NemoReRemix-12B / README.md
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metadata
library_name: transformers
tags:
  - mergekit
  - merge
base_model: []
model-index:
  - name: NemoReRemix-12B
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 33.43
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MarinaraSpaghetti/NemoReRemix-12B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 36.12
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MarinaraSpaghetti/NemoReRemix-12B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 6.42
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MarinaraSpaghetti/NemoReRemix-12B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 9.06
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MarinaraSpaghetti/NemoReRemix-12B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 15.67
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MarinaraSpaghetti/NemoReRemix-12B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 28.87
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MarinaraSpaghetti/NemoReRemix-12B
          name: Open LLM Leaderboard

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Information

Details

Improved NemoRemix for storytelling and roleplay. Plus, this one can also be used as a general assistant model. The prose is pretty much the same, but it was made smarter, thanks to the addition of the amazing Migtissera's Tess model. I yeeted out Gryphe's Pantheon-RP, though, because it was trained with asterisks in mind, unlike the rest of the models in the merge, which caused it to mess the formatting from time to time; this one doesn't do that anymore. Hooray! All credits and thanks go to the amazing Migtissera, MistralAI, Anthracite, Sao10K and ShuttleAI for their amazing models.

Instruct

ChatML but Mistral Instruct should work too (theoretically). Important: remember to add <|im_end|> to custom stopping strings, otherwise it will appear in the output.

<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{message}<|im_end|>
<|im_start|>assistant
{response}<|im_end|>

Parameters

I recommend running Temperature 1.0-1.2 with 0.1 Top A or 0.01-0.1 Min P, and with 0.8/1.75/2/0 DRY. Also works with lower Temperatures below 1.0. Nothing more needed.

Settings

You can use my exact settings from here (use the ones from the ChatML Base/Customized folder): https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main.

GGUF

https://huggingface.co/MarinaraSpaghetti/NemoReRemix-GGUF

NemoReRemix-12B

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the della_linear merge method using E:\mergekit\mistralaiMistral-Nemo-Base-2407 as a base.

Models Merged

The following models were included in the merge:

  • E:\mergekit\Sao10K_MN-12B-Lyra-v1
  • E:\mergekit\mistralaiMistral-Nemo-Instruct-2407
  • E:\mergekit\migtissera_Tess-3-Mistral-Nemo
  • E:\mergekit\shuttleai_shuttle-2.5-mini
  • E:\mergekit\anthracite-org_magnum-12b-v2

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: E:\mergekit\mistralaiMistral-Nemo-Instruct-2407
    parameters:
      weight: 0.1
      density: 0.4
  - model: E:\mergekit\Sao10K_MN-12B-Lyra-v1
    parameters:
      weight: 0.12
      density: 0.5
  - model: E:\mergekit\shuttleai_shuttle-2.5-mini
    parameters:
      weight: 0.2
      density: 0.6
  - model: E:\mergekit\migtissera_Tess-3-Mistral-Nemo
    parameters:
      weight: 0.25
      density: 0.7
  - model: E:\mergekit\anthracite-org_magnum-12b-v2
    parameters:
      weight: 0.33
      density: 0.8
merge_method: della_linear
base_model: E:\mergekit\mistralaiMistral-Nemo-Base-2407
parameters:
  epsilon: 0.05
  lambda: 1
dtype: bfloat16

Ko-fi

Enjoying what I do? Consider donating here, thank you!

https://ko-fi.com/spicy_marinara

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 21.59
IFEval (0-Shot) 33.43
BBH (3-Shot) 36.12
MATH Lvl 5 (4-Shot) 6.42
GPQA (0-shot) 9.06
MuSR (0-shot) 15.67
MMLU-PRO (5-shot) 28.87