pub struct TokenClassificationModel { /* private fields */ }
Expand description
§TokenClassificationModel for Named Entity Recognition or Part-of-Speech tagging
Implementations§
Source§impl TokenClassificationModel
impl TokenClassificationModel
Sourcepub fn new(
config: TokenClassificationConfig,
) -> Result<TokenClassificationModel, RustBertError>
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())?;
Sourcepub fn new_with_tokenizer(
config: TokenClassificationConfig,
tokenizer: TokenizerOption,
) -> Result<TokenClassificationModel, RustBertError>
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)?;
Sourcepub fn get_tokenizer(&self) -> &TokenizerOption
pub fn get_tokenizer(&self) -> &TokenizerOption
Get a reference to the model tokenizer.
Sourcepub fn get_tokenizer_mut(&mut self) -> &mut TokenizerOption
pub fn get_tokenizer_mut(&mut self) -> &mut TokenizerOption
Get a mutable reference to the model tokenizer.
Sourcepub fn predict<S>(
&self,
input: &[S],
consolidate_sub_tokens: bool,
return_special: bool,
) -> Vec<Vec<Token>>
pub fn predict<S>( &self, input: &[S], consolidate_sub_tokens: bool, return_special: bool, ) -> Vec<Vec<Token>>
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 levelreturn_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);
Auto Trait Implementations§
impl !Freeze for TokenClassificationModel
impl RefUnwindSafe for TokenClassificationModel
impl Send for TokenClassificationModel
impl !Sync for TokenClassificationModel
impl Unpin for TokenClassificationModel
impl UnwindSafe for TokenClassificationModel
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
Source§impl<T> Instrument for T
impl<T> Instrument for T
Source§fn instrument(self, span: Span) -> Instrumented<Self>
fn instrument(self, span: Span) -> Instrumented<Self>
Source§fn in_current_span(self) -> Instrumented<Self>
fn in_current_span(self) -> Instrumented<Self>
Source§impl<T> IntoEither for T
impl<T> IntoEither for T
Source§fn into_either(self, into_left: bool) -> Either<Self, Self>
fn into_either(self, into_left: bool) -> Either<Self, Self>
Converts
self
into a Left
variant of Either<Self, Self>
if into_left
is true
.
Converts self
into a Right
variant of Either<Self, Self>
otherwise. Read moreSource§fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
Converts
self
into a Left
variant of Either<Self, Self>
if into_left(&self)
returns true
.
Converts self
into a Right
variant of Either<Self, Self>
otherwise. Read more