README.md

---
base_model:
- microsoft/Phi-3-small-8k-instruct
library_name: transformers
tags:
- mergekit
- merge
license: mit
language:
- en
---
# Phi-3-small-8k-instruct: 6 layers pruned

This is a layer-pruned language model created using [mergekit](https://github.com/cg123/mergekit). Layers to prune were selected based off of the average distances as follows:

![image](phi3small.png)

## Usage

While some further pre-training will be good, it seems capable of generating coherent text as is.

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained(
    "microsoft/Phi-3-small-8k-instruct", trust_remote_code=True
)
model = AutoModelForCausalLM.from_pretrained(
    "pszemraj/Phi-3-small-8k-prune6", trust_remote_code=True
)
```

## Merge Details
### Merge Method

This model was merged using the passthrough merge method.

### Models Merged

The following models were included in the merge:
* [microsoft/Phi-3-small-8k-instruct](https://huggingface.co/microsoft/Phi-3-small-8k-instruct)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 25]
    model: microsoft/Phi-3-small-8k-instruct
- sources:
  - layer_range: [31, 32]
    model: microsoft/Phi-3-small-8k-instruct
```