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Benchmarking Large Language Models.
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A general-purpose network embedding framework: pair-wise representations optimization Network Edit.
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A platform for reproducible and scalable machine learning and deep learning on kubernetes.
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A better version of Jieba, developed by Peking University.
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This package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.
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Gitingest - Turn any Git repository into a simple text digest of its codebase so it can be fed into any LLM.
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A PyTorch-based framework to train and validate the models producing high-quality embeddings.
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Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
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Open-source module for running AI workloads on Kubernetes in an optimized way.
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CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms.
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OpenAI compatible API for LLMs and embeddings (LLaMA, Vicuna, ChatGLM and many others).
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MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
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An open source robotics benchmark for meta- and multi-task reinforcement learning.
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Inspired on Private GPT with the GPT4ALL model replaced with the Vicuna-7B model and using the InstructorEmbeddings instead of LlamaEmbeddings.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Machine Learning Pipelines for Kubeflow.
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Machine Learning Toolkit for Kubernetes.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Library for hyperparameter optimization and black box optimization benchmarks.
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Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
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Beer glass classifier created with Synaptic.
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"a collaborative benchmark intended to probe large language models and extrapolate their future capabilities".
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Package for computer vision using OpenCV 4 and beyond.
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Benchmarks of machine learning inference for Go.