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

0.11.0

0.10.15

This version

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-0.10.12.tar.gz (3.9 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-0.10.12-py3-none-any.whl (4.8 kB view details)

Uploaded Python 3

File details

Details for the file ray_embedding-0.10.12.tar.gz.

File metadata

  • Download URL: ray_embedding-0.10.12.tar.gz
  • Upload date:
  • Size: 3.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for ray_embedding-0.10.12.tar.gz
Algorithm Hash digest
SHA256 bfcf65bcd486416dd3a27af288bae6464a96d2a4a3a1eaa74645a4212a4efe54
MD5 1260eb17c2711a0b67baca709f4e7abc
BLAKE2b-256 0ca346d92483564fa13b22b42fc99138d0b49ae4ec56443de30dd4be470c0ac7

See more details on using hashes here.

File details

Details for the file ray_embedding-0.10.12-py3-none-any.whl.

File metadata

File hashes

Hashes for ray_embedding-0.10.12-py3-none-any.whl
Algorithm Hash digest
SHA256 5a01d3972e7fbb60fd5e041205bed20c97a2ecb4817ac9af9fb35dda69f6b3ce
MD5 d60ffa798b7582237faf88bcf5caf85b
BLAKE2b-256 c44b0eaa3613ab82a24b39834692ae60624a7668b1b6f7ecbe68b9a8a776d959

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