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Mistral-7B-Merge-14-v0

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license: cc-by-nc-4.0
language:
  - en

Update 2023-12-19

In light of dataset contamination issue among the merged models raised by the community in recent days, in particular berkeley-nest/Starling-LM-7B-alpha, and Q-bert/MetaMath-Cybertron-Starling, we decided to remake another model without the models mentioned. Additionally, their CC-by-NC-4.0 license is restrictive and thus are not suitable for an open model.

Model Description

This is an experiment to test merging 14 models using DARE TIES 🦙

The result is a base model that performs quite well but requires some further instruction fine-tuning.

The 14 models are as follows:

  1. mistralai/Mistral-7B-Instruct-v0.2
  2. ehartford/dolphin-2.2.1-mistral-7b
  3. SciPhi/SciPhi-Mistral-7B-32k
  4. ehartford/samantha-1.2-mistral-7b
  5. Arc53/docsgpt-7b-mistral
  6. berkeley-nest/Starling-LM-7B-alpha
  7. Q-bert/MetaMath-Cybertron-Starling
  8. Open-Orca/Mistral-7B-OpenOrca
  9. v1olet/v1olet_marcoroni-go-bruins-merge-7B
  10. beowolx/MistralHermes-CodePro-7B-v1
  11. TIGER-Lab/MAmmoTH-7B-Mistral
  12. teknium/OpenHermes-2.5-Mistral-7B
  13. Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
  14. mlabonne/NeuralHermes-2.5-Mistral-7B

The yaml config file for this model is here:

models:
  - model: mistralai/Mistral-7B-Instruct-v0.2
    # no parameters necessary for base model
  - model: ehartford/dolphin-2.2.1-mistral-7b
    parameters:
      weight: 0.08
      density: 0.4
  - model: SciPhi/SciPhi-Mistral-7B-32k
    parameters:
      weight: 0.08
      density: 0.4
  - model: ehartford/samantha-1.2-mistral-7b
    parameters:
      weight: 0.08
      density: 0.4
  - model: Arc53/docsgpt-7b-mistral
    parameters:
      weight: 0.08
      density: 0.4
  - model: berkeley-nest/Starling-LM-7B-alpha
    parameters:
      weight: 0.08
      density: 0.4
  - model: Q-bert/MetaMath-Cybertron-Starling
    parameters:
      weight: 0.08
      density: 0.4
  - model: Open-Orca/Mistral-7B-OpenOrca
    parameters:
      weight: 0.08
      density: 0.4
  - model: v1olet/v1olet_marcoroni-go-bruins-merge-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: beowolx/MistralHermes-CodePro-7B-v1
    parameters:
      weight: 0.08
      density: 0.4
  - model: TIGER-Lab/MAmmoTH-7B-Mistral
    parameters:
      weight: 0.08
      density: 0.4
  - model: teknium/OpenHermes-2.5-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
    parameters:
      weight: 0.08
      density: 0.4
  - model: mlabonne/NeuralHermes-2.5-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: mistralai/Mistral-7B-Instruct-v0.2
    parameters:
      weight: 0.08
      density: 0.5
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16