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- NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
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- NeuralNovel/Gecko-7B-v0.1-DPO
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tags:
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- mergekit
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- merge
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license: apache-2.0
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datasets:
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---
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![tiger](https://cdn-uploads.huggingface.co/production/uploads/645cfe4603fc86c46b3e46d1/a9GqRTNoGZQsRVU-C6XRO.jpeg)
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# Tiger-7b-v0.1
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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[Join our Discord!](https://discord.gg/Qge8Ds9C)
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## Metrics
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/645cfe4603fc86c46b3e46d1/Z58bB5sYr3pyE2Ilbk7Dk.png)
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### Merge Method
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This model was merged using the SLERP merge method.
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### Models Merged
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The following models were included in the merge:
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* [NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story](https://huggingface.co/NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story)
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* [NeuralNovel/Gecko-7B-v0.1-DPO](https://huggingface.co/NeuralNovel/Gecko-7B-v0.1-DPO)
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# merge
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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slices:
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- sources:
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- model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
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layer_range: [0, 32]
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- model: NeuralNovel/Gecko-7B-v0.1-DPO
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layer_range: [0, 32]
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merge_method: slerp
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base_model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
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parameters:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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---
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license: apache-2.0
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datasets:
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- NeuralNovel/Neural-DPO
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![tiger](https://cdn-uploads.huggingface.co/production/uploads/645cfe4603fc86c46b3e46d1/a9GqRTNoGZQsRVU-C6XRO.jpeg)
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# Tiger-7b-v0.1-Laser-DPO
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