README.md

---
base_model:
- GritLM/GritLM-7B
- argilla/notus-7b-v1
- GreenNode/GreenNode-mini-7B-multilingual-v1olet
tags:
- merge
- mergekit
- lazymergekit
- GritLM/GritLM-7B
- argilla/notus-7b-v1
- GreenNode/GreenNode-mini-7B-multilingual-v1olet
---

# Shark-1

Shark-1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [GritLM/GritLM-7B](https://huggingface.co/GritLM/GritLM-7B)
* [argilla/notus-7b-v1](https://huggingface.co/argilla/notus-7b-v1)
* [GreenNode/GreenNode-mini-7B-multilingual-v1olet](https://huggingface.co/GreenNode/GreenNode-mini-7B-multilingual-v1olet)

## 🧩 Configuration

```yaml
slices:
  - sources:
    - model: GritLM/GritLM-7B
      layer_range: [0, 8]
  - sources:
    - model: argilla/notus-7b-v1
      layer_range: [8, 20]
  - sources:
    - model: GreenNode/GreenNode-mini-7B-multilingual-v1olet
      layer_range: [20, 32]
merge_method: passthrough
tokenizer_source: union
dtype: float16
    ```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "powermove72/Shark-1"
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"])
```