Struct TokenClassificationModel

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pub struct TokenClassificationModel { /* private fields */ }
Expand description

§TokenClassificationModel for Named Entity Recognition or Part-of-Speech tagging

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impl TokenClassificationModel

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pub fn new( config: TokenClassificationConfig, ) -> Result<TokenClassificationModel, RustBertError>

Build a new TokenClassificationModel

§Arguments
  • config - TokenClassificationConfig object containing the resource references (model, vocabulary, configuration) and device placement (CPU/GPU)
§Example
use rust_bert::pipelines::token_classification::TokenClassificationModel;

let model = TokenClassificationModel::new(Default::default())?;
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pub fn new_with_tokenizer( config: TokenClassificationConfig, tokenizer: TokenizerOption, ) -> Result<TokenClassificationModel, RustBertError>

Build a new TokenClassificationModel with a provided tokenizer.

§Arguments
  • config - TokenClassificationConfig object containing the resource references (model, vocabulary, configuration) and device placement (CPU/GPU)
  • tokenizer - TokenizerOption tokenizer to use for token classification
§Example
use rust_bert::pipelines::common::{ModelType, TokenizerOption};
use rust_bert::pipelines::token_classification::TokenClassificationModel;
let tokenizer = TokenizerOption::from_file(
    ModelType::Bert,
    "path/to/vocab.txt",
    None,
    false,
    None,
    None,
)?;
let model = TokenClassificationModel::new_with_tokenizer(Default::default(), tokenizer)?;
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pub fn get_tokenizer(&self) -> &TokenizerOption

Get a reference to the model tokenizer.

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pub fn get_tokenizer_mut(&mut self) -> &mut TokenizerOption

Get a mutable reference to the model tokenizer.

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pub fn predict<S>( &self, input: &[S], consolidate_sub_tokens: bool, return_special: bool, ) -> Vec<Vec<Token>>
where S: AsRef<str>,

Classify tokens in a text sequence

§Arguments
  • input - &[&str] Array of texts to extract entities from.
  • consolidate_subtokens - bool flag indicating if subtokens should be consolidated at the token level
  • return_special - bool flag indicating if labels for special tokens should be returned
§Returns
  • Vec<Vec<Token>> containing Tokens with associated labels (for example POS tags) for each input provided
§Example

let ner_model = TokenClassificationModel::new(Default::default())?;
let input = [
    "My name is Amy. I live in Paris.",
    "Paris is a city in France.",
];
let output = ner_model.predict(&input, true, true);

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