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@@ -112,20 +112,26 @@ model-index:
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  ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/gFEhcIDSKa3AWpkNfH91q.jpeg)
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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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- It is an improved version of the abliterated model.
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  ## πŸ”Ž Applications
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- This is an uncensored model. You can use it for any application that doesn't require alignment, like role-playing.
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- Tested on LM Studio using the "Llama 3" preset.
 
 
 
 
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  ## πŸ† Evaluation
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  ### Open LLM Leaderboard
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- TBD.
 
 
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  ### Nous
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  | [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [πŸ“„](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) [πŸ“„](https://gist.github.com/mlabonne/616b6245137a9cfc4ea80e4c6e55d847) | 45.42 | 31.1 | 69.95 | 43.91 | 36.7 |
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-
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  ## 🌳 Model family tree
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/ekwRGgnjzEOyprT8sEBFt.png)
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- # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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- Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__Daredevil-8B-abliterated-dpomix)
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-
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- | Metric |Value|
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- |---------------------------------|----:|
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- |Avg. |72.32|
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- |AI2 Reasoning Challenge (25-Shot)|69.28|
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- |HellaSwag (10-Shot) |85.05|
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- |MMLU (5-Shot) |69.10|
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- |TruthfulQA (0-shot) |60.00|
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- |Winogrande (5-shot) |78.69|
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- |GSM8k (5-shot) |71.80|
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  ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/gFEhcIDSKa3AWpkNfH91q.jpeg)
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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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  ## πŸ”Ž 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" preset.
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+
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+ ## ⚑ Quantization
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+
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+ * **GGUF**: https://huggingface.co/mlabonne/NeuralDaredevil-8B-abliterated-GGUF
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  ## πŸ† 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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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/TqTEbSQ7HAE7QTQBSyKoi.png)
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  ### Nous
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  | [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [πŸ“„](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) [πŸ“„](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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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/ekwRGgnjzEOyprT8sEBFt.png)
 
 
 
 
 
 
 
 
 
 
 
 
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+ ## πŸ’» Usage
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+
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+ ```python
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+ !pip install -qU transformers accelerate
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+
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+ from transformers import AutoTokenizer
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+ import transformers
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+ import torch
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+
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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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+
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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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+
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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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+ ```