--- license: cc-by-nc-4.0 language: - en tags: - merge base_model: - mistralai/Mistral-7B-Instruct-v0.2 - ehartford/dolphin-2.2.1-mistral-7b - SciPhi/SciPhi-Mistral-7B-32k - ehartford/samantha-1.2-mistral-7b - Arc53/docsgpt-7b-mistral - berkeley-nest/Starling-LM-7B-alpha - Q-bert/MetaMath-Cybertron-Starling - Open-Orca/Mistral-7B-OpenOrca - v1olet/v1olet_marcoroni-go-bruins-merge-7B - beowolx/MistralHermes-CodePro-7B-v1 - TIGER-Lab/MAmmoTH-7B-Mistral - teknium/OpenHermes-2.5-Mistral-7B - Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp - mlabonne/NeuralHermes-2.5-Mistral-7B --- # Update 2023-12-19 In light of [dataset contamination issue among the merged models](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/474) raised by the community in recent days, in particular [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha), [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling), and [janai-hq/trinity-v1](https://huggingface.co/janai-hq/trinity-v1), we decided to remake another model without the models mentioned. Additionally, their CC-by-NC-4.0 license is restrictive and thus are not suitable for an open model. # Model Description This is an experiment to test merging 14 models using DARE TIES 🦙 The merged model is then merged again with [janai-hq/trinity-v1](https://huggingface.co/janai-hq/trinity-v1) using Gradient SLERP. The result is a base model that performs quite well but requires some further instruction fine-tuning. The 14 models are as follows: 1. [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) 2. [ehartford/dolphin-2.2.1-mistral-7b](https://huggingface.co/ehartford/dolphin-2.2.1-mistral-7b) 3. [SciPhi/SciPhi-Mistral-7B-32k](https://huggingface.co/SciPhi/SciPhi-Mistral-7B-32k) 4. [ehartford/samantha-1.2-mistral-7b](https://huggingface.co/ehartford/samantha-1.2-mistral-7b) 5. [Arc53/docsgpt-7b-mistral](https://huggingface.co/Arc53/docsgpt-7b-mistral) 6. [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha) 7. [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling) 8. [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca) 9. [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-7B) 10. [beowolx/MistralHermes-CodePro-7B-v1](https://huggingface.co/beowolx/MistralHermes-CodePro-7B-v1) 11. [TIGER-Lab/MAmmoTH-7B-Mistral](https://huggingface.co/TIGER-Lab/MAmmoTH-7B-Mistral) 12. [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) 13. [Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp](https://huggingface.co/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp) 14. [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B) - base model: [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) The yaml config file for this model is here: ```yaml slices: - sources: - model: EmbeddedLLM/Mistral-7B-Merge-14-v0 layer_range: [0, 32] - model: janai-hq/trinity-v1 layer_range: [0, 32] merge_method: slerp base_model: EmbeddedLLM/Mistral-7B-Merge-14-v0 parameters: t: - filter: self_attn value: [0, 0.5, 0.3, 0.7, 1] - filter: mlp value: [1, 0.5, 0.7, 0.3, 0] - value: 0.5 dtype: bfloat16 ```