this can take several minutes to download big files!llm = Petals(model_name="bigscience/bloom-petals")    Downloading:   1%|‚ñè                        | 40.8M/7.19G [00:24<15:44, 7.57MB/s]Create a Prompt Template‚ÄãWe 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‚Äãllm_chain = LLMChain(prompt=prompt, llm=llm)Run the LLMChain‚ÄãProvide 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 LLMChainCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
Petals runs 100B+ language models at home, BitTorrent-style.
Petals runs 100B+ language models at home, BitTorrent-style. ->: this can take several minutes to download big files!llm = Petals(model_name="bigscience/bloom-petals")    Downloading:   1%|‚ñè                        | 40.8M/7.19G [00:24<15:44, 7.57MB/s]Create a Prompt Template‚ÄãWe 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‚Äãllm_chain = LLMChain(prompt=prompt, llm=llm)Run the LLMChain‚ÄãProvide 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 LLMChainCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.