ramonda-monarch-7b

ramonda-monarch-7b is a merge of the following models using LazyMergekit:

• eren23/ogno-monarch-jaskier-merge-7b
• liminerity/Omningotex-7b-slerp
• yleo/OgnoMonarch-7B

🏆 Benchmarks

Open LLM Leaderboard

Model	Average	ARC_easy	HellaSwag	MMLU	TruthfulQA-mc2	Winogrande	GSM8K	ARC_challenge
mayacinka/ramonda-monarch-7b	76.66	86.91	87.45	61.97	77.4	81.61	73.01	68.26

MMLU

Groups	Version	Filter	n-shot	Metric	Value		Stderr
mmlu	N/A	none	0	acc	0.6197	±	0.0039
- humanities	N/A	none	None	acc	0.5762	±	0.0067
- other	N/A	none	None	acc	0.6936	±	0.0080
- social_sciences	N/A	none	None	acc	0.7192	±	0.0079
- stem	N/A	none	None	acc	0.5147	±	0.0085

Nous benchmark

autoEval

Model	AGIEval	GPT4All	TruthfulQA	Bigbench	Average
mayacinka/ramonda-monarch-7b	44.63	77.41	77.41	49.59	62.26

🧩 Configuration

models:
  - model: bardsai/jaskier-7b-dpo-v5.6
    # No parameters necessary for base model
  - model: eren23/ogno-monarch-jaskier-merge-7b
    parameters:
      density: 0.53
      weight: 0.4
  - model: liminerity/Omningotex-7b-slerp
    parameters:
      density: 0.53
      weight: 0.3
  - model: yleo/OgnoMonarch-7B
    parameters:
      density: 0.53
      weight: 0.3
merge_method: dare_ties
base_model: bardsai/jaskier-7b-dpo-v5.6
parameters:
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mayacinka/ramonda-monarch-7b"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])