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.
For Apple Silicon(M1/M2) users please follow this guide https://github.com/bigscience-workshop/petals/issues/147#issuecomment-1365379642 to install petals
!pip3 install petals
Imports
import os
from langchain.chains import LLMChain
from langchain_community.llms import Petals
from langchain_core.prompts import PromptTemplate
API Reference:
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.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)