---
tags:
- merge
- mergekit
- lazymergekit
- teknium/OpenHermes-2.5-Mistral-7B
- openchat/openchat-3.5-0106
- andrijdavid/macaroni-7b
- mistralai/Mistral-7B-Instruct-v0.2
- Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
- Intel/neural-chat-7b-v3-1
- mlabonne/Beagle14-7B
- mlabonne/NeuralBeagle14-7B
base_model:
- teknium/OpenHermes-2.5-Mistral-7B
- openchat/openchat-3.5-0106
- andrijdavid/macaroni-7b
- mistralai/Mistral-7B-Instruct-v0.2
- Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
- Intel/neural-chat-7b-v3-1
- mlabonne/Beagle14-7B
- mlabonne/NeuralBeagle14-7B
---

# Daschund

Daschund is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
* [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106)
* [andrijdavid/macaroni-7b](https://huggingface.co/andrijdavid/macaroni-7b)
* [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
* [Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp](https://huggingface.co/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp)
* [Intel/neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1)
* [mlabonne/Beagle14-7B](https://huggingface.co/mlabonne/Beagle14-7B)
* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)

## 🧩 Configuration

```yaml
slices:
  - sources:
    - model: teknium/OpenHermes-2.5-Mistral-7B 
      layer_range: [0, 4]
  - sources:
    - model: openchat/openchat-3.5-0106
      layer_range: [4, 8]
  - sources:
    - model: andrijdavid/macaroni-7b
      layer_range: [8, 12]
  - sources:
    - model: mistralai/Mistral-7B-Instruct-v0.2 
      layer_range: [12, 16]
  - sources:
    - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
      layer_range: [16, 20]
  - sources:
    - model: Intel/neural-chat-7b-v3-1
      layer_range: [20, 24]
  - sources:
    - model: mlabonne/Beagle14-7B
      layer_range: [24, 28]
  - sources:
    - model: mlabonne/NeuralBeagle14-7B
      layer_range: [28, 32]
merge_method: passthrough
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "N8Programs/Daschund"
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"])
```