README.md

---
library_name: transformers
license: gemma
datasets:
- ai4bharat/sangraha
language:
- mr
- en
pipeline_tag: text-generation
---

# Model Card for Model ID

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## Model Details
Shivneri Marathi LLM is being built with the wish to bring the benefits of Generative AI to non-English (especially Marathi) speaking population of India.
Marathi has the third largest number of native speakers in India, after Hindi and Bengali. 
Almost 83 million people speak the language. 
This is a  preliminary version of our Marathi LLM (Large Language Model)!
Built on the mighty Gemma 7B base model, Shivneri LLM can generate creative and informative text in both Marathi and English.  This is just the beginning – we're constantly improving Shivneri, and even more exciting features are on the horizon!

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** Amit Ghadge
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [Amit Ghadge]
- **Model type:** [ Decoder-only large language model (LLM) with a transformer architecture]
- **Language(s) (NLP):** [Marathi, English]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [Gemma-7B]

### Model Sources [optional]

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- **Repository:** [https://github.com/amitagh/shivneri-llm]
- **Paper [optional]:** [https://medium.com/@amitagh/shivneri-marathi-llm-e823f0a045d8]
- **Demo [optional]:** [Coming soon]

## Uses

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This is a very preliminary version. Please use with caution. Would suggest to more updates and final models to try out.


## Training Details

### Training Data

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[Continually Pretrained with Lora on AI4Bharat/Sangraha dataset]

### Training Procedure

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Continually Pretrained with Lora




### Model Architecture and Objective

[ Decoder-only large language model (LLM) with a transformer architecture]

### Compute Infrastructure

[A100 80 GB]

## Meet the Developers

Get to know the creators behind this innovative model and follow their contributions to the field:

- [Amit Ghadge](https://www.linkedin.com/in/amit-ghadge-a162a115/)


## Citation [optional]

If you use this model in your research, please cite:

```bibtex
@misc{amitghadge2024ShivneriLLMv01,
      title={Shivneri-LLM: Your Bilingual Marathi and English Text Generation LLM}, 
      author={Amit Ghadge},
      year={2024},
      eprint={https://medium.com/@amitagh/shivneri-marathi-llm-e823f0a045d8},

}
```

We hope this model serves as a valuable tool in your NLP toolkit and look forward to seeing the advancements it will enable in the understanding and generation of the Marathi language.