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-0.8.10.tar.gz (251.3 kB view details)

Uploaded Source

Built Distribution

autotrain_advanced-0.8.10-py3-none-any.whl (338.4 kB view details)

Uploaded Python 3

File details

Details for the file autotrain-advanced-0.8.10.tar.gz.

File metadata

  • Download URL: autotrain-advanced-0.8.10.tar.gz
  • Upload date:
  • Size: 251.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.14

File hashes

Hashes for autotrain-advanced-0.8.10.tar.gz
Algorithm Hash digest
SHA256 1a0e36660f61350c451e2dc29e50e6411b75f70efecfc36c768670cae8790c8b
MD5 b87fef118ab0d3638ceda5f85201f193
BLAKE2b-256 f7940fa6efed390532fc183d3a0ccacade54d892102840fa867e7803ed1dbaf1

See more details on using hashes here.

File details

Details for the file autotrain_advanced-0.8.10-py3-none-any.whl.

File metadata

File hashes

Hashes for autotrain_advanced-0.8.10-py3-none-any.whl
Algorithm Hash digest
SHA256 b6e75121fb5f3e3da5d2c79d9eb510a14942b8fb0e2f65ceb2001138ea1c906b
MD5 c78d150fe8e78309a23e5965ec9c0cc8
BLAKE2b-256 d64c046a6b55b15ada91125158d71be2142c4e7ba229097b288e37191cf97e31

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