Phi | NVIDIA NeMo AutoModel

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:26.04.00

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.