | ja | Full | |
| | | Arabic | ar | Full | |
| |
|
| | ## Use Cases |
| |
|
| | - **Crop Disease Identification:** Ask about symptoms and treatments for plant diseases |
| | - **Farming Advice:** Get guidance on agricultural practices |
| | - **Pest Management:** Learn about controlling pests affecting crops |
| | - **Multilingual Support:** Communicate in 7 different languages |
| |
|
| | ## Quick Start |
| |
|
| | ```python |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| | |
| | # Load model |
| | model = AutoModelForCausalLM.from_pretrained("mesabo/agri-chat-multilingual") |
| | tokenizer = AutoTokenizer.from_pretrained("mesabo/agri-chat-multilingual") |
| | |
| | # Chat example |
| | messages = [ |
| | {"role": "user", "content": "How do I identify cassava mosaic disease?"} |
| | ] |
| | |
| | text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
| | inputs = tokenizer(text, return_tensors="pt") |
| | |
| | outputs = model.generate(**inputs, max_new_tokens=256, temperature=0.7) |
| | response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| | print(response) |
| | ``` |
| |
|
| | ## Training Details |
| |
|
| | - **Training Data:** 38 curated Q&A examples across 7 languages |
| | - **Epochs:** 3 |
| | - **LoRA Parameters:** 2.16M trainable (0.44% of total) |
| | - **Training Loss:** 2.54 |
| | - **Hardware:** NVIDIA RTX 3090 (25.3 GB) |
| | - **Training Time:** ~17 seconds |
| |
|
| | ## Covered Topics |
| |
|
| | ### Crop Diseases |
| | - Cassava mosaic disease |
| | - Maize leaf blight |
| | - Tomato bacterial wilt |
| | - Cashew anthracnose |
| | - Rice blast disease |
| |
|
| | ### Farming Practices |
| | - Organic pest control |
| | - Soil health management |
| | - Crop rotation benefits |
| | - Water conservation |
| |
|
| | ## Limitations |
| |
|
| | - Fine-tuned on limited agricultural domain data |
| | - Best suited for common crop diseases in West Africa |
| | - May not cover specialized or rare conditions |
| | - Responses should be verified with local agricultural experts |
| |
|
| | ## Intended Use |
| |
|
| | This model is designed for: |
| | - Agricultural extension workers |
| | - Small-scale farmers |
| | - Agricultural education platforms |
| | - Farming assistance applications |
| |
|
| | ## Citation |
| |
|
| | ```bibtex |
| | @misc{agri-chat-multilingual, |
| | author = {mesabo}, |
| | title = {AgriChat Multilingual - Agricultural Assistant}, |
| | year = {2024}, |
| | publisher = {Hugging Face}, |
| | url = {https://huggingface.co/mesabo/agri-chat-multilingual} |
| | } |
| | ``` |
| |
|
| | ## Related Models |
| |
|
| | - [mesabo/agri-plant-disease-resnet50](https://huggingface.co/mesabo/agri-plant-disease-resnet50) - Plant disease image classification (95%+ accuracy) |
| |
|
| | ## Contact |
| |
|
| | For questions or issues, please open a discussion on the model page. |
| |
|
