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+ Quantization made by Richard Erkhov.
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+
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+ [Github](https://github.com/RichardErkhov)
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+
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+ [Discord](https://discord.gg/pvy7H8DZMG)
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+
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+ [Request more models](https://github.com/RichardErkhov/quant_request)
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+
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+
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+ NeuralDaredevil-7B - bnb 4bits
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+ - Model creator: https://huggingface.co/mlabonne/
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+ - Original model: https://huggingface.co/mlabonne/NeuralDaredevil-7B/
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+
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+
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+
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+
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+ Original model description:
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+ ---
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+ license: cc-by-nc-4.0
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+ tags:
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+ - merge
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+ - mergekit
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+ - lazymergekit
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+ - dpo
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+ - rlhf
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+ - mlabonne/example
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+ base_model: mlabonne/Daredevil-7B
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+ model-index:
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+ - name: NeuralDaredevil-7B
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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: 69.88
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+ name: normalized accuracy
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+ source:
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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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+ 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: 87.62
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+ name: normalized accuracy
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+ source:
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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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+ 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: 65.12
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+ name: accuracy
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+ source:
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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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+ 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: 66.85
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+ source:
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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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+ 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: 82.08
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+ name: accuracy
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+ source:
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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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+ 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: 73.16
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+ name: accuracy
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+ source:
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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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+ ---
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+
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+ ![](https://i.imgur.com/D80Ua7T.png)
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+
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+ # NeuralDaredevil-7B
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+
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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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+
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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). πŸ’ͺ
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+
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+ ## πŸ† Evaluation
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+
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+ ### Nous
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+
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+ The evaluation was performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval) on Nous suite.
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+
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+ | Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
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+ |---|---:|---:|---:|---:|---:|
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+ | [**mlabonne/NeuralDaredevil-7B**](https://huggingface.co/mlabonne/NeuralDaredevil-7B) [πŸ“„](https://gist.github.com/mlabonne/cbeb077d1df71cb81c78f742f19f4155) | **59.39** | **45.23** | **76.2** | **67.61** | **48.52** |
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+ | [mlabonne/Beagle14-7B](https://huggingface.co/mlabonne/Beagle14-7B) [πŸ“„](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) [πŸ“„](https://gist.github.com/mlabonne/9082c4e59f4d3f3543c5eda3f4807040) | 58.93 | 45.38 | 76.48 | 65.68 | 48.18 |
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+ | [mlabonne/NeuralMarcoro14-7B](https://huggingface.co/mlabonne/NeuralMarcoro14-7B) [πŸ“„](https://gist.github.com/mlabonne/b31572a4711c945a4827e7242cfc4b9d) | 58.4 | 44.59 | 76.17 | 65.94 | 46.9 |
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+ | [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) [πŸ“„](https://gist.github.com/mlabonne/1afab87b543b0717ec08722cf086dcc3) | 53.71 | 44.17 | 73.72 | 52.53 | 44.4 |
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+ | [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) [πŸ“„](https://gist.github.com/mlabonne/88b21dd9698ffed75d6163ebdc2f6cc8) | 52.42 | 42.75 | 72.99 | 52.99 | 40.94 |
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+
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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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+
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+ # [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+
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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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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |74.12|
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+ |AI2 Reasoning Challenge (25-Shot)|69.88|
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+ |HellaSwag (10-Shot) |87.62|
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+ |MMLU (5-Shot) |65.12|
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+ |TruthfulQA (0-shot) |66.85|
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+ |Winogrande (5-shot) |82.08|
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+ |GSM8k (5-shot) |73.16|
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+
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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/NeuralDaredevil-7B"
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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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+ ```
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+
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+ <p align="center">
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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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+
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+