README.md

---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Qwen/Qwen2.5-7B-Instruct-1M
- bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora
model-index:
- name: Qwen2.5-7B-RRP-1M
  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: 74.81
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-RRP-1M
      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: 35.65
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-RRP-1M
      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: 28.17
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-RRP-1M
      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: 7.05
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-RRP-1M
      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: 15.8
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-RRP-1M
      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: 36.29
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-RRP-1M
      name: Open LLM Leaderboard
---
LoRA trained on a thinking/reasoning and roleplaying dataset and then merged with the Qwen2.5-7B-Instruct-1M model, which supports up to 1 million token context lengths.

## What this Model Can Do:

- Roleplay: Engage in creative conversations and storytelling!
- Reasoning: Tackle problems and answer your questions in a logical way (thanks to the LoRA layer).
- Thinking: Use the ```<think>``` tag in your system prompts to activate the model's thinking abilities.

### Merge Method

This model was merged using the Passthrough merge method using [Qwen/Qwen2.5-7B-Instruct-1M](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-1M) + [bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora](https://huggingface.co/bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora) as a base.

### Models Merged

The following models were included in the merge:


### Configuration

The following YAML configuration was used to produce this model:

```yaml

base_model: Qwen/Qwen2.5-7B-Instruct-1M+bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora
dtype: bfloat16
merge_method: passthrough
models:
  - model: Qwen/Qwen2.5-7B-Instruct-1M+bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora
tokenizer_source: Qwen/Qwen2.5-7B-Instruct-1M

```

# [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/bunnycore__Qwen2.5-7B-RRP-1M-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |32.96|
|IFEval (0-Shot)    |74.81|
|BBH (3-Shot)       |35.65|
|MATH Lvl 5 (4-Shot)|28.17|
|GPQA (0-shot)      | 7.05|
|MuSR (0-shot)      |15.80|
|MMLU-PRO (5-shot)  |36.29|