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