Gaja
Collection
Variants of Gaja
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9 items
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Updated
Model
🐘 Gaja
Gaja is a Hindi/Hinglish chat model, initially trained on SarvamAI's OpenHathi model and further fine-tuned for conversational interactions.
Additional Information
- It outperforms Airavata, AI4Bharat's chat version, on Huggingface OpenLLM benchmark suite.
- It was fine-tuned on only 5k samples
Inference
hey guys thanks to Bhabha AI, you guys can finally try my model
Additional Information
- The code for this can be found in The github code - Github
💬 Prompt template
<|im_start|>user
{}<|im_end|>
<|im_start|>assistant
{}<|im_end|>
😎 Features:
- Language Support: Gaja is designed to understand and generate responses in both Hindi and Hinglish, catering to a diverse range of users.
- Base Model: Built upon SarvamAI's OpenHathi model, Gaja inherits its foundational capabilities while being optimized for conversational tasks.
- Fine-tuning: Gaja has undergone fine-tuning specifically for chat-based interactions, enhancing its ability to engage in meaningful conversations with users.
- Experimental Platform: With its flexibility and adaptability, Gaja serves as a valuable platform for conducting experiments and exploring innovative approaches to chatbot development.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 46.98 |
| AI2 Reasoning Challenge (25-Shot) | 51.79 |
| HellaSwag (10-Shot) | 75.79 |
| MMLU (5-Shot) | 40.69 |
| TruthfulQA (0-shot) | 41.50 |
| Winogrande (5-shot) | 71.90 |
| GSM8k (5-shot) | 0.23 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard51.790
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard75.790
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard40.690
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard41.500
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard71.900
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard0.230