Hugo-7B-slerp/README.md

---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- mistralai/Mistral-7B-Instruct-v0.2
- beowolx/CodeNinja-1.0-OpenChat-7B
base_model:
- mistralai/Mistral-7B-Instruct-v0.2
- beowolx/CodeNinja-1.0-OpenChat-7B
model-index:
- name: Hugo-7B-slerp
  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: 64.51
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=paulilioaica/Hugo-7B-slerp
      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: 84.77
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=paulilioaica/Hugo-7B-slerp
      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: 62.54
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=paulilioaica/Hugo-7B-slerp
      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: 57.13
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=paulilioaica/Hugo-7B-slerp
      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: 80.03
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=paulilioaica/Hugo-7B-slerp
      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: 53.45
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=paulilioaica/Hugo-7B-slerp
      name: Open LLM Leaderboard
---


# Hugo-7B-slerp

<p align="center"> 
<img src="https://cdn.openart.ai/stable_diffusion/54be6f0516fee5ce9b3f8a8b68620a05059fc4cf_2000x2000.webp" alt="alt text" class="center" width="300"/>
  </p>


Hugo-7B-slerp is a successful merge of the following models using mergekit:
* [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
* [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B)




## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: mistralai/Mistral-7B-Instruct-v0.2
        layer_range: [0, 32]
      - model: beowolx/CodeNinja-1.0-OpenChat-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-Instruct-v0.2
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
```
## 📈 Performance
| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |  
| --- | --- | --- | --- | --- | --- | --- | --- |  
| [paulilioaica/Hugo-7B-slerp](#) | **67.07** | **64.51** | 84.77 | **62.54** | 57.13 | **80.03** | 53.45 |  
| [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) | 65.71 | 63.14 | 84.88 | 60.78 | 68.26 | 77.19 | 40.03 |  
| [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B) | 67.4 | 63.48 | 83.65 | 63.77 | 47.16 | 79.79 | 66.57 |  

With bold one can see the benchmarks where this merge overtakes the basemodel in performance.

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "paulilioaica/Hugo-7B-slerp"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "conversational",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(messages, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs)
```

## 🛈 More on megekit
[mergekit](https://huggingface.co/blog/mlabonne/merge-models)
# [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_paulilioaica__Hugo-7B-slerp)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |67.07|
|AI2 Reasoning Challenge (25-Shot)|64.51|
|HellaSwag (10-Shot)              |84.77|
|MMLU (5-Shot)                    |62.54|
|TruthfulQA (0-shot)              |57.13|
|Winogrande (5-shot)              |80.03|
|GSM8k (5-shot)                   |53.45|