Reverse Dependencies of cloudpickle

The following projects have a declared dependency on cloudpickle:

• a2rl — Make recommendations for sequential decision problems using offline data
• a7n-global-cli — cli
• abcpy — A framework for approximate Bayesian computation (ABC) that speeds up inference by parallelizing computation on single computers or whole clusters.
• abdelrahman-obfuscate — Convo: the AI powered chatbot API 2.0
• abdo — kjdfdlsjlkdfl
• abdo-obfuscate — Obfuscate Convo Test
• abdoconvo — dynamic forms updated
• ac_solver — no summary
• actorch — Deep reinforcement learning framework for fast prototyping based on PyTorch
• adaptive — Parallel active learning of mathematical functions
• adaptive-scheduler — Run many `adaptive.Learner`s on many cores (>10k) using `mpi4py.futures`, `ipyparallel`, `dask-mpi`, or `process-pool`.
• adeptRL — Reinforcement Learning Framework
• aegisblade — Deploy & run your code in a single function call.
• agavepy — SDK for Tapis
• agentifyme — Framework for building agentic workflows
• agentscope — AgentScope: A Flexible yet Robust Multi-Agent Platform.
• agnes — AGNES - Flexible Reinforcement Learning Framework with PyTorch
• ai-dataproc — no summary
• ai-flow-nightly — An open source framework that bridges big data and AI.
• ai-python — Microsoft AI Python Package
• ai2-kit — no summary
• aichatbot — Python library for building custom AI Chatbot with just one line of code.
• aiida-workgraph — Design flexible node-based workflow for AiiDA calculation.
• aironsuit — A model wrapper for automatic model design and visualization purposes.
• aistore — A (growing) set of client-side APIs to access and utilize clusters, buckets, and objects on AIStore.
• aligned-textgrid — Classes for defining sequential information from TextGrids
• allonias3 — Class to interact with S3 in a similar fashion as pathlib.Path
• alphabetsoup — tile phylogenetic space with subtrees
• alphadetector — object detection using yolo, tf2 and detectron2
• alphafed — AlphaMed Federated Learning Module
• alphamed-federated — AlphaMed Federated Learning Module
• amazon-braket-sdk — An open source library for interacting with quantum computing devices on Amazon Braket
• ampform-dpd — Symbolic expressions for Dalitz-Plot Decomposition
• amtrak — no summary
• anamod — Feature Importance Analysis of Models
• anc — cli
• andvaranaut — Predictive modelling and UQ suite.
• animal-classification — classification of animals using machine learning models
• ansible-please — Helper package to make running Ansible a bit smoother
• anyrl — A library for Reinforcement Learning
• anystore — Store and cache things anywhere
• aospy — Automated gridded climate data analysis and management
• apache-airflow — Programmatically author, schedule and monitor data pipelines
• apache-airflow-providers-daskexecutor — Provider package apache-airflow-providers-daskexecutor for Apache Airflow
• apache-beam — Apache Beam SDK for Python
• apache-beam-ai2 — A FORK! for testing with different dill version
• apache-flink — Apache Flink Python API
• apipe — Data pipelines with lazy computation and caching
• apollo-lunar — A Python SDK/CLI for Lunar API
• appenginetaskutils — Utilities for using appengine tasks. Inspired by deferred.
• aqueduct-ml — The control center for ML in the cloud
• aqueduct-sdk — Python SDK for Aqueduct
• arc-ai — Economies of models
• arcnet — Economies of models
• arcos — Economies of models
• arctic-ai — Python package for Arctic Workflow. Mirrors jupyter developments.
• arviz-base — Base ArviZ features and converters.
• AssayingAnomalies — This library is a Python implementation of the MATLAB Toolkit that accompanies Novy-Marx and Velikov (2023) and is to be used for empirical academic asset pricing research, particularly focused on studying anomalies in the cross-section of stock returns.
• async-notify — Asyncio-based Library for send notifications (messages) to users.
• asyncio-run-in-process — asyncio-run-in-process: Asyncio friendly replacement for multiprocessing
• atelierflow — An ML pipeline using apache beam for run experiments
• atq — Async task queue for Python
• attrs — Classes Without Boilerplate
• auto-mlops — Deploy your model in one line of code
• auto-surprise — A python package that automates algorithm selection and hyperparameter tuning for the recommender system library Surprise
• autobiasdetector — tools for detecting bias patterns of LLMs
• automationobjectdetection-sandeepjena7 — no summary
• autonomi-nos — Nitrous oxide system (NOS) for computer-vision.
• autonomous-learning-library — A library for building reinforcement learning agents in Pytorch
• autopilotml — A package for automating machine learning tasks
• autoprognosis — A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
• awflow — Reusable acyclic workflows in Python. Execute code on HPC systems as if you executed them on your laptop!
• Axelrod — Reproduce the Axelrod iterated prisoners dilemma tournament
• axon-ECRG — RPC proxy framework
• azureml-dataprep — Azure ML Data Preparation SDK is used to load, transform, and write data for machine learning workflows
• azureml-designer-core — Core functionalities for data-type definition, data io and frequently-used functions.
• azureml-rag — Contains Retrieval Augmented Generation related utilities for Azure Machine Learning and OSS interoperability.
• babelnet — Python API for BabelNet
• badook-tests — badook data testing framework for Python
• bancor-research — Bancor v3 python spec, simulator, and emulator library. This is an open-source python package developed by Bancor Research. It is meant to assist in the design, testing, and validating of Bancor v3 behavior.
• bart-survival — Survival analyses with Bayesian Additivie Regression Trees using PyMC-BART as BART backend.
• bayesloop — Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
• bciavm — bciAVM is a machine learning pipeline used to predict property prices.
• beluga — A general purpose indirect trajectory optimization framework.
• BentoML — BentoML: The easiest way to serve AI apps and models
• beta9 — no summary
• bf-nlu — no summary
• bf-nlu-banki — no summary
• bigdl-nano — High-performance scalable acceleration components for intel.
• bigframes — BigQuery DataFrames -- scalable analytics and machine learning with BigQuery
• bionic — A Python framework for building, running, and sharing data science workflows
• bitfount — Machine Learning and Federated Learning Library.
• blind — Blind Client: The easiest ML tracking library
• block-cascade — Library for model training in multi-cloud environment.
• bluesky — Experiment specification & orchestration.
• bn-testing — A test bench to benchmark learn algorithms for graphical models
• bofire — no summary
• boost-histogram — The Boost::Histogram Python wrapper.
• botifyme — Framework for agentic workflows
• bpnet — BPNet: toolkit to learn motif synthax from high-resolution functional genomics data using convolutional neural networks