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MosaicML
MosaicML#
MosaicML offers a managed inference service. You can either use a variety of open source models, or deploy your own.
This example goes over how to use LangChain to interact with MosaicML Inference for text completion.
# 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.llms import MosaicML
from langchain import PromptTemplate, LLMChain
template = """Question: {question}"""
prompt = PromptTemplate(template=template, input_variables=["question"])
llm = MosaicML(inject_instruction_format=True, model_kwargs={'do_sample': False})
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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NLP Cloud
By Harrison Chase
    
      © Copyright 2023, Harrison Chase.
      
  Last updated on Jun 16, 2023.
rtdocs_stable/api.python.langchain.com/en/stable/modules/models/llms/integrations/mosaicml.html