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 + 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

Detailed results can be found here

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

bunnycore/Qwen2.5-7B-RRP-1M

What this Model Can Do:

Merge Method

Models Merged

Configuration

Open LLM Leaderboard Evaluation Results

bunnycore/
Qwen2.5-7B-RRP-1M