Remove Auto-classification Remove DevOps Remove LLM
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Top MLOps Tools Guide: Weights & Biases, Comet and More

Unite.AI

It combines principles from DevOps, such as continuous integration, continuous delivery, and continuous monitoring, with the unique challenges of managing machine learning models and datasets. It checks data and model quality, data drift, target drift, and regression and classification performance. What is MLOps?

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Falcon 2 11B is now available on Amazon SageMaker JumpStart

AWS Machine Learning Blog

It’s a next generation model in the Falcon family—a more efficient and accessible large language model (LLM) that is trained on a 5.5 It’s built on causal decoder-only architecture, making it powerful for auto-regressive tasks. Similarly, you can deploy the Falcon 2 11B LLM using its own model ID.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Some of its features include a data labeling workforce, annotation workflows, active learning and auto-labeling, scalability and infrastructure, and so on. The platform provides a comprehensive set of annotation tools, including object detection, segmentation, and classification.

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Accelerate your generative AI distributed training workloads with the NVIDIA NeMo Framework on Amazon EKS

AWS Machine Learning Blog

The NVIDIA NeMo Framework provides a comprehensive set of tools, scripts, and recipes to support each stage of the LLM journey, from data preparation to training and deployment. His work spans multilingual text-to-speech, time series classification, ed-tech, and practical applications of deep learning.