crates.yaml

# Crates listed in this file are used to generate crates_generated.yaml
#
# Notes:
# - Entries are alphabetical by crate name
# - Any value listed in this file will take precendence over the value retrieved from crates.io or the GitHub API
#     This is especially useful for writing more complete descriptions
# - Crates not published to crates.io can be added by 'repository', but will lack some generated data
# - Crates with non-Github repos are fine, but will currently lack some generated data
# - Topics are defined are defined in the _topics directory; new topics require new topic pages

- name: accel
  topics: ["scientific-computing", "gpu-computing"]

- name: ai-dataloader
  topics: ["data-preprocessing"]

- name: alumina
  topics: ["neural-networks"]

- name: arff
  topics: ["data-preprocessing"]

- name: argmin
  topics: ["scientific-computing", "metaheuristics"]

- name: arrayfire
  topics: ["gpu-computing"]

- name: arrow
  topics: ["data-preprocessing", "data-structures"]

- name: auto-diff
  topics: ["neural-networks"]

- name: autograd
  topics: ["neural-networks"]

- name: autograph
  topics: ["neural-networks"]

- name: bacon-sci
  topics: ["scientific-computing"]

- name: bio
  topics: ["scientific-computing", "data-structures"]

- name: blas
  topics: ["scientific-computing", "gpu-computing"]

- name: blasoxide
  topics: ["scientific-computing"]

- name: burn
  topics: ["neural-networks"]

- name: bvh
  topics: ["data-structures"]

- name: candle-core
  repository: https://github.com/huggingface/candle
  description: "Minimalist ML framework with CUDA acceleration and quantization support"
  topics: ["neural-networks"]

- name: cgmath
  topics: ["scientific-computing"]

- name: clarabel
  topics: ["scientific-computing"]
  documentation: https://oxfordcontrol.github.io/ClarabelDocs/

- name: classifier
  topics: ["linear-classifiers"]

- name: clustering
  topics: ["clustering"]

- name: coaster
  topics: ["scientific-computing", "gpu-computing"]

- name: cobyla
  topics: ["scientific-computing", "metaheuristics"]

- name: cogent
  topics: ["neural-networks"]

- name: cogset
  topics: ["clustering"]

- name: collenchyma
  topics: ["scientific-computing", "gpu-computing"]

- name: cntk
  topics: ["neural-networks"]

- name: convolutions_rs
  repository: https://github.com/Conzel/convolutions-rs
  topics: ["neural-networks"]
  description: "Torch-compatible convolutions crate implemented in pure rust."

- name: csv
  topics: ["data-preprocessing"]

- name: cublas
  description: "safe Rust wrapper for CUDA's cuBLAS"
  topics: ["gpu-computing"]

- name: cuda
  topics: ["gpu-computing"]

- name: cuda-std
  topics: ["gpu-computing"]

- name: cudarc
  topics: ["gpu-computing"]

- name: cudnn
  topics: ["gpu-computing"]

- name: cumath
  topics: ["gpu-computing"]

- name: cuticula
  topics: ["data-preprocessing"]

- name: daggy
  documentation: http://mitchmindtree.github.io/daggy/daggy/
  topics: ["data-structures"]

- name: darwin-rs
  topics: ["metaheuristics"]

- name: datafusion
  topics: ["data-preprocessing"]

- name: densearray
  topics: ["data-structures"]

- name: dfdx
  topics:
    [
      "neural-networks",
      "reinforcement",
      "linear-classifiers",
      "gpu-computing",
      "scientific-computing",
    ]

- name: drug
  topics: ["neural-networks"]

- name: egobox
  topics: ["scientific-computing", "metaheuristics"]

- name: em
  description: "A macro for executing a subset of Rust with OpenCL"
  topics: ["gpu-computing", "scientific-computing"]

- name: emu_core
  repository: https://github.com/calebwin/emu
  description: "A low-level modular, extensible GPGPU compute library with cross-platform support"
  documentation: https://calebwin.github.io/emu
  topics: ["gpu-computing", "scientific-computing"]

- name: emu_core
  repository: https://github.com/calebwin/emu
  description: "A wrapper type for storing/manipulating data on a GPU"
  documentation: https://calebwin.github.io/emu
  topics: ["data-structures"]

- name: evo
  topics: ["metaheuristics"]

- name: euclid
  topics: ["scientific-computing"]

- name: faiss
  topics: ["clustering", "data-structures"]

- name: fann
  topics: ["neural-networks"]

- name: finalfusion
  topics: ["nlp", "data-structures"]

- name: forester
  topics: ["decision-trees"]

- name: genetic
  topics: ["metaheuristics"]

- name: GSL
  topics: ["scientific-computing"]

- name: hal-ml
  topics: ["neural-networks"]

- name: hdf5
  topics: ["data-preprocessing"]

- name: juice
  topics: ["neural-networks"]

- name: kddbscan
  topics: ["clustering"]

- name: kmeans-colors
  topics: ["clustering", "scientific-computing"]

- name: kmedoids
  topics: ["clustering"]

- name: lapack
  topics: ["scientific-computing"]

- name: leaf
  topics: ["neural-networks"]

- name: linfa
  documentation: "https://rust-ml.github.io/linfa/"
  topics: ["clustering", "decision-trees", "linear-classifiers"]

- name: linxal
  topics: ["scientific-computing"]

- name: llm
  topics: ["nlp"]

- name: llm-chain
  topics: ["nlp"]

- name: matrixmultiply
  topics: ["scientific-computing"]

- name: metaheuristics
  topics: ["metaheuristics"]

- name: mop
  topics: ["metaheuristics", "scientific-computing"]

- name: nalgebra
  topics: ["scientific-computing"]

- name: ndarray
  topics: ["data-structures"]

- name: ndarray-glm
  topics: ["scientific-computing"]

- name: ndarray-linalg
  topics: ["scientific-computing"]

- name: ndarray-stats
  topics: ["scientific-computing"]

- name: ndsparse
  topics: ["data-structures"]

- name: neuroflow
  topics: ["neural-networks"]

- name: neuronika
  topics: ["neural-networks", "scientific-computing"]

- name: newton_rootfinder
  topics: ["scientific-computing"]

- name: ngt
  topics: ["data-structures"]

- name: nn
  topics: ["neural-networks"]

- name: num
  topics: ["data-structures"]

- name: numeric
  topics: ["data-structures"]

- name: numrs
  topics: ["scientific-computing"]

- name: ocl
  topics: ["gpu-computing"]

- name: openml
  topics: ["data-preprocessing"]

- name: oxigen
  topics: ["metaheuristics"]

- name: parenchyma
  topics: ["scientific-computing", "gpu-computing"]

- name: peroxide
  topics: ["scientific-computing"]

- name: petgraph
  topics: ["data-structures"]

- name: polars
  topics: ["data-preprocessing", "data-structures"]

- name: prophet
  topics: ["neural-networks"]

- name: qcgpu
  topics: ["scientific-computing"]

- name: rds
  topics: ["data-structures"]

- name: rettle
  topics: ["data-preprocessing"]

- name: revonet
  topics: ["metaheuristics", "neural-networks"]

- name: roulette-wheel
  topics: ["data-structures"]

- name: rsgenetic
  topics: ["metaheuristics"]

- name: rsrl
  topics: ["reinforcement"]

- name: rstats
  topics: ["scientific-computing"]

- name: rulinalg
  topics: ["scientific-computing"]

- name: rurel
  topics: ["reinforcement"]

- name: rust2vec
  topics: ["nlp", "data-structures"]

- name: rustacuda
  topics: ["scientific-computing", "gpu-computing"]

- name: rustlearn
  topics: ["linear-classifiers", "decision-trees"]

- name: rusticsom
  topics: ["clustering"]

- name: rustml
  topics: ["neural-networks", "clustering"]

- name: rust-bert
  topics: ["nlp"]

- name: rusty-data
  documentation: https://athemathmo.github.io/rusty-data/
  topics: ["data-preprocessing"]

- name: rust-gpu
  repository: https://github.com/rust-gpu/rust-gpu
  description: "Making Rust a first-class language and ecosystem for GPU graphics & compute shaders"
  topics: ["gpu-computing"]

- name: rusty-machine
  topics: ["neural-networks", "linear-classifiers", "clustering"]

- name: scirust
  topics: ["scientific-computing"]

- name: simplers_optimization
  topics: ["metaheuristics"]

- name: slsqp
  topics: ["scientific-computing", "metaheuristics"]

- name: smartcore
  documentation: https://smartcorelib.org/
  topics:
    [
      "data-structures",
      "linear-classifiers",
      "clustering",
      "scientific-computing",
      "decision-trees",
    ]

- name: statrs
  topics: ["scientific-computing"]

- name: sprs
  topics: ["data-structures", "scientific-computing"]

- name: tch
  topics: ["neural-networks"]

- name: tokenizers
  topics: ["data-preprocessing"]

- name: tensorflow
  topics: ["neural-networks"]

- name: timely
  topics: ["data-preprocessing"]

- name: tflite
  topics: ["neural-networks"]

- name: tract
  topics: ["neural-networks"]

- name: triton_grow
  repository: https://github.com/BradenEverson/triton
  topics: ["neural-networks"]

- name: tvm
  topics: ["neural-networks"]

- name: utah
  repository: https://github.com/kernelmachine/utah
  topics: ["data-structures"]

- name: vulkano
  topics: ["gpu-computing"]

- name: xgboost
  topics: ["decision-trees"]
  description: "Rust bindings for the XGBoost gradient boosted trees library."

- name: wgpu
  topics: ["gpu-computing"]

- name: wonnx
  topics: ["neural-networks", "gpu-computing"]

- repository: https://github.com/torchrs/torchrs
  description: "Torch.rs (torturous) is a set of Rust bindings for torch intended to provide an API very close to that of PyTorch."
  license: BSD-2-Clause
  topics: ["neural-networks"]

- repository: https://github.com/luqmana/rust-opencl
  description: "OpenCL bindings for Rust."
  license: MIT/Apache-2.0
  topics: ["gpu-computing"]

- repository: https://github.com/pengowen123/eant2
  description: "EANT2 is an metaheuristicsary algorithm that uses the Common Genetic Encoding (CGE) to encode neural networks and CMA-ES as a weight optimizer. EANT2 evolves the topology of the Neural Network and CMA-ES tries to find the optimal weights for each topology."
  documentation: https://pengowen123.github.io/eant2/eant2/index.html
  license: GPL-3.0
  topics: ["metaheuristics"]

- repository: https://github.com/tedsta/deeplearn-rs
  description: "Deep neural networks in Rust"
  license: MIT
  topics: ["neural-networks"]

- repository: https://github.com/NivenT/REnforce
  description: "Reinforcement library written in Rust"
  topics: ["reinforcement"]

- repository: https://github.com/opendifferentialprivacy/whitenoise-core
  description: "Differential privacy validator and runtime"
  license: MIT
  topics: ["data-preprocessing"]

- repository: https://github.com/outbrain/fwumious_wabbit
  description: "Fast logistic regression and field-aware factorization machines in Rust"
  license: BSD-3-Clause
  topics: ["neural-networks", "linear-classifiers"]

- repository: https://github.com/tensorzero/tensorzero
  description: "data & learning flywheel for LLMs that unifies inference, observability, optimization, and experimentation"
  license: Apache-2.0
  topics: ["mlops"]

- repository: https://github.com/evilsocket/cake
  description: "Distributed LLM and StableDiffusion inference for mobile, desktop and server."
  license: GPL-3.0
  topics: ["mlops"]

- repository: https://github.com/qdrant/qdrant
  description: "High-performance, massive-scale Vector Database for the next generation of AI."
  license: Apache-2.0
  topics: ["mlops"]