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--- |
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language: |
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- en |
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license: other |
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library_name: transformers |
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tags: |
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- orpo |
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- llama 3 |
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- rlhf |
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- sft |
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datasets: |
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- mlabonne/orpo-dpo-mix-40k |
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--- |
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# OrpoLlama-3-8B |
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This is an ORPO 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). |
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It's a successful fine-tune that follows the ChatML template! |
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**Try the demo**: https://huggingface.co/spaces/mlabonne/OrpoLlama-3-8B |
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## 🔎 Application |
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This model uses a context window of 8k. It was trained with the ChatML template. |
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## ⚡ Quantized models |
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Thanks to bartowski, solidrust, and LoneStriker for the quantized models. |
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* **GGUF**: https://huggingface.co/bartowski/OrpoLlama-3-8B-GGUF |
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* **AWQ**: https://huggingface.co/solidrust/OrpoLlama-3-8B-AWQ |
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* **EXL2**: |
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* https://huggingface.co/LoneStriker/OrpoLlama-3-8B-3.0bpw-h6-exl2 |
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* https://huggingface.co/LoneStriker/OrpoLlama-3-8B-4.0bpw-h6-exl2 |
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* https://huggingface.co/LoneStriker/OrpoLlama-3-8B-5.0bpw-h6-exl2 |
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* https://huggingface.co/LoneStriker/OrpoLlama-3-8B-6.0bpw-h6-exl2 |
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* https://huggingface.co/LoneStriker/OrpoLlama-3-8B-8.0bpw-h8-exl2 |
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## 🏆 Evaluation |
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### Nous |
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OrpoLlama-4-8B outperforms Llama-3-8B-Instruct on the GPT4All and TruthfulQA datasets. |
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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). |
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| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench | |
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| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------: | --------: | --------: | ---------: | --------: | |
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| [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 | |
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| [**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** | |
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| [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 | |
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| [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 | |
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`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)). |
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### Open LLM Leaderboard |
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TBD. |
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## 📈 Training curves |
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You can find the experiment on W&B at [this address](https://wandb.ai/mlabonne/DPO/runs/vxnmq24z/workspace?nw=nwusermlabonne). |
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## 💻 Usage |
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```python |
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!pip install -qU transformers accelerate |
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from transformers import AutoTokenizer |
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import transformers |
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import torch |
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model = "mlabonne/OrpoLlama-3-8B" |
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messages = [{"role": "user", "content": "What is a large language model?"}] |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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torch_dtype=torch.float16, |
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device_map="auto", |
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) |
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
