39 lines
1.3 KiB
Markdown
39 lines
1.3 KiB
Markdown
---
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license: cc-by-4.0
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language:
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- en
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tags:
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- merge
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---
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<!-- header start -->
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# Model Description
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This model uses the `Slerp` merge method from 2 models:
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1. [openchat/openchat-3.5-1210](https://huggingface.co/openchat/openchat-3.5-1210)
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2. [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha)
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- base model: [openchat/openchat-3.5-1210](https://huggingface.co/openchat/openchat-3.5-1210)
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I SLERPed these two together because they're both OpenChat-ish models. Fundamentally, OpenChat-3.5-1210 appears to be trained similarly to OpenChat-3.5 but now with [Feedback-Collection](https://huggingface.co/datasets/kaist-ai/Feedback-Collection)
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and [a de-contaminated Capybara](https://huggingface.co/datasets/LDJnr/Capybara). Starling is OpenChat-3.5 but trained with a novel training method on the Nectar set.
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My hope is that a SLERP between the two retains the benefits of both.
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The yaml config file for this model is here:
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```yaml
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slices:
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- sources:
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- model: openchat/openchat-3.5-1210
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layer_range: [0, 32]
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- model: berkeley-nest/Starling-LM-7B-alpha
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layer_range: [0, 32]
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merge_method: slerp
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base_model: openchat/openchat-3.5-1210
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parameters:
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t:
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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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``` |