README.md

---
library_name: transformers
tags:
- merge
- llama-3.1
- roleplay
- function calling
base_model:
- unsloth/Meta-Llama-3.1-8B-Instruct
- REILX/Llama-3-8B-Instruct-750Mb-lora
datasets:
- databricks/databricks-dolly-15k
- microsoft/orca-math-word-problems-200k
- LooksJuicy/ruozhiba
base_model_relation: merge
model-index:
- name: KRONOS-8B-V1-P3
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: wis-k/instruction-following-eval
      split: train
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 71.37
      name: averaged accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: SaylorTwift/bbh
      split: test
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 30.27
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: lighteval/MATH-Hard
      split: test
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 18.35
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P3
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      split: train
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 1.34
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P3
      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: 5.96
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P3
      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: 26.72
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P3
      name: Open LLM Leaderboard
---
# KRONOS V1 P3

This is a merge of Meta Llama 3.1 Instruct and REILIX's "750MB" LORA, created using [llm-tools](https://github.com/oobabooga/llm-tools).

The primary purpose of this model is to be merged into other models in the same family using the TIES merge method.

Creating quants for this is entirely unnecessary.

## Merge Details

### Configuration

The following Bash command was used to produce this model:

```bash
python /llm-tools/merge-lora.py -m unsloth/Meta-Llama-3.1-8B-Instruct -l REILX/Llama-3-8B-Instruct-750Mb-lora
```

# [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/T145__KRONOS-8B-V1-P3-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=T145%2FKRONOS-8B-V1-P3&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!

|      Metric       |Value (%)|
|-------------------|--------:|
|**Average**        |    25.67|
|IFEval (0-Shot)    |    71.37|
|BBH (3-Shot)       |    30.27|
|MATH Lvl 5 (4-Shot)|    18.35|
|GPQA (0-shot)      |     1.34|
|MuSR (0-shot)      |     5.96|
|MMLU-PRO (5-shot)  |    26.72|