File size: 3,085 Bytes
c472c57 ba0d4ee c472c57 e422ac6 c472c57 09c9096 68c532e e422ac6 68c532e 09c9096 68c532e ba0d4ee e422ac6 c472c57 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
---
license: other
datasets:
- mlabonne/orpo-dpo-mix-40k
tags:
- abliterated
---
# Llama-3-8B-Instruct-abliterated-dpomix
This model is an experimental DPO fine-tune of an abliterated Llama 3 8B Instruct model on the full [mlabonne/orpo-dpo-mix-40k](https://huggingface.co/datasets/mlabonne/orpo-dpo-mix-40k) dataset.
It improves Llama 3 8B Instruct's performance while being uncensored.
## 🔎 Applications
This is an uncensored model. You can use it for any application that doesn't require alignment, like role-playing.
Tested on LM Studio using the "Llama 3" preset.
## ⚡ Quantization
* **GGUF**: https://huggingface.co/mlabonne/Llama-3-8B-Instruct-abliterated-dpomix-GGUF
## 🏆 Evaluation
### Open LLM Leaderboard
This model improves the performance of the abliterated source model and recovers the MMLU that was lost in the abliteration process.
### Nous
| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
|---|---:|---:|---:|---:|---:|
| [**mlabonne/Llama-3-8B-Instruct-abliterated-dpomix**](https://huggingface.co/mlabonne/Llama-3-8B-Instruct-abliterated-dpomix) [📄](https://gist.github.com/mlabonne/d711548df70e2c04771cc68ab33fe2b9) | **52.26** | **41.6** | **69.95** | **54.22** | **43.26** |
| [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 |
| [failspy/Meta-Llama-3-8B-Instruct-abliterated-v3](https://huggingface.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3) [📄](https://gist.github.com/mlabonne/f46cce0262443365e4cce2b6fa7507fc) | 51.21 | 40.23 | 69.5 | 52.44 | 42.69 |
| [abacusai/Llama-3-Smaug-8B](https://huggingface.co/abacusai/Llama-3-Smaug-8B) [📄](https://gist.github.com/mlabonne/91369d9c372f80b6a42a978b454d3b5e) | 49.65 | 37.15 | 69.12 | 51.66 | 40.67 |
| [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 |
| [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 |
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mlabonne/Llama-3-8B-Instruct-abliterated-dpomix"
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"])
``` |