1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
// Copyright 2019-present, the HuggingFace Inc. team, The Google AI Language Team and Facebook, Inc.
// Copyright 2019 Guillaume Becquin
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
use rust_bert::bert::{BertConfigResources, BertModelResources, BertVocabResources};
use rust_bert::pipelines::common::{ModelResource, ModelType};
use rust_bert::pipelines::ner::NERModel;
use rust_bert::pipelines::token_classification::{
LabelAggregationOption, TokenClassificationConfig,
};
use rust_bert::resources::RemoteResource;
fn main() -> anyhow::Result<()> {
// Load a configuration
let config = TokenClassificationConfig::new(
ModelType::Bert,
ModelResource::Torch(Box::new(RemoteResource::from_pretrained(
BertModelResources::BERT_NER,
))),
RemoteResource::from_pretrained(BertConfigResources::BERT_NER),
RemoteResource::from_pretrained(BertVocabResources::BERT_NER),
None, //merges resource only relevant with ModelType::Roberta
false, //lowercase
false,
None,
LabelAggregationOption::Mode,
);
// Create the model
let token_classification_model = NERModel::new(config)?;
let input = [
"My name is Amélie. I live in Москва.",
"Chongqing is a city in China.",
];
let token_outputs = token_classification_model.predict(&input);
for token in token_outputs {
println!("{token:?}");
}
Ok(())
}