---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- Open-Orca/Mistral-7B-OpenOrca
- openchat/openchat-3.5-0106
- WizardLM/WizardMath-7B-V1.1
---

# TIES-Merging

TIES-Merging is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co./Open-Orca/Mistral-7B-OpenOrca)
* [openchat/openchat-3.5-0106](https://huggingface.co./openchat/openchat-3.5-0106)
* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co./WizardLM/WizardMath-7B-V1.1)

## 🧩 Configuration

```yaml
models:
  - model: mistralai/Mistral-7B-Instruct-v0.2
    # no parameters necessary for base model
  - model: Open-Orca/Mistral-7B-OpenOrca
    parameters:
      density: 0.5
      weight: 0.5
  - model: openchat/openchat-3.5-0106
    parameters:
      density: 0.5
      weight: 0.5
  - model: WizardLM/WizardMath-7B-V1.1
    parameters:
      density: 0.5
      weight: 0.5
merge_method: ties
base_model: mistralai/Mistral-7B-Instruct-v0.2
parameters:
  normalize: true
dtype: float16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Cartinoe5930/TIES-Merging"
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"])
```