configs

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

Example: Load an AutoConfig.

import { AutoConfig } from '@huggingface/transformers';
const 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)
      • instance
        • .model_type : string | null
        • .is_encoder_decoder : boolean
        • .max_position_embeddings : number
      • static
        • .from_pretrained(pretrained_model_name_or_path, options) ⇒ Promise.<PretrainedConfig>
    • .AutoConfig
      • new AutoConfig()
      • .from_pretrained() : *
    • .getKeyValueShapes(config) ⇒ Record.<string, Array<number>>
      • ~decoderFeeds : Record.<string, Array<number>>
  • inner
    • ~loadConfig(pretrained_model_name_or_path, options) ⇒ Promise.<Object>
    • ~getNormalizedConfig(config) ⇒ Object
    • ~PretrainedOptions : *
    • ~ProgressCallback : *
    • ~ProgressInfo : *

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)
  • instance
    • .model_type : string | null
    • .is_encoder_decoder : boolean
    • .max_position_embeddings : number
  • static
    • .from_pretrained(pretrained_model_name_or_path, options) ⇒ Promise.<PretrainedConfig>

new PretrainedConfig(configJSON)

Create a new PreTrainedTokenizer instance.

pretrainedConfig.model_type : <code> string </code> | <code> null </code>

Kind: instance property of PretrainedConfig

pretrainedConfig.is_encoder_decoder : <code> boolean </code>

Kind: instance property of PretrainedConfig

pretrainedConfig.max_position_embeddings : <code> number </code>

Kind: instance property of PretrainedConfig

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
  • new AutoConfig()
  • .from_pretrained() : *

new AutoConfig()

Example

const config = await AutoConfig.from_pretrained('Xenova/bert-base-uncased'); 

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

Kind: static method of AutoConfig

configs.getKeyValueShapes(config) ⇒ <code> Record. < string, Array < number > > </code>

Kind: static method of configs

getKeyValueShapes~decoderFeeds : <code> Record. < string, Array < number > > </code>

Kind: inner constant of getKeyValueShapes

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

Loads a config from the specified path.

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

configs~getNormalizedConfig(config) ⇒ <code> Object </code>

Kind: inner method of configs
Returns: Object - The normalized configuration.

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

Kind: inner typedef of configs

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

Kind: inner typedef of configs

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

Kind: inner typedef of configs