ComponentsLLMsCerebriumAIOn this pageCerebriumAICerebrium 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 packagepip3 install cerebriumImports​import osfrom langchain.llms import CerebriumAIfrom langchain.prompts import PromptTemplatefrom langchain.chains import LLMChainSet 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)PreviousBittensorNextChatGLMInstall cerebriumImportsSet the Environment API KeyCreate the CerebriumAI instanceCreate a Prompt TemplateInitiate the LLMChainRun the LLMChain