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Are you curious about how entry-level infrastructure can outperform expectations in AI model hosting?
A recent study titled "Vers un auto-hébergement des modèles VLM/LLM" reveals that deploying a 14B LLM and a 7B VLM on a NVIDIA T4 achieved an impressive 91% success rate across 7,310 queries! This research not only highlights the resilience of budget-friendly architectures but also dives into essential aspects like cost, service level objectives (SLO), and user experience for optimal self-hosting of models.
Having explored different hosting options myself, I can attest to how impactful efficient deployments can be. This article provides valuable insights for anyone looking to enhance their AI endeavors.
What challenges have you faced in model deployment?
Read more here: https://blog.octo.com/vers-un-auto-hebergement-des-modeles-vlmllm-etude-empirique-sur-une-infrastructure-entree-de-gamme-defis-et-recommandations
#AI #MachineLearning #SelfHosting #TechInsights #NVIDIA
A recent study titled "Vers un auto-hébergement des modèles VLM/LLM" reveals that deploying a 14B LLM and a 7B VLM on a NVIDIA T4 achieved an impressive 91% success rate across 7,310 queries! This research not only highlights the resilience of budget-friendly architectures but also dives into essential aspects like cost, service level objectives (SLO), and user experience for optimal self-hosting of models.
Having explored different hosting options myself, I can attest to how impactful efficient deployments can be. This article provides valuable insights for anyone looking to enhance their AI endeavors.
What challenges have you faced in model deployment?
Read more here: https://blog.octo.com/vers-un-auto-hebergement-des-modeles-vlmllm-etude-empirique-sur-une-infrastructure-entree-de-gamme-defis-et-recommandations
#AI #MachineLearning #SelfHosting #TechInsights #NVIDIA
🌟 Are you curious about how entry-level infrastructure can outperform expectations in AI model hosting?
A recent study titled "Vers un auto-hébergement des modèles VLM/LLM" reveals that deploying a 14B LLM and a 7B VLM on a NVIDIA T4 achieved an impressive 91% success rate across 7,310 queries! This research not only highlights the resilience of budget-friendly architectures but also dives into essential aspects like cost, service level objectives (SLO), and user experience for optimal self-hosting of models.
Having explored different hosting options myself, I can attest to how impactful efficient deployments can be. This article provides valuable insights for anyone looking to enhance their AI endeavors.
What challenges have you faced in model deployment?
Read more here: https://blog.octo.com/vers-un-auto-hebergement-des-modeles-vlmllm-etude-empirique-sur-une-infrastructure-entree-de-gamme-defis-et-recommandations
#AI #MachineLearning #SelfHosting #TechInsights #NVIDIA
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