Phi#

Microsoft’s Phi are compact, high-capability language models designed to punch above their weight class. Phi-1.5 and Phi-2 use a standard transformer decoder architecture (PhiForCausalLM). For Phi-3 and Phi-4 see Phi-3 / Phi-4.

Task

Text Generation

Architecture

PhiForCausalLM

Parameters

1.3B – 2.7B

HF Org

microsoft

Available Models#

  • Phi-2: 2.7B

  • Phi-1.5: 1.3B

Architecture#

  • PhiForCausalLM

Example HF Models#

Model

HF ID

Phi-2

microsoft/phi-2

Phi-1.5

microsoft/phi-1_5

Example Recipes#

Recipe

Description

phi_2_squad.yaml

SFT — Phi-2 on SQuAD

phi_2_squad_peft.yaml

LoRA — Phi-2 on SQuAD

Try with NeMo AutoModel#

1. Install (full instructions):

pip install nemo-automodel

2. Clone the repo to get the example recipes:

git clone https://github.com/NVIDIA-NeMo/Automodel.git
cd Automodel

3. Run the recipe from inside the repo:

automodel --nproc-per-node=8 examples/llm_finetune/phi/phi_2_squad.yaml
Run with Docker

1. Pull the container and mount a checkpoint directory:

docker run --gpus all -it --rm \
  --shm-size=8g \
  -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
  nvcr.io/nvidia/nemo-automodel:26.02.00

2. Navigate to the AutoModel directory (where the recipes are):

cd /opt/Automodel

3. Run the recipe:

automodel --nproc-per-node=8 examples/llm_finetune/phi/phi_2_squad.yaml

See the Installation Guide and LLM Fine-Tuning Guide.

Fine-Tuning#

See the LLM Fine-Tuning Guide.

Hugging Face Model Cards#