Petals#

Petals runs 100B+ language models at home, BitTorrent-style.

This notebook goes over how to use Langchain with Petals.

Install petals#

The petals package is required to use the Petals API. Install petals using pip3 install petals.

!pip3 install petals

Imports#

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

Set the Environment API Key#

Make sure to get your API key from Huggingface.

from getpass import getpass

HUGGINGFACE_API_KEY = getpass()

os.environ["HUGGINGFACE_API_KEY"] = HUGGINGFACE_API_KEY

Create the Petals instance#

You can specify different parameters such as the model name, max new tokens, temperature, etc.

# this can take several minutes to download big files!

llm = Petals(model_name="bigscience/bloom-petals")

Downloading:   1%|▏                        | 40.8M/7.19G [00:24<15:44, 7.57MB/s]

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)