Llama-3-6B-Instruct-pruned
Experimental
Using PruneMe to find minimal average distance. Thank you for awesome toolkit @arcee-ai !
It shows pruning the 22-30 layer is the best option, but I'm worried about drasitical change between 22 to 23.
Disclaimer
I haven't done any post-training (called 'healing' process as the paper suggests), will do it later but no guarantee at all.
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the passthrough merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
- layer_range: [0, 21]
model:
model:
path: meta-llama/Meta-Llama-3-8B-Instruct
- sources:
- layer_range: [29, 32]
model:
model:
path: meta-llama/Meta-Llama-3-8B-Instruct
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Model tree for kuotient/Llama-3-6B-Instruct-pruned
Base model
meta-llama/Meta-Llama-3-8B-Instruct