In this blog post, we’ll walk you through the exciting world of merging language models using MergeKit. Think of it like creating a delicious smoothie where we blend flavors (models) to create a delightful new concoction (the merged model). Our focus today will be on the Nemomix series, specifically the Nemomix-v0.4-12B.

Understanding the Merge Process

Before we dive into the steps, let’s understand how merging models works. It’s akin to taking the best attributes of different fruits—say strawberries for sweetness, bananas for creaminess, and blueberries for antioxidants—and blending them together to make a super smoothie! Here’s a step-by-step breakdown:

• Base Model: This is our primary ingredient, just like the yogurt or juice in a smoothie. For Nemomix, it’s the mistralaiMistral-Nemo-Base-2407.
• Merged Models: These are additional flavors added to enhance the mix. The models used are:
  • intervitens_mini-magnum-12b-v1.1
  • mistralaiMistral-Nemo-Instruct-2407
  • invisietch_Atlantis-v0.1-12B
  • NeverSleepHistorical_lumi-nemo-e2.0
• Merge Method: The della_linear merge method is like the blender settings that control how thoroughly things get mixed. It’s essential for achieving the right consistency!

Setting Up Your Environment

Follow these instructions to prepare your setup:

• Ensure you have MergeKit installed from GitHub.
• Gather all the model files mentioned above in a designated folder, for example, F:\mergekit\.
• Create a YAML configuration file as detailed below:

models:
  - model: F:\mergekit\invisietch_Atlantis-v0.1-12B
    parameters:
      weight: 0.16
      density: 0.4
  - model: F:\mergekit\mistralaiMistral-Nemo-Instruct-2407
    parameters:
      weight: 0.23
      density: 0.5
  - model: F:\mergekit\NeverSleepHistorical_lumi-nemo-e2.0
    parameters:
      weight: 0.27
      density: 0.6
  - model: F:\mergekit\intervitens_mini-magnum-12b-v1.1
    parameters:
      weight: 0.34
      density: 0.8
merge_method: della_linear
base_model: F:\mergekit\mistralaiMistral-Nemo-Base-2407
parameters:
  epsilon: 0.05
  lambda: 1
  int8_mask: true
dtype: bfloat16

Running the Merge

Once your environment is set, you can run the merge using the following command:

mergekit merge --config 

Replace <YOUR_YAML_FILE_PATH> with the actual path to your YAML configuration. Sit back and watch as your models get blended into a new masterpiece!

Tuning the Model

After merging, it’s time to test and tune your new model. The recommended settings for the InstructMistral model, including temperature and parameters, are:

• Lower Temperature: 0.35 (or higher, between 1.0-1.2 with Min P at 0.01-0.1).
• Base Dry: 0.8/1.75/2/0.

Troubleshooting

If you encounter issues during the merging process or find the model isn’t performing as expected, here are some troubleshooting tips:

• Ensure all paths in your YAML file are correct and that the model files are accessible.
• Experiment with different temperatures and dry settings. Sometimes, small adjustments can create substantial differences.
• Check the console output for any error messages, and adjust settings based on the feedback.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

Congratulations! You’ve successfully merged language models using MergeKit. Similar to crafting that perfect smoothie, practice makes perfect. Keep exploring different combinations and configurations to find what suits your needs best.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.