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# Phi-3-Small

[Phi-3-Small](https://azure.microsoft.com/en-us/products/phi) is Microsoft's 7B model using a distinct `Phi3SmallForCausalLM` architecture with blocksparse attention, separate from the standard Phi-3 family.

|                  |                                               |
| ---------------- | --------------------------------------------- |
| **Task**         | Text Generation                               |
| **Architecture** | `Phi3SmallForCausalLM`                        |
| **Parameters**   | 7B                                            |
| **HF Org**       | [microsoft](https://huggingface.co/microsoft) |

## Available Models

* **Phi-3-small-8k-instruct**: 7B, 8K context
* **Phi-3-small-128k-instruct**: 7B, 128K context

## Architecture

* `Phi3SmallForCausalLM`

## Example HF Models

| Model                     | HF ID                                                                                               |
| ------------------------- | --------------------------------------------------------------------------------------------------- |
| Phi-3-small-8k-instruct   | [`microsoft/Phi-3-small-8k-instruct`](https://huggingface.co/microsoft/Phi-3-small-8k-instruct)     |
| Phi-3-small-128k-instruct | [`microsoft/Phi-3-small-128k-instruct`](https://huggingface.co/microsoft/Phi-3-small-128k-instruct) |

## Try with NeMo AutoModel

Install NeMo AutoModel and follow the fine-tuning guide to configure a recipe for this model.

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

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

**2. Clone the repo** to get example recipes you can adapt:

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

**3. Fine-tune** by adapting a base LLM recipe — override the model ID on the CLI:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/llama3_2/llama3_2_1b_squad.yaml \
  --model.pretrained_model_name_or_path <MODEL_HF_ID>
```

Replace `<MODEL_HF_ID>` with the model ID from **Example HF Models** above.

**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:26.06.00
```

**2.** The recipes are at `/opt/Automodel/examples/` — navigate there:

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

**3. Fine-tune**:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/llama3_2/llama3_2_1b_squad.yaml \
  --model.pretrained_model_name_or_path <MODEL_HF_ID>
```

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-3-small-8k-instruct](https://huggingface.co/microsoft/Phi-3-small-8k-instruct)
* [microsoft/Phi-3-small-128k-instruct](https://huggingface.co/microsoft/Phi-3-small-128k-instruct)