def load(cls, name, src=None, api_key=None, alias=None, **kwargs):
"""
Loads a model and Interface from an external source repo
Parameters:
name (str): the name of the model (e.g. "gpt2"), can include the `src` as prefix (e.g. "huggingface/gpt2")
src (str): the source of the model: `huggingface` or `gradio` (or empty if source is provided as a prefix in `name`)
api_key (str): optional api key for use with Hugging Face Model Hub
alias (str): optional, used as the name of the loaded model instead of the default name
Returns:
(Interface): an Interface object for the given model
"""
interface_info = load_interface(name, src, api_key, alias)
interface_info.update(kwargs)
return cls(**interface_info)
def load(cls, name, src=None, api_key=None, alias=None, **kwargs):
"""
Class method to construct an Interface from an external source repository, such as huggingface.
Parameters:
name (str): the name of the model (e.g. "gpt2"), can include the `src` as prefix (e.g. "huggingface/gpt2")
src (str): the source of the model: `huggingface` or `gradio` (or empty if source is provided as a prefix in `name`)
api_key (str): optional api key for use with Hugging Face Model Hub
alias (str): optional, used as the name of the loaded model instead of the default name
Returns:
(gradio.Interface): a Gradio Interface object for the given model
"""
interface_info = load_interface(name, src, api_key, alias)
# create a dictionary of kwargs without overwriting the original interface_info dict because it is mutable
# and that can cause some issues since the internal prediction function may rely on the original interface_info dict
kwargs = dict(interface_info, **kwargs)
return cls(**kwargs)
def load(
cls,
name: str,
src: Optional[str] = None,
api_key: Optional[str] = None,
alias: Optional[str] = None,
**kwargs,
) -> Interface:
"""
Class method to construct an Interface from an external source repository, such as huggingface.
Parameters:
name (str): the name of the model (e.g. "gpt2"), can include the `src` as prefix (e.g. "huggingface/gpt2")
src (str): the source of the model: `huggingface` or `gradio` (or empty if source is provided as a prefix in `name`)
api_key (str): optional api key for use with Hugging Face Model Hub
alias (str): optional, used as the name of the loaded model instead of the default name
Returns:
(gradio.Interface): a Gradio Interface object for the given model
"""
interface_info = load_interface(name, src, api_key, alias)
kwargs = dict(interface_info, **kwargs)
interface = cls(**kwargs)
interface.api_mode = True # So interface doesn't run pre/postprocess.
return interface