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---
language:
- en
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- maywell/PiVoT-0.1-Evil-a
- mlabonne/NeuralOmniBeagle-7B-v2
- roleplay
- rp
- not-for-all-audiences
base_model:
- maywell/PiVoT-0.1-Evil-a
- mlabonne/NeuralOmniBeagle-7B-v2
model-index:
- name: Konstanta-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: 70.05
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-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: 87.5
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-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: 65.06
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-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: 65.43
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-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: 82.16
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-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: 71.04
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-7B
name: Open LLM Leaderboard
---
# Konstanta-7B
Konstanta-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [maywell/PiVoT-0.1-Evil-a](https://huggingface.co/maywell/PiVoT-0.1-Evil-a)
* [mlabonne/NeuralOmniBeagle-7B-v2](https://huggingface.co/mlabonne/NeuralOmniBeagle-7B-v2)
This is a test merge that is supposed to improve Kunoichi by merging it with new Beagle model and PiVoT Evil, which both show good performance. Even though the model's name is in Russian, it is not really capable of properly using it, as it was not the main goal of the model.
## 🧩 Configuration
```yaml
merge_method: dare_ties
dtype: bfloat16
parameters:
int8_mask: true
base_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
models:
- model: SanjiWatsuki/Kunoichi-DPO-v2-7B
- model: maywell/PiVoT-0.1-Evil-a
parameters:
density: 0.65
weight: 0.15
- model: mlabonne/NeuralOmniBeagle-7B-v2
parameters:
density: 0.85
weight: 0.45
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Inv/Konstanta-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_Inv__Konstanta-7B)
| Metric |Value|
|---------------------------------|----:|
|Avg. |73.54|
|AI2 Reasoning Challenge (25-Shot)|70.05|
|HellaSwag (10-Shot) |87.50|
|MMLU (5-Shot) |65.06|
|TruthfulQA (0-shot) |65.43|
|Winogrande (5-shot) |82.16|
|GSM8k (5-shot) |71.04|
|