Skip to main content

No project description provided

Project description

🤗 AutoTrain Advanced

AutoTrain Advanced: faster and easier training and deployments of state-of-the-art machine learning models. AutoTrain Advanced is a no-code solution that allows you to train machine learning models in just a few clicks. Please note that you must upload data in correct format for project to be created. For help regarding proper data format and pricing, check out the documentation.

NOTE: AutoTrain is free! You only pay for the resources you use in case you decide to run AutoTrain on Hugging Face Spaces. When running locally, you only pay for the resources you use on your own infrastructure.

Run on Colab or Hugging Face Spaces

  • Run AutoTrain on Colab: Open In Colab

  • Deploy AutoTrain on Hugging Face Spaces: Deploy on Spaces

  • Run AutoTrain UI on Colab via ngrok: Open In Colab

Local Installation

You can Install AutoTrain-Advanced python package via PIP. Please note you will need python >= 3.10 for AutoTrain Advanced to work properly.

pip install autotrain-advanced

Please make sure that you have git lfs installed. Check out the instructions here: https://github.com/git-lfs/git-lfs/wiki/Installation

You also need to install torch, torchaudio and torchvision.

The best way to run autotrain is in a conda environment. You can create a new conda environment with the following command:

conda create -n autotrain python=3.10
conda activate autotrain
pip install autotrain-advanced
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
conda install -c "nvidia/label/cuda-12.1.0" cuda-nvcc

Once done, you can start the application using:

autotrain app --port 8080 --host 127.0.0.1

If you are not fond of UI, you can use AutoTrain Configs to train using command line or simply AutoTrain CLI.

To use config file for training, you can use the following command:

autotrain --config <path_to_config_file>

You can find sample config files in the configs directory of this repository.

Colabs

Task Colab Link
LLM Fine Tuning Open In Colab
DreamBooth Training Open In Colab

Documentation

Documentation is available at https://hf.co/docs/autotrain/

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

autotrain-advanced-0.7.105.tar.gz (230.2 kB view details)

Uploaded Source

Built Distribution

autotrain_advanced-0.7.105-py3-none-any.whl (297.2 kB view details)

Uploaded Python 3

File details

Details for the file autotrain-advanced-0.7.105.tar.gz.

File metadata

  • Download URL: autotrain-advanced-0.7.105.tar.gz
  • Upload date:
  • Size: 230.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.14

File hashes

Hashes for autotrain-advanced-0.7.105.tar.gz
Algorithm Hash digest
SHA256 3ee8d2c755b4f4b1ad6a9bddd2a54cbdc46851887d1f285d7db2d36ecc74981b
MD5 3d289b9bdefa94c017c553d8e1622d45
BLAKE2b-256 cb45154a405ce6701e1cfa08ff4698e3de5fecd66513b72e2d278ffec8a18bcd

See more details on using hashes here.

File details

Details for the file autotrain_advanced-0.7.105-py3-none-any.whl.

File metadata

File hashes

Hashes for autotrain_advanced-0.7.105-py3-none-any.whl
Algorithm Hash digest
SHA256 7caf7210110aa1232095377f928355064be07b05936a95b4f8895243b66b3c7d
MD5 02a5859e0cebe3a817b4d5bc4ed99eeb
BLAKE2b-256 9f8a91597d46b7ac9780c2395027c10709ab52d4e2fb94a17635f1b319174b69

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