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Open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease.
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A real-time multi-person keypoint detection library for body, face, hands, and foot estimation.
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openserp tracks rankings, SERP visibility, and keyword performance across search results.
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Jan - Run LLMs like Mistral or Llama2 locally and offline on your computer, or connect to remote AI APIs.
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Open source tool that searches newly registered domain feeds to find typosquatting, IDN homograph, doppelganger and bitsquatting domains impersonating
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An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
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Lambda Architecture Framework using Apache Spark and Apache Kafka with a specialization for real-time large-scale machine learning.
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Resource scheduling and cluster management for AI.
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Enables single machine or distributed training and evaluation of deep learning models.
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GitHub OSINT collection with tools, links, and resources for online investigation workflows.
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Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone.
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A JavaScript application framework for machine learning and its engineering.
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Python Machine Learning Pentesting Toolbox for Adversarial Attacks. Works with LLMs, DNNs, and other machine learning algorithms.
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OSINT tool for checking Proton Mail addresses and ProtonVPN-related IP information during security research.
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Tensors and Dynamic neural networks in Python with strong GPU acceleration.
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Deep learning framework to train, deploy, and ship AI products Lightning fast.
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CLI tool for debugging and benchmarking RAG retrieval. EXPLAIN ANALYZE for your retrieval layer.
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Statistics, data mining and machine learning toolbox in Java.
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A "machine learning framework to automate text-and voice-based conversations.".
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Extensible system for analyzing and manipulating natural language.
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Testing infrastructure for LLM and agentic applications with collaborative evaluation.
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Text processing tools and wrappers (e.g. Vowpal Wabbit).
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Fast MATLAB-syntax runtime with automatic CPU/GPU execution and fused array kernels.
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Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...).