Cohere Tutorial: Efficient Multilingual Support for Businesses

How to Use Coheres' Multilingual Model for Efficient Customer Support

If you run a business, you’re aware of the countless questions customers ask, often in their native languages. This can lead to duplicated inquiries and unnecessary workload for customer support. Imagine being able to cluster and respond to these inquiries with a single reply. This is where Cohere’s new multilingual model comes into play, leveraging generative AI to streamline your customer communication.

The Hotel Example: A Practical Application

In this tutorial, we’ll assume that you own a hotel and need to respond to questions from diverse customers. These inquiries might come in various languages, and your goal is to provide answers cohesively in English. The powerful multilingual model by Cohere not only clusters similar questions but also simplifies the support process.

Why Choose Cohere's Multilingual Model?

Cohere's new model boasts being the industry's first multilingual text understanding model capable of processing over 100 languages with 3X better performance compared to existing open-source models. Here are a few compelling use cases:

• Multilingual Semantic Search: Enhance the quality of search results efficiently across languages.
• Aggregate Customer Feedback: Streamline customer feedback across various languages for international operations.
• Cross-Lingual Zero-Shot Content Moderation: Identify harmful content in global online communities effectively.

How Does Cohere's Multilingual Model Work?

The model utilizes semantic vector space mapping. This technique groups texts with similar meanings, offering significant improvements in multilingual settings. A substantial dataset of 1.4 billion question/answer pairs, captured in various languages, trains this model, allowing it to comprehend language-specific nuances effectively.

Clustering Questions in Different Languages

Using the hotel example, we'll analyze questions in multiple languages, identifying five specific topic clusters:

• Food
• Pool
• Charging Station
• Theater
• Breakfast

Utilizing Cohere’s multilingual model, we can easily automate the clustering of these questions.

Getting Started with Cohere's Playground

For practical implementation, it’s recommended to test this model using the Cohere Playground. Here’s how you can use the model:

1. Add your collected questions into the 'Texts' field.
2. On the right side, set your parameters: change the model to 'multilingual-22-12' and ensure truncation is set to 'None'.
3. Click on 'Calculate' to see the model aggregate your questions into clusters.

Once you see the clustered results, you can formulate responses to inquiries that fall within the same topics.

Exporting Code for Further Use

After testing in the Playground, you may want to extend your functionality via your own coding environment. You can export your current example with the 'Export Code' button and choose your preferred programming language—Python is a common choice.

Join the AI Community!

Expand your knowledge and skills by participating in AI Hackathons. Test your capabilities and collaborate with mentors by checking the upcoming events at Lablab AI.

Conclusion

Cohere's multilingual model represents a transformative solution for businesses facing diverse customer inquiries. By efficiently clustering questions and facilitating unified answers, your customer support can become more agile, responsive, and accommodating to your global clientele.