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Feature engineering package with SKlearn like functionality.
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Python library for automated feature engineering.
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A Scala library for constructing probabilistic models.
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Secure zero-knowledge encrypted file sharing (AES-256-GCM in-browser). No account required, MIT licensed, self-hostable, optional link expiry.
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PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.
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Finds accurate ML models automatically, efficiently and economically.
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Dynamic Tensor Graph library in Clojure (think PyTorch, DynNet, etc.).
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Running large language models on a single GPU for throughput-oriented scenarios. (Archived).
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Easy-to-use and flexible AutoML library for Python.
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Friendly Federated Learning Framework.
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Drag & drop UI to build your customized LLM flow using LangchainJS.
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Library for high performance deep learning inference on NVIDIA GPUs.
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Memory-based NLP suite developed for Dutch: PoS tagger, lemmatiser, dependency parser, NER, shallow parser, morphological analyzer.
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Julia package for Gaussian processes.
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A curated list of generative deep learning tools, works, models, etc. for artistic uses, by @filipecalegario.
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A Chinese segment based on Conditional Random Field.
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Testing framework dedicated to ML models, from tabular to LLMs. Detect risks of biases, performance issues and errors in 4 lines of code.
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AI code reviewer for GitHub Actions or local use, compatible with any LLM and integrated with Jira/Linear.
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Cloud-Native LLM Routing Engine. Improve LLM app resilience and speed.
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Open Bilingual Pre-Trained Model (ICLR 2023).
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Open Bilingual Pre-Trained Model, quantization of ChatGLM-130B, can run on consumer-level GPUs.
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Package for computer vision using OpenCV 4 and beyond.
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"a collaborative benchmark intended to probe large language models and extrapolate their future capabilities".
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Hyperparameter optimization framework, inspired by Optuna.