metadata

base_model:
  - sarvamai/sarvam-translate
license: gpl-3.0
tags:
  - gemma3
  - indic
  - onnx
  - onnxruntime-genai
  - sarvam
  - text-generation-inference
  - transformers
  - translation
language:
  - as
  - bn
  - brx
  - doi
  - gom
  - gu
  - en
  - hi
  - kn
  - ks
  - mai
  - ml
  - mni
  - mr
  - ne
  - or
  - pa
  - sa
  - sat
  - sd
  - ta
  - te
  - ur
base_model_relation: quantized

Uploaded model

Converted by: Prince-1
License: gpl-3.0
Original model : sarvamai/sarvam-translate

Sarvam-Translate

Sarvam-Translate is an advanced translation model from Sarvam AI, specifically designed for comprehensive, document-level translation across the 22 official Indian languages, built on Gemma3-4B-IT. It addresses modern translation needs by moving beyond isolated sentences to handle long-context inputs, diverse content types, and various formats. Sarvam-Translate aims to provide high-quality, contextually aware translations for Indian languages, which have traditionally lagged behind high-resource languages in LLM performance.

Learn more about Sarvam-Translate in our detailed blog post.

Key Features

Comprehensive Indian Language Support: Focus on the 22 official Indian languages, ensuring nuanced and accurate translations.
Advanced Document-Level Translation: Translates entire documents, web pages, speeches, textbooks, and scientific articles, not just isolated sentences.
Versatile Format Handling: Processes a wide array of input formats, including markdown, digitized content (handling OCR errors), documents with embedded math and chemistry equations, and code files (translating only comments).
Context-Aware & Inclusive: Engineered to respect different contexts, formats, styles (formal/informal), and ensure inclusivity (e.g., appropriate gender attribution).

Supported languages list

Assamese, Bengali, Bodo, Dogri, Gujarati, English, Hindi, Kannada, Kashmiri, Konkani, Maithili, Malayalam, Manipuri, Marathi, Nepali, Odia, Punjabi, Sanskrit, Santali, Sindhi, Tamil, Telugu, Urdu

Covertion

The onnx model is created using onnxruntime-genai