---
base_model:
- NousResearch/Nous-Hermes-2-Mistral-7B-DPO
- NousResearch/Hermes-2-Pro-Mistral-7B
tags:
- merge
- mergekit
- lazymergekit
- NousResearch/Nous-Hermes-2-Mistral-7B-DPO
- NousResearch/Hermes-2-Pro-Mistral-7B
---

# Trismal-Hermand-7B-Base-Ties

Trismal-Hermand-7B-Base-Ties is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [NousResearch/Nous-Hermes-2-Mistral-7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO)
* [NousResearch/Hermes-2-Pro-Mistral-7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)

## 🧩 Configuration

```yaml
models:
  - model: NousResearch/Nous-Hermes-2-Mistral-7B-DPO
    parameters:
      weight: 1
      density: 1
  - model: NousResearch/Hermes-2-Pro-Mistral-7B
    parameters:
      weight: 1
      density: 1
merge_method: ties
base_model: NousResearch/Nous-Hermes-2-Mistral-7B-DPO
parameters:
  weight: 1
  density: 1
  normalize: true
  int8_mask: false
dtype: float16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "JoPmt/Trismal-Hermand-7B-Base-Ties"
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"])
```