---
language:
- en
license: other
library_name: transformers
tags:
- orpo
- llama 3
datasets:
- mlabonne/orpo-dpo-mix-40k
---

# OrpoLlama-3-8B

![](https://i.imgur.com/ZHwzQvI.png)

This is a quick fine-tune of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on 1k samples of [mlabonne/orpo-dpo-mix-40k](https://huggingface.co/datasets/mlabonne/orpo-dpo-mix-40k) created for [this article](https://huggingface.co/blog/mlabonne/orpo-llama-3).

It's not very good at the moment (it's the sassiest model ever), but I'm currently training a version on the entire dataset.

**Try the demo**: https://huggingface.co/spaces/mlabonne/OrpoLlama-3-8B

## 🏆 Evaluation

### Nous

Evaluation performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval), see the entire leaderboard [here](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard).

| Model                                                                                                                                                                     |   Average |   AGIEval |   GPT4All | TruthfulQA |  Bigbench |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------: | --------: | --------: | ---------: | --------: |
| [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) [📄](https://gist.github.com/mlabonne/88b21dd9698ffed75d6163ebdc2f6cc8)     |     52.42 |     42.75 |     72.99 |      52.99 |     40.94 |
| [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [📄](https://gist.github.com/mlabonne/8329284d86035e6019edb11eb0933628) |     51.34 |     41.22 |     69.86 |      51.65 |     42.64 |
| [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) [📄](https://gist.github.com/mlabonne/7a0446c3d30dfce72834ef780491c4b2)   |     49.15 |     33.36 |     67.87 |      55.89 |     39.48 |
| [**mlabonne/OrpoLlama-3-8B**](https://huggingface.co/mlabonne/OrpoLlama-3-8B) [📄](https://gist.github.com/mlabonne/f41dad371d1781d0434a4672fd6f0b82)                     | **46.76** | **31.56** | **70.19** |  **48.11** | **37.17** |
| [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [📄](https://gist.github.com/mlabonne/616b6245137a9cfc4ea80e4c6e55d847)                   |     45.42 |      31.1 |     69.95 |      43.91 |      36.7 |

## 📈 Training curves

![](https://i.imgur.com/r78hGrl.png)

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/OrpoLlama-3-8B"
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"])
```