metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model: []
model-index:
  - name: L3-Dark-Planet-8B
    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: 41.34
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Dark-Planet-8B
          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: 29.79
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Dark-Planet-8B
          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: 7.48
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Dark-Planet-8B
          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: 6.71
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Dark-Planet-8B
          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: 6.33
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Dark-Planet-8B
          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: 30.41
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Dark-Planet-8B
          name: Open LLM Leaderboard

L3-Dark-Planet-8B

This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats. The source code can also be used directly.

For full information about this model, including:

Details about this model and its use case(s).
Context limits
Special usage notes / settings.
Any model(s) used to create this model.
Template(s) used to access/use this model.
Example generation(s)
GGUF quants of this model

Please go to:

[ https://huggingface.co/DavidAU/L3-Dark-Planet-8B-GGUF ]

For "Dark Planet Horror City 8b" :

[ https://huggingface.co/DavidAU/L3-Dark-Planet-Horror-City-8B-NEO-Imatrix-GGUF ]

(To create GGUFs for Dark Planet Horror City 8B use the ".dat" file for Imatrix in this repo )

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	20.34
IFEval (0-Shot)	41.34
BBH (3-Shot)	29.79
MATH Lvl 5 (4-Shot)	7.48
GPQA (0-shot)	6.71
MuSR (0-shot)	6.33
MMLU-PRO (5-shot)	30.41