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)