GPT4All
GitHub:nomic-ai/gpt4all an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue.
This example goes over how to use LangChain to interact with GPT4All
models.
%pip install --upgrade --quiet gpt4all > /dev/null
Note: you may need to restart the kernel to use updated packages.
Import GPT4All
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
from langchain.chains import LLMChain
from langchain_community.llms import GPT4All
from langchain_core.prompts import PromptTemplate
Set Up Question to pass to LLM
template = """Question: {question}
Answer: Let's think step by step."""
prompt = PromptTemplate.from_template(template)
Specify Model
To run locally, download a compatible ggml-formatted model.
The gpt4all page has a useful Model Explorer
section:
- Select a model of interest
- Download using the UI and move the
.bin
to thelocal_path
(noted below)
For more info, visit https://github.com/nomic-ai/gpt4all.
local_path = (
"./models/ggml-gpt4all-l13b-snoozy.bin" # replace with your desired local file path
)
# Callbacks support token-wise streaming
callbacks = [StreamingStdOutCallbackHandler()]
# Verbose is required to pass to the callback manager
llm = GPT4All(model=local_path, callbacks=callbacks, verbose=True)
# If you want to use a custom model add the backend parameter
# Check https://docs.gpt4all.io/gpt4all_python.html for supported backends
llm = GPT4All(model=local_path, backend="gptj", callbacks=callbacks, verbose=True)
llm_chain = LLMChain(prompt=prompt, llm=llm)
question = "What NFL team won the Super Bowl in the year Justin Bieber was born?"
llm_chain.run(question)
Justin Bieber was born on March 1, 1994. In 1994, The Cowboys won Super Bowl XXVIII.