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35 lines
1.4 KiB
Rust
35 lines
1.4 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::{squad_processor, QuestionAnsweringModel};
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use std::env;
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use std::path::PathBuf;
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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 mut squad_path = PathBuf::from(env::var("squad_dataset")
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.expect("Please set the \"squad_dataset\" environment variable pointing to the SQuAD dataset folder"));
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squad_path.push("dev-v2.0.json");
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let qa_inputs = squad_processor(squad_path);
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// Get answer
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let answers = qa_model.predict(&qa_inputs, 1, 64);
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println!("Sample answer: {:?}", answers.first().unwrap());
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println!("{}", answers.len());
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Ok(())
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}
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