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--- |
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license: apache-2.0 |
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tags: |
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- MoE |
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- merge |
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- mergekit |
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- Mistral |
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- Microsoft/WizardLM-2-7B |
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--- |
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# WizardLM-2-4x7B-MoE |
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The model is currently uploading and should be available in a couple of hours! |
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This is an experimental MoE model made with [Mergekit](https://github.com/arcee-ai/mergekit). It was made by combining four [WizardLM-2-7B](https://huggingface.co./microsoft/WizardLM-2-7B) models using the random gate mode. Please be sure to set experts per token to 4 for the best results! Context length should be the same as Mistral-7B-Instruct-v0.1 (8k tokens). For instruction templates, Vicuna-v1.1 is recommended. |
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# Quanitized versions |
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Hopefully coming soon. |
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# Evaluation |
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I don't expect this model to be that great since it's something that I made as an experiment. However, I will submit it to the Open LLM Leaderboard to see how it matches up against some other models (particularly WizardLM-2-7B and WizardLM-2-70B). |
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# Mergekit config |
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``` |
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base_model: models/WizardLM-2-7B |
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gate_mode: random |
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dtype: float16 |
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experts_per_token: 4 |
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experts: |
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- source_model: models/WizardLM-2-7B |
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- source_model: models/WizardLM-2-7B |
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- source_model: models/WizardLM-2-7B |
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- source_model: models/WizardLM-2-7B |
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``` |
