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.

Deploy on Spaces Open In Colab

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-0.7.85.tar.gz (219.0 kB view details)

Uploaded Source

Built Distribution

autotrain_advanced-0.7.85-py3-none-any.whl (281.3 kB view details)

Uploaded Python 3

File details

Details for the file autotrain-advanced-0.7.85.tar.gz.

File metadata

  • Download URL: autotrain-advanced-0.7.85.tar.gz
  • Upload date:
  • Size: 219.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.14

File hashes

Hashes for autotrain-advanced-0.7.85.tar.gz
Algorithm Hash digest
SHA256 eb8c3ab2eed70323aac2ae1e416a5d16e9292a8e7d3f7aa68bc1dcd7c1917f11
MD5 2f765e455c64beb4d8799c0279597d48
BLAKE2b-256 7180d7edd34e93a1360f3c8eba8d40df4cec8d106e644b9ad70b2f597dfd25b7

See more details on using hashes here.

File details

Details for the file autotrain_advanced-0.7.85-py3-none-any.whl.

File metadata

File hashes

Hashes for autotrain_advanced-0.7.85-py3-none-any.whl
Algorithm Hash digest
SHA256 fd625ad7e1c69de84463c152d0e2e894ce09eeb1ace6beae133420c685ecf009
MD5 1a1706b37b46c769c557cd7b695478e7
BLAKE2b-256 f6950560d3cd43292bd34ad7d52a34c4090663a5bdaecaab8016ef0bf92cac43

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