Mistral AI has introduced its first large language model (LLM) for coding, which is fluent in 80 programming languages. The new model, known as Codestral, can be integrated with code interpreting capabilities using @MistralAI and the Code Interpreter SDK. Developers can use Mistral AI's Codestral to build applications, such as a RAG (Retrieval-Augmented Generation) app, in a matter of minutes. This model also supports the creation of applications that can interact with PDFs using simple English prompts. Performance evaluation is crucial before deploying these applications to production environments.
Build a LLM app with RAG to Chat with PDF using Mistral AI's Codestral in less than 5 minutes. Go from a simple english prompt to fully working Python application. https://t.co/5BiAY4vVEd
Mistral #AI introduces its first #LLM for coding, fluent in 80 programming languages #AI #RoboticsAINews https://t.co/1RSmbntBZk https://t.co/nl9rN2gDyI
You can now add code interpreting to the new Codestral model from @MistralAILabs Check the example in our cookbook https://t.co/QZXIEU0ZDZ
Check out the new data analysis example with @MistralAI's LLM + @e2b_dev Code Interpreter SDK. Code: https://t.co/76PnqfOuRB https://t.co/Bo8HgEG5bH
How to build a basic #RAG app #machinelearning #ml #artificialintelligence #ai #dormosheio https://t.co/e90BuGgwzb
Evaluating RAG using @ragas_io and #GPT4o Try it on Colab - https://t.co/8zcb9d3U81 Building a POC for RAG applications is easy with frameworks, but making it production-ready is challenging. Evaluating performance metrics is crucial before deployment. @lancedb @Shahules786 https://t.co/RVVHDEc2Tw