metadata

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. Layers to prune were selected based off of the average distances as follows:

Usage

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

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

Configuration

The following YAML configuration was used to produce this model:

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