Looking for experience!
The app lets you check if the queries you have have already been asked on MachineLearning subreddit! It shows 10 related matches to your query along with the relatedness distance, url and date when it was asked. [Cohere was used to generate about 17k embeddings from the queries mined on reddit. It is also used real time to generate the embeddings for the user's query to find related matches. (Though the ~17k embeddings took a lot of time to collect due to rate limit owing to free tier, the api had no downtime and embeddings were seamlessly stored over a period of 6 hours without throwing any exception.) ]
The app lets you classify your text into Elementary, Intermediate and Advanced according to the level of complexity. Simplify functionality lets you generate an alternate simplified version of it.
The idea is to be able to create an app that lets users add documents they would like to read which are then vectorized to create a search functionality. The app supports inbuilt features like clarifying hard-to-understand phrases in a certain context, generating keywords that would help the user remember better and generating queries that would test the understanding of the reader. The app also creates a network of all the documents that are added to it (using the embeddings).
We welcome you to join us for episode one of Cohere Online Hackathon! We're partnering with Cohere to give the LabLab community the opportunity to build with one of the world's most powerful artificial intelligence language models.
We are excited to welcome you to the second episode of the Cohere AI Hackathon! In partnership with Cohere, we are giving lablab.ai community access to one of the most powerful AI language models on the market. Join us and innovate to build a better future for everyone!
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