---
license: cc-by-4.0
model-index:
- name: piccolo-8x7b
  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: 69.62
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/piccolo-8x7b
      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: 86.98
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/piccolo-8x7b
      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: 64.13
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/piccolo-8x7b
      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: 64.17
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/piccolo-8x7b
      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: 79.87
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/piccolo-8x7b
      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: 72.02
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/piccolo-8x7b
      name: Open LLM Leaderboard
---
# Piccolo-8x7b


  **In loving memory of my dog Klaus (Piccolo)**
    
  _~ Piccolo (Italian): the little one ~_

 ![piccolo.png](piccolo.png)


Based on mlabonne/NeuralBeagle-7b
Quants are available [here](https://huggingface.co/macadeliccc/piccolo-8x7b-GGUF)

# Code Example

Inference and Evaluation colab available [here](https://colab.research.google.com/drive/1ZqLNvVvtFHC_4v2CgcMVh7pP9Fvx0SbI?usp=sharing)

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

def generate_response(prompt):
    """
    Generate a response from the model based on the input prompt.
    Args:
    prompt (str): Prompt for the model.

    Returns:
    str: The generated response from the model.
    """
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_new_tokens=256, eos_token_id=tokenizer.eos_token_id, pad_token_id=tokenizer.pad_token_id)

    response = tokenizer.decode(outputs[0], skip_special_tokens=True)

    return response

model_id = "macadeliccc/piccolo-8x7b"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id,load_in_4bit=True)

prompt = "What is the best way to train Cane Corsos?"

print("Response:")
print(generate_response(prompt), "\n")
```

The model is capable of quality code, math, and logical reasoning. Try whatever questions you think of.

## Example output 

![example_output](https://huggingface.co/macadeliccc/piccolo-8x7b-GGUF/resolve/main/piccolo-llama-2.png)

# Evaluations

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6455cc8d679315e4ef16fbec/mN8jXeBsgTGL6fC09s5nx.png)

https://huggingface.co/datasets/open-llm-leaderboard/details_macadeliccc__piccolo-8x7b

# [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_macadeliccc__piccolo-8x7b)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |72.80|
|AI2 Reasoning Challenge (25-Shot)|69.62|
|HellaSwag (10-Shot)              |86.98|
|MMLU (5-Shot)                    |64.13|
|TruthfulQA (0-shot)              |64.17|
|Winogrande (5-shot)              |79.87|
|GSM8k (5-shot)                   |72.02|