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  * [ Install  ](https://ai.pydantic.dev/models/cerebras/#install)
  * [ Configuration  ](https://ai.pydantic.dev/models/cerebras/#configuration)
  * [ Environment variable  ](https://ai.pydantic.dev/models/cerebras/#environment-variable)
  * [ provider argument  ](https://ai.pydantic.dev/models/cerebras/#provider-argument)


  1. [ Pydantic AI  ](https://ai.pydantic.dev/)
  2. [ Documentation  ](https://ai.pydantic.dev/agent/)
  3. [ Models & Providers  ](https://ai.pydantic.dev/models/overview/)


# Cerebras
## Install
To use `CerebrasModel`, you need to either install `pydantic-ai`, or install `pydantic-ai-slim` with the `cerebras` optional group:
[pip](https://ai.pydantic.dev/models/cerebras/#__tabbed_1_1)[uv](https://ai.pydantic.dev/models/cerebras/#__tabbed_1_2)
```
pip install "pydantic-ai-slim[cerebras]"

```

```
uv add "pydantic-ai-slim[cerebras]"

```

## Configuration
To use [Cerebras](https://cerebras.ai/) through their API, go to [cloud.cerebras.ai](https://cloud.cerebras.ai/?utm_source=3pi_pydantic-ai&utm_campaign=partner_doc) and generate an API key.
For a list of available models, see the [Cerebras models documentation](https://inference-docs.cerebras.ai/models).
## Environment variable
Once you have the API key, you can set it as an environment variable:
```
export CEREBRAS_API_KEY='your-api-key'

```

You can then use `CerebrasModel` by name:
```
from pydantic_ai import Agent

agent = Agent('cerebras:llama-3.3-70b')
...

```

Or initialise the model directly with just the model name:
```
from pydantic_ai import Agent
from pydantic_ai.models.cerebras import CerebrasModel

model = CerebrasModel('llama-3.3-70b')
agent = Agent(model)
...

```

##  `provider` argument
You can provide a custom `Provider` via the `provider` argument:
```
from pydantic_ai import Agent
from pydantic_ai.models.cerebras import CerebrasModel
from pydantic_ai.providers.cerebras import CerebrasProvider

model = CerebrasModel(
    'llama-3.3-70b', provider=CerebrasProvider(api_key='your-api-key')
)
agent = Agent(model)
...

```

You can also customize the `CerebrasProvider` with a custom `httpx.AsyncClient`:
```
from httpx import AsyncClient

from pydantic_ai import Agent
from pydantic_ai.models.cerebras import CerebrasModel
from pydantic_ai.providers.cerebras import CerebrasProvider

custom_http_client = AsyncClient(timeout=30)
model = CerebrasModel(
    'llama-3.3-70b',
    provider=CerebrasProvider(api_key='your-api-key', http_client=custom_http_client),
)
agent = Agent(model)
...

```

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