> ## Documentation Index
> Fetch the complete documentation index at: https://docs.adaptive-ml.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Model loading guide

> Load a model in a custom recipe

## Loading a model

To load a model in a custom recipe, you should use the harmony client and provide the model path to the `model` method:

```python theme={null}
from adaptive_harmony.runtime import recipe_main, RecipeContext

@recipe_main
async def main(ctx: RecipeContext):
    client = ctx.client
    model = await client.model("model_registry://llama-3.1-8b-instruct").tp(1).spawn_train("model", 4096) 
```

## Passing models as input

If a model should be given as input, there are two ways to give it.

### From the context

In custom recipes, you are always asked to input a model to train. This model is retrieved from the recipe context in the attribute `model_to_train`.

The model can then by loaded using the client. Make sure to pass the model `path` attribute to the harmony client and not the model itself.

```python theme={null}
from adaptive_harmony.runtime import recipe_main, RecipeContext

@recipe_main
async def main(ctx: RecipeContext):
    client = ctx.client
    assert ctx.model_to_train, "Model must be set for training"
    print("Model To Train: {ctx.model_to_train}")

    model = await client.model(ctx.model_to_train.path).tp(ctx.world_size).spawn_train("model", 4096) 
```

### From the config

In custom recipes, you can pass models in the recipe config. The model is then loaded by giving its path to the harmony client.

```python theme={null}
from typing import Annotated
from adaptive_harmony import InputConfig, AdaptiveModel

class MyConfig(InputConfig):
    judge_model: AdaptiveModel

@recipe_main
async def main(config: InputConfig, ctx: RecipeContext):
    client = ctx.client
    print("Judge Model: {config.judge_model}")

    model = await client.model(config.judge_model.path).tp(1).spawn_train("model", 4096) 
```

## Load a model from Hugging Face

Use `load_from_hf()` to load models directly from Hugging Face if you have an internet connection:

```python theme={null}
from adaptive_harmony.core.dataset import load_from_hf

model = load_from_hf("mistralai/Mistral-7B-Instruct-v0.3")
```