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Parallel Action CLI for AI agents. Run 50 actions across 20 sites at onece.
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Open-source implementation of Google Vizier for hyper parameters tuning.
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Open source container-native workflow engine for orchestrating parallel jobs on Kubernetes.
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Scalable deep learning for industry with parallel GPUs.
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A lightweight Python library for building execution pipelines with retry, parallel execution, cron scheduling, and async support.
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GMS Flags is a tool for changing parameters in Google services to activate or deactivate certain functionality in Google applications
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GooFuzz is a tool to perform fuzzing with an OSINT approach, managing to enumerate directories, files, subdomains or parameters without leaving evidence on the target's server and by means of advanced Google searches (Google Dorking).
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Implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
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A tensor-based framework for large-scale data computation which is often regarded as a parallel and distributed version of NumPy.
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A high performance, memory efficient, maximally parallelized ensemble learning, integrated with scikit-learn.
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A parallel neural net microframework.
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Transactional alternative to Elasticsearch, built on Postgres.
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Open-source project that applies AI to data analysis, extraction, visualization, or business intelligence.
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State-of-the-art Parameter-Efficient Fine-Tuning.
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Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters, has python API.
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A self-hosted copilot clone that uses the library behind llama.cpp to run the 6 billion parameter Salesforce Codegen model in 4 GB of RAM.