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---
tags:
- merge
- mergekit
- kaist-ai/mistral-orpo-beta
- NousResearch/Hermes-2-Pro-Mistral-7B
base_model:
- kaist-ai/mistral-orpo-beta
- NousResearch/Hermes-2-Pro-Mistral-7B
---
# Orpomis-Prime-7B-dare
Orpomis-Prime-7B-dare 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)
## 🧩 Configuration
```yamlname: Orpomis-Prime-7B-dare
models:
- model: kaist-ai/mistral-orpo-beta
parameters:
density: 0.5
weight: 0.6
# No parameters necessary for base model
- model: NousResearch/Hermes-2-Pro-Mistral-7B
parameters:
density: 0.5
weight: 0.4
merge_method: dare_ties
base_model: kaist-ai/mistral-orpo-beta
parameters:
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "saucam/Orpomis-Prime-7B-dare"
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"])
``` |