---
tags:
- merge
- mergekit
- MTSAIR/multi_verse_model
- rwitz/experiment26-truthy-iter-0
- MaziyarPanahi/Calme-7B-Instruct-v0.2
- chemistry
- biology
- math
base_model:
- MTSAIR/multi_verse_model
- rwitz/experiment26-truthy-iter-0
- MaziyarPanahi/Calme-7B-Instruct-v0.2
license: apache-2.0
language:
- en
library_name: transformers
pipeline_tag: text-generation
model-index:
- name: Maxine-7B-0401-stock
  results:
  - task:
      type: text-generation
    metrics:
    - name: Average
      type: Average
      value: 76.73
    - name: ARC
      type: ARC
      value: 73.12
    - name: GSM8K
      type: GSM8K
      value: 70.66
    - name: Winogrande
      type: Winogrande
      value: 85
    - name: TruthfulQA
      type: TruthfulQA
      value: 78.07
    - name: HellaSwag
      type: HellaSwag
      value: 89.13
    source:
      name: Open LLM Leaderboard
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
---
<center><img src='https://i.imgur.com/dU9dUh0.png' width='500px'></center>

# Maxine-7B-0401-stock, an xtraordinary 7B model

**03-22-2024 - To date, louisbrulenaudet/Pearl-34B-ties is the "Best 🤝 base merges and moerges model of around 30B" on the Open LLM Leaderboard.**

## Configuration

```yaml
models:
    - model: OpenPipe/mistral-ft-optimized-1227
    - model: MTSAIR/multi_verse_model
    - model: rwitz/experiment26-truthy-iter-0
    - model: MaziyarPanahi/Calme-7B-Instruct-v0.2
merge_method: model_stock
base_model: OpenPipe/mistral-ft-optimized-1227
dtype: bfloat16
```

## Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "louisbrulenaudet/Maxine-7B-0401-stock"
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"])
```

## Citing & Authors

If you use this code in your research, please use the following BibTeX entry.

```BibTeX
@misc{louisbrulenaudet2024,
  author =       {Louis Brulé Naudet},
  title =        {Maxine-7B-0401-stock, an xtraordinary 7B model},
  year =         {2024}
  howpublished = {\url{https://huggingface.co/louisbrulenaudet/Maxine-7B-0401-stock}},
}
```

## Feedback

If you have any feedback, please reach out at [louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).