README.md

---
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
---

<h2>L3-Dark-Planet-8B</h2>

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 )

Additional Quants:

[ https://huggingface.co/RichardErkhov/DavidAU_-_L3-Dark-Planet-8B-gguf ]

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

Imatrix GGUFS:

[ https://huggingface.co/mradermacher/L3-Dark-Planet-8B-i1-GGUF ]

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


---

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_DavidAU__L3-Dark-Planet-8B)

|      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|