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A PyTorch based deep learning library for drug pair scoring.
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Project that automatically maps relationship networks by parsing public data using LLMs and visualizes it as an interactive graph.
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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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Python library for data-centric AI and machine learning with messy, real-world data and labels.
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Open-source project that supports AI agents, automated workflows, orchestration, or delegated tasks.
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Optimization library focused on machine learning, pythonic implementations of gradient descent, LBFGS, rmsprop, adadelta and others.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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A machine learning library for Clojure built on top of Weka and friends.
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Interop with R and Renjin (R on the JVM).
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Natural Language Processing in Clojure (opennlp).
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Open-source library for implementing CI/CD in machine learning projects.
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Code is a GitHub repository or organization with source code, releases, documentation, or project resources.
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A curated list of language modeling researches for code and related datasets.
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CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023).
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CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.
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Open Code LLMs for Code Understanding and Generation.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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A Modern, Fast, and Modular Deep Learning and Machine Learning framework for Python.
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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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Track your datasets, code changes, experimentation history, and models.
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Track, log, visualize and evaluate your LLM prompts and prompt chains.