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ChatGLM2-6B is the second-generation version of the open-source bilingual (Chinese-English) chat model ChatGLM-6B.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Open-source tool that lets you package ML models in a standard, production-ready container.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Fast inference engine for Transformer models in C++.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.
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Train and run a computer vision model with 5-10 lines of code.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Design and Deploy Large Language Model Apps.
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10x faster, cheaper, and better vector database.
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Interactive reports to analyze ML models during validation or production monitoring.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Feature store for machine learning.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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FeatherCNN is a high performance inference engine for convolutional neural networks.
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An enterprise-grade, high performance feature store.
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A Virtual Feature Store. Turn your existing data infrastructure into a feature store.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.