Skip to main content

unofficial-ascend-tools

Project description

Ascend NPU accelerate Embedding model

Please ensure that you haved installed CANN and torch_npu.

Example:

  1. source the environment
source /usr/local/Ascend/ascend-toolkit/env.sh
  1. install torch and torch_npu

  2. now use like bellow

from unofficial_ascend_tools.embeddings import AscendEmbeddings
model = AscendEmbeddings(model_path=<path_to_model>,
    device_id=0,
    query_instruction="Represend this sentence for searching relevant passages: "
)

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

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

unofficial_ascend_tools-0.0.7.post4-py3-none-any.whl (46.9 kB view details)

Uploaded Python 3

File details

Details for the file unofficial_ascend_tools-0.0.7.post4-py3-none-any.whl.

File metadata

File hashes

Hashes for unofficial_ascend_tools-0.0.7.post4-py3-none-any.whl
Algorithm Hash digest
SHA256 cfaac418fd6cc9f01914260f52a5a6b99e3c8b459c1fe80b05ce721fca85eede
MD5 e278a333978ac1d1db30b3ba1bf338f0
BLAKE2b-256 3c06eee799cde97e26698da6797ed395c83e028bdc3079aae055daee18961df7

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