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.chains import LLMChain
from langchain_community.llms import CerebriumAI
from langchain_core.prompts import PromptTemplate

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.from_template(template)

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)