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

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.


python-deepxde 1.14.0
Propagated dependencies: python-matplotlib@3.8.2 python-numpy@1.26.4 python-scikit-learn@1.7.0 python-scikit-optimize@0.10.2 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://deepxde.readthedocs.io/en/latest/
Licenses: LGPL 2.1+
Build system: pyproject
Synopsis: Library for scientific machine learning
Description:

DeepXDE is a library for scientific machine learning and physics-informed learning. It includes implementations for the PINN (physics-informed neural networks), DeepONet (deep operator network) and MFNN (multifidelity neural network) algorithms.

python-threadpoolctl 3.1.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/joblib/threadpoolctl
Licenses: Modified BSD
Build system: pyproject
Synopsis: Python helpers for common threading libraries
Description:

Thread-pool Controls provides Python helpers to limit the number of threads used in the threadpool-backed of common native libraries used for scientific computing and data science (e.g. BLAS and OpenMP).

gst-kaldi-nnet2-online 0-3.7888ae5
Dependencies: glib@2.83.3 gstreamer@1.26.3 jansson@2.14 openfst@1.8.4 kaldi@0-2.01aadd7
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://kaldi-asr.org/
Licenses: ASL 2.0
Build system: gnu
Synopsis: Gstreamer plugin for decoding speech
Description:

This package provides a GStreamer plugin that wraps Kaldi's SingleUtteranceNnet2Decoder. It requires iVector-adapted DNN acoustic models. The iVectors are adapted to the current audio stream automatically.

python-gguf 0.17.1
Propagated dependencies: python-numpy@1.26.4 python-pyyaml@6.0.2 python-pyside-6@6.9.2 python-sentencepiece@0.2.1 python-tqdm@4.67.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://ggml.ai
Licenses: Expat
Build system: pyproject
Synopsis: Read and write ML models in GGUF for GGML
Description:

A Python library for reading and writing GGUF & GGML format ML models.

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
Build system: pyproject
Synopsis: Lightning Cloud command line client
Description:

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

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
Build system: pyproject
Synopsis: SentencePiece python wrapper
Description:

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

ideep-pytorch 3.3.2
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/intel/ideep
Licenses: Expat
Build system: copy
Synopsis: Ideep headers for internal use by PyTorch
Description:

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

python-transformers 4.44.2
Propagated dependencies: python-filelock@3.16.1 python-huggingface-hub@0.31.4 python-numpy@1.26.4 python-pytorch@2.9.0 python-pyyaml@6.0.2 python-regex@2024.11.6 python-requests@2.32.5 python-safetensors@0.4.3 python-tokenizers@0.19.1 python-tqdm@4.67.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/huggingface/transformers
Licenses: ASL 2.0
Build system: pyproject
Synopsis: Machine Learning for PyTorch and TensorFlow
Description:

This package provides easy download of thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.

These models can be applied on:

  • Text, for tasks like text classification, information extraction, question answering, summarization, translation, and text generation, in over 100 languages.

  • Images, for tasks like image classification, object detection, and segmentation.

  • Audio, for tasks like speech recognition and audio classification.

Transformer models can also perform tasks on several modalities combined, such as table question answering, optical character recognition, information extraction from scanned documents, video classification, and visual question answering.

This package provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community. At the same time, each Python module defining an architecture is fully standalone and can be modified to enable quick research experiments.

Transformers is backed by the three most popular deep learning libraries — Jax, PyTorch and TensorFlow — with a seamless integration between them.

tflite-micro 0-0.a94423c
Dependencies: flatbuffers@23.5.26 gemmlowp@0.1-2.16e8662 kissfft-for-tflite-micro@130 ruy@0-1.caa2443
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://ai.google.dev/edge/litert/microcontrollers/overview
Licenses: ASL 2.0
Build system: gnu
Synopsis: Infrastructure to enable deployment of ML models to embedded targets
Description:

TensorFlow Lite for Microcontrollers is a port of TensorFlow Lite designed to run machine learning models on DSPs, microcontrollers and other devices with limited memory.

python-cleanlab 2.7.1
Propagated dependencies: python-numpy@1.26.4 python-pandas@2.2.3 python-scikit-learn@1.7.0 python-termcolor@2.5.0 python-tqdm@4.67.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://cleanlab.ai
Licenses: AGPL 3+
Build system: pyproject
Synopsis: Automatically find and fix dataset issues
Description:

cleanlab automatically finds and fixes errors in any ML dataset. This data-centric AI package facilitates machine learning with messy, real-world data by providing clean labels during training.

python-captum 0.8.0
Propagated dependencies: python-matplotlib@3.8.2 python-numpy@1.26.4 python-pytorch@2.9.0 python-tqdm@4.67.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://captum.ai
Licenses: Modified BSD
Build system: pyproject
Synopsis: Model interpretability for PyTorch
Description:

Captum is a model interpretability and understanding library for PyTorch. Captum contains general purpose implementations of integrated gradients, saliency maps, smoothgrad, vargrad and others for PyTorch models. It has quick integration for models built with domain-specific libraries such as torchvision, torchtext, and others.

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
Build system: pyproject
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.

python-autograd 1.8.0
Propagated dependencies: python-future@1.0.0 python-numpy@1.26.4
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/HIPS/autograd
Licenses: Expat
Build system: pyproject
Synopsis: Efficiently computes derivatives of NumPy code
Description:

Autograd can automatically differentiate native Python and NumPy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily. The main intended application of Autograd is gradient-based optimization.

randomjungle 2.1.0
Dependencies: boost@1.89.0 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+
Build system: gnu
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.

python-ml-dtypes 0.5.3
Dependencies: eigen-for-python-ml-dtypes@3.4.0-0.7bf2968
Propagated dependencies: python-numpy@1.26.4
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/jax-ml/ml_dtypes
Licenses: ASL 2.0
Build system: pyproject
Synopsis: NumPy dtype extensions used in machine learning
Description:

This package is a stand-alone implementation of several NumPy dtype extensions used in machine learning libraries, including:

  • bfloat16: an alternative to the standard float16 format

  • float8_*: several experimental 8-bit floating point representations including:

    • float8_e4m3b11fnuz

    • float8_e4m3fn

    • float8_e4m3fnuz

    • float8_e5m2

    • float8_e5m2fnuz

  • int4 and uint4: low precision integer types.

python-visdom 0.2.4
Propagated dependencies: python-jsonpatch@1.33 python-networkx@3.4.2 python-numpy@1.26.4 python-pillow@11.1.0 python-requests@2.32.5 python-scipy@1.12.0 python-six@1.17.0 python-tornado@5.1.1 python-websocket-client@1.8.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/fossasia/visdom
Licenses: ASL 2.0
Build system: pyproject
Synopsis: Visualizations of live, rich data for Torch and Numpy
Description:

This package provides a tool for visualizing live, rich data for Torch and Numpy.

python-pytorch 2.7.1
Dependencies: 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@0.0.0-2.81925d1 googletest@1.12.1 googlebenchmark@1.9.1 libuv@1.44.2 miniz@pytorch-2.7.0 oneapi-dnnl@3.5.3 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-2.9.0 rdma-core@60.0 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@0.0-4.51a0103 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
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://pytorch.org/
Licenses: Modified BSD
Build system: python
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-torchdiffeq 0.2.5-0.a88aac5
Propagated dependencies: python-numpy@1.26.4 python-scipy@1.12.0 python-pytorch@2.9.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/rtqichen/torchdiffeq
Licenses: Expat
Build system: pyproject
Synopsis: ODE solvers and adjoint sensitivity analysis in PyTorch
Description:

This tool provides ordinary differential equation solvers implemented in PyTorch. Backpropagation through ODE solutions is supported using the adjoint method for constant memory cost.

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
Build system: pyproject
Synopsis: Torch7 binary serialized file parser
Description:

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

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
Build system: cmake
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.

gloo 0.0.0-4.54cbae0
Dependencies: openssl@1.1.1u rdma-core@60.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/facebookincubator/gloo
Licenses: Modified BSD
Build system: cmake
Synopsis: Collective communications library
Description:

Gloo is a collective communications library. It comes with a number of collective algorithms useful for machine learning applications. These include a barrier, broadcast, and allreduce.

python-safetensors 0.4.3
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://huggingface.co/docs/safetensors
Licenses: ASL 2.0
Build system: cargo
Synopsis: Simple and safe way to store and distribute tensors
Description:

This package provides a fast (zero-copy) and safe (dedicated) format for storing tensors safely.

python-tflite-runtime 2.16.2
Dependencies: abseil-cpp@20250814.1 cpuinfo@0.0-5.b73ae6c eigen@3.4.0 fp16@0.0-1.0a92994 flatbuffers@23.5.26 gemmlowp@0.1-2.16e8662 mesa-headers@25.2.3 neon2sse@0-1.097a5ec nsync@1.26.0 opencl-icd-loader@2024.10.24 pthreadpool@0.1-3.560c60d python@3.11.14 python-ml-dtypes@0.5.3 ruy@0-1.caa2443 re2@2022-12-01 xnnpack@0.0-4.51a0103 vulkan-headers@1.4.321.0 zlib@1.3.1
Propagated dependencies: python-numpy@1.26.4
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://www.tensorflow.org
Licenses: ASL 2.0
Build system: trivial
Synopsis: Machine learning framework
Description:

TensorFlow is a flexible platform for building and training machine learning models. This package provides the "lite" variant for mobile devices.

python-faster-whisper 1.2.0
Propagated dependencies: onnxruntime@1.22.0 python-av@16.0.1 python-ctranslate2@4.6.0 python-huggingface-hub@0.31.4 python-tokenizers@0.19.1 python-tqdm@4.67.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/SYSTRAN/faster-whisper
Licenses: Expat
Build system: pyproject
Synopsis: Whisper transcription reimplementation
Description:

This package provides a reimplementation of OpenAI's Whisper model using CTranslate2, which is a inference engine for transformer models.

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Total results: 69264