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40 lines
1.5 KiB
Rust
40 lines
1.5 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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extern crate anyhow;
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use rust_bert::pipelines::question_answering::{QaInput, QuestionAnsweringModel};
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fn main() -> anyhow::Result<()> {
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// Set-up Question Answering model
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let qa_model = QuestionAnsweringModel::new(Default::default())?;
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// Define input
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let question_1 = String::from("Where does Amy live ?");
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let context_1 = String::from("Amy lives in Amsterdam");
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let question_2 = String::from("Where does Eric live");
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let context_2 = String::from("While Amy lives in Amsterdam, Eric is in The Hague.");
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let qa_input_1 = QaInput {
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question: question_1,
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context: context_1,
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};
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let qa_input_2 = QaInput {
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question: question_2,
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context: context_2,
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};
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// Get answer
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let answers = qa_model.predict(&[qa_input_1, qa_input_2], 1, 32);
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println!("{:?}", answers);
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Ok(())
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}
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