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abhinand/gemma-2b-it-tamil-v0.1-alpha
gemma-2b-it-tamil-v0.1-alpha is a text generation model from abhinand. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
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 show…
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From the Hugging Face model README
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:
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.
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 |
bfloat16If you appreciate this work and would like to support its continued development, consider buying me a coffee. Your support is invaluable and greatly appreciated.
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}
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.
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.
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 47.60 |
| AI2 Reasoning Challenge (25-Shot) | 50.09 |
| HellaSwag (10-Shot) | 71.41 |
| MMLU (5-Shot) | 39.94 |
| TruthfulQA (0-shot) | 42.63 |
| Winogrande (5-shot) | 64.96 |
| GSM8k (5-shot) | 16.60 |