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README.md
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# Kavi
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**v0.5**
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- Improved reasoning and clarity
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- Fine-tuned on curated life-advice conversations
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- Better consistency in responses
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##
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## Training
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## Intended Use
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## Limitations
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- Not professional advice
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- Tamil support planned in future versions
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---
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license: apache-2.0
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language:
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- en
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- ta
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base_model:
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- TinyLlama/TinyLlama-1.1B-Chat-v1.0
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---
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# Kavi
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**Kavi** is a compact, instruction-tuned language model focused on delivering **clear, simple, and practical life advice**. It is designed to be approachable, consistent, and easy to deploy, making it suitable for educational and personal guidance use cases.
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---
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## Model Details
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- **Model name:** Kavi
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- **Version:** v0.5
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- **Author:** Abhinivesh (0xAbhi)
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- **Base model:** TinyLlama/TinyLlama-1.1B-Chat-v1.0
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- **Model type:** Causal Language Model
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- **Language:** English (Tamil support planned)
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- **License:** Apache 2.0
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---
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## What’s New in v0.5
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- Improved reasoning and response clarity
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- Fine-tuned on curated life-advice conversations
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- More consistent and structured answers
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- Better alignment for supportive, guidance-oriented dialogue
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---
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## Training
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- **Fine-tuning method:** QLoRA (Low-Rank Adaptation)
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- **Hardware:** NVIDIA Tesla T4 (Google Colab)
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- **Precision:** 4-bit base model with LoRA adapters (merged)
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- **Dataset:** Curated English life-advice and guidance conversations
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The model was fine-tuned to improve conversational quality, tone, and practical reasoning without significantly increasing model size or inference cost.
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---
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## Intended Use
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Kavi is intended for:
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- General life guidance and self-reflection prompts
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- Educational and learning-oriented conversations
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- Supportive, non-clinical advice interactions
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- Chatbots focused on clarity, simplicity, and encouragement
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---
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## Out-of-Scope Use
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Kavi is **not** intended for:
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- Medical, legal, or financial advice
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- Crisis counseling or mental health diagnosis
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- Professional or authoritative decision-making systems
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---
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## Limitations
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- Not a substitute for professional advice
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- English-first; Tamil reasoning and responses are planned for future releases
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- As a small (1.1B) model, complex multi-step reasoning may be limited
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---
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## Ethical Considerations
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- Responses are generated based on patterns learned from training data and may not always be accurate or complete
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- Users should apply human judgment when interpreting outputs
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- The model does not possess awareness, intent, or personal understanding
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---
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## Usage Example
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```python
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from transformers import pipeline
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pipe = pipeline(
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"text-generation",
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model="0xAbhi/kavi",
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device_map="auto",
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)
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pipe("I feel stuck in life and don’t know what to do next.")
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```
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---
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## Future Work
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Incremental Tamil language fine-tuning
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Multilingual reasoning improvements
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Additional alignment for emotional nuance and long-form guidance
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Citation
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```python
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@misc{tinyllama,
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title={TinyLlama: An Open-Source Small Language Model},
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author={TinyLlama Team},
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year={2023},
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url={https://huggingface.co/TinyLlama}
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}
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```
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## Acknowledgements
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TinyLlama team for the base model
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Hugging Face ecosystem (Transformers, PEFT, TRL)
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Unsloth for efficient fine-tuning on low-resource hardware
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