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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)