Fast HuggingFace model downloader

Navigation

Verified details

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

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers
Report project as malware

Project description

HFD - Hugging Face Downloader

A fast and efficient tool for downloading models from Hugging Face.

Features

  • Fast parallel downloads
  • Support for multiple platforms (Linux, Windows, macOS)
  • Easy to use command-line interface
  • Progress bar for download tracking
  • Local directory support

Installation

pip install hfd

Usage

# Download a model to the default cache directory
hfd bert-base-uncased

# Download a model to a specific directory
hfd bert-base-uncased --local-dir ./bert

# Use a mirror for faster downloads
HF_ENDPOINT=https://hf-mirror.com hfd bert-base-uncased

License

MIT License

Project details

Verified details

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

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

0.1.5

0.1.4

0.1.3

This version

0.1.2

0.1.0

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 Distributions

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

hfd-0.1.2-cp311-cp311-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.11Windows x86-64

hfd-0.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

hfd-0.1.2-cp311-cp311-macosx_11_0_arm64.whl (2.9 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

hfd-0.1.2-cp310-cp310-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.10Windows x86-64

hfd-0.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

hfd-0.1.2-cp310-cp310-macosx_11_0_arm64.whl (2.9 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

hfd-0.1.2-cp39-cp39-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9Windows x86-64

hfd-0.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

hfd-0.1.2-cp39-cp39-macosx_11_0_arm64.whl (2.9 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

hfd-0.1.2-cp38-cp38-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.8Windows x86-64

hfd-0.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

hfd-0.1.2-cp38-cp38-macosx_11_0_arm64.whl (2.9 MB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

File details

Details for the file hfd-0.1.2-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: hfd-0.1.2-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for hfd-0.1.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 b4b4fee90e1a6c3a3ab131f277f432d8ba9848b97a088c2e345cfc1269efb68d
MD5 b6124b9d1b116146417f1442c6b60f28
BLAKE2b-256 9c30c02e32e40c80e09b2a7e8137ae2185ca7cf1909651442813709363b97960

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for hfd-0.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 618bc09efea5335cffa441f945be391fd18ba01d07b5496e3005494ffba084bf
MD5 cc1b89802833a715ceb71a5da3f447a0
BLAKE2b-256 76be67af1ae93ff92922c547f0cab61204a3175e14ecc6328c2b29f69077e419

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

  • Download URL: hfd-0.1.2-cp311-cp311-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.11, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for hfd-0.1.2-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4b63dd63c1b552cce5cdc131ed5fe82c147b74f9c9dc60bfeb19588568c29642
MD5 f7a7994e684a165ee5001f26b7dae3d1
BLAKE2b-256 491505e8d51b1e84730283ea8ee54eef802ddb16de621fa8b2d40d22d3e2613c

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: hfd-0.1.2-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for hfd-0.1.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 164181b17438e29cc1e1309c6261ef46dde09bd776428962532bafd9882c2a74
MD5 b97f2d3455555289b2a169d4c65b64a4
BLAKE2b-256 385ebb00af407623ebf912eeb191c18a8908087f7677aec87378d33e9ef1463c

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for hfd-0.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 16902b6b8f42839dae041a8638b61f2b5af24800eea8bf85faed16e10019cbf4
MD5 254518fa32f9535466225facee12648d
BLAKE2b-256 baaba0b709e3d06b07068e5be8bed211340714cd476749a72d04a0f23ca94d47

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

  • Download URL: hfd-0.1.2-cp310-cp310-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.10, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for hfd-0.1.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d006984fb2b5fb77a37f249f513db039b8e3c1d05f3fdc8fb6573c06fe07c832
MD5 e3b9f91ee959fcad1e112e65c0273081
BLAKE2b-256 ec4a438773aef4270e703ee6855c2d70d90d092e2243adceaf8375e7abace93b

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: hfd-0.1.2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for hfd-0.1.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 9ad81e3fa5bd3d9c9d420e0a540db73f0a994468bfb307e00b097c8b68298d5d
MD5 5d2b8a3181cfab68b281b4f8bb55c7c3
BLAKE2b-256 cfe1281071baf6010fb8a9a6aeeec145337412e5bdb0672f9685598b5b1c1d0c

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for hfd-0.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b97b4dd6ee90ef780ac567449425c0395919db581d43a47d081fe75d04dbc160
MD5 249d148f72888d4e63344b4d904f82f2
BLAKE2b-256 f3a8890a7efd930cad828adf74356afc6bb7e053f3cb9c08ba970a0478cffbd2

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

  • Download URL: hfd-0.1.2-cp39-cp39-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.9, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for hfd-0.1.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 dc957424f44a074b9bc5ecd334e5aaf2bc22c798fa5bb80d228cbc835590c931
MD5 93ce01b521f6d3e3edf8226f08d5424a
BLAKE2b-256 67c983b0be2416fd2bd7c832ecd9cbd2b129ac125e442b46bf09a5b9b5e9fcdc

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: hfd-0.1.2-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for hfd-0.1.2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 5779c5e1ab82c9b4224d9650c7637fabc176a966d4ca0db31e1d9d0588ccf802
MD5 4a77f5a4b3aed00d49642f5a69d1c305
BLAKE2b-256 b0801622ba0bb7720ba6e7687e8804bb1758c3f62c7d6f4e4b9841c1ada45e6f

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for hfd-0.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e060f8c3569599d1fbcdbcd10e6f4e1ac04da4b036ce17e7b0abc397519fdbd9
MD5 d6af46d35a4c17a4382f152bfeef9f37
BLAKE2b-256 ada9165a37bda70685d02067b9d239d105ee3f9d5ad2685c7f6289c1ef91a3b2

See more details on using hashes here.

File details

Details for the file hfd-0.1.2-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

  • Download URL: hfd-0.1.2-cp38-cp38-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.8, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for hfd-0.1.2-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 aab06c04ca65b44bbea5971105b77fd564d60df4892a7c2577a23d152eb9c3d0
MD5 4a9e8d4c590358133ad68169d33b9dbc
BLAKE2b-256 06dae945f927794fa3bdaefcc6cdbd27f61cab33d06c5bc4bbfd0cac4ac0ac4d

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