93 lines
4.3 KiB
Markdown
93 lines
4.3 KiB
Markdown
---
|
|
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
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
## 📈 Training curves
|
|
|
|
You can find the experiment on W&B at [this address](https://wandb.ai/mlabonne/DPO/runs/vxnmq24z/workspace?nw=nwusermlabonne).
|
|
|
|
|
|
|
|
## 💻 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"])
|
|
``` |