configs

Helper module for using model configs. For more information, see the corresponding Python documentation.

Example: Load an AutoConfig.

import { AutoConfig } from '@xenova/transformers';
let config = await AutoConfig.from_pretrained('bert-base-uncased');
console.log(config);
// PretrainedConfig {
//   "model_type": "bert",
//   "is_encoder_decoder": false,
//   "architectures": [
//       "BertForMaskedLM"
//   ],
//   "vocab_size": 30522
//   "num_attention_heads": 12,
//   "num_hidden_layers": 12,
//   "hidden_size": 768,
//   "max_position_embeddings": 512,
//   ...
// }

• configs
  • static
    • .PretrainedConfig
      • new PretrainedConfig(configJSON)
      • .from_pretrained(pretrained_model_name_or_path, options) ⇒ Promise.<PretrainedConfig>
    • .AutoConfig
      • .from_pretrained() : PretrainedConfig.from_pretrained
  • inner
    • ~loadConfig(pretrained_model_name_or_path, options) ⇒ Promise.<Array>
    • ~PretrainedOptions : *

configs.PretrainedConfig

Base class for all configuration classes. For more information, see the corresponding Python documentation.

Kind: static class of configs

• .PretrainedConfig
  • new PretrainedConfig(configJSON)
  • .from_pretrained(pretrained_model_name_or_path, options) ⇒ Promise.<PretrainedConfig>

new PretrainedConfig(configJSON)

Create a new PreTrainedTokenizer instance.

PretrainedConfig.from_pretrained(pretrained_model_name_or_path, options) ⇒ <code> Promise. < PretrainedConfig > </code>

Loads a pre-trained config from the given pretrained_model_name_or_path.

Kind: static method of PretrainedConfig
Returns: Promise.<PretrainedConfig> - A new instance of the PretrainedConfig class.
Throws:

• Error Throws an error if the config.json is not found in the `pretrained_model_name_or_path`.

configs.AutoConfig

Helper class which is used to instantiate pretrained configs with the from_pretrained function.

Kind: static class of configs

AutoConfig.from_pretrained() : <code> PretrainedConfig.from_pretrained </code>

Kind: static method of AutoConfig

configs~loadConfig(pretrained_model_name_or_path, options) ⇒ <code> Promise. < Array > </code>

Loads a config from the specified path.

Kind: inner method of configs
Returns: Promise.<Array> - A promise that resolves with information about the loaded config.

configs~PretrainedOptions : <code> * </code>

Kind: inner typedef of configs