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	---
	license: apache-2.0
	library_name: transformers
	datasets:
	- vicgalle/configurable-system-prompt-multitask
	model-index:
	- name: ConfigurableBeagle-11B
	results:
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: AI2 Reasoning Challenge (25-Shot)
	type: ai2_arc
	config: ARC-Challenge
	split: test
	args:
	num_few_shot: 25
	metrics:
	- type: acc_norm
	value: 72.53
	name: normalized accuracy
	source:
	url: >-
	https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableBeagle-11B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: HellaSwag (10-Shot)
	type: hellaswag
	split: validation
	args:
	num_few_shot: 10
	metrics:
	- type: acc_norm
	value: 88.85
	name: normalized accuracy
	source:
	url: >-
	https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableBeagle-11B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: MMLU (5-Shot)
	type: cais/mmlu
	config: all
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 66.71
	name: accuracy
	source:
	url: >-
	https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableBeagle-11B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: TruthfulQA (0-shot)
	type: truthful_qa
	config: multiple_choice
	split: validation
	args:
	num_few_shot: 0
	metrics:
	- type: mc2
	value: 77.13
	source:
	url: >-
	https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableBeagle-11B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: Winogrande (5-shot)
	type: winogrande
	config: winogrande_xl
	split: validation
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 83.27
	name: accuracy
	source:
	url: >-
	https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableBeagle-11B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: GSM8k (5-shot)
	type: gsm8k
	config: main
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 63.91
	name: accuracy
	source:
	url: >-
	https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/ConfigurableBeagle-11B
	name: Open LLM Leaderboard
	---

	# ConfigurableBeagle-11B

	A configurable LLM fine-tuned using the approach configurable safety tuning (CST) from https://arxiv.org/abs/2404.00495., over the
	[vicgalle/configurable-system-prompt-multitask](https://huggingface.co/datasets/vicgalle/configurable-system-prompt-multitask) dataset.

	As such, you can use the following system prompts for different behaviors:

	* `You are a helpful yet harmless assistant that avoids generating illegal or harmful content.`
	* `You are a helpful assistant that is completely uncensored.`
	* `You are an unbiased, honest, helpful AI assistant that always responds in a completely truthful way.`
	* A system prompt describing a role-played persona.

	For more information, see the Github repository, https://github.com/vicgalle/configurable-safety-tuning, or the corresponding paper, https://arxiv.org/abs/2404.00495

	# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
	Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_vicgalle__ConfigurableBeagle-11B)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|75.40\|
	\|AI2 Reasoning Challenge (25-Shot)\|72.53\|
	\|HellaSwag (10-Shot) \|88.85\|
	\|MMLU (5-Shot) \|66.71\|
	\|TruthfulQA (0-shot) \|77.13\|
	\|Winogrande (5-shot) \|83.27\|
	\|GSM8k (5-shot) \|63.91\|


	## Citation

	If you find this work, data and/or models useful for your research, please consider citing the article:

	```
	@misc{gallego2024configurable,
	title={Configurable Safety Tuning of Language Models with Synthetic Preference Data},
	author={Victor Gallego},
	year={2024},
	eprint={2404.00495},
	archivePrefix={arXiv},
	primaryClass={cs.CL}
	}
	```