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MosaicML

MosaicML 提供托管推理服务。您可以使用各种开源模型,或部署您自己的模型。

此示例介绍如何使用 LangChain 与 MosaicML 推理进行文本补全交互。

# sign up for an account: https://forms.mosaicml.com/demo?utm_source=langchain

from getpass import getpass

MOSAICML_API_TOKEN = getpass()
import os

os.environ["MOSAICML_API_TOKEN"] = MOSAICML_API_TOKEN
from langchain.chains import LLMChain
from langchain_community.llms import MosaicML
from langchain_core.prompts import PromptTemplate
template = """Question: {question}"""

prompt = PromptTemplate.from_template(template)
llm = MosaicML(inject_instruction_format=True, model_kwargs={"max_new_tokens": 128})
llm_chain = LLMChain(prompt=prompt, llm=llm)
question = "What is one good reason why you should train a large language model on domain specific data?"

llm_chain.run(question)

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您也可以在 GitHub 上留下详细的反馈 在 GitHub 上.