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--- |
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license: llama3 |
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tags: |
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- dpo |
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datasets: |
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- mlabonne/orpo-dpo-mix-40k |
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model-index: |
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- name: Daredevil-8B-abliterated-dpomix |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 69.28 |
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name: normalized accuracy |
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source: |
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url: >- |
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B-abliterated-dpomix |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 85.05 |
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name: normalized accuracy |
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source: |
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url: >- |
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B-abliterated-dpomix |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 69.1 |
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name: accuracy |
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source: |
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url: >- |
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B-abliterated-dpomix |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 60 |
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source: |
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url: >- |
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B-abliterated-dpomix |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 78.69 |
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name: accuracy |
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source: |
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url: >- |
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B-abliterated-dpomix |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 71.8 |
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name: accuracy |
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source: |
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url: >- |
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B-abliterated-dpomix |
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name: Open LLM Leaderboard |
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--- |
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# NeuralDaredevil-8B-abliterated |
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This is a DPO fine-tune of [mlabonne/Daredevil-8-abliterated](https://huggingface.co/mlabonne/Daredevil-8B-abliterated), trained on one epoch of [mlabonne/orpo-dpo-mix-40k](https://huggingface.co/datasets/mlabonne/orpo-dpo-mix-40k). |
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The DPO fine-tuning successfully recovers the performance loss due to the abliteration process, making it an excellent uncensored model. |
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## 🔎 Applications |
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NeuralDaredevil-8B-abliterated performs better than the Instruct model on my tests. |
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You can use it for any application that doesn't require alignment, like role-playing. Tested on LM Studio using the "Llama 3" and "Llama 3 v2" presets. |
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## ⚡ Quantization |
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Thanks to QuantFactory, ZeroWw, Zoyd, solidrust, and tarruda for providing these quants. |
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* **GGUF**: https://huggingface.co/QuantFactory/NeuralDaredevil-8B-abliterated-GGUF |
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* **GGUF (FP16)**: https://huggingface.co/ZeroWw/NeuralDaredevil-8B-abliterated-GGUF |
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* **EXL2**: https://huggingface.co/Zoyd/mlabonne_NeuralDaredevil-8B-abliterated-4_0bpw_exl2 |
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* **AWQ**: https://huggingface.co/solidrust/NeuralDaredevil-8B-abliterated-AWQ |
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* **ollama**: |
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* **16-bit**: https://ollama.com/tarruda/neuraldaredevil-8b-abliterated |
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* **8-bit**: https://ollama.com/lstep/neuraldaredevil-8b-abliterated |
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* **5-bit**: https://ollama.com/closex/neuraldaredevil-8b-abliterated |
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## 🏆 Evaluation |
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### Open LLM Leaderboard |
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NeuralDaredevil-8B is the best-performing uncensored 8B model on the Open LLM Leaderboard (MMLU score). |
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### Nous |
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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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| [**mlabonne/NeuralDaredevil-8B-abliterated**](https://huggingface.co/mlabonne/NeuralDaredevil-8B-abliterated) [📄](https://gist.github.com/mlabonne/ae0bf16936cef900b72964b33c99edbc) | **55.87** | **43.73** | **73.6** | **59.36** | **46.8** | |
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| [mlabonne/Daredevil-8B](https://huggingface.co/mlabonne/Daredevil-8B) [📄](https://gist.github.com/mlabonne/080f9c5f153ea57a7ab7d932cf896f21) | 55.87 | 44.13 | 73.52 | 59.05 | 46.77 | |
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| [mlabonne/Daredevil-8B-abliterated](https://huggingface.co/mlabonne/Daredevil-8B-abliterated) [📄](https://gist.github.com/mlabonne/32cdd8460804662c856bcb2a20acd49e) | 55.06 | 43.29 | 73.33 | 57.47 | 46.17 | |
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| [NousResearch/Hermes-2-Theta-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Theta-Llama-3-8B) [📄](https://gist.github.com/mlabonne/5df2a3051dd6eb3368a77b684635dc05) | 54.28 | 43.9 | 72.62 | 56.36 | 44.23 | |
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| [openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522) [📄](https://gist.github.com/mlabonne/95eef8e8d26b7b17910dcb78e1c95f4a) | 53.49 | 44.03 | 73.67 | 49.78 | 46.48 | |
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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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| [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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## 🌳 Model family tree |
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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/Daredevil-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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``` |
