ComponentsLLMsPetalsOn this pagePetalsPetals 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 petalsImports​import osfrom langchain.llms import Petalsfrom langchain.prompts import PromptTemplatefrom langchain.chains import LLMChainSet the Environment API Key​Make sure to get your API key from Huggingface.from getpass import getpassHUGGINGFACE_API_KEY = getpass()     ········os.environ["HUGGINGFACE_API_KEY"] = HUGGINGFACE_API_KEYCreate 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)PreviousOpenLMNextPipelineAIInstall petalsImportsSet the Environment API KeyCreate the Petals instanceCreate a Prompt TemplateInitiate the LLMChainRun the LLMChain