README.md

---
library_name: transformers
tags:
- merge
- llama-3.1
- roleplay
- function calling
base_model:
- unsloth/Meta-Llama-3.1-8B-Instruct
- yuriachermann/Not-so-bright-AGI-Llama3.1-8B-UC200k-v2
datasets:
- HuggingFaceH4/ultrachat_200k
base_model_relation: merge
model-index:
- name: KRONOS-8B-V1-P1
  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: 78.5
      name: averaged accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
      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: 29.97
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
      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: 18.96
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
      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: 6.04
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
      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: 8.48
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
      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: 30.67
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
      name: Open LLM Leaderboard
---
# KRONOS 8B V1 P1

This is a merge of Meta Llama 3.1 Instruct and the "Not so Bright" 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 yuriachermann/Not-so-bright-AGI-Llama3.1-8B-UC200k-v2
```

# [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-P1-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=T145%2FKRONOS-8B-V1-P1&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!

|      Metric       |Value (%)|
|-------------------|--------:|
|**Average**        |    28.77|
|IFEval (0-Shot)    |    78.50|
|BBH (3-Shot)       |    29.97|
|MATH Lvl 5 (4-Shot)|    18.96|
|GPQA (0-shot)      |     6.04|
|MuSR (0-shot)      |     8.48|
|MMLU-PRO (5-shot)  |    30.67|