# Apertus

Apertus is a family of opensource models trained by Swiss-ai.

This guide shows how to fine-tune it with Axolotl with multi-turn conversations and proper masking.

## Getting started

1. Install Axolotl following the installation guide. You need to install from main as Apertus is only on nightly or use our latest Docker images.

   Here is an example of how to install from main for pip:

    # Ensure you have Pytorch installed (Pytorch 2.6.0 min)
    git clone https://github.com/axolotl-ai-cloud/axolotl.git
    cd axolotl

    pip3 install packaging==26.0 setuptools==75.8.0 wheel ninja
    pip3 install --no-build-isolation -e '.[flash-attn]'

    # Install CCE https://docs.axolotl.ai/docs/custom_integrations.html#cut-cross-entropy
    python scripts/cutcrossentropy_install.py | sh

2. (Optional, highly recommended) Install XIELU CUDA

    ## Recommended for reduced VRAM and faster speeds

    # Point to CUDA toolkit directory
    # For those using our Docker image, use the below path.
    export CUDA_HOME=/usr/local/cuda

    pip3 install git+https://github.com/nickjbrowning/XIELU@59d6031 --no-build-isolation --no-deps

For any installation errors, see XIELU Installation Issues

3. Run the finetuning example:

    axolotl train examples/apertus/apertus-8b-qlora.yaml

This config uses about 8.7 GiB VRAM.

Let us know how it goes. Happy finetuning! 🚀

### Tips

- For inference, the official Apertus team recommends `top_p=0.9` and `temperature=0.8`.
- You can instead use full paremter fine-tuning by removing the `adapter: qlora` and `load_in_4bit: true` from the config.
- Read more on how to load your own dataset at docs.
- The dataset format follows the OpenAI Messages format as seen here.

### XIELU Installation Issues

#### `ModuleNotFoundError: No module named 'torch'`

Please check these one by one: - Running in correct environment - Env has PyTorch installed - CUDA toolkit is at `CUDA_HOME`

If those didn’t help, please try the below solutions:

1. Pass env for CMAKE and try install again:

       Python_EXECUTABLE=$(which python) pip3 install git+https://github.com/nickjbrowning/XIELU@59d6031 --no-build-isolation --no-deps

2. Git clone the repo and manually hardcode python path:

       git clone https://github.com/nickjbrowning/XIELU
       cd xielu
       git checkout 59d6031

       cd xielu
       nano CMakeLists.txt  # or vi depending on your preference

       execute_process(
       -    COMMAND ${Python_EXECUTABLE} -c "import torch.utils; print(torch.utils.cmake_prefix_path)"
       +    COMMAND /root/miniconda3/envs/py3.11/bin/python -c "import torch.utils; print(torch.utils.cmake_prefix_path)"
           RESULT_VARIABLE TORCH_CMAKE_PATH_RESULT
           OUTPUT_VARIABLE TORCH_CMAKE_PATH_OUTPUT
           ERROR_VARIABLE TORCH_CMAKE_PATH_ERROR
       )

       pip3 install . --no-build-isolation --no-deps

## Optimization Guides

- Multi-GPU Training
- Multi-Node Training
- LoRA Optimizations

## Related Resources

- Apertus Tech Report
- Axolotl Docs
- Axolotl Website
- Axolotl GitHub
- Axolotl Discord