Skip to main content

ONNX Runtime is a runtime accelerator for Machine Learning models

Project description

ONNX Runtime is a performance-focused scoring engine for Open Neural Network Exchange (ONNX) models. For more information on ONNX Runtime, please see aka.ms/onnxruntime or the Github project.

Changes

1.13.1

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.13.1

1.13.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.13.0

1.12.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.12.0

1.11.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.11.0

1.10.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.10.0

1.9.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.9.0

1.8.2

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.8.2

1.8.1

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.8.1

1.8.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.8.0

1.7.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.7.0

1.6.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.6.0

1.5.3

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.5.3

1.5.2

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.5.2

1.5.1

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.5.1

1.4.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.4.0

1.3.1

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.3.1

1.3.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.3.0

1.2.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.2.0

1.1.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.1.0

1.0.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v1.0.0

0.5.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v0.5.0

0.4.0

Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v0.4.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

onnxruntime_gpu-1.13.1-cp310-cp310-win_amd64.whl (117.3 MB view details)

Uploaded CPython 3.10 Windows x86-64

onnxruntime_gpu-1.13.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (115.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

onnxruntime_gpu-1.13.1-cp39-cp39-win_amd64.whl (117.3 MB view details)

Uploaded CPython 3.9 Windows x86-64

onnxruntime_gpu-1.13.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (115.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

onnxruntime_gpu-1.13.1-cp38-cp38-win_amd64.whl (117.3 MB view details)

Uploaded CPython 3.8 Windows x86-64

onnxruntime_gpu-1.13.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (115.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

onnxruntime_gpu-1.13.1-cp37-cp37m-win_amd64.whl (117.3 MB view details)

Uploaded CPython 3.7m Windows x86-64

onnxruntime_gpu-1.13.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (115.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

File details

Details for the file onnxruntime_gpu-1.13.1-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: onnxruntime_gpu-1.13.1-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 117.3 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.8.3 requests/2.28.1 setuptools/63.2.0 requests-toolbelt/0.10.0 tqdm/4.64.1 CPython/3.10.8

File hashes

Hashes for onnxruntime_gpu-1.13.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 f535a4957e7e5c352911a0e6378c516ba90ae6558dc55482e6c138a97e6e2c58
MD5 d708b24d16ded3f5adffc67ba4821c11
BLAKE2b-256 c88761e9bfba47d56d3c04c0d9450209e28ef3383088c542e900a2a15c9bad79

See more details on using hashes here.

File details

Details for the file onnxruntime_gpu-1.13.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for onnxruntime_gpu-1.13.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 96f2bf6cb1f8a06309d7729b6b5b461a22a1af81ceec65d9bf7c4a97b72ab8b0
MD5 0dec07e29089e1dddf688f1d5b2a2134
BLAKE2b-256 1db28012f366b26ab444419fc906c940e2d0e88e64f62d2dfa6bebba54ee160d

See more details on using hashes here.

File details

Details for the file onnxruntime_gpu-1.13.1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: onnxruntime_gpu-1.13.1-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 117.3 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.8.3 requests/2.28.1 setuptools/63.2.0 requests-toolbelt/0.10.0 tqdm/4.64.1 CPython/3.10.8

File hashes

Hashes for onnxruntime_gpu-1.13.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 5347fe3a6f2f723e2f94ea625310dc37f31146c4517329c9532954410cf9b72e
MD5 3a48cae222d142da2d929bd9e6a21353
BLAKE2b-256 5475800beeaa518222f886d8a2de2eb5708806eb4dcb3b2388e341cf7402acfd

See more details on using hashes here.

File details

Details for the file onnxruntime_gpu-1.13.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for onnxruntime_gpu-1.13.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 40e468102d0bda6704bd2edea2946e413110be1288803a8597f0cf001a0a0233
MD5 e7e3291c0b72cac68e1baae9c6ec1f18
BLAKE2b-256 fb1258047e8aff9a284a4a04268d21d72db522fe5a22c4b63e06154ac4a793c1

See more details on using hashes here.

File details

Details for the file onnxruntime_gpu-1.13.1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: onnxruntime_gpu-1.13.1-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 117.3 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.8.3 requests/2.28.1 setuptools/63.2.0 requests-toolbelt/0.10.0 tqdm/4.64.1 CPython/3.10.8

File hashes

Hashes for onnxruntime_gpu-1.13.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 cda229e4fb069acd848680c59bedd86ecaf08ee773ef83414feb16d74b4f8404
MD5 16642377003f764796de6f8daabea606
BLAKE2b-256 81645e6bb0463425418978071641ba0deeaea3b322634c6d3f979eeffdf934d4

See more details on using hashes here.

File details

Details for the file onnxruntime_gpu-1.13.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for onnxruntime_gpu-1.13.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 06204a56d8c754ad90d4d0f27ce3a86154b02603b5a3e346e03fd8074a19e8d8
MD5 20a170ee41d75b3cac11cbaaf228797a
BLAKE2b-256 c6354a24fffb931334a80a69d5c9705fb8a86e6e73de3806c061fa288a440632

See more details on using hashes here.

File details

Details for the file onnxruntime_gpu-1.13.1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: onnxruntime_gpu-1.13.1-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 117.3 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.8.3 requests/2.28.1 setuptools/63.2.0 requests-toolbelt/0.10.0 tqdm/4.64.1 CPython/3.10.8

File hashes

Hashes for onnxruntime_gpu-1.13.1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 4161e3a0af092b5df5ddc46262434c90e0cd78852cf654c4e8988b838a6ace39
MD5 cb47c8db95eedb12ec11684d7dc369e1
BLAKE2b-256 b45de79e2f2f59b297c715a27ea2ec6171d851d49536f03c3584a05b40d73b4d

See more details on using hashes here.

File details

Details for the file onnxruntime_gpu-1.13.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for onnxruntime_gpu-1.13.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 caaa4c0cbc648f091a1de89d8a9921d770c345d6ab689c6438d0a9826d3297c5
MD5 ac0fba75d77392008734ca8ac1650ee5
BLAKE2b-256 6ceb76be952378b96d73e9b70958278ecc3013175faeab7ca74ba43906171eb8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page