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Mistral-7B-Merge-14-v0.3

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metadata
license: apache-2.0
language:
  - en
tags:
  - merge

Model Description

This is an update to EmbeddedLLM/Mistral-7B-Merge-14-v0.2 that removes potentially TruthfulQA-contaminated models and non-commercially licensed models:

  1. berkeley-nest/Starling-LM-7B-alpha
  2. Q-bert/MetaMath-Cybertron-Starling
  3. v1olet/v1olet_marcoroni-go-bruins-merge-7B

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

The result is a base model that performs quite well but may need some further chat 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. HuggingFaceH4/zephyr-7b-beta
  7. meta-math/MetaMath-Mistral-7B
  8. Open-Orca/Mistral-7B-OpenOrca
  9. openchat/openchat-3.5-1210
  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-v0.1
    # 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: HuggingFaceH4/zephyr-7b-beta
    parameters:
      weight: 0.08
      density: 0.4
  - model: meta-math/MetaMath-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: Open-Orca/Mistral-7B-OpenOrca
    parameters:
      weight: 0.08
      density: 0.4
  - model: openchat/openchat-3.5-1210
    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