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Deploy and scale machine learning models on Kubernetes. Built for LLMs, embeddings, and speech-to-text.
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Port of OpenAI's Whisper model in C/C++. It can be executed locally.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Open source web client for ChatGPT-style assistants, API keys, prompts, and self-hosted AI chat.
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Chatbox is a GitHub repository or organization with source code, releases, documentation, or project resources.
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Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.
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Build and control your personal LLMs with fast and efficient fine-tuning.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library.
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An Autonomous LLM Agent for Complex Task Solving.
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Minimize LLM token complexity to save API costs and model computations.
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A Java implementation of Twitter's text processing library.
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Python library for automatic extraction of relevant features from time series.
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Text Retrieval and Annotation Toolkit, definitely the most comprehensive toolkit I’ve encountered so far for Ruby.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Example of how the neural network learns to predict the angle between two points created with Synaptic.
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Flexible, high-performance serving system for machine learning models.
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Creates, rewrites or summarizes written content with language models.
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Text preprocessing package for use in NLP tasks.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Large Language Model Text Generation Inference.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Suite of tools that users, both novice and advanced, can use to optimize machine learning models for deployment and execution.