README.md

---
language:
- en
license: apache-2.0
datasets:
- Intel/orca_dpo_pairs
model-index:
- name: agiin-13.6B-v0.1
  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: 69.45
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mncai/agiin-13.6B-v0.1
      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: 86.64
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mncai/agiin-13.6B-v0.1
      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: 61.15
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mncai/agiin-13.6B-v0.1
      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: 67.97
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mncai/agiin-13.6B-v0.1
      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: 78.69
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mncai/agiin-13.6B-v0.1
      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: 46.47
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mncai/agiin-13.6B-v0.1
      name: Open LLM Leaderboard
---

# Model Card for mncai/agiin-13.6B-v0.1

### Introduction of MindsAndCompany

https://mnc.ai/

We create various AI models and develop solutions that can be applied to businesses. And as for generative AI, we are developing products like Code Assistant, TOD Chatbot, LLMOps, and are in the process of developing Enterprise AGI (Artificial General Intelligence).

### Model Summary
This model was built based on the Mistral architecture. It was inspired by neural connection technology and rehabilitation therapy.
I have created a new model architecture that does not require pretraining, and training the model is sufficient with just one H100 for 7 hours.

### Data
Intel/orca_dpo_pairs (DPO) 

### Surgery and Training

stack mistral 62 layers and DPO.

### How to Use 

```python
message = [
    {"role": "system", "content": "You are a helpful assistant chatbot."},
    {"role": "user", "content": "두 개의 구가 각각 지름이 1, 2일때 두 구의 부피는 몇배지? 설명도 같이 해줘."}
]
tokenizer = AutoTokenizer.from_pretrained(hf_model)
prompt = tokenizer.apply_chat_template(message, add_generation_prompt=True, tokenize=False)

pipeline = transformers.pipeline(
    "text-generation",
    model=hf_model,
    tokenizer=tokenizer
)


sequences = pipeline(
    prompt,
    do_sample=True,
    temperature=0.7,
    top_p=0.9,
    num_return_sequences=1,
    max_length=512,
)
print(sequences[0]['generated_text'])
```

### Contact 
If you have any questions, please raise an issue or contact us at [email protected]
# [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_mncai__agiin-13.6B-v0.1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |68.40|
|AI2 Reasoning Challenge (25-Shot)|69.45|
|HellaSwag (10-Shot)              |86.64|
|MMLU (5-Shot)                    |61.15|
|TruthfulQA (0-shot)              |67.97|
|Winogrande (5-shot)              |78.69|
|GSM8k (5-shot)                   |46.47|