axolotl/examples/apertus

Finetune Swiss-AI's Apertus with Axolotl

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

uv pip 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

uv pip 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) uv pip 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
   )
   

   uv pip 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