Sarvam 1 Sarvam 1 is a 2 billion parameter language model specifically optimized for Indian languages. It provides best in class performance in 10 Indic languages (bn, gu, hi, kn, ml, mr, or, pa, ta, te) when compared with popular models like Gemma 2 2B and Llama 3.2 3B. It is also competitive against the much larger models like Llama 3.1 8B in these languages. More details can be found in our release blog. The model was trained with NVIDIA NeMo™ Framework on the Yotta Shakti Cloud using HGX H100 systems. Note: This is a text completion model. It is meant to be finetuned on downstream tasks, and cannot be used directly as a chat or an instruction following model. Key Features Optimized for 10 Indian Languages : Built from the ground up to support major Indian languages alongside English Superior Token Efficiency : Achieves fertility rates of 1.4 2.1 across all supported languages, 2 4x more efficient than existing multilingual models High Quality Training Data : Trained on a curated corpus of ~4 trillion tokens with 2 trillion high quality Indic tokens Efficient Inference : 4 6x faster inference compared to larger models while matching or exceeding their performance on Indic langua…
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