Large language models (LLMs) have enabled AI tools that help you write more code faster, but as we ask these tools to take on more and more complex tasks, there are limitations that become apparent. Challenges such as understanding the nuances of programming languages, complex dependencies, and adapting to codebase-specific context can lead to lower-quality code and cause bottlenecks down the line.
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Dracarys, fine-tuned from Llama 3.1 70B and available from NVIDIA NIM microservice, supports a variety of applications, including data analysis, text summarization, and multi-language support.
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NVIDIA collaborated with Mistral to co-build the next-generation language model that achieves leading performance across benchmarks in its class. With a growing number of language models purpose-built for select tasks, NVIDIA Research and Mistral AI combined forces to offer a versatile, open language model that��s performant and runs on a single GPU, such as NVIDIA A100 or H100 GPUs.
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Experience Codestral, packaged as an NVIDIA NIM inference microservice for code completion, writing tests, and debugging in over 80 languages using the NVIDIA API catalog.
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Experience the advanced LLM API for code generation, completion, mathematical reasoning, and instruction following with free cloud credits.
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Large language models (LLMs) have revolutionized natural language processing (NLP) in recent years, enabling a wide range of applications such as text summarization, question answering, and natural language generation. Arctic, developed by Snowflake, is a new open LLM designed to achieve high inference performance while maintaining low cost on various NLP tasks. Arctic Arctic is��
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Speakers from NVIDIA, Meta, Microsoft, OpenAI, and ServiceNow will be talking about the latest tools, optimizations, trends and best practices for large language models (LLMs).
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