README.md

---
tags:
- merge
- mergekit
- lazymergekit
- WizardLM/WizardMath-7B-V1.1
- mlabonne/NeuralDaredevil-7B
- Kukedlc/Neural4gsm8k
- Eric111/Mayo
- Kukedlc/NeuralSirKrishna-7b
base_model:
- WizardLM/WizardMath-7B-V1.1
- mlabonne/NeuralDaredevil-7B
- Kukedlc/Neural4gsm8k
- Eric111/Mayo
- Kukedlc/NeuralSirKrishna-7b
license: apache-2.0
model-index:
- name: NeuralSirKrishna-7b
  results:
  - 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: 75.21
      name: accuracy
---

# NeuralMaths-Experiment-7b

## Number One in GSM8K LeaderBoard!


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64d71ab4089bc502ceb44d29/G4jLrTxkxE4knJAaZB3u6.png)

NeuralMaths-Experiment-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
* [mlabonne/NeuralDaredevil-7B](https://huggingface.co/mlabonne/NeuralDaredevil-7B)
* [Kukedlc/Neural4gsm8k](https://huggingface.co/Kukedlc/Neural4gsm8k)
* [Eric111/Mayo](https://huggingface.co/Eric111/Mayo)
* [Kukedlc/NeuralSirKrishna-7b](https://huggingface.co/Kukedlc/NeuralSirKrishna-7b)

## 🧩 Configuration

```yaml
models:
  - model: Kukedlc/NeuralSirKrishna-7b
    # No parameters necessary for base model
  - model: WizardLM/WizardMath-7B-V1.1
    parameters:
      density: 0.66
      weight: 0.2
  - model: mlabonne/NeuralDaredevil-7B
    parameters:
      density: 0.55
      weight: 0.2
  - model: Kukedlc/Neural4gsm8k
    parameters:
      density: 0.55
      weight: 0.2
  - model: Eric111/Mayo
    parameters:
      density: 0.44
      weight: 0.2
  - model: Kukedlc/NeuralSirKrishna-7b
    parameters:
      density: 0.66
      weight: 0.2
merge_method: dare_ties
base_model: Kukedlc/NeuralSirKrishna-7b
parameters:
  int8_mask: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/NeuralMaths-Experiment-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"])
```