README.md

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

---
# merged

This is a "merge" of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
It is a prune of Meta-Llama-3-8B-Instruct down to 20 layers, or about 5.4B parameter.
Mostly, this is a test of pruning & healing an instruct-tuned model.
THIS MODEL HAS NOT BEEN HEALED. It is presently unusable. The healed version will be in a different repository.
This size should allow bf16 inference on 24GB VRAM, Q8 or Q6 inference on 6GB VRAM, Q5 inference on 4GB VRAM, and fine-tuning ... well, with less VRAM than an 8B model.

## 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, 16]
    model: meta-llama/Meta-Llama-3-8B-Instruct
- sources:
  - layer_range: [20, 21]
    model: meta-llama/Meta-Llama-3-8B-Instruct
- sources:
  - layer_range: [29, 32]
    model: meta-llama/Meta-Llama-3-8B-Instruct
```