Deploy SentenceTransformers embedding models to a ray cluster

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for calmodovar23 from gravatar.com calmodovar23

Unverified details

These details have not been verified by PyPI
Meta
  • License: MIT License
  • Author: Crispin Almodovar
  • Requires: Python >=3.12
Classifiers
Report project as malware

Project description

ray-embedding

A Python library for deploying SentenceTransformers models to a ray cluster. This tool encapsulates inference logic that uses SentenceTransformers to load any compatible embedding model from the Hugging Face hub and compute embeddings for input text.

This library is meant to be used with the embedding-models Ray cluster.

Refer to this Ray Serve deployment config to see how this library is used.

Supports the following backends

  • pytorch-gpu
  • pytorch-cpu

Planned:

  • onnx-gpu
  • onnx-cpu
  • openvino-cpu
  • fastembed-onnx-cpu

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for calmodovar23 from gravatar.com calmodovar23

Unverified details

These details have not been verified by PyPI
Meta
  • License: MIT License
  • Author: Crispin Almodovar
  • Requires: Python >=3.12
Classifiers

Release history Release notifications | RSS feed

0.17.5

0.17.4

0.17.3

0.17.2

0.17.1

0.16.9

0.16.8

0.16.6

0.16.5

0.16.2

0.16.1

0.16.0

0.15.9

0.15.8

0.15.6

0.15.5

0.15.4

0.15.3

0.15.2

0.15.1

0.15.0

0.14.8

0.14.7

0.14.6

0.14.5

0.14.4

0.14.3

0.14.2

0.14.1

0.14.0

0.13.20

0.13.19

0.13.18

0.13.17

0.13.16

0.13.15

0.13.14

0.13.13

0.13.12

0.13.11

0.13.10

0.13.9

0.13.8

0.13.7

0.13.6

0.13.5

0.13.4

0.13.3

0.13.2

0.13.1

0.13.0

0.12.12

0.12.11

0.12.10

0.12.9

0.12.8

0.12.7

0.12.6

0.12.5

0.12.4

0.12.3

0.12.2

0.12.1

0.12.0

0.11.8

0.11.7

0.11.6

0.11.5

0.11.4

0.11.3

0.11.2

0.11.1

This version

0.11.0

0.10.15

0.10.12

0.10.11

0.10.10

0.10.5

0.10.1

0.10.0

0.9.10

0.9.8

0.9.0

Download files

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

Source Distribution

ray_embedding-0.11.0.tar.gz (4.7 kB view details)

Uploaded Source

Built Distribution

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

ray_embedding-0.11.0-py3-none-any.whl (5.9 kB view details)

Uploaded Python 3

File details

Details for the file ray_embedding-0.11.0.tar.gz.

File metadata

  • Download URL: ray_embedding-0.11.0.tar.gz
  • Upload date:
  • Size: 4.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for ray_embedding-0.11.0.tar.gz
Algorithm Hash digest
SHA256 4a77dbd4fdedbc358778e8ee0eca901a0c98806d4092e62b85cd098fc4432b06
MD5 54ab36974d89799185185a7a837e65cb
BLAKE2b-256 5f8c52cd8ac4476cbda21315796063a8a5b992b856cdc7532100eae2778c1581

See more details on using hashes here.

File details

Details for the file ray_embedding-0.11.0-py3-none-any.whl.

File metadata

  • Download URL: ray_embedding-0.11.0-py3-none-any.whl
  • Upload date:
  • Size: 5.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for ray_embedding-0.11.0-py3-none-any.whl
Algorithm Hash digest
SHA256 1c026f26bb2c5548c79ebb579f26c32240331579ac6c8ae830ea6994b76dcecd
MD5 ae9b8466acc9e9cc2d8b402678ace1d6
BLAKE2b-256 6d2e1b95a455760b056915915c65023e4e37537da02dc6a70d1e7b3e33df02fb

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