Compare, Contrast, Contribute: Model Deployment Standards and How You Can Help
Explore ML model deployment standards like PMML, PFA, and ONNX. Learn their features, use cases, and how to contribute to open-source initiatives advancing AI/ML interoperability.
Set Up a Llama2 Endpoint for Your LLM App in OctoAI
Learn to create a Llama2 endpoint in OctoAI for building LLM applications using RAG framework. Covers model cloning, endpoint setup, cost and hardware preferences, and testing in a sample app.
Fine-tuning PaliGemma for Custom Object Detection
Step-by-step guide to fine-tune PaliGemma for custom object detection, covering setup, dataset preparation, training, evaluation, and deployment. Includes practical tips and important considerations.
Machine Learning Inside the Container - Simplifying ML Workflows with envd
Explore envd, a tool simplifying machine learning workflows in Docker containers. Learn how it enhances reproducibility, isolation, and deployment of ML models using standardized environments and Starlark configuration.
Navigating the MLOps Journey - Key Considerations for Successful Implementations
Explore essential MLOps components for streamlining machine learning model development, deployment, and maintenance. Learn about infrastructure, data management, and team roles to enhance performance and foster innovation.
Deploying Mixtral 8X7B - An Open AI Agent for Advanced NLP Tasks
Explore deploying Mixtral 8X7B, an impressive open-source LLM outperforming GPT-3.5. Learn setup, prompt formatting, agent capabilities, and integration with RAG for enhanced AI applications.
Executorch: Enabling and Accelerating PyTorch Models on Edge Devices
Learn about ExecuTorch, a new stack for accelerating PyTorch models on edge devices, addressing on-device ML challenges and enabling efficient, portable execution without compromising user experience.
The Future is Fine-Tuned - Deploying Task-Specific LLMs
Explore deploying task-specific AI models using fine-tuned LLMs. Learn motivations, technical details, and cost-effective deployment strategies for specialized AI solutions in organizations.
YOLOv9 Tutorial - Train Model on Custom Dataset
Learn to set up, train, and deploy YOLOv9 for custom object detection, including model evaluation, inference, and practical applications like self-service checkout systems.
Effortless Scalability - Orchestrating Large Language Model Inference with Kubernetes
Explore automating deployment of large AI models on Kubernetes, leveraging CRDs for seamless management and optimizing GPU utilization through preset configurations and auto-provisioning.
KubeDDR - Predictive Scoring with MLOps on Kubernetes
Explore AI-driven predictive scoring for Dance Dance Revolution using Kubernetes and CNCF projects. Learn MLOps best practices, deployment strategies, and how to leverage cloud-native technologies for AI applications.
Llama 3 - 8B and 70B Models Deep Dive and Implementation Guide
Explore Llama 3's 8B and 70B models: capabilities, benchmarks, and deployment options. Learn about scaling, licensing, and future developments in this comprehensive overview of Meta AI's latest language model release.
Effortless Scalability: Orchestrating Large Language Model Inference with Kubernetes
Explore automated deployment of large AI models on Kubernetes, leveraging CRDs for seamless management and optimizing GPU utilization through preset configurations and auto-provisioning.
Meet DBRX - The New Standard for High-Quality LLMs and Custom LLM Deployment
Explore DBRX, a high-quality open-source LLM, and learn to build custom models using MosaicAI. Discover how to overcome challenges in GenAI applications and create efficient, tailored solutions.
Effortless Scalability - Orchestrating Large Language Model Inference with Kubernetes
Explore automating deployment of large AI models on Kubernetes, leveraging CRDs for seamless management and optimizing GPU utilization through preset configurations and auto-provisioning.
Cloud-Native LLM Deployments Made Easy Using LangChain
Discover how to deploy LLM applications efficiently using LangChain and Kubernetes. Learn to streamline NLP components and manage infrastructure for smooth transition from training to real-world scenarios.
Kubernetes and MLOps for Scalable and Reproducible Generative AI
Explore how Kubernetes and MLOps practices enable scalable, reliable, and reproducible generative AI workflows, empowering organizations to unlock the full potential of AI with seamless scalability and operational excellence.
MLOps: Crafting Custom Models with Python Model and PyFunc in MLFlow
Craft custom models using MLFlow's PythonModel and pyfunc, enhancing your MLOps workflow with flexible and reusable machine learning components.
MLOPS: How to Work with Hugging Face Hub CLI
Aprende a instalar y utilizar la CLI de Hugging Face Hub para gestionar modelos y datasets de aprendizaje automático de manera eficiente.
The Future of AI for Drug Discovery
Explore the future of AI in drug discovery with leading experts discussing challenges, opportunities, and practical applications of machine learning in molecular research.
How to Get Started with MLOps in Azure Databricks
Explore the machine learning lifecycle and operationalize models using Databricks Machine Learning, focusing on scaling deployments with MLOps for company-wide implementation.