README.md

---
tags:
- merge
- mergekit
- kaist-ai/mistral-orpo-beta
- NousResearch/Hermes-2-Pro-Mistral-7B
- mistralai/Mistral-7B-Instruct-v0.2
base_model:
- kaist-ai/mistral-orpo-beta
- NousResearch/Hermes-2-Pro-Mistral-7B
- mistralai/Mistral-7B-Instruct-v0.2
---

# Orpomis-Prime-7B-it

Orpomis-Prime-7B-it is a merge of the following models using [Mergekit](https://github.com/arcee-ai/mergekit):
* [kaist-ai/mistral-orpo-beta](https://huggingface.co/kaist-ai/mistral-orpo-beta)
* [NousResearch/Hermes-2-Pro-Mistral-7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)
* [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)

## 🧩 Configuration

```yamlname: Orpomis-Prime-7B-it
models:
  - model: kaist-ai/mistral-orpo-beta
  - model: NousResearch/Hermes-2-Pro-Mistral-7B
  - model: mistralai/Mistral-7B-Instruct-v0.2
merge_method: model_stock
base_model: mistralai/Mistral-7B-Instruct-v0.2
dtype: bfloat16```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "saucam/Orpomis-Prime-7B-it"
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"])
```