README.md

---
license: cc-by-nc-4.0
tags:
- merge
- mergekit
- lazymergekit
- mlabonne/NeuralBeagle14-7B
- bardsai/jaskier-7b-dpo-v6.1
base_model:
- mlabonne/NeuralBeagle14-7B
- bardsai/jaskier-7b-dpo-v6.1
---
<center><img src='https://i.postimg.cc/zXSnJ8J3/8358efa9-30c7-4c4d-9fdb-42191f501e70.png' width='1024px' height='1024'></center>
# NeuralBeagleJaskier

NeuralBeagleJaskier is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
* [bardsai/jaskier-7b-dpo-v6.1](https://huggingface.co/bardsai/jaskier-7b-dpo-v6.1)

## 🧩 Configuration

```yaml
models:
  - model: mlabonne/NeuralBeagle14-7B
    parameters:
      density: 0.9
      weight: 0.5
  - model: bardsai/jaskier-7b-dpo-v6.1
    parameters:
      density: 0.5
      weight: 0.3
merge_method: ties
base_model: mlabonne/NeuralBeagle14-7B
parameters:
  normalize: true
  int8_mask: true
dtype: float16

```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "eldogbbhed/NeuralBeagleJaskier"
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"])
```