LLama.cpp embedder library python bindings

Navigation

Verified details

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

Unverified details

These details have not been verified by PyPI
Meta
  • License: MIT License (The MIT License Copyright (c) 2024 Amikos Tech Ltd. Permission is hereby granted, free of charge, ...)
  • Author: Trayan Azarov
  • Requires: Python >=3.8
  • Provides-Extra: test
Classifiers

Project description

Llama Embedder

This is a python binding for llama embedder, a purpose-built library for embeddings.

Installation

pip install llama_embedder

Usage

from llama_embedder import LlamaEmbedder

embedder = LlamaEmbedder(model_path='./path/to/model.gguf')

# Embed stings

embeddings = embedder.embed(['Hello World!', 'My name is Ishmael.'])

Project details

Verified details

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

Unverified details

These details have not been verified by PyPI
Meta
  • License: MIT License (The MIT License Copyright (c) 2024 Amikos Tech Ltd. Permission is hereby granted, free of charge, ...)
  • Author: Trayan Azarov
  • Requires: Python >=3.8
  • Provides-Extra: test
Classifiers

Release history Release notifications | RSS feed

0.0.8

This version

0.0.7

Download files

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

Source Distribution

llama_embedder-0.0.7.tar.gz (18.8 MB view details)

Uploaded Source

Built Distributions

llama_embedder-0.0.7-cp312-cp312-win_amd64.whl (719.6 kB view details)

Uploaded CPython 3.12 Windows x86-64

llama_embedder-0.0.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

llama_embedder-0.0.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ARM64

llama_embedder-0.0.7-cp312-cp312-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

llama_embedder-0.0.7-cp312-cp312-macosx_10_9_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.12 macOS 10.9+ x86-64

llama_embedder-0.0.7-cp311-cp311-win_amd64.whl (719.3 kB view details)

Uploaded CPython 3.11 Windows x86-64

llama_embedder-0.0.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

llama_embedder-0.0.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

llama_embedder-0.0.7-cp311-cp311-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

llama_embedder-0.0.7-cp311-cp311-macosx_10_9_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

llama_embedder-0.0.7-cp310-cp310-win_amd64.whl (718.3 kB view details)

Uploaded CPython 3.10 Windows x86-64

llama_embedder-0.0.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

llama_embedder-0.0.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

llama_embedder-0.0.7-cp310-cp310-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

llama_embedder-0.0.7-cp310-cp310-macosx_10_9_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

llama_embedder-0.0.7-cp39-cp39-win_amd64.whl (718.4 kB view details)

Uploaded CPython 3.9 Windows x86-64

llama_embedder-0.0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

llama_embedder-0.0.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

llama_embedder-0.0.7-cp39-cp39-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

llama_embedder-0.0.7-cp39-cp39-macosx_10_9_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

llama_embedder-0.0.7-cp38-cp38-win_amd64.whl (718.3 kB view details)

Uploaded CPython 3.8 Windows x86-64

llama_embedder-0.0.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

llama_embedder-0.0.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

llama_embedder-0.0.7-cp38-cp38-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

llama_embedder-0.0.7-cp38-cp38-macosx_10_9_x86_64.whl (1.4 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

File details

Details for the file llama_embedder-0.0.7.tar.gz.

File metadata

  • Download URL: llama_embedder-0.0.7.tar.gz
  • Upload date:
  • Size: 18.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.5

File hashes

Hashes for llama_embedder-0.0.7.tar.gz
Algorithm Hash digest
SHA256 578b638457555abceb6e98e638cc5361306add64a5d93ea751f8f23f0dc80e40
MD5 d4eba4bdf8ba4c15934551630c61e894
BLAKE2b-256 f7d7a50e522e5c1834bbd0aef09d3db97098a8273ad05a69bb3e8628acec118f

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 705a933316979f19d670897c3655937507a0e117989e83bdd72abf3020ebdf94
MD5 317ae7ac487a8dc4397f68f5dad3d1b9
BLAKE2b-256 926e6c6ba3ced11b50ce3a7a1796c74ddc4bfc1c5ee787c4159ea966cd573af9

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6f0f2597c72077af3885c01931187942cac19f9b44004e6f9ebfe2bb895c8671
MD5 abb937f4d802ee25605033a8321e1628
BLAKE2b-256 4634aee08647e9fc7763701e2affc7bc9d03cd4b5f163344f189fdc607854598

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 67ad0077b1e7d1fd3d71ee611ec0a7b517eb8e4055c5254d733ec8e2a0ff77ce
MD5 a45b4ee5eae5f4e66b228cbb08aaec52
BLAKE2b-256 b3eae9b3ea633a707fb9fd7a0a1348fab83c714f8ed3b9e4374854475fe70025

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 813602f2d3a50d57b7a803a35889f09754abed3508a867d9551c280af228c9cd
MD5 0b5ad909decf212d99c89e25306d2019
BLAKE2b-256 23d16c0e77fdc285235da70f0aa75ac1169f5eb4843b32c8c39988b7ff57923d

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 60b74dffe4bb5786cefdb75ccdc0a3534f9b2d097213ba34d766c03ac519b206
MD5 3dd21850c407ad802940ec6e5769d53f
BLAKE2b-256 2582b9654f29b372343d926de7463e8a2f07e833df4e53c8bc5ee4f1fa3a6689

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 505b5dcd7999e039907ccee9f8f705ec9287404a79e175f6f0894df73d794894
MD5 3afaa7182b8c172d30177e0e9bc5dbe4
BLAKE2b-256 867276c7e7b3d476d8873fda971a6076d0237504f5cfb5a7d06e6977af0fe641

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2f00dc03de57415f65dbdb48755c47005d86020fa143dbf11eb75953356786e3
MD5 2dfa88cd8183ffbd60f00f0dd4279822
BLAKE2b-256 df2744cd301712f7bbe929146c2b2b07a6d3d74a5a439138b5741e6f12f60591

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c309bcfd32d2540dc48c045b84eb6ecaf5e1ba32d978939bbc46a2051bf13c3b
MD5 b39def3cab3572aeaf8bc2936ab0056a
BLAKE2b-256 a0a91aeb65c2c74b09fffffa4ca5fb021e1e0470b0f14fafed99f0557fbc32a4

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f0c95c8a9ad82b23ae726b8f237f6f5430c03b1a8b3a0cc0e67722e06fb3494a
MD5 c45536d711acef74584f9f16a864383f
BLAKE2b-256 ce2c4bea13b06a404ace65fb41b15e19bd78b69c969ef455cad61440851bf2b1

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e5f87c609cb2506fb1b75927cae718fa750dc1d7a9410d3a283e1ebe6a446318
MD5 bfaf6ecd81991af6338d074b59f6d8eb
BLAKE2b-256 529735e76edebfad8abf5d1e0dc82f45fb9117248ae7e029341f9a7e71cfad82

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 8333b86f0967b967b0d3f149dc5ad466e5b8b69b247f2a33cfb7c4c55af7e59f
MD5 744607344ac11be1525241cdfbe1ea92
BLAKE2b-256 e2b2abe6c4c051d4c4ddc726182dd5a27ee021711cd6d30f319da2211d67db79

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0fccbe2fcdc7fe196e3874795242db31c63c0d0b3cca453932dbc35de0616b4e
MD5 e28ec46e23b73e3c01176657f92c726f
BLAKE2b-256 c82ffe6bbcfc5b5493e4ec10dc03546c855a0988d1c250a9fdc4a8e315ff7db0

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7d2e60e6498e46f966d5049bec76d1d10f025d5e69c130d26a519cdfc5de4c1e
MD5 5d96b11a0eefb9093604978a09e65859
BLAKE2b-256 0facd67a90a60802f7e826fa31bf39169982571d381f638a46cdd3b70095c469

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4826cad345fa4b3947e51251aae4d5abf411c5c654ae867fb2a51edfbfbf8603
MD5 41c52e74736067f456c1f1d352ad6d38
BLAKE2b-256 1985f55388cf1fa64bc5e2160e886cc572acc8eca1cda7f26bd07f9a4e45e48c

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 143c1dd1e493098e1bc5fd5ef173ef4b6cdb46eca2ec89e4be817aa08cc94620
MD5 ce04415fb2aaf9d1a0ed9a17b1b189e2
BLAKE2b-256 18b7d309798cc1e23c42d0fc061e1e134bc5ed5968ec2d81fa18ffd0e74a9f4a

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 f73f8ea1eecdd1ccd7f48bb23a61625c824921d3cfcea6998e43f80935d74680
MD5 20233812bb8095a9d47a91f4435cc5c2
BLAKE2b-256 42eed993c2e5f0ca81f6276c68d1a3c373f33b17cce618c0b0fb855a1c052fbe

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2fca336108dc4b0d8a47b56a6c01c19dd91cbd042c14a20e6f297827e53feda3
MD5 c3476dbd0d9b9529891bc0336f593090
BLAKE2b-256 e04b20f5065f5507acec7f2006f14bf4745585288656aaf42b2b4cf0e30ea739

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2c0de5b95be1c69ece6ad23e3896a28a43cb791d2aecdcf22f9f2eb247e5c864
MD5 7d2d077805a48e195dacf7ef6728b480
BLAKE2b-256 00edbcb2d31970a00d542f6674c6d6906ed75fb0acf62f21f49b011b401062b8

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7f4b4b4e6c9750d775063f19df0d1889a0b766d818854c06963b378236143307
MD5 c4600cf4ef3cca0854fea44b9e606a86
BLAKE2b-256 ae7c76d2693178814ce04c939fb6563326994620f4d1c824a838dc2fe6182902

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 dd493e4509487cfa60252077169b09398ef74ed73cf236204eed73f8e9bf3a19
MD5 c389bd899accfe0ec5d728bf5745fc8b
BLAKE2b-256 92b8b0546a1aad9fd97cf48dc866fc276d9cb7abb96c362614ce3d32488721b3

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 885008f74a0d53e519624193a73b38176951a6ca9229dd9ab3d36f19e5b01180
MD5 462325314961d85d333f112da858fda4
BLAKE2b-256 9e69ee774479d3c1b96b90a817693202b9e52577dab810f8f18f92bdc25fc237

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9d8e75e816d06ef82962598dfbad5e7ce64819b15a6bdaf0abd1cc77fb0b0972
MD5 21d143b3c7d94f188988536c4b72e203
BLAKE2b-256 05e675a43e4d34778dbeba6ecc873d19b7bfd0f5aef87a79ebeba52b4749f4ed

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7f279ed5548c3d19e0fa08ab2fc075d973c64f8b7932a581aab74231ebac2094
MD5 7322d86bdebd2cb6add4201149e4f2e2
BLAKE2b-256 41aac6f1823a6f60cb45a3151a16f5018c1509edb9e9404a8f14abcaeffc90ea

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b5b3c3c1f518f365fca6284a710ec9bee8c312edafc0534e450f55cf9dd35be3
MD5 879210d3024c5e32187848ad4b0df609
BLAKE2b-256 6044d0e81e0fa9afff3b80165314b1c59df44e31ae34653a7cc0b3e07b8673d9

See more details on using hashes here.

File details

Details for the file llama_embedder-0.0.7-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for llama_embedder-0.0.7-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2d62a4b11bd70b3919bb076bbabb75ae50545365736f896893d87d9ce7cbad7e
MD5 e4ccc5a3afbf51b490f34b0648faeea6
BLAKE2b-256 db5a55fd43ab73e825379b376b219a939c6535a33d8daa1640f4ada1c6799b06

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