---
library_name: transformers
license: llama3
datasets: mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha
tags:
- DPO
- Llama3-8B
---
This is an ExLlamaV2 quantized model in 4bpw of [Muhammad2003/Llama3-8B-OpenHermes-DPO](https://huggingface.co/Muhammad2003/Llama3-8B-OpenHermes-DPO) using the default calibration dataset.

# Original Model card:

# Llama3-8B-OpenHermes-DPO


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64fc6d81d75293f417fee1d1/QF2OsDu9DJKP4QYPBu4aK.png)

Llama3-8B-OpenHermes-DPO is DPO-Finetuned model of Llama3-8B, on the OpenHermes-2.5 preference dataset using QLoRA.

* [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
* [mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha](https://huggingface.co/datasets/mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha)

</details><br>

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Muhammad2003/Llama3-8B-OpenHermes-DPO"
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"])
```

## 🏆 Evaluation results

### Coming Soon