![]() It is beneficial for high-volume customer interactions in telecom, online retail, and cloud services. This means - the ability to support many users at once while enjoying very low inference costs. When combined with Infery-LLM, Deci’s Inference SDK, it achieves 4.4x greater speed than Mistral 7B with vLLM Records 125% increase in throughput over Llama 2 7B. Achieves 82% higher throughput than Mistral 7B in PyTorch comparison. Outperforms all current competitors in the 7 billion parameter class. Let's look at some of its specifications: Licensed under Apache 2.0 DeciLM 7B is a fast, accurate and efficient language model out there. Reach out to Harpreet Sahota □ for any further queries regarding model architecture and performance.ĭeci has unveiled DeciLM 7B, a groundbreaking development in the realm of language models. You can pass in a URL, upload an image, or use your webcam for inference. □YOLO-NAS Pose Fine Tuning guide notebook□Įxperience the live demo of the model using below HF model space. You can have the smallest variant that has 9.9M parameters while the largest one has 79.4M parameters for much more complex tasks and higher efficiencyĭeep dive into the mechanics of YOLO-NAS Pose's inference capabilities and fine-tuning process to apply these principles to your models. The model is available in four different flavors with distinct sizes and different latency to cater to various needs. It uses a neural architecture search developed by the team at Deci AI which has redefined the standard of accuracy and performance YOLO-NAS-POSE is a groundbreaking model in the field of pose detection in many critical sectors. Training enhancements and a streamlined post-processing pipeline set new standards for efficiency ![]() ![]() It delivers on both speed and accuracy, reimaging use cases in sports, healthcare, alikeīuilt on YOLO-NAS with a novel pose estimation head, it's optimized via Deci's AutoNAC for peak performance. Meet YOLO-NAS Pose, the next-gen pose estimation model from Deci. ![]() □Excited to introduce YOLO-NAS Pose: A new benchmark in pose estimation for images and videos ![]()
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