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MLX is an array framework for machine learning on Apple silicon, developed by Apple machine learning research.
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Published directory entries matching your search.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Helps find, analyze or synthesize information for research and knowledge discovery.
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The lightweight PyTorch wrapper for high-performance AI research.
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Open-source project that supports AI-assisted research, knowledge retrieval, summarization, or source analysis.
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Open-source project that supports AI-assisted research, knowledge retrieval, summarization, or source analysis.
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Helps find, analyze or synthesize information for research and knowledge discovery.
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The AI Scientist: Towards Fully Automated Open-Ended Scientific.
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A super-easy way to record, search and compare 1000s of ML training runs.
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Easy way to turn any app into searchable data for LLMs.
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Easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.
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Platform for Neural Network Search (NAS) that allows you to generate efficient deep networks for your applications.
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Automatic architecture search and hyperparameter optimization for PyTorch.
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AI Native database for embedding vectors.
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A curated list of open-source tools for systematic reviews, meta-analysis, and evidence synthesis.
Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
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LinkedIn's generalized metadata search & discovery tool.
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A PyTorch implementation of CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation".
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Basic proof of concept for genetic architecture search in Keras.
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Example of RAG architecture using semantic search and summarization for retrieving Bible passages.
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ImageBind One Embedding Space to Bind Them All.
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Foundational Models for State-of-the-Art Speech and Text Translation.
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Framework for building applications with LLMs and Transformers (e.g. agents, semantic search, question-answering).
Implementation of image to image (pix2pix) translation from the paper by isola et al.[DEEP LEARNING].