NeuralPipe-7B-slerp

This is a merge of pre-trained language models created using LazyMergekit, combining the capabilities of OpenPipe's optimized Mistral and NeuralHermes through an efficient SLERP fusion.

About Me

I'm David Soeiro-Vuong, a third-year Computer Science student working as an apprentice at TW3 Partners, a company specialized in Generative AI. Passionate about artificial intelligence and language models optimization, I focus on creating efficient model merges that balance performance and capabilities.

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Merge Details

Merge Method

This model uses SLERP (Spherical Linear Interpolation) with carefully tuned parameters:

• Optimized attention layer fusion patterns
• Balanced MLP layer transitions
• bfloat16 format for efficient memory usage
• Full layer utilization for maximum capability retention

Models Merged

• OpenPipe/mistral-ft-optimized-1218
• mlabonne/NeuralHermes-2.5-Mistral-7B

Configuration

slices:
  - sources:
      - model: OpenPipe/mistral-ft-optimized-1218
        layer_range: [0, 32]
      - model: mlabonne/NeuralHermes-2.5-Mistral-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: OpenPipe/mistral-ft-optimized-1218
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16