The AI landscape is a whirlwind of large language models (LLMs), making it tough for enterprises to pinpoint the right fit for their projects and avoid high compute costs or inefficient performance. Taylor Smith, Senior Technical Marketing Manager for Generative AI at Red Hat, explains how Red Hat AI Validated Models bring clarity and confidence to your AI adoption journey.
In this video, Taylor explains:
● What are Red Hat AI Validated Models? Learn about our rigorously tested third-party models, validated for performance and efficiency on the Red Hat AI platform (Red Hat OpenShift AI, Red Hat Enterprise Linux AI, and Red Hat AI Inference Server).
● Key Benefits: Understand how these models accelerate time to value, promote consistency across teams, provide flexibility in model choice, and offer deployment guidance for rightsizing and optimal hardware selection.
● Find Them with Ease: Validated models are available on the Red Hat AI page on Hugging Face, easily identified by the "Red Hat AI validated model badge."
● Transparent Validation Process: We use open source tools like GuideLLM for capacity planning, Language Model Evaluation Harness for accuracy, and vLLM for top-tier inference serving performance—ensuring reproducibility and trust.
By leveraging Red Hat AI Validated Models, gain the confidence, predictability, and flexibility needed to successfully deploy powerful third-party LLMs across your enterprise.
Explore Red Hat AI Validated Models and Resources:
🧠 Learn more about Red Hat AI solutions → https://www.redhat.com/en/products/ai
⚙️ Discover Red Hat OpenShift AI → https://www.redhat.com/en/products/ai/openshift-ai
📖 What is vLLM? (Efficient LLM serving) → https://www.redhat.com/en/topics/ai/what-is-vllm
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