Artificial intelligence plays a significant role in daily life. From ChatGPT, which offers easy information access, to chatbots, which allow you to book appointments effortlessly, AI has become an integral part of everyday tasks.
The key feature of AI has been the release of large language models, enabling you to use natural language to interact with models and get adequate responses. However, the conceptual understanding of LLM still needs to be improved for all users.
Through this article, you can get a thorough understanding of large language models and the top Indian Large Language Models available in the market. Leveraging these models, you can enhance your daily tasks in different industries with native languages.
What Are Large Language Models?
Large language models, or LLMs, are a subset of AI models trained on large volumes of data to understand and generate natural language and other forms of content. They leverage deep neural networks with billions of parameters to perform numerous tasks, including text summarization and translation.
Advanced deep learning models like HuggingFace’s transformers help the models process data and produce effective responses. The training process of LLMs usually involves converting a large corpus of text into processable chunks, also referred to as tokens. These tokens are then converted into embeddings, which are numerical vector representations of data, using different libraries and algorithms like HuggingFace Tokenizer.
The embeddings are fed to the model to train and produce responses. LLMs themselves produce vectors as output, which are then decoded into tokens. This process makes LLMs a technique for generating the next best token that is compatible with the previous token.
Here are some of the ways LLMs can be helpful:
- Code Generation: LLMs can efficiently generate code for you. This is especially useful if you have slim-to-none technical expertise. Leveraging LLMs to create clean code can enable you to build your applications from scratch.
- Text Summarizer: LLMs can quickly summarize articles and documents, saving you time when getting essential information from their content. You can also use LLMs to extract useful information from research papers, enabling you to work on projects.
- Language Translation: You can use LLM to translate different languages. This is especially useful when you want to understand text or documents that are in a different language than yours.
Best Indian LLMs
The AI revolution has already begun in India, with over 10.71% of OpenAI’s ChatGPT users located in the country. Multiple Indian startups have recognized the potential of LLMs and are building their product in this landscape.
Let’s look at the famous Indian models in the market right now.
Dhenu 1.0
Dhenu is an AI solution for the agriculture sector. It offers a series of LLMs focused on assisting farmers in enhancing crop growth and determining crop diseases.
Dhenu-vision-lora-v0.1 is an open-source agricultural disease detection model that mainly focuses on three majorly grown crops in India: wheat, rice, and maize. This model was trained on 9000 synthetic images of crops ruined by diseases. The v0.1 model achieved 36.13% accuracy on 500 test images, significantly enhancing the base model.
With a conversational interface, it empowers farmers and breaks the language barrier by providing the best agricultural advice in English and Hindi. Currently, Dhenu offers a low-cost fine-tuning methodology for agricultural datasets by incorporating Low-Rank adaptation techniques.
This LLM is fine-tuned using the Qwen-VL-chat model, enhancing the detection of common crop diseases, such as Wheat Loose Smut, Leaf Blight, and Leaf Spot.
Navarasa 2.0
Developed by Telugu LLM Labs, Navarasa 2.0 is a Gemma 7B/2B instruction-tuned model. This Indian LLM model offers support in 16 different languages, including 15 Indian languages and English.
Navarasa 2.0 enhances the previous model, as the researchers added six additional Indian languages to the earlier version. This expansion was made possible by translating the alpaca-cleaned-filtered dataset to include languages like Konkani, Marathi, Urdu, Assamese, Sindhi, and Nepali.
This model’s primary use cases will span various applications, including translation, content generation, educational resources, and customer support. Expanding LLMs in regional languages will promote inclusivity and allow you to leverage advanced technologies in your native language.
OpenHathi
OpenHathi is an LLM that empowers Indian markets to leverage the AI model bilingually. Developed by Sarvam AI, this model supports Hindi and English. OpenHathi is regarded as the first publicly available Hindi language LLM, marking India’s AI revolution.
This LLM significantly reduces tokenization overhead for Hindi text by merging the sentence piece tokenizer using 16K Hindi vocabulary with the Llama2 tokenizer.
The training process for OpenHathi is three-phased. Phase one establishes cross-lingual understanding utilizing low-rank adapters. The second phase is bilingual next-token prediction, and the third is supervised fine-tuning of internal datasets. These phases enable context-aware language generation and the model’s ability to handle diverse applications.
OdiaGenAI
OdiaGenAI is a team of AI researchers that continuously deploys multiple language models. It has five releases, including the Bengali-GPT model, Llama 2-7B, Olive Farm, Olive Scrapper, and Olive Whisper model. Each model is trained to respect the cultural heritage of specific languages involved, which helps ensure the content produced resonates with consumers.
The OdiaGenAI team emphasizes the empowerment of the Odia-speaking population to work with the latest AI technological trends. These models are open-sourced for developers and researchers to work with and enhance the model’s use case independently.
Krutrim
Developed by Ola Cabs founder Bhavish Aggarwal, Krutrim is a generative AI chatbot that supports more than ten languages. This piece of technology breaks down the barriers between the latest AI tech and cultures with different languages.
Currently, Krutrim’s beta version is available publicly. You can check it out by prompting in English, Hindi, or any other language that the platform supports.
Kannada Llama
Kannada Llama is an Indian LLM that specifically targets the Kannada-speaking community. It enables models to process the language to produce effective responses. It utilizes Low-Rank Adaptation (LoRA) to train and fine-tune the model and is pre-trained with 600 million Kannada tokens to enhance its vocabulary.
With open-source support, Kannada Llama allows you to collaborate with ongoing projects to improve the quality of model performance.
Bhashini
Bhashini, launched by the Indian government, is a digital platform that leverages artificial intelligence to develop various products and services. This platform’s main services are automatic speech recognition, name entity recognition, text-to-speech, neural machine translation, and more.
Bhashini focuses on introducing large language models (LLMs) into numerous technological project domains. This will help bridge the gap between the latest technologies and rich Indian heritage, breaking the barriers between digital and traditional aspects of language models.
In addition to these benefits, Bhashini offers a Universal Language Contribution API, enabling you to collect and store different datasets in Indian languages. The Indian government aims to revolutionize various sectors, including education, healthcare, and legal, using Bhashini’s multi-featured functionalities. The application is already available to download on the popular Play Stores.
Project Indus
Project Indus is one of the most highly anticipated Indian LLM initiatives developed by Tech Mahindra. This model aims to empower all the Indic languages that originated during the Indus Valley civilization.
The main objective of Project Indus is to develop large language models tailored for Indian communities, excelling at the benchmark set by existing LLMs. With 539 million parameters and 10 billion Hindi and dialect tokens, this model has been launched for beta testing.
In the first phase of release, Project Indus will work as a decoder to generate text. The subsequent phases will include reinforcement learning from human feedback (RLHF) and converting the project into a chat model. RLHF is a machine learning technique that optimizes the model performance.
With this initiative, Tech Mahindra expects to enter the LLM race and provide Indian consumers with better public healthcare infrastructure and mobile conversational systems, among other benefits.
BharatGPT
BharatGPT is a top Indian LLM built by CoRover.ai. It supports 12 different languages and allows interactions using text, voice, and video. It aligns with the Indian government’s vision of making AI accessible to all Indian citizens while securing personal data.
BharatGPT offers numerous features, including KYC with Aadhaar-based authentication, sentiment analysis, and integration with payment platforms. With text—and voice-enabled multilingual assistance, you can create bots that can address your customers’ specific needs.
In the field of businesses with AI-driven solutions, the key focus of BharatGPT is to provide versatility, accessibility, accuracy, and data security. These key components allow you to utilize this LLM without worrying about potential data misuse.
Key Takeaways
By now, you must have understood the concept of Large Language Models and how to use them to interact with models catering to different use cases. To efficiently utilize the LLMs, you must have a basic understanding of how they can benefit you.
The involvement of Indian LLMs in this technological trend has significantly increased access to the latest information for the non-English-speaking population. Diverse large language model examples are available in the market that you can try out to see if the product is compatible with your business.
