IceCocoaRP-7b / README.md
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Adding Evaluation Results (#1)
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metadata
license: cc-by-nc-4.0
library_name: transformers
tags:
  - mergekit
  - merge
  - alpaca
  - mistral
  - not-for-all-audiences
  - nsfw
base_model:
  - icefog72/IceCoffeeRP-7b
  - icefog72/IceBlendedLatteRP-7b
  - eldogbbhed/NeuralBeagleJaskier
model-index:
  - name: IceCocoaRP-7b
    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: 49.62
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b
          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: 29.64
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b
          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: 5.44
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b
          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: 6.04
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b
          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: 11.17
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b
          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: 23.32
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=icefog72/IceCocoaRP-7b
          name: Open LLM Leaderboard

IceCocoaRP-7b

image/png

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

SillyTavern Discord thread

Rules-lorebook and settings I'm using you can find here

ko-fi

Merge Details

The best one so far for me.

thx mradermacher for

Merge Method

This model was merged using the TIES merge method using NeuralBeagleJaskier as a base.

Models Merged

The following models were included in the merge:

  • NeuralBeagleJaskier
  • IceBlendedCoffeeRP-7b (slerp bfloat16)
    • IceCoffeeRP-7b
    • IceBlendedLatteRP-7b base

Configuration

The following YAML configuration was used to produce this model:

I recommend using the huggingface-hub Python library:

pip3 install huggingface-hub

To download the main branch to a folder called IceCocoaRP-7b:

mkdir IceCocoaRP-7b
huggingface-cli download icefog72/IceCocoaRP-7b --local-dir IceCocoaRP-7b --local-dir-use-symlinks False
More advanced huggingface-cli download usage

If you remove the --local-dir-use-symlinks False parameter, the files will instead be stored in the central Hugging Face cache directory (default location on Linux is: ~/.cache/huggingface), and symlinks will be added to the specified --local-dir, pointing to their real location in the cache. This allows for interrupted downloads to be resumed, and allows you to quickly clone the repo to multiple places on disk without triggering a download again. The downside, and the reason why I don't list that as the default option, is that the files are then hidden away in a cache folder and it's harder to know where your disk space is being used, and to clear it up if/when you want to remove a download model.

The cache location can be changed with the HF_HOME environment variable, and/or the --cache-dir parameter to huggingface-cli.

For more documentation on downloading with huggingface-cli, please see: HF -> Hub Python Library -> Download files -> Download from the CLI.

To accelerate downloads on fast connections (1Gbit/s or higher), install hf_transfer:

pip3 install hf_transfer

And set environment variable HF_HUB_ENABLE_HF_TRANSFER to 1:

mkdir FOLDERNAME
HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download MODEL --local-dir FOLDERNAME --local-dir-use-symlinks False

Windows Command Line users: You can set the environment variable by running set HF_HUB_ENABLE_HF_TRANSFER=1 before the download command.

models:
  - model: NeuralBeagleJaskier
    parameters:
      density: 0.9
      weight: 0.5
  - model: IceBlendedCoffeeRP-7b
    parameters:
      density: 0.5
      weight: 0.3
merge_method: ties
base_model: NeuralBeagleJaskier
parameters:
  normalize: true
  int8_mask: true
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 20.87
IFEval (0-Shot) 49.62
BBH (3-Shot) 29.64
MATH Lvl 5 (4-Shot) 5.44
GPQA (0-shot) 6.04
MuSR (0-shot) 11.17
MMLU-PRO (5-shot) 23.32