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An NLP library built in node over Natural, with entity extraction, sentiment analysis, automatic language identify, and so more.
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Published directory entries matching your search.
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A Julia package for non-negative matrix factorization.
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Nn builder is a python package that lets you build neural networks in 1 line.
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This package provides graphical computation for nn library in Torch7.
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An open source AutoML toolkit for automate machine learning lifecycle.
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A completely unstable and experimental package that extends Torch's builtin nn library.
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Open-source module for running AI workloads on Kubernetes in an optimized way.
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Free open-source SPSS alternative — menu-driven desktop statistics (t-tests, ANOVA, regression, survival analysis, ROC) with SPSS.sav import/export.
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Serve Llama 2 and other large language models locally from command line or through a browser interface.
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A general statistics and machine learning library.
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Fujitsu Research's post-training quantization pipeline for LLMs (QEP, AutoBit, JointQ, rotation) with vLLM plugin (arXiv:2603.28845).
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An open-source cross-platform performance library for deep learning applications.
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OneFlow is a performance-centered and open-source deep learning framework.
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Compiler technology to transform a valid Open Neural Network Exchange (ONNX) graph into code that implements the graph with minimum runtime support.
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An ONNX (Open Neural Network eXchange) API and backend for typeful, functional deep learning in Scala (3).
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A library that enables training PyTorch models with differential privacy.
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A list of open LLMs available for commercial use.
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Grok - An LLM by xAI with and open weights. opensource.
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Open-source project that supports AI agents, automated workflows, orchestration, or delegated tasks.
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Source code and experiments results for TGS Salt Identification Challenge.
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Source code and experiments results for Airbus Ship Detection Challenge.
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Source code for Toxic Comment Classification Challenge.
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Source code and experiments results for Santander Value Prediction Challenge.
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Open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease.