Gemma 2B Tamil v0.1 Alpha - GGUF Quantized Variants [Experimental Release]
This is a Tamil instruction finetuned version of Google's Gemma 2B model. This is an experiment to see if Gemma can be adapted for Tamil without expanding vocabulary. While the responses may be rusty at times, it shows a lot of promise for a 2B parameter model.
Procedure:
- The Gemma base model was continually pretrained on all available Tamil Wikipedia data for 3 epochs.
- The updated model was then finetuned on a mix of English and Tamil alpaca datasets for 5 epochs.
Note: This project is currently under development (FOR TAMIL). The initial pretraining phase may not have been extensive enough, which suggests that the model's performance could improve by extending the pretraining on a larger dataset, such as CulturaX.
🏆 Benchmarks
This model outperforms Google's Gemma 2B base and instruct models on all benchmarks in Nous evaluation suite. It also surprisingly outperforms mlabonne/Gemmalpaca-2B (the best performing 2B model in benchmarks as of Feb 25, 2024) despite being a model aimed at language adaptation.
| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
|---|---|---|---|---|---|
| gemma-2b-it-tamil-v0.1-alpha📄 | 39.41 | 23.38 | 58.94 | 43.18 | 32.14 |
| mlabonne/Gemmalpaca-2B 📄 | 38.39 | 24.48 | 51.22 | 47.02 | 30.85 |
| google/gemma-2b-it 📄 | 36.1 | 23.76 | 43.6 | 47.64 | 29.41 |
| google/gemma-2b 📄 | 34.26 | 22.7 | 43.35 | 39.96 | 31.03 |
Model description
- Model type: A 2B parameter GPT-like model finetuned on 100,000 samples consisting of an equal proportion of English and Tamil samples.
- Language(s): Bilingual. English and Tamil.
- License: Google Gemma Terms of Use
- Finetuned from model: abhinand/gemma-2b-tamil
- Training Precision:
bfloat16 - Training Hardware: 4x Nvidia RTX 3090 GPUs
- Training Cost: $20
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Prompting Format [Alpaca]
Prompt Template Without Input
{system_prompt}
### Instruction:
{instruction or query}
### Response:
{response}
Prompt Template With Input
{system_prompt}
### Instruction:
{instruction or query}
### Input:
{input}
### Response:
{response}
Usage Note
It's important to note that 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. We urge users 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:
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.
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