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---
license: cc-by-nc-2.0
tags:
- merge
- mergekit
- lazymergekit
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
base_model:
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
model-index:
- name: kuno-royale-v2-7b
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 72.01
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-royale-v2-7b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 88.15
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-royale-v2-7b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 65.07
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-royale-v2-7b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 71.1
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-royale-v2-7b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 82.24
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-royale-v2-7b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 70.2
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-royale-v2-7b
name: Open LLM Leaderboard
---
# kuno-royale-v2-7b
An attempt to further strengthen the roleplaying prose of [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co./SanjiWatsuki/Kunoichi-DPO-v2-7B) using [eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO](https://huggingface.co./eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO), a high-scorer for 7B models on the [Open LLM Leaderboard](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard).
Personal RP tests prove promising, and meaningless leaderboard metrics have improved vs [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co./SanjiWatsuki/Kunoichi-DPO-v2-7B).
Some GGUF quants available [here](https://huggingface.co./core-3/kuno-royale-v2-7b-GGUF).
Works well with Silly Tavern Noromaid template recommended by [SanjiWatsuki for Kunoichi-7B](https://huggingface.co./SanjiWatsuki/Kunoichi-7B): [Context](https://files.catbox.moe/ifmhai.json), [Instruct](https://files.catbox.moe/ttw1l9.json)
|Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
|-------------------|---------|-----|-----------|------|------------|------------|-------|
| eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO | 76.45 | 73.12 | 89.09 | 64.80 | 77.45 | 84.77 | 69.45 |
| **core-3/kuno-royale-v2-7b** | **74.80** | **72.01** | **88.15** | **65.07** | **71.10** | **82.24** | **70.20** |
| [core-3/kuno-royale-7B](https://huggingface.co./core-3/kuno-royale-7B) | 74.74 | 71.76 | 88.20 | 65.13 | 71.12 | 82.32 | 69.90
| SanjiWatsuki/Kunoichi-DPO-v2-7B | 72.46 | 69.62 | 87.44 | 64.94 | 66.06 | 80.82 | 65.88 |
| SanjiWatsuki/Kunoichi-7B | 72.13 | 68.69 | 87.10 | 64.90 | 64.04 | 81.06 | 67.02 |
# Original LazyMergekit Card:
kuno-royale-v2-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co./SanjiWatsuki/Kunoichi-DPO-v2-7B)
* [eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO](https://huggingface.co./eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO)
## 🧩 Configuration
```yaml
slices:
- sources:
- model: SanjiWatsuki/Kunoichi-DPO-v2-7B
layer_range: [0, 32]
- model: eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
layer_range: [0, 32]
merge_method: slerp
base_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "core-3/kuno-royale-v2-7b"
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"])
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_core-3__kuno-royale-v2-7b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |74.80|
|AI2 Reasoning Challenge (25-Shot)|72.01|
|HellaSwag (10-Shot) |88.15|
|MMLU (5-Shot) |65.07|
|TruthfulQA (0-shot) |71.10|
|Winogrande (5-shot) |82.24|
|GSM8k (5-shot) |70.20|
|