metadata

base_model:
  - meta-llama/Meta-Llama-3-8B-Instruct
library_name: transformers
tags:
  - mergekit
  - merge

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:

meta-llama/Meta-Llama-3-8B-Instruct

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