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Model: mlabonne/OrpoLlama-3-8B Source: Original Platform
2026-06-03 05:18:13 +08:00
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+---
+language:
+- en
+license: other
+library_name: transformers
+tags:
+- orpo
+- llama 3
+- rlhf
+- sft
+base_model: meta-llama/Meta-Llama-3-8B
+datasets:
+- mlabonne/orpo-dpo-mix-40k
+---
+
+# OrpoLlama-3-8B
+
+![](https://i.imgur.com/ZHwzQvI.png)
+
+This is an ORPO fine-tune of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on [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 a successful fine-tune that follows the ChatML template!
+
+**Try the demo**: https://huggingface.co/spaces/mlabonne/OrpoLlama-3-8B
+
+## 🔎 Application
+
+This model uses a context window of 8k. It was trained with the ChatML template.
+
+## ⚡ Quantized models
+
+Thanks to bartowski, solidrust, and LoneStriker for the quantized models.
+
+* **GGUF**: https://huggingface.co/bartowski/OrpoLlama-3-8B-GGUF
+* **AWQ**: https://huggingface.co/solidrust/OrpoLlama-3-8B-AWQ
+* **EXL2**:
+  * https://huggingface.co/LoneStriker/OrpoLlama-3-8B-3.0bpw-h6-exl2
+  * https://huggingface.co/LoneStriker/OrpoLlama-3-8B-4.0bpw-h6-exl2
+  * https://huggingface.co/LoneStriker/OrpoLlama-3-8B-5.0bpw-h6-exl2
+  * https://huggingface.co/LoneStriker/OrpoLlama-3-8B-6.0bpw-h6-exl2
+  * https://huggingface.co/LoneStriker/OrpoLlama-3-8B-8.0bpw-h8-exl2
+
+## 🏆 Evaluation
+
+### Nous
+
+OrpoLlama-4-8B outperforms Llama-3-8B-Instruct on the GPT4All and TruthfulQA datasets.
+
+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 |
+| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------: | --------: | --------: | ---------: | --------: |
+| [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 |
+| [**mlabonne/OrpoLlama-3-8B**](https://huggingface.co/mlabonne/OrpoLlama-3-8B) [📄](https://gist.github.com/mlabonne/22896a1ae164859931cc8f4858c97f6f)                     | **48.63** | **34.17** | **70.59** | **52.39** | **37.36** |
+| [mlabonne/OrpoLlama-3-8B-1k](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 |
+
+`mlabonne/OrpoLlama-3-8B-1k` corresponds to a version of this model trained on 1K samples (you can see the parameters in [this article](https://huggingface.co/blog/mlabonne/orpo-llama-3)). The current version was trained on a full epoch.
+
+### Open LLM Leaderboard
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/5auE1oyKJ-TsvrUVeQBYr.png)
+
+## 📈 Training curves
+
+You can find the experiment on W&B at [this address](https://wandb.ai/mlabonne/DPO/runs/vxnmq24z/workspace?nw=nwusermlabonne).
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/zm71HyZiG96YY1GUtpfHq.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"])
+```