property lc_attributes: Dict#
Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]#
Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]#
Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool#
Return whether or not the class is serializable.
pydantic model langchain.llms.GPT4All[source]#
Wrapper around GPT4All language models.
To use, you should have the gpt4all python package installed, the
pre-trained model file, and the model’s config information.
Example
from langchain.llms import GPT4All
model = GPT4All(model="./models/gpt4all-model.bin", n_ctx=512, n_threads=8)
# Simplest invocation
response = model("Once upon a time, ")
Validators
raise_deprecation » all fields
set_verbose » verbose
validate_environment » all fields
field allow_download: bool = False#
If model does not exist in ~/.cache/gpt4all/, download it.
field context_erase: float = 0.5#
Leave (n_ctx * context_erase) tokens
starting from beginning if the context has run out.
field echo: Optional[bool] = False#
Whether to echo the prompt.
field embedding: bool = False#
Use embedding mode only.
field f16_kv: bool = False#
Use half-precision for key/value cache.
field logits_all: bool = False#
Return logits for all tokens, not just the last token.
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html