README.md

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

---
# Llama-3-6B-Instruct-pruned
*Experimental*

Using [PruneMe](https://github.com/arcee-ai/PruneMe) to find minimal average distance. Thank you for awesome toolkit @arcee-ai !
<img src="./distance.png" alt="distance" width="390"/>
*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](https://arxiv.org/abs/2403.17887) suggests), will do it later but no guarantee at all.

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/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](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
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
```