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# Phi-3 / Phi-4

[Phi-3](https://azure.microsoft.com/en-us/products/phi) and [Phi-4](https://azure.microsoft.com/en-us/products/phi) are Microsoft's high-capability small language models using a shared transformer decoder architecture (`Phi3ForCausalLM`). Phi-4-mini and Phi-4 achieve strong benchmark results at relatively small parameter counts.

|                  |                                               |
| ---------------- | --------------------------------------------- |
| **Task**         | Text Generation                               |
| **Architecture** | `Phi3ForCausalLM`                             |
| **Parameters**   | 3.8B – 14B                                    |
| **HF Org**       | [microsoft](https://huggingface.co/microsoft) |

## Available Models

* **Phi-4**: 14B
* **Phi-4-mini-instruct**: 3.8B
* **Phi-3.5-mini-instruct**: 3.8B
* **Phi-3-medium-128k-instruct**: 14B
* **Phi-3-mini-128k-instruct**: 3.8B
* **Phi-3-mini-4k-instruct**: 3.8B

## Architecture

* `Phi3ForCausalLM`

## Example HF Models

| Model                      | HF ID                                                                                                 |
| -------------------------- | ----------------------------------------------------------------------------------------------------- |
| Phi-4                      | [`microsoft/Phi-4`](https://huggingface.co/microsoft/Phi-4)                                           |
| Phi-4-mini-instruct        | [`microsoft/Phi-4-mini-instruct`](https://huggingface.co/microsoft/Phi-4-mini-instruct)               |
| Phi-3-mini-4k-instruct     | [`microsoft/Phi-3-mini-4k-instruct`](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)         |
| Phi-3-mini-128k-instruct   | [`microsoft/Phi-3-mini-128k-instruct`](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct)     |
| Phi-3-medium-128k-instruct | [`microsoft/Phi-3-medium-128k-instruct`](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct) |

## Example Recipes

| Recipe                                                                                                                                           | Description                         |
| ------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------- |
| [phi\_4\_squad.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/phi/phi_4_squad.yaml)                              | SFT — Phi-4 on SQuAD                |
| [phi\_4\_squad\_peft.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/phi/phi_4_squad_peft.yaml)                   | LoRA — Phi-4 on SQuAD               |
| [phi\_3\_mini\_it\_squad.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/phi/phi_3_mini_it_squad.yaml)            | SFT — Phi-3-mini Instruct on SQuAD  |
| [phi\_3\_mini\_it\_squad\_peft.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/phi/phi_3_mini_it_squad_peft.yaml) | LoRA — Phi-3-mini Instruct on SQuAD |

## Try with NeMo AutoModel

**1. Install** ([full instructions](/get-started/installation)):

```bash
pip install nemo-automodel
```

**2. Clone the repo** to get the example recipes:

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

**3. Run the recipe** from inside the repo:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/phi/phi_4_squad.yaml
```

**1. Pull the container** and mount a checkpoint directory:

```bash
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):

```bash
cd /opt/Automodel
```

**3. Run the recipe**:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/phi/phi_4_squad.yaml
```

See the [Installation Guide](/get-started/installation) and [LLM Fine-Tuning Guide](/recipes-e2e-examples/sft-peft).

## Fine-Tuning

See the [LLM Fine-Tuning Guide](/recipes-e2e-examples/sft-peft).

## Hugging Face Model Cards

* [microsoft/Phi-4](https://huggingface.co/microsoft/Phi-4)
* [microsoft/Phi-4-mini-instruct](https://huggingface.co/microsoft/Phi-4-mini-instruct)
* [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)