pyvene.models.configuration_intervenable_model.IntervenableConfig

class IntervenableConfig(representations=[(0, 'block_output', 'pos', 1, None, None, None, None, None, None, None, None, None, None)], intervention_types=<class 'pyvene.models.interventions.VanillaIntervention'>, mode='parallel', sorted_keys=None, model_type=None, intervention_dimensions=None, intervention_constant_sources=None, **kwargs)

Bases: PretrainedConfig

__init__(representations=[(0, 'block_output', 'pos', 1, None, None, None, None, None, None, None, None, None, None)], intervention_types=<class 'pyvene.models.interventions.VanillaIntervention'>, mode='parallel', sorted_keys=None, model_type=None, intervention_dimensions=None, intervention_constant_sources=None, **kwargs)

Methods

__init__([representations, ...])
add_intervention(representations)
dict_torch_dtype_to_str(d)	Checks whether the passed dictionary and its nested dicts have a torch_dtype key and if it's not None, converts torch.dtype to a string of just the type.
from_dict(config_dict, **kwargs)	Instantiates a [PretrainedConfig] from a Python dictionary of parameters.
from_json_file(json_file)	Instantiates a [PretrainedConfig] from the path to a JSON file of parameters.
from_pretrained(pretrained_model_name_or_path)	Instantiate a [PretrainedConfig] (or a derived class) from a pretrained model configuration.
get_config_dict(...)	From a pretrained_model_name_or_path, resolve to a dictionary of parameters, to be used for instantiating a [PretrainedConfig] using from_dict.
get_text_config([decoder])	Returns the config that is meant to be used with text IO.
push_to_hub(repo_id[, use_temp_dir, ...])	Upload the configuration file to the 🤗 Model Hub.
register_for_auto_class([auto_class])	Register this class with a given auto class.
save_pretrained(save_directory[, push_to_hub])	Save a configuration object to the directory save_directory, so that it can be re-loaded using the [~PretrainedConfig.from_pretrained] class method.
to_dict()	Serializes this instance to a Python dictionary.
to_diff_dict()	Removes all attributes from config which correspond to the default config attributes for better readability and serializes to a Python dictionary.
to_json_file(json_file_path[, use_diff])	Save this instance to a JSON file.
to_json_string([use_diff])	Serializes this instance to a JSON string.
update(config_dict)	Updates attributes of this class with attributes from config_dict.
update_from_string(update_str)	Updates attributes of this class with attributes from update_str.

Attributes

attribute_map
is_composition
model_type
name_or_path
num_labels	int: The number of labels for classification models.
use_return_dict	bool: Whether or not return [~utils.ModelOutput] instead of tuples.