// Copyright 2018 Google AI and Google Brain team. // Copyright 2018 Carnegie Mellon University Authors. // Copyright 2020-present, the HuggingFace Inc. team. // Copyright 2020 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::gpt_neo::{ GptNeoConfigResources, GptNeoMergesResources, GptNeoModelResources, GptNeoVocabResources, }; use rust_bert::pipelines::common::{ModelResource, ModelType}; use rust_bert::pipelines::text_generation::{TextGenerationConfig, TextGenerationModel}; use rust_bert::resources::RemoteResource; use tch::Device; fn main() -> anyhow::Result<()> { // Set-up model resources let config_resource = Box::new(RemoteResource::from_pretrained( GptNeoConfigResources::GPT_NEO_125M, )); let vocab_resource = Box::new(RemoteResource::from_pretrained( GptNeoVocabResources::GPT_NEO_125M, )); let merges_resource = Box::new(RemoteResource::from_pretrained( GptNeoMergesResources::GPT_NEO_125M, )); let model_resource = Box::new(RemoteResource::from_pretrained( GptNeoModelResources::GPT_NEO_125M, )); let generate_config = TextGenerationConfig { model_type: ModelType::GPTNeo, model_resource: ModelResource::Torch(model_resource), config_resource, vocab_resource, merges_resource: Some(merges_resource), min_length: 10, max_length: Some(32), do_sample: false, early_stopping: true, num_beams: 4, num_return_sequences: 1, device: Device::Cpu, ..Default::default() }; let mut model = TextGenerationModel::new(generate_config)?; model.set_device(Device::cuda_if_available())?; let input_context_1 = "It was a very nice and sunny"; let input_context_2 = "It was a gloom winter night, and"; let output = model.generate(&[input_context_1, input_context_2], None)?; for sentence in output { println!("{sentence}"); } Ok(()) }