Welcome to our exploration of the Nemomix model—a remarkable blend of artificial intelligence that combines the brilliance of fine-tuned Instruct models with vivid prose. For enthusiasts and developers alike, this guide will help you navigate the process of using and experimenting with the best version of Nemomix to date.

Understanding the Nemomix Model

The Nemomix model is like a well-crafted stew; it combines various ingredients—the best base flavors (the Instruct Nemo) with spices (fine-tuned models) that enhance the final dish (the output). But how do we achieve this perfect mélange? Let’s dive into the specifics!

Description

The main goal of the Nemomix model is to merge the smartness of the base Instruct Nemo with the enhanced prose quality from different roleplaying fine-tunes. As the current iteration stands, it appears to surpass all previous versions. Special thanks go to the brilliant minds at Intervitens, Mistralai, Invisietch, and NeverSleep for their astounding contributions to the model.

Getting Started with InstructMistral

To interact with this model, you must utilize the specified format:

<s>[INST] {system} [/INST]{assistant}</s>
[INST] {user} [/INST]

Settings: Finding Your Optimal Temperature

• Lower Temperature: 0.35 (recommended)
• Higher Temperatures: 1.0-1.2 (effective with higher Min P settings)
• Base DRY: Recommended settings are 0.8/1.75/2/0

Experimenting with these settings can help you tailor the output to your specific needs!

Presets for Enhanced Performance

Utilize my custom context/instruct/parameters presets for the model from this link!

Accessing the Models

The current version of Nemomix can be accessed through the following links:

• Nemomix v4.0 GGUF
• Nemomix v1.0
• Nemomix v2.0
• Nemomix v3.0

Merge Details

The heart of our model is its merge process, performed using a method designed to enhance its capabilities:

Merge Method: Della_linear

The models included in this blend are:

• Invisietch Atlantis v0.1-12B
• Mistralai Mistral-Nemo-Instruct-2407
• Intervitens Mini-Magnum-12B v1.1
• NeverSleep Historical Lumi-Nemo e2.0

Configuration

Here’s the YAML configuration that powers this model:

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

Troubleshooting Tips

Here are some common issues you might encounter while working with the Nemomix model, along with potential solutions:

• Model Errors: Ensure that all paths to models are correct and accessible.
• Performance Issues: Adjust the temperature settings as mentioned earlier.
• Output Quality: Experiment with different model weights and densities for optimal results.

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

Conclusion

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.

Enjoy experimenting with the Nemomix model, and happy coding!