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# CerebriumAI

`Cerebrium` is an AWS Sagemaker alternative. It also provides API access to several LLM models.

This notebook goes over how to use Langchain with CerebriumAI.

## Install cerebrium

The `cerebrium` package is required to use the `CerebriumAI` API. Install `cerebrium` using `pip3 install cerebrium`.

    # Install the package
    !pip3 install cerebrium

## Imports

    import os
    from langchain.llms import CerebriumAI
    from langchain import PromptTemplate, LLMChain

## Set the Environment API Key

Make sure to get your API key from CerebriumAI. See here. You are given a 1 hour free of serverless GPU compute to test different models.

    os.environ["CEREBRIUMAI_API_KEY"] = "YOUR_KEY_HERE"

## Create the CerebriumAI instance

You can specify different parameters such as the model endpoint url, max length, temperature, etc. You must provide an endpoint url.

    llm = CerebriumAI(endpoint_url="YOUR ENDPOINT URL HERE")

## Create a Prompt Template

We will create a prompt template for Question and Answer.

    template = """Question: {question}

    Answer: Let's think step by step."""

    prompt = PromptTemplate(template=template, input_variables=["question"])

## Initiate the LLMChain

    llm_chain = LLMChain(prompt=prompt, llm=llm)

## Run the LLMChain

Provide a question and run the LLMChain.

    question = "What NFL team won the Super Bowl in the year Justin Beiber was born?"

    llm_chain.run(question)