# Installation and Configuration Before you start, you will need to setup your environment, install the appropriate packages, and configure 🤗 Accelerate. 🤗 Accelerate is tested on **Python 3.8+**. ## Installing 🤗 Accelerate 🤗 Accelerate is available on pypi and conda, as well as on GitHub. Details to install from each are below: ### pip To install 🤗 Accelerate from pypi, perform: ```bash pip install accelerate ``` ### conda 🤗 Accelerate can also be installed with conda with: ```bash conda install -c conda-forge accelerate ``` ### Source New features are added every day that haven't been released yet. To try them out yourself, install from the GitHub repository: ```bash pip install git+https://github.com/huggingface/accelerate ``` If you're working on contributing to the library or wish to play with the source code and see live results as you run the code, an editable version can be installed from a locally-cloned version of the repository: ```bash git clone https://github.com/huggingface/accelerate cd accelerate pip install -e . ``` ## Configuring 🤗 Accelerate After installing, you need to configure 🤗 Accelerate for how the current system is setup for training. To do so run the following and answer the questions prompted to you: ```bash accelerate config ``` To write a barebones configuration that doesn't include options such as DeepSpeed configuration or running on TPUs, you can quickly run: ```bash python -c "from accelerate.utils import write_basic_config; write_basic_config(mixed_precision='fp16')" ``` 🤗 Accelerate will automatically utilize the maximum number of GPUs available and set the mixed precision mode. To check that your configuration looks fine, run: ```bash accelerate env ``` An example output is shown below, which describes two GPUs on a single machine with no mixed precision being used: ```bash - `Accelerate` version: 0.11.0.dev0 - Platform: Linux-5.10.0-15-cloud-amd64-x86_64-with-debian-11.3 - Python version: 3.7.12 - Numpy version: 1.19.5 - PyTorch version (GPU?): 1.12.0+cu102 (True) - `Accelerate` default config: - compute_environment: LOCAL_MACHINE - distributed_type: MULTI_GPU - mixed_precision: no - use_cpu: False - num_processes: 2 - machine_rank: 0 - num_machines: 1 - main_process_ip: None - main_process_port: None - main_training_function: main - deepspeed_config: {} - fsdp_config: {} ```