🚀 Tamil LLaMA 7B Instruct v0.1
Welcome to the inaugural release of the Tamil LLaMA 7B instruct model – a significant stride in advancing large language models (LLMs) for the Tamil language. This model is ready for immediate inference and can also be further fine - tuned to meet your specific NLP requirements.
To gain in - depth insights into the development and capabilities of this model, please refer to the research paper and the introductory blog post (WIP) that detail our journey and the model's potential impact.
✨ Features
- Enhanced Vocabulary: The Tamil LLaMA models are built upon the original LLaMA - 2 and are enhanced with an extensive Tamil vocabulary of 16,000 tokens.
- Fine - Tuned Datasets: A 7B parameter GPT - like model fine - tuned on Tamil - Alpaca - Orca, a combination of Tamil - translated Stanford - Alpaca and a subset of [OpenOrca](https://huggingface.co/datasets/Open - Orca/OpenOrca) datasets.
- Multilingual Support: Supports both Tamil and English languages.
📦 Installation
No installation steps are provided in the original document, so this section is skipped.
📚 Documentation
Model description
The Tamil LLaMA models have been enhanced and tailored specifically with an extensive Tamil vocabulary of 16,000 tokens, building upon the foundation set by the original LLaMA - 2.
Property |
Details |
Model Type |
A 7B parameter GPT - like model fine - tuned on Tamil - Alpaca - Orca - a mix of Tamil - translated [Stanford - Alpaca](https://huggingface.co/datasets/tatsu - lab/alpaca) and a subset of [OpenOrca](https://huggingface.co/datasets/Open - Orca/OpenOrca) datasets. |
Language(s) |
Tamil and English |
License |
GNU General Public License v3.0 |
Finetuned from model |
[abhinand/tamil - llama - 7b - base - v0.1](https://huggingface.co/abhinand/tamil - llama - 7b - base - v0.1) |
Training Precision |
float16 |
Code |
[GitHub](https://github.com/abhinand5/tamil - llama) |
Prompting Format
Basic Usage
Prompt Template Without Input
{system_prompt}
### Instruction:
{instruction or query}
### Response:
{response}
Advanced Usage
Prompt Template With Input
{system_prompt}
### Instruction:
{instruction or query}
### Input:
{input}
### Response:
{response}
Related Models
Model |
Type |
Data |
Base Model |
# Params |
Download Links |
Tamil LLaMA 7B Base |
Base model |
12GB |
LLaMA 7B |
7B |
[HF Hub](https://huggingface.co/abhinand/tamil - llama - 7b - base - v0.1) |
Tamil LLaMA 13B Base |
Base model |
4GB |
LLaMA 13B |
13B |
[HF Hub](https://huggingface.co/abhinand/tamil - llama - 13b - base - v0.1) |
Tamil LLaMA 7B Instruct |
Instruction following model |
145k instructions |
Tamil LLaMA 7B Base |
7B |
[HF Hub](https://huggingface.co/abhinand/tamil - llama - 7b - instruct - v0.1) |
Tamil LLaMA 13B Instruct |
Instruction following model |
145k instructions |
Tamil LLaMA 13B Base |
13B |
[HF Hub](abhinand/tamil - llama - 13b - instruct - v0.1) |
Usage Note
⚠️ Important Note
The models have not undergone detoxification. Therefore, while they possess impressive linguistic capabilities, there is a possibility for them to generate content that could be deemed harmful or offensive. Users are urged to exercise discretion and supervise the model's outputs closely, especially in public or sensitive applications.
Meet the Developers
Get to know the creators behind this innovative model and follow their contributions to the field:
- [Abhinand Balachandran](https://www.linkedin.com/in/abhinand - 05/)
Citation
If you use this model or any of the the Tamil - Llama datasets in your research, please cite:
@misc{balachandran2023tamilllama,
title={Tamil - Llama: A New Tamil Language Model Based on Llama 2},
author={Abhinand Balachandran},
year={2023},
eprint={2311.05845},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Detailed results can be found [here](https://huggingface.co/datasets/open - llm - leaderboard/details_abhinand__tamil - llama - 7b - instruct - v0.1)
Metric |
Value |
Avg. |
45.52 |
AI2 Reasoning Challenge (25 - Shot) |
48.04 |
HellaSwag (10 - Shot) |
70.97 |
MMLU (5 - Shot) |
39.95 |
TruthfulQA (0 - shot) |
41.70 |
Winogrande (5 - shot) |
70.64 |
GSM8k (5 - shot) |
1.82 |
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 Tamil language.