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