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// 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.
extern crate anyhow;
use rust_bert::bert::{BertConfigResources, BertModelResources, BertVocabResources};
use rust_bert::pipelines::common::{ModelResource, ModelType};
use rust_bert::pipelines::masked_language::{MaskedLanguageConfig, MaskedLanguageModel};
use rust_bert::resources::RemoteResource;
fn main() -> anyhow::Result<()> {
// Set-up model
let config = MaskedLanguageConfig::new(
ModelType::Bert,
ModelResource::Torch(Box::new(RemoteResource::from_pretrained(
BertModelResources::BERT,
))),
RemoteResource::from_pretrained(BertConfigResources::BERT),
RemoteResource::from_pretrained(BertVocabResources::BERT),
None,
true,
None,
None,
Some(String::from("<mask>")),
);
let mask_language_model = MaskedLanguageModel::new(config)?;
// Define input
let input = [
"Hello I am a <mask> student",
"Paris is the <mask> of France. It is <mask> in Europe.",
];
// Run model
let output = mask_language_model.predict(input)?;
for sentence_output in output {
println!("{sentence_output:?}");
}
Ok(())
}