52 lines
2.0 KiB
Markdown
52 lines
2.0 KiB
Markdown
---
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datasets:
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- ehartford/dolphin
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- jondurbin/airoboros-2.2.1
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- ehartford/dolphin-coder
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- teknium/openhermes
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- ise-uiuc/Magicoder-OSS-Instruct-75K
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- ise-uiuc/Magicoder-Evol-Instruct-110K
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- LDJnr/Capybara
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language:
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- en
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license: apache-2.0
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---
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This is a pruned version of [cognitivecomputations/dolphin-2.6-mistral-7b-dpo](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo) from 7.24B params to 5.93B params (~ 82%).
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# Steps to replicate:
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Use [laserQlora.ipynb](https://github.com/cognitivecomputations/laserRMT/blob/main/laserQlora.ipynb) from [cognitivecomputations/laserRMT](https://github.com/cognitivecomputations/laserRMT) to determine which layers should be eliminated.
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Replace `model_name = "mistralai/Mistral-7B-v0.1"` with `model_name = "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"`.
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I also ran the script only for `self_attn.v_proj` (so change the script to `layer_types=["self_attn.v_proj"]`)
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Order by snr descending and eliminate top layers using [mergekit](https://github.com/arcee-ai/mergekit).
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The threshold for elimination is up to you, depeding on how many layers you want removed. I decided to remove 6 layers (indexes: 3, 5, 16, 18, 19, 24 )
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Here is the mergekit config:
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```yml
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slices:
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- sources:
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- model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
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layer_range: [0, 3]
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- sources:
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- model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
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layer_range: [4, 5]
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- sources:
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- model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
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layer_range: [6, 16]
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- sources:
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- model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
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layer_range: [17, 18]
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- sources:
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- model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
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layer_range: [20, 24]
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- sources:
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- model: "cognitivecomputations/dolphin-2.6-mistral-7b-dpo"
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layer_range: [25, 32]
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merge_method: passthrough
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dtype: bfloat16
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```
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The model outputted by mergekit with this configuration is this model (dolphin-2.6-mistral-7b-dpo-5.93B). |