---
base_model:
- OmnicromsBrain/StoryFusion-7B
- OmnicromsBrain/NeuralStar-7b-Lazy
tags:
- merge
- mergekit
- lazymergekit
- OmnicromsBrain/StoryFusion-7B
- OmnicromsBrain/NeuralStar-7b-Lazy
---

# NeuralStar_Story-9b

**TESTING**

NeuralStar_Story-9b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [OmnicromsBrain/StoryFusion-7B](https://huggingface.co/OmnicromsBrain/StoryFusion-7B)
* [OmnicromsBrain/NeuralStar-7b-Lazy](https://huggingface.co/OmnicromsBrain/NeuralStar-7b-Lazy)

## 🧩 Configuration

```yaml
slices:
  - sources:
    - model: OmnicromsBrain/StoryFusion-7B
      layer_range: [0, 24]
  - sources:
    - model: OmnicromsBrain/NeuralStar-7b-Lazy
      layer_range: [8, 32]
merge_method: passthrough
dtype: float16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "OmnicromsBrain/NeuralStar_Story-9b"
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"])
```