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

This version

0.11.4

0.11.3

0.11.2

0.11.1

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-0.11.4.tar.gz (4.8 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-0.11.4-py3-none-any.whl (6.1 kB view details)

Uploaded Python 3

File details

Details for the file ray_embedding-0.11.4.tar.gz.

File metadata

  • Download URL: ray_embedding-0.11.4.tar.gz
  • Upload date:
  • Size: 4.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for ray_embedding-0.11.4.tar.gz
Algorithm Hash digest
SHA256 467bc678f843a3acb85c7d8215e891fc97e9a6dd18cbefd746a24f86a6007b3d
MD5 86a6ed98b1dfdf202c36da4ccdff44c2
BLAKE2b-256 f892c2088381a9a03534e9ad948e3c4775fb94c81b589e73ebc0ce2b38d2dd3a

See more details on using hashes here.

File details

Details for the file ray_embedding-0.11.4-py3-none-any.whl.

File metadata

  • Download URL: ray_embedding-0.11.4-py3-none-any.whl
  • Upload date:
  • Size: 6.1 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-0.11.4-py3-none-any.whl
Algorithm Hash digest
SHA256 14bb930882ba0a4f28e4f2680ac891eb4e83a863d0132bbc9fce904c7cf7fbf8
MD5 80afd5b965b90c25ef08d715eae2e738
BLAKE2b-256 49198a16ce923dbff30921b77eb90b5aa1584b4d75192f4adcfd70d603233fef

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