1. Upscale mlabonne/NeuralBeagle14-7B to vicgalle/franken-Beagle-11B. 2. DPO-tune vicgalle/franken-Beagle-11B to vicgalle/NeuralBeagle-11B. 3. Merge vicgalle/NeuralBeagle-11B and jeonsworld/CarbonVillain-en-10.7B-v4. The following models were included in the merge: * vicgalle/NeuralBeagle-11B * jeonsworld/CarbonVillain-en-10.7B-v4 At the time of its creation (21-01-2024), it is the best model in the Open LLM Leaderboard for its size class (10.7B-11B), and also 13B models:
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View details ↗A configurable NousResearch/Hermes-2-Pro-Llama-3-8B fine-tuned using the approach *configurable safety tuning* (CST) from https://arxiv.org/abs/2404.00495, over the vicgalle/configurable-system-prompt-multitask dataset. For more information, see the Github repository, https://github.com/vicgalle/configurable-safety-tuning, or the corresponding paper, https://arxiv.org/abs/2404.00495 This model may be used to generate harmful or offensive material. It has been made publicly available only to serve as a research artifact in the fields of safety and alignment.
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View details ↗The following models were included in the merge: * vicgalle/Configurable-Mistral-7B * kaist-ai/janus-dpo-7b
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View details ↗A configurable Llama-3 fine-tuned using the approach *configurable safety tuning* (CST) from https://arxiv.org/abs/2404.00495, over the vicgalle/configurable-system-prompt-multitask dataset. For more information, see the Github repository, https://github.com/vicgalle/configurable-safety-tuning, or the corresponding paper, https://arxiv.org/abs/2404.00495 This model may be used to generate harmful or offensive material. It has been made publicly available only to serve as a research artifact in the fields of safety and alignment.
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View details ↗This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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View details ↗A configurable Yi.1.5-9B fine-tuned using the approach *configurable safety tuning* (CST) from https://arxiv.org/abs/2404.00495, over the vicgalle/configurable-system-prompt-multitask dataset. For more information, see the Github repository, https://github.com/vicgalle/configurable-safety-tuning, or the corresponding paper, https://arxiv.org/abs/2404.00495 This model may be used to generate harmful or offensive material. It has been made publicly available only to serve as a research artifact in the fields of safety and alignment.
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View details ↗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 dataset. For more information, see the Github repository, https://github.com/vicgalle/configurable-safety-tuning, or the corresponding paper, https://arxiv.org/abs/2404.00495 If you find this work, data and/or models useful for your research, please consider citing the article:
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View details ↗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 dataset. For more information, see the Github repository, https://github.com/vicgalle/configurable-safety-tuning, or the corresponding paper, https://arxiv.org/abs/2404.00495 If you find this work, data and/or models useful for your research, please consider citing the article:
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