How small language models offer clues on customer psyche

economictimes.indiatimes.com:

language models (SLM), which are trained on smaller datasets and have limited capabilities than large language models, because they meet their domain-specific requirements at a lower cost.

These companies include ecommerce firm Flipkart, which has developed an SLM to help it understand the interests of shoppers. Another model was developed jointly by Hyderabad-based non-profit Swecha (formerly Free Software Foundation Andhra Pradesh) and call centre software provider Ozonetel.

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There are several large language models in Indian languages. Flipkart, after working on innovations with generative AI tools such as ChatGPT, a large language model, and Stable Diffusion, has lately started experimenting with small language models.

“We are using some open-source models and finetuning them for our use cases,” said Mayur Datar, Flipkart’s chief data scientist.

The online retail platform is training the model on curated datasets such as search queries by customers, or reviews posted for different products to understand the intent of a user, whether it is for shopping or for comparison of products.

Language models are also useful in summarisation of customer reviews in multiple languages which are otherwise difficult to comprehend manually.

Flipkart’s SLMs are finetuned using open-source foundational language models such as Meta’s LlaMa2, and vary from 3 billion to 13 billion parameters in size.

Using finetuned SLMs brings useful trade-offs in terms of enhancing the