--- license: apache-2.0 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 - HuggingFaceH4/zephyr-7b-beta - meta-math/MetaMath-Mistral-7B - Open-Orca/Mistral-7B-OpenOrca - openchat/openchat-3.5-1210 - 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 2024-01-03 Check out our [v0.4 model](https://huggingface.co./EmbeddedLLM/Mistral-7B-Merge-14-v0.4) which is based on this and achieves better average score of 71.19 versus 69.66. # Model Description This is an update to [EmbeddedLLM/Mistral-7B-Merge-14-v0.2](https://huggingface.co./EmbeddedLLM/Mistral-7B-Merge-14-v0.2) that removes potentially TruthfulQA-contaminated models and non-commercially licensed models: 1. [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co./berkeley-nest/Starling-LM-7B-alpha) 2. [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co./Q-bert/MetaMath-Cybertron-Starling) 3. [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co./v1olet/v1olet_marcoroni-go-bruins-merge-7B) This is an experiment to test merging 14 models using DARE TIES 🦙 The result is a base model that performs quite well but may need some further chat 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. [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co./HuggingFaceH4/zephyr-7b-beta) 7. [meta-math/MetaMath-Mistral-7B](https://huggingface.co./meta-math/MetaMath-Mistral-7B) 8. [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co./Open-Orca/Mistral-7B-OpenOrca) 9. [openchat/openchat-3.5-1210](https://huggingface.co./openchat/openchat-3.5-1210) 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) ## Open LLM Leaderboard | | v0.3 | v0.4 | |------------|-------|-------| | Average | 69.66 | 71.19 | | ARC | 65.96 | 66.81 | | HellaSwag | 85.29 | 86.15 | | MMLU | 64.35 | 65.10 | | TruthfulQA | 57.80 | 58.25 | | Winogrande | 78.30 | 80.03 | | GSM8K | 66.26 | 70.81 | ## Chat Template We tried ChatML and Llama-2 chat template, but feel free to try other templates. ## Merge Configuration The merge config file for this model is here: ```yaml models: - model: mistralai/Mistral-7B-v0.1 # no parameters necessary for base model - model: ehartford/dolphin-2.2.1-mistral-7b parameters: weight: 0.08 density: 0.4 - model: SciPhi/SciPhi-Mistral-7B-32k parameters: weight: 0.08 density: 0.4 - model: ehartford/samantha-1.2-mistral-7b parameters: weight: 0.08 density: 0.4 - model: Arc53/docsgpt-7b-mistral parameters: weight: 0.08 density: 0.4 - model: HuggingFaceH4/zephyr-7b-beta parameters: weight: 0.08 density: 0.4 - model: meta-math/MetaMath-Mistral-7B parameters: weight: 0.08 density: 0.4 - model: Open-Orca/Mistral-7B-OpenOrca parameters: weight: 0.08 density: 0.4 - model: openchat/openchat-3.5-1210 parameters: weight: 0.08 density: 0.4 - model: beowolx/MistralHermes-CodePro-7B-v1 parameters: weight: 0.08 density: 0.4 - model: TIGER-Lab/MAmmoTH-7B-Mistral parameters: weight: 0.08 density: 0.4 - model: teknium/OpenHermes-2.5-Mistral-7B parameters: weight: 0.08 density: 0.4 - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp parameters: weight: 0.08 density: 0.4 - model: mlabonne/NeuralHermes-2.5-Mistral-7B parameters: weight: 0.08 density: 0.4 - model: mistralai/Mistral-7B-Instruct-v0.2 parameters: weight: 0.08 density: 0.5 merge_method: dare_ties base_model: mistralai/Mistral-7B-v0.1 parameters: int8_mask: true dtype: bfloat16 ```