README.md

---
license: apache-2.0
tags:
- merge
- beowolx/CodeNinja-1.0-OpenChat-7B
- beowolx/MistralHermes-CodePro-7B-v1
model-index:
- name: NinjaDolphin-7B
  results:
  - task:
      type: text-generation             # Required. Example: automatic-speech-recognition
    dataset:
      type: openai_humaneval         # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
      name: HumanEval         # Required. A pretty name for the dataset. Example: Common Voice (French)
    metrics:
      - type: pass@1         # Required. Example: wer. Use metric id from https://hf.co/metrics
        value: 52.4390243902439       # Required. Example: 20.90
        name: pass@1         # Optional. Example: Test WER
        verified: false
---

# NinjaDolphin-7B

NinjaDolphin-7B is a merge of the following models using:
* [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B)
* [beowolx/MistralHermes-CodePro-7B-v1](https://huggingface.co/beowolx/MistralHermes-CodePro-7B-v1)

Improving coding ability from [FelixChao/WizardDolphin-7B](https://huggingface.co/FelixChao/WizardDolphin-7B).

## HumanEval (uninstructed and no post-process)

| Metric | Value |
| --- | --- |
| humaneval-python |52.4390243902439|


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64a53b0747a04f0512941b6f/NIALzUR53HC1eB1i_xwKD.png)

## 🧩 Configuration

```yaml
models:
  - model: FelixChao/WizardDolphin-7B
  - model: beowolx/CodeNinja-1.0-OpenChat-7B
    parameters:
      density: 0.53
      weight: 0.3
  - model: beowolx/MistralHermes-CodePro-7B-v1
    parameters:
      density: 0.53
      weight: 0.3
merge_method: dare_ties
base_model: FelixChao/WizardDolphin-7B
parameters:
  int8_mask: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "FelixChao/NinjaDolphin-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_FelixChao__NinjaDolphin-7B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.74|
|AI2 Reasoning Challenge (25-Shot)|65.61|
|HellaSwag (10-Shot)              |85.35|
|MMLU (5-Shot)                    |64.43|
|TruthfulQA (0-shot)              |54.94|
|Winogrande (5-shot)              |80.27|
|GSM8k (5-shot)                   |67.85|