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An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
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Open-source module for running AI workloads on Kubernetes in an optimized way.
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A PyTorch implementation of Justin Johnson's neural-style (neural style transfer).
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Global, black box optimization engine for real world metric optimization by Yelp.
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Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"s.
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A Clojure library of optimisation and control theory tools and convenience functions based on Neanderthal.
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TypeScript SDK to easily call 100+ LLMs using OpenAI's format.
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Tensorflow and OpenAI Clarity's Lucid adapted for PyTorch.
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Using Low-rank adaptation to quickly fine-tune diffusion models.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Inspired on Private GPT with the GPT4ALL model replaced with the Vicuna-7B model and using the InstructorEmbeddings instead of LlamaEmbeddings.
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Easy-to-use, scalable hyperparameter optimization framework.
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A python package that integrates an LLM copilot inside the keras model development workflow.
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A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.
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A project to make it easier to use large external knowledge bases with LLMs.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Rails-like inflection library for Clojure and ClojureScript.
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An open-source visual programming environment for battle-testing prompts to LLMs.
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Toolset for black-box hyperparameter optimisation.
Code for hyperparameter tuning/optimization of machine learning and deep learning algorithms.
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Distributed Asynchronous Hyperparameter Optimization in Python.
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A very simple wrapper for convenient hyperparameter optimization.
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Library for hyperparameter optimization and black box optimization benchmarks.