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https://github.com/guillaume-be/rust-bert.git
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54 lines
2.1 KiB
Rust
54 lines
2.1 KiB
Rust
// Copyright 2019-present, the HuggingFace Inc. team, The Google AI Language Team and Facebook, Inc.
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// Copyright 2019 Guillaume Becquin
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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use rust_bert::bert::{BertConfigResources, BertModelResources, BertVocabResources};
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use rust_bert::pipelines::common::ModelType;
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use rust_bert::pipelines::token_classification::{
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LabelAggregationOption, TokenClassificationConfig, TokenClassificationModel,
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};
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use rust_bert::resources::{RemoteResource, Resource};
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fn main() -> anyhow::Result<()> {
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// Load a configuration
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let config = TokenClassificationConfig::new(
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ModelType::Bert,
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Resource::Remote(RemoteResource::from_pretrained(
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BertModelResources::BERT_NER,
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)),
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Resource::Remote(RemoteResource::from_pretrained(
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BertConfigResources::BERT_NER,
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)),
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Resource::Remote(RemoteResource::from_pretrained(
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BertVocabResources::BERT_NER,
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)),
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None, //merges resource only relevant with ModelType::Roberta
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false, //lowercase
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false,
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None,
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LabelAggregationOption::Mode,
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);
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// Create the model
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let token_classification_model = TokenClassificationModel::new(config)?;
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let input = [
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"My name is Amélie. I live in Москва.",
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"Chongqing is a city in China.",
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];
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let token_outputs = token_classification_model.predict(&input, true, false); //ignore_first_label = true (only returns the NER parts, ignoring first label O)
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for token in token_outputs {
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println!("{:?}", token);
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}
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Ok(())
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}
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