README.md

---
license: other
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Test157t/Prima-Pastacles-7b
- Test157t/Pasta-Sea-7b-128k
model-index:
- name: Prima-Pastacles-7b-128k
  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: 68.09
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Prima-Pastacles-7b-128k
      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: 86.57
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Prima-Pastacles-7b-128k
      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: 64.58
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Prima-Pastacles-7b-128k
      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: 62.51
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Prima-Pastacles-7b-128k
      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: 81.06
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Prima-Pastacles-7b-128k
      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: 59.36
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Prima-Pastacles-7b-128k
      name: Open LLM Leaderboard
---
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/642265bc01c62c1e4102dc36/Gs09MsXrzyJdDx7IrnkDa.jpeg)

### Models Merged

The following models were included in the merge:
* [Test157t/Prima-Pastacles-7b](https://huggingface.co/Test157t/Prima-Pastacles-7b)
* [Test157t/Pasta-Sea-7b-128k](https://huggingface.co/Test157t/Pasta-Sea-7b-128k)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
      - model: Test157t/Prima-Pastacles-7b
        layer_range: [0, 32]
      - model: Test157t/Pasta-Sea-7b-128k
        layer_range: [0, 32]
merge_method: slerp
base_model: Test157t/Prima-Pastacles-7b
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

```
# [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_Test157t__Prima-Pastacles-7b-128k)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |70.36|
|AI2 Reasoning Challenge (25-Shot)|68.09|
|HellaSwag (10-Shot)              |86.57|
|MMLU (5-Shot)                    |64.58|
|TruthfulQA (0-shot)              |62.51|
|Winogrande (5-shot)              |81.06|
|GSM8k (5-shot)                   |59.36|