67 lines
2.7 KiB
Markdown
67 lines
2.7 KiB
Markdown
---
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library_name: transformers
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tags:
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- llama-factory
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base_model:
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- Qwen/Qwen3-4B
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---
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# Model Card for ThinkingDhenu1-CRSA-India-preview
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This is an experimental research preview of a reasoning-augmented climate-smart agriculture (CRSA) model for Indian Agriculture.
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## Model Details
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| | |
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|-----------------------|------------------------------------------------|
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| **Developed by** | KissanAI (https://kissan.ai) |
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| **Base model** | [`Qwen/Qwen3-4B`](https://huggingface.co/Qwen/Qwen3-4B) |
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| **Architecture** | Qwen3 decoder-only causal-LM, 32 k context |
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| **Fine-tuning method**| Supervised fine-tuning (SFT) via *llama-factory* |
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| **Languages** | Primarily English + technical Indian-agricultural vocabulary |
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| **License** | Apache 2.0 (inherits from base model) |
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## Intended Use
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**Primary purpose**
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Assist farmers, agronomists and ag-tech developers with *Climate-Resilient and Sustainable Agriculture* (CRSA) recommendations tailored to Indian conditions (e.g., APCNF/organic practices, climate-smart cropping, pest IPM, soil/nutrient management).
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**Direct use examples**
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* Decision-support micro-service answering agronomic queries.
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* Content generation for ag-extension material.
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**Out-of-scope uses**
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* Any medical, legal, or financial advice.
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* Real-time critical decision making without human validation.
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* Disinformation, hateful or extremist content.
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## Training Data
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| Dataset | Size | Notes |
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|---------|------|-------|
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| [`KissanAI/Thinking-climate-100k`](https://huggingface.co/datasets/KissanAI/Thinking-climate-100k) | 101 k multi-turn dialogues on climate-smart ag topics with thinking tags |
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The dataset is synthetic/aligned through *“chain-of-thought + answer”* format that explicitly separates the model’s private reasoning (`<think> … </think>`) from the final answer, reducing chain-of-thought leakage at inference time.
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## Bias, Risks & Limitations
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* May embed agronomic bias toward Indian Natural Farming practices (APCNF).
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* Climate data cited is *static* (2024) – cross-check against latest IMD advisories.
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* Still prone to LLM hallucinations; always validate high-stakes advice with qualified professionals.
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## Citation
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```
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@misc{KissanAI2025ThinkingDhenu1,
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title = {ThinkingDhenu1-CRSA-India-preview},
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author = {KissanAI},
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howpublished = {\url{https://huggingface.co/KissanAI/ThinkingDhenu1-CRSA-India-preview}},
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year = {2025},
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note = {Fine-tuned from Qwen3-4B on Indian climate-smart agriculture data.}
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}
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```
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## Contact
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Contact
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Questions or feedback? Open an issue on the model repo.
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## Next steps you might consider
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1. **Add private eval numbers.**
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2. **Specify dataset licences.** |