---
language:
- en
license: other
library_name: transformers
tags:
- mergekit
- merge
base_model: []
model-index:
- name: Bepis_9B
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 62.54
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Bepis_9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 80.12
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Bepis_9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 62.84
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Bepis_9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 53.3
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Bepis_9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 76.48
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Bepis_9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 39.12
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Bepis_9B
      name: Open LLM Leaderboard
---
# Bepis

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/626dfb8786671a29c715f8a9/H0_oJhrIEGBIwogB77p5w.jpeg)

A new 9B model from jeiku. This one is smart, proficient at markdown, knows when to stop talking, and is quite soulful. The merge was an equal 3 way split between https://huggingface.co/ChaoticNeutrals/Prodigy_7B, https://huggingface.co/Test157t/Prima-LelantaclesV6-7b, and https://huggingface.co/cgato/Thespis-CurtainCall-7b-v0.2.1

If there's any 7B to 11B merge or finetune you'd like to see, feel free to leave a message.

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
      - model: primathespis
        layer_range: [0, 20]
  - sources:
      - model: prodigalthespis
        layer_range: [12, 32]
merge_method: passthrough
dtype: float16

```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ChaoticNeutrals__Bepis_9B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |62.40|
|AI2 Reasoning Challenge (25-Shot)|62.54|
|HellaSwag (10-Shot)              |80.12|
|MMLU (5-Shot)                    |62.84|
|TruthfulQA (0-shot)              |53.30|
|Winogrande (5-shot)              |76.48|
|GSM8k (5-shot)                   |39.12|