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* - Changed the return type of generate method to be `Result`, removed fallible unwraps * Fix doctests
62 lines
2.3 KiB
Rust
62 lines
2.3 KiB
Rust
// Copyright 2018 Google AI and Google Brain team.
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// Copyright 2018 Carnegie Mellon University Authors.
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// Copyright 2020-present, the HuggingFace Inc. team.
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// Copyright 2020 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::common::{ModelResource, ModelType};
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use rust_bert::pipelines::text_generation::{TextGenerationConfig, TextGenerationModel};
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use rust_bert::reformer::{
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ReformerConfigResources, ReformerModelResources, ReformerVocabResources,
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};
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use rust_bert::resources::RemoteResource;
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fn main() -> anyhow::Result<()> {
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// Set-up model
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// Resources paths
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let config_resource = Box::new(RemoteResource::from_pretrained(
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ReformerConfigResources::CRIME_AND_PUNISHMENT,
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));
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let vocab_resource = Box::new(RemoteResource::from_pretrained(
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ReformerVocabResources::CRIME_AND_PUNISHMENT,
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));
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let model_resource = Box::new(RemoteResource::from_pretrained(
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ReformerModelResources::CRIME_AND_PUNISHMENT,
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));
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let generate_config = TextGenerationConfig {
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model_type: ModelType::Reformer,
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model_resource: ModelResource::Torch(model_resource),
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config_resource,
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vocab_resource,
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merges_resource: None,
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min_length: 100,
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max_length: Some(100),
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do_sample: true,
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early_stopping: false,
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num_beams: 3,
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num_return_sequences: 1,
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..Default::default()
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};
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let model = TextGenerationModel::new(generate_config)?;
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let input_context_1 = "The really great men must, I think,";
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let input_context_2 = "It was a gloom winter night, and";
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let output = model.generate(&[input_context_1, input_context_2], None)?;
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for sentence in output {
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println!("{sentence}");
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}
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Ok(())
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}
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