_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.

API method:

GET /api/packages?search=hello&page=1&limit=20

where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned in response headers.

If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


tensorpipe 0-0.bb1473a
Dependencies: libuv@1.44.2
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/pytorch/tensorpipe
Licenses: Modified BSD
Synopsis: Tensor-aware point-to-point communication primitive for machine learning
Description:

TensorPipe provides a tensor-aware channel to transfer rich objects from one process to another while using the fastest transport for the tensors contained therein.

ocaml-mcl 12-068oasis4
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/fhcrc/mcl
Licenses: GPL 3
Synopsis: OCaml wrappers around MCL
Description:

This package provides OCaml bindings for the MCL graph clustering algorithm.

fbgemm 1.2.0
Dependencies: asmjit@0.0.0-2.cfc9f81 cpuinfo@0.0-5.b73ae6c
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/pytorch/fbgemm
Licenses: Modified BSD
Synopsis: Facebook GEneral Matrix Multiplication
Description:

Low-precision, high-performance matrix-matrix multiplications and convolution library for server-side inference.

qnnpack-pytorch pytorch-2.8.0
Dependencies: clog@0.0-5.b73ae6c cpuinfo@0.0-5.b73ae6c fp16@0.0-1.0a92994 fxdiv@0.0-1.63058ef psimd@0.0-1.072586a pthreadpool@0.1-3.560c60d
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/pytorch/qnnpack
Licenses: Modified BSD
Synopsis: Quantized Neural Network PACKage
Description:

QNNPACK is a library for low-precision neural network inference. It contains the implementation of common neural network operators on quantized 8-bit tensors.

python-readchar 4.2.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/magmax/python-readchar
Licenses: Expat
Synopsis: Library to easily read single chars and key strokes
Description:

This package provides a Python library to easily read single characters and key strokes.

tvm 0.20.dev0-1.d3a2ed6
Dependencies: dmlc-core@0.5-1.1334185 dlpack@1.1 libedit@20191231-3.1 libxml2@2.14.6 llvm@19.1.7 opencl-clhpp@2024.10.24 opencl-headers@2024.10.24 rang@3.2 mesa@25.2.3 mesa-opencl@25.2.3 spirv-headers@1.4.321.0 spirv-tools@1.4.321.0 vulkan-headers@1.4.321.0 vulkan-loader@1.4.321.0 zlib@1.3.1 zstd@1.5.6
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://tvm.apache.org/
Licenses: ASL 2.0
Synopsis: Machine learning compiler framework for CPUs, GPUs and accelerators
Description:

Apache TVM is a compiler stack for deep learning systems. It is designed to close the gap between the productivity-focused deep learning frameworks, and the performance- and efficiency-focused hardware backends. TVM works with deep learning frameworks to provide end to end compilation to different backends

python-scikit-rebate 0.62
Propagated dependencies: python-numpy@1.26.4 python-scipy@1.12.0 python-scikit-learn@1.7.0 python-joblib@1.5.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://epistasislab.github.io/scikit-rebate/
Licenses: Expat
Synopsis: Relief-based feature selection algorithms for Python
Description:

Scikit-rebate is a scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning. These algorithms excel at identifying features that are predictive of the outcome in supervised learning problems, and are especially good at identifying feature interactions that are normally overlooked by standard feature selection algorithms.

python-lightning-cloud 0.5.70
Propagated dependencies: python-boto3@1.40.61 python-click@8.1.8 python-fastapi@0.115.6 python-multipart@0.0.20 python-protobuf@3.20.3 python-pyjwt@2.10.1 python-requests@2.32.5 python-rich@13.7.1 python-six@1.17.0 python-urllib3@2.5.0 python-uvicorn@0.34.0 python-websocket-client@1.8.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://lightning.ai
Licenses: ASL 2.0
Synopsis: Lightning Cloud command line client
Description:

This package provides a command line interface for Lightning AI services.

python-torchfile 0.1.0-0.fbd434a
Propagated dependencies: python-numpy@1.26.4 python-setuptools@80.9.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/bshillingford/python-torchfile
Licenses: Modified BSD
Synopsis: Torch7 binary serialized file parser
Description:

This package enables you to deserialize Lua torch-serialized objects from Python.

python-sentencepiece 0.2.1
Propagated dependencies: sentencepiece@0.2.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/google/sentencepiece
Licenses: ASL 2.0
Synopsis: SentencePiece python wrapper
Description:

This package provides a Python wrapper for the SentencePiece unsupervised text tokenizer.

python-pytorch 2.0.1
Dependencies: qnnpack@0-0.7d2a4e9 foxi@1.4.1-0.c278588 asmjit@0.0.0-2.cfc9f81 brotli@1.0.9 clog@0.0-5.b73ae6c concurrentqueue@1.0.3 cpp-httplib@0.20.0 eigen@3.4.0 flatbuffers@24.12.23 fmt@9.1.0 fp16@0.0-1.0a92994 fxdiv@0.0-1.63058ef gemmlowp@0.1-2.16e8662 gloo@0.0.0-3.c7b7b02 googletest@1.12.1 googlebenchmark@1.9.1 libuv@1.44.2 miniz@pytorch-2.7.0 oneapi-dnnl@2.7.3 openblas@0.3.30 openmpi@4.1.6 openssl@3.0.8 pthreadpool@0.1-3.560c60d protobuf@3.21.9 pybind11@2.13.6 qnnpack-pytorch@pytorch-2.0.1 rdma-core@59.0 sleef@3.6.1 tensorpipe@0-0.bb1473a vulkan-headers@1.4.321.0 vulkan-loader@1.4.321.0 vulkan-memory-allocator@3.3.0 xnnpack@0.0-2.51a9875 zlib@1.3.1 zstd@1.5.6
Propagated dependencies: cpuinfo@0.0-5.b73ae6c onnx@1.17.0 onnx-optimizer@0.3.19 python-astunparse@1.6.3 python-click@8.1.8 python-filelock@3.16.1 python-fsspec@2025.9.0 python-future@1.0.0 python-jinja2@3.1.2 python-networkx@3.4.2 python-numpy@1.26.4 python-opt-einsum@3.3.0 python-optree@0.14.0 python-packaging@25.0 python-psutil@7.0.0 python-pyyaml@6.0.2 python-requests@2.32.5 python-sympy@1.13.3 python-typing-extensions@4.15.0 python-filelock@3.16.1 python-jinja2@3.1.2 python-networkx@3.4.2 python-opt-einsum@3.3.0 python-sympy@1.13.3
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://pytorch.org/
Licenses: Modified BSD
Synopsis: Python library for tensor computation and deep neural networks
Description:

PyTorch is a Python package that provides two high-level features:

  • tensor computation (like NumPy) with strong GPU acceleration;

  • deep neural networks (DNNs) built on a tape-based autograd system.

You can reuse Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed.

Note: currently this package does not provide GPU support.

python-brian2 2.5.1
Propagated dependencies: python-cython@3.1.2 python-jinja2@3.1.2 python-numpy@1.26.4 python-py-cpuinfo@9.0.0 python-pyparsing@3.2.3 python-setuptools@80.9.0 python-sympy@1.13.3
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://briansimulator.org/
Licenses: CeCILL
Synopsis: Clock-driven simulator for spiking neural networks
Description:

Brian is a simulator for spiking neural networks written in Python. It is therefore designed to be easy to learn and use, highly flexible and easily extensible.

python-onnx 1.17.0
Dependencies: protobuf@3.21.9
Propagated dependencies: python-numpy@1.26.4 python-protobuf@3.20.3 python-six@1.17.0 python-tabulate@0.9.0 python-typing-extensions@4.15.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://onnx.ai/
Licenses: Expat
Synopsis: Open Neural Network Exchange
Description:

ONNX is a format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.

randomjungle 2.1.0
Dependencies: boost@1.83.0 gsl@2.8 libxml2@2.14.6 zlib@1.3.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://www.imbs.uni-luebeck.de/forschung/software/details.html#c224
Licenses: GPL 3+
Synopsis: Implementation of the Random Forests machine learning method
Description:

Random Jungle is an implementation of Random Forests. It is supposed to analyse high dimensional data. In genetics, it can be used for analysing big Genome Wide Association (GWA) data. Random Forests is a powerful machine learning method. Most interesting features are variable selection, missing value imputation, classifier creation, generalization error estimation and sample proximities between pairs of cases.

ideep-pytorch 2.7.3-1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/intel/ideep
Licenses: Expat
Synopsis: Ideep headers for internal use by PyTorch
Description:

This library is used internally as header-only library by PyTorch.

kaldi-gstreamer-server 0-3.f79e204
Dependencies: gstreamer@1.26.3 gst-kaldi-nnet2-online@0-3.7888ae5 gst-plugins-base@1.26.3 gst-plugins-good@1.26.3 kaldi@0-2.01aadd7 python-wrapper@3.11.11 python-pygobject@3.50.0 python-pyyaml@6.0.2 python-tornado@6.4.2
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/alumae/kaldi-gstreamer-server
Licenses: FreeBSD
Synopsis: Real-time full-duplex speech recognition server
Description:

This is a real-time full-duplex speech recognition server, based on the Kaldi toolkit and the GStreamer framework and implemented in Python.

sentencepiece 0.2.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/google/sentencepiece
Licenses: ASL 2.0
Synopsis: Unsupervised tokenizer for Neural Network-based text generation
Description:

SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabulary size is predetermined prior to the neural model training. SentencePiece implements subword units---e.g., byte-pair-encoding (BPE) and unigram language model---with the extension of direct training from raw sentences. SentencePiece allows us to make a purely end-to-end system that does not depend on language-specific pre- or post-processing.

python-hdbscan 0.8.40
Propagated dependencies: python-joblib@1.5.1 python-numpy@1.26.4 python-scikit-learn@1.7.0 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/scikit-learn-contrib/hdbscan
Licenses: Modified BSD
Synopsis: High performance implementation of HDBSCAN clustering
Description:

HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates the result to find a clustering that gives the best stability over epsilon. This allows HDBSCAN to find clusters of varying densities (unlike DBSCAN), and be more robust to parameter selection. HDBSCAN is ideal for exploratory data analysis; it's a fast and robust algorithm that you can trust to return meaningful clusters (if there are any).

python-hopcroftkarp 1.2.5-1.2846e1d
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/sofiatolaosebikan/hopcroftkarp
Licenses: GPL 3
Synopsis: Implementation of the Hopcroft-Karp algorithm
Description:

This package implements the Hopcroft-Karp algorithm, producing a maximum cardinality matching from a bipartite graph.

onnx 1.17.0
Dependencies: protobuf@3.21.9
Propagated dependencies: python-numpy@1.26.4 python-protobuf@3.20.3 python-six@1.17.0 python-tabulate@0.9.0 python-typing-extensions@4.15.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://onnx.ai/
Licenses: Expat
Synopsis: Open Neural Network Exchange
Description:

ONNX is a format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.

openfst 1.8.4
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://www.openfst.org
Licenses: ASL 2.0
Synopsis: Library for weighted finite-state transducers
Description:

OpenFst is a library for constructing, combining, optimizing, and searching weighted finite-state transducers (FSTs).

python-hmmlearn 0.3.3
Propagated dependencies: python-numpy@1.26.4 python-scikit-learn@1.7.0 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/hmmlearn/hmmlearn
Licenses: Modified BSD
Synopsis: Hidden Markov Models with scikit-learn like API
Description:

Hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models.

python-autograd-gamma 0.5.0
Propagated dependencies: python-autograd@1.8.0 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/CamDavidsonPilon/autograd-gamma
Licenses: Expat
Synopsis: Autograd-compatible approximations to the gamma family of functions
Description:

This package provides Autograd-compatible approximations to the gamma family of functions.

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