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| 1 |
+
Quantization made by Richard Erkhov.
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| 2 |
+
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| 3 |
+
[Github](https://github.com/RichardErkhov)
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| 4 |
+
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| 5 |
+
[Discord](https://discord.gg/pvy7H8DZMG)
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| 6 |
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+
[Request more models](https://github.com/RichardErkhov/quant_request)
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| 8 |
+
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| 9 |
+
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| 10 |
+
NeuralDaredevil-7B - bnb 4bits
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| 11 |
+
- Model creator: https://huggingface.co/mlabonne/
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| 12 |
+
- Original model: https://huggingface.co/mlabonne/NeuralDaredevil-7B/
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| 13 |
+
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| 14 |
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| 15 |
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| 16 |
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| 17 |
+
Original model description:
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| 18 |
+
---
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| 19 |
+
license: cc-by-nc-4.0
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| 20 |
+
tags:
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| 21 |
+
- merge
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| 22 |
+
- mergekit
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| 23 |
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- lazymergekit
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| 24 |
+
- dpo
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| 25 |
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- rlhf
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| 26 |
+
- mlabonne/example
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| 27 |
+
base_model: mlabonne/Daredevil-7B
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| 28 |
+
model-index:
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| 29 |
+
- name: NeuralDaredevil-7B
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| 30 |
+
results:
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| 31 |
+
- task:
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| 32 |
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type: text-generation
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| 33 |
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name: Text Generation
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| 34 |
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dataset:
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| 35 |
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name: AI2 Reasoning Challenge (25-Shot)
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| 36 |
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type: ai2_arc
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| 37 |
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config: ARC-Challenge
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| 38 |
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split: test
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| 39 |
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args:
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| 40 |
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num_few_shot: 25
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| 41 |
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metrics:
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| 42 |
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- type: acc_norm
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| 43 |
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value: 69.88
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| 44 |
+
name: normalized accuracy
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| 45 |
+
source:
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| 46 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralDaredevil-7B
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| 47 |
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name: Open LLM Leaderboard
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| 48 |
+
- task:
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| 49 |
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type: text-generation
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| 50 |
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name: Text Generation
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| 51 |
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dataset:
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| 52 |
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name: HellaSwag (10-Shot)
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| 53 |
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type: hellaswag
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| 54 |
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split: validation
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| 55 |
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args:
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| 56 |
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num_few_shot: 10
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| 57 |
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metrics:
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| 58 |
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- type: acc_norm
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| 59 |
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value: 87.62
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| 60 |
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name: normalized accuracy
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| 61 |
+
source:
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| 62 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralDaredevil-7B
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| 63 |
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name: Open LLM Leaderboard
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| 64 |
+
- task:
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| 65 |
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type: text-generation
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| 66 |
+
name: Text Generation
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| 67 |
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dataset:
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| 68 |
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name: MMLU (5-Shot)
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| 69 |
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type: cais/mmlu
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| 70 |
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config: all
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| 71 |
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split: test
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| 72 |
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args:
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| 73 |
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num_few_shot: 5
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| 74 |
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metrics:
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| 75 |
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- type: acc
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| 76 |
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value: 65.12
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| 77 |
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name: accuracy
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| 78 |
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source:
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| 79 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralDaredevil-7B
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name: Open LLM Leaderboard
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- task:
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| 82 |
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type: text-generation
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| 83 |
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name: Text Generation
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dataset:
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| 85 |
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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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| 92 |
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- type: mc2
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value: 66.85
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| 94 |
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source:
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| 95 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralDaredevil-7B
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| 96 |
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name: Open LLM Leaderboard
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| 97 |
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- task:
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| 98 |
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type: text-generation
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name: Text Generation
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dataset:
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| 101 |
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name: Winogrande (5-shot)
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type: winogrande
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| 103 |
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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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| 108 |
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- type: acc
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| 109 |
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value: 82.08
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| 110 |
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name: accuracy
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| 111 |
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source:
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| 112 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralDaredevil-7B
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name: Open LLM Leaderboard
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| 114 |
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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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| 118 |
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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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| 126 |
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value: 73.16
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| 127 |
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name: accuracy
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| 128 |
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source:
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| 129 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralDaredevil-7B
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| 130 |
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name: Open LLM Leaderboard
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| 131 |
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---
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| 133 |
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# NeuralDaredevil-7B
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NeuralDaredevil-7B is a DPO fine-tune of [mlabonne/Daredevil-7B](https://huggingface.co/mlabonne/Daredevil-7B) using the [argilla/distilabel-intel-orca-dpo-pairs](https://huggingface.co/datasets/argilla/distilabel-intel-orca-dpo-pairs) preference dataset and my DPO notebook from [this article](https://towardsdatascience.com/fine-tune-a-mistral-7b-model-with-direct-preference-optimization-708042745aac).
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Thanks [Argilla](https://huggingface.co/argilla) for providing the dataset and the training recipe [here](https://huggingface.co/argilla/distilabeled-Marcoro14-7B-slerp). πͺ
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## π Evaluation
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### Nous
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The evaluation was performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval) on Nous suite.
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| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
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| 148 |
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|---|---:|---:|---:|---:|---:|
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| [**mlabonne/NeuralDaredevil-7B**](https://huggingface.co/mlabonne/NeuralDaredevil-7B) [π](https://gist.github.com/mlabonne/cbeb077d1df71cb81c78f742f19f4155) | **59.39** | **45.23** | **76.2** | **67.61** | **48.52** |
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| 150 |
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| [mlabonne/Beagle14-7B](https://huggingface.co/mlabonne/Beagle14-7B) [π](https://gist.github.com/mlabonne/f5a5bf8c0827bbec2f05b97cc62d642c) | 59.4 | 44.38 | 76.53 | 69.44 | 47.25 |
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| [argilla/distilabeled-Marcoro14-7B-slerp](https://huggingface.co/argilla/distilabeled-Marcoro14-7B-slerp) [π](https://gist.github.com/mlabonne/9082c4e59f4d3f3543c5eda3f4807040) | 58.93 | 45.38 | 76.48 | 65.68 | 48.18 |
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| 152 |
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| [mlabonne/NeuralMarcoro14-7B](https://huggingface.co/mlabonne/NeuralMarcoro14-7B) [π](https://gist.github.com/mlabonne/b31572a4711c945a4827e7242cfc4b9d) | 58.4 | 44.59 | 76.17 | 65.94 | 46.9 |
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| 153 |
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| [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) [π](https://gist.github.com/mlabonne/1afab87b543b0717ec08722cf086dcc3) | 53.71 | 44.17 | 73.72 | 52.53 | 44.4 |
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| 154 |
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| [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) [π](https://gist.github.com/mlabonne/88b21dd9698ffed75d6163ebdc2f6cc8) | 52.42 | 42.75 | 72.99 | 52.99 | 40.94 |
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| 155 |
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You can find the complete benchmark on [YALL - Yet Another LLM Leaderboard](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard).
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# [Open LLM Leaderboard](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__NeuralDaredevil-7B)
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| Metric |Value|
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| 163 |
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|---------------------------------|----:|
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| 164 |
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|Avg. |74.12|
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| 165 |
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|AI2 Reasoning Challenge (25-Shot)|69.88|
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| 166 |
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|HellaSwag (10-Shot) |87.62|
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| 167 |
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|MMLU (5-Shot) |65.12|
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| 168 |
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|TruthfulQA (0-shot) |66.85|
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| 169 |
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|Winogrande (5-shot) |82.08|
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| 170 |
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|GSM8k (5-shot) |73.16|
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| 171 |
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## π» Usage
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| 174 |
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```python
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!pip install -qU transformers accelerate
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| 176 |
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| 177 |
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from transformers import AutoTokenizer
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import transformers
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| 179 |
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import torch
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model = "mlabonne/NeuralDaredevil-7B"
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| 182 |
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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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| 185 |
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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| 186 |
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pipeline = transformers.pipeline(
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| 187 |
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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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| 194 |
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print(outputs[0]["generated_text"])
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```
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<p align="center">
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| 198 |
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<a href="https://github.com/argilla-io/distilabel">
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<img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
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</a>
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</p>
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