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-0.7.99.tar.gz (230.0 kB view details)

Uploaded Source

Built Distribution

autotrain_advanced-0.7.99-py3-none-any.whl (297.2 kB view details)

Uploaded Python 3

File details

Details for the file autotrain-advanced-0.7.99.tar.gz.

File metadata

  • Download URL: autotrain-advanced-0.7.99.tar.gz
  • Upload date:
  • Size: 230.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.14

File hashes

Hashes for autotrain-advanced-0.7.99.tar.gz
Algorithm Hash digest
SHA256 552ee8a61cc5906ba5103ffe86e840114a93c9506316544704ea4ab63885ff1c
MD5 b2b55104434e0bc93f7430cf3f32170d
BLAKE2b-256 d84ca57fe5dc80fe1c04db23903261d5d0320d8477c1efc1461f1d2ce5ccc1e4

See more details on using hashes here.

File details

Details for the file autotrain_advanced-0.7.99-py3-none-any.whl.

File metadata

File hashes

Hashes for autotrain_advanced-0.7.99-py3-none-any.whl
Algorithm Hash digest
SHA256 b380fbc68ef4c4ff03f19af2a4f56d3680ee308383366545c42b86591fefbb00
MD5 21026f0c22de7903afeb78f05d163874
BLAKE2b-256 1613f21cc43d9a0a3a8f7a932c6819182f176e6fc4902171da1a38ad9747fa43

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