Skip to main content

A machine learning package for interfacing with various frameworks.

Project description

The author of this package has not provided a project description

Project details


Download files

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

Source Distribution

surrealml-0.0.3.tar.gz (20.4 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

surrealml-0.0.3-py3-none-win_amd64.whl (20.5 MB view details)

Uploaded Python 3Windows x86-64

surrealml-0.0.3-py3-none-manylinux2014_x86_64.whl (20.5 MB view details)

Uploaded Python 3

surrealml-0.0.3-py3-none-manylinux2014_aarch64.whl (20.5 MB view details)

Uploaded Python 3

surrealml-0.0.3-py3-none-macosx_11_0_arm64.whl (20.5 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

surrealml-0.0.3-py3-none-macosx_10_9_x86_64.whl (20.5 MB view details)

Uploaded Python 3macOS 10.9+ x86-64

File details

Details for the file surrealml-0.0.3.tar.gz.

File metadata

  • Download URL: surrealml-0.0.3.tar.gz
  • Upload date:
  • Size: 20.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for surrealml-0.0.3.tar.gz
Algorithm Hash digest
SHA256 9238f6548471095f12f5d237c5fe6ec5d5688f8c47a0ded8b71d74004276e991
MD5 a420be47360ee2d53567977bc6e326df
BLAKE2b-256 51afdd34686a57732cbaf5ec011b7bdab399c48c584e93048d7e137905ce694e

See more details on using hashes here.

File details

Details for the file surrealml-0.0.3-py3-none-win_amd64.whl.

File metadata

  • Download URL: surrealml-0.0.3-py3-none-win_amd64.whl
  • Upload date:
  • Size: 20.5 MB
  • Tags: Python 3, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for surrealml-0.0.3-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 c5287d03e8c1fef4937bfdd70175c57b6e45e3cbeb33bedc375eb8aa80474253
MD5 16da4d3be29da4e2281c0b925f5c0178
BLAKE2b-256 38f896ba3ef495e0a7b2f8b27b396f9137bc058e809c94950be738ff25c67ad2

See more details on using hashes here.

File details

Details for the file surrealml-0.0.3-py3-none-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for surrealml-0.0.3-py3-none-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3dbb63b685b78e38d6fabea1325b3dda6cd9e99ad46304e4c4044b6eb717067c
MD5 a196721c85fd79dd38846e2cdd7779a2
BLAKE2b-256 c17733be783ad71862d41e3f86e92b0b8f19dcb84b0bc519f538a7767f76aefb

See more details on using hashes here.

File details

Details for the file surrealml-0.0.3-py3-none-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for surrealml-0.0.3-py3-none-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b81aba2e11dbcfe4fad5f4d8a7b943a0639e7450223338713b892b3eb11e3593
MD5 98f1ca7cf0d85268e050f2100c314173
BLAKE2b-256 77840dd0b2c719009a0a6f01dfd2215f938bea7b4f9af34db976930881fe83c4

See more details on using hashes here.

File details

Details for the file surrealml-0.0.3-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for surrealml-0.0.3-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 305b2f07f282fc6bb170b48e4dd39f8c195fde0aec3b8df632fec9a066d2a439
MD5 2c7a77fa5e82f3f0dfd8bc4a5048003e
BLAKE2b-256 d03a4ae7b0a242b65dccfea568434f118c4df223024a8305e84d601d9599095a

See more details on using hashes here.

File details

Details for the file surrealml-0.0.3-py3-none-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for surrealml-0.0.3-py3-none-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ad4e0ac59232a0920f5b2c0ea8d3acbe2a261031633b0c96b660b62837d9476b
MD5 f96acc17954081516ed5560c0ad6c08c
BLAKE2b-256 e551e60db95e63edb54f4743856cc8a51f8fa853f79e711136eeb6194b102adf

See more details on using hashes here.

Supported by

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