{"draftJsState":{"blocks":[{"data":{"embedData":{"type":"external","host":"5487fb.skillspace.ru","image":{"src":"https://avatars.dzeninfra.ru/get-zen_brief_embed/271828/pub_67338713eecc123fcf89965b_697f81882c4e332e94db71c6/smart_crop_600x300","width":600,"height":300,"mainColor":"#080810"},"src":"https://5487fb.skillspace.ru/l/rust-ml-19003b","title":"ML на RUST без заморочек"}},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"atomic:embed","key":"ftekc"},{"data":{},"depth":0,"entityRanges":[{"key":0,"length":19,"offset":0}],"inlineStyleRanges":[],"text":"t.me/oneRustnoqRust","type":"unstyled","key":"498ml"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":29,"offset":0,"style":"ITALIC"}],"text":"Для чего нужна данная статья? :","type":"unstyled","key":"100q4"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Создать представления текста, генерировать и обрабатывать их несколькими способами с использованием базовых библиотек.","type":"unordered-list-item","key":"3qoul"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":21,"offset":0,"style":"ITALIC"}],"text":"Зачем Вам это уметь? :","type":"unstyled","key":"2ppt8"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":69,"offset":12,"style":"BOLD"}],"text":"1. Создать статические вложения с использованием предварительно обученных моделей","type":"header-three","key":"vsk2"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Загрузить предварительно обученные вложения (например, GloVe или Word2Vec) в память и использовать их для представления слов или фраз.","type":"unstyled","key":"79o7u"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":6,"offset":0,"style":"BOLD"}],"text":"Пример :","type":"unstyled","key":"7urcp"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":31,"offset":0,"style":"BOLD"}],"text":"use std::collections::HashMap; ","type":"unstyled","key":"dp195"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":67,"offset":0,"style":"BOLD"}],"text":" fn load_embeddings(file_path: &str) -> HashMap> {","type":"unstyled","key":"8loqk"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":42,"offset":0,"style":"BOLD"}],"text":"\n let mut embeddings = HashMap::new();\n","type":"unstyled","key":"c0h4h"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":15,"offset":0,"style":"BOLD"}],"text":" embeddings ","type":"unstyled","key":"cps2g"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":1,"offset":0,"style":"BOLD"}],"text":"}","type":"unstyled","key":"emon2"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":74,"offset":0,"style":"BOLD"}],"text":" fn get_embedding(word: &str, embeddings: &HashMap>) -> ","type":"unstyled","key":"8q9k0"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":46,"offset":0,"style":"BOLD"}],"text":"Option<&Vec> { embeddings.get(word) }","type":"unstyled","key":"7otcp"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Предварительно обученные векторы могут храниться в текстовых файлах (например glove.6B.300d.txt, ) или сериализованных форматах. После загрузки вы можете получить доступ к векторам по ключу или использовать средние значения для представления фраз из нескольких слов.","type":"unstyled","key":"cc62i"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":30,"offset":0,"style":"BOLD"}],"text":"use std::collections::HashMap;","type":"unstyled","key":"3hfv3"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":18,"offset":0,"style":"BOLD"}],"text":"use std::fs::File;","type":"unstyled","key":"24c7i"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":34,"offset":0,"style":"BOLD"}],"text":"use std::io::{BufRead, BufReader};","type":"unstyled","key":"tc3f"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":66,"offset":0,"style":"BOLD"}],"text":"fn load_embeddings(file_path: &str) -> HashMap> {","type":"unstyled","key":"60f7u"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":36,"offset":0,"style":"BOLD"}],"text":"let mut embeddings = HashMap::new();","type":"unstyled","key":"fcsrq"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":60,"offset":0,"style":"BOLD"}],"text":"let file = File::open(file_path).expect(\"Cannot open file\");","type":"unstyled","key":"7g7qn"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":34,"offset":0,"style":"BOLD"}],"text":"let reader = BufReader::new(file);","type":"unstyled","key":"6nnj7"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":28,"offset":0,"style":"BOLD"}],"text":"for line in reader.lines() {","type":"unstyled","key":"4fhd5"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":46,"offset":0,"style":"BOLD"}],"text":"let line = line.expect(\"Could not read line\");","type":"unstyled","key":"65jg6"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":40,"offset":0,"style":"BOLD"}],"text":"let mut parts = line.split_whitespace();","type":"unstyled","key":"4vrdn"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":45,"offset":0,"style":"BOLD"}],"text":"let word = parts.next().unwrap().to_string();","type":"unstyled","key":"596rd"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":70,"offset":0,"style":"BOLD"}],"text":"let embedding: Vec = parts.map(|s| s.parse().unwrap()).collect();","type":"unstyled","key":"21j7f"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":35,"offset":0,"style":"BOLD"}],"text":"embeddings.insert(word, embedding);","type":"unstyled","key":"8nv2i"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":1,"offset":0,"style":"BOLD"}],"text":"}","type":"unstyled","key":"87g84"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":10,"offset":0,"style":"BOLD"}],"text":"embeddings","type":"unstyled","key":"86o19"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":1,"offset":0,"style":"BOLD"}],"text":"}","type":"unstyled","key":"c56tq"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":11,"offset":0,"style":"BOLD"}],"text":"fn main() {","type":"unstyled","key":"4r6bm"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":79,"offset":0,"style":"BOLD"}],"text":"let embeddings = load_embeddings(\"glove.6B.50d.txt\"); // Path to the GloVe file","type":"unstyled","key":"fp07l"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":44,"offset":0,"style":"BOLD"}],"text":"if let Some(vec) = embeddings.get(\"hello\") {","type":"unstyled","key":"bg8kh"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":45,"offset":0,"style":"BOLD"}],"text":"println!(\"Embedding for 'hello': {:?}\", vec);","type":"unstyled","key":"1btn8"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":8,"offset":0,"style":"BOLD"}],"text":"} else {","type":"unstyled","key":"b97kg"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":41,"offset":0,"style":"BOLD"}],"text":"println!(\"Word not found in embeddings\");","type":"unstyled","key":"e4f9t"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":1,"offset":0,"style":"BOLD"}],"text":"}","type":"unstyled","key":"ftgu0"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":1,"offset":0,"style":"BOLD"}],"text":"}","type":"unstyled","key":"3c4gk"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"4c3dc"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":40,"offset":3,"style":"BOLD"}],"text":"2. Использование библиотек встраивания Rust","type":"header-three","key":"evs0u"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":9,"offset":0,"style":"BOLD"}],"text":"Rust-Bert : реализация модели языка BERT на языке Rust с предварительно обученными моделями и встраиваниями.","type":"unstyled","key":"9a02l"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":8,"offset":0,"style":"BOLD"}],"text":"rust2vec : библиотека для загрузки и использования внедрений в Rust, поддерживающая различные форматы, такие как GloVe и Word2Vec.","type":"unstyled","key":"95sr2"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":18,"offset":0,"style":"BOLD"}],"text":"Пример с Rust-Bert :","type":"unstyled","key":"2v9sb"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":75,"offset":0,"style":"BOLD"}],"text":"use rust_bert::pipelines::sentence_embeddings::{SentenceEmbeddingsBuilder, ","type":"unstyled","key":"fq9v3"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":81,"offset":0,"style":"BOLD"}],"text":"SentenceEmbeddingsModelType}; fn main() -> anyhow::Result<()> {\n let model = ","type":"unstyled","key":"cohtj"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":71,"offset":0,"style":"BOLD"}],"text":"SentenceEmbeddingsBuilder::remote(SentenceEmbeddingsModelType::AllMiniL","type":"unstyled","key":"aqlvh"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":24,"offset":0,"style":"BOLD"}],"text":"mL6V2).create_model()?;\n","type":"unstyled","key":"8824q"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":68,"offset":0,"style":"BOLD"}],"text":" let embeddings = model.encode(&[\"This is a sample sentence.\"])?;","type":"unstyled","key":"dnne5"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":14,"offset":0,"style":"BOLD"}],"text":" println!","type":"unstyled","key":"69uho"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":73,"offset":0,"style":"BOLD"}],"text":"(\"{:?}\", embeddings[0]); // Print embedding for the sentence Ok(()) }","type":"unstyled","key":"1v8fe"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"efmpu"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Установите rust-bertдля встраивания на основе трансформатора. Обязательно добавьте rust-bertи tchв свой Cargo.toml.","type":"unstyled","key":"dhp32"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"[dependencies]","type":"unstyled","key":"49cg0"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"rust-bert = \"0.16.0\"","type":"unstyled","key":"7citj"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"tch = { version = \"0.6.1\", features = [\"libtorch-sys\"] }","type":"unstyled","key":"cl9co"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"6lqp7"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"3. Создание пользовательских вложений с помощью библиотек машинного обучения","type":"header-three","key":"3sk08"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"8au1m"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":5,"offset":0,"style":"BOLD"}],"text":"Linfa : инструменты для машинного обучения, похожие на scikit-learn Python. Его можно использовать для создания пользовательских алгоритмов встраивания, таких как PCA или t-SNE.","type":"unordered-list-item","key":"eo4hc"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":49,"offset":0,"style":"BOLD"}],"text":"Пример использования PCA для снижения размерности :","type":"unstyled","key":"r3on"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":28,"offset":0,"style":"BOLD"}],"text":"use linfa::dataset::Dataset;","type":"unstyled","key":"6knln"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":44,"offset":0,"style":"BOLD"}],"text":"\nuse linfa_reduction::pca::Pca; fn main() {","type":"unstyled","key":"5forj"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":49,"offset":0,"style":"BOLD"}],"text":"\n let dataset = Dataset::new(/* data here */);","type":"unstyled","key":"9q416"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":53,"offset":0,"style":"BOLD"}],"text":"\n let pca = Pca::params(3).fit(&dataset).unwrap();","type":"unstyled","key":"2v7c"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":46,"offset":0,"style":"BOLD"}],"text":"\n let embeddings = pca.transform(&dataset);","type":"unstyled","key":"7d1mm"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":42,"offset":0,"style":"BOLD"}],"text":"\n println!(\"{:?}\", embeddings.records);","type":"unstyled","key":"168cd"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":1,"offset":0,"style":"BOLD"}],"text":"}","type":"unstyled","key":"2fp7l"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Чтобы создать пользовательские вложения с помощью Linfa, добавьте linfaи linfa-reductionв Cargo.toml.","type":"unstyled","key":"4egv0"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"[dependencies]","type":"unstyled","key":"evdj2"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"linfa = \"0.3.0\"","type":"unstyled","key":"83aes"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"linfa-reduction = \"0.3.0\"","type":"unstyled","key":"lv5m"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"ndarray = \"0.15.4\"","type":"unstyled","key":"ele01"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"aekfm"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":22,"offset":3,"style":"BOLD"}],"text":"4. FFI вложения из Python","type":"header-three","key":"ag7v9"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Для расширенных или пользовательских встраиваний можно вызывать библиотеки Python (например, gensimWord2Vec) из Rust с помощью pyo3или rust-cpython.","type":"unstyled","key":"db3uv"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":12,"offset":0,"style":"BOLD"}],"text":"Пример сpyo3 :","type":"unstyled","key":"8khr3"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":21,"offset":0,"style":"BOLD"}],"text":"use pyo3::prelude::*;","type":"unstyled","key":"2togf"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":59,"offset":0,"style":"BOLD"}],"text":"\nuse pyo3::types::IntoPyDict; fn main() -> PyResult<()> { ","type":"unstyled","key":"ebv5f"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":27,"offset":0,"style":"BOLD"}],"text":" Python::with_gil(|py| {","type":"unstyled","key":"64fql"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":43,"offset":0,"style":"BOLD"}],"text":"\n let gensim = py.import(\"gensim\")?;","type":"unstyled","key":"9g72m"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":29,"offset":0,"style":"BOLD"}],"text":"\n let keyed_vectors = ","type":"unstyled","key":"f6cq9"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":72,"offset":0,"style":"BOLD"}],"text":"gensim.get(\"models\").unwrap().call_method(\"KeyedVectors\", (), None)?; ","type":"unstyled","key":"1trbr"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":79,"offset":0,"style":"BOLD"}],"text":" keyed_vectors.call_method(\"load_word2vec_format\", (\"model.bin\",), None)?;","type":"unstyled","key":"afus4"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":85,"offset":0,"style":"BOLD"}],"text":"\n let embedding = keyed_vectors.call_method(\"get_vector\", (\"hello\",), None)?; ","type":"unstyled","key":"egopd"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":48,"offset":0,"style":"BOLD"}],"text":" println!(\"Embedding: {:?}\", embedding);","type":"unstyled","key":"ff1qh"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":24,"offset":0,"style":"BOLD"}],"text":"\n Ok(()) }) }","type":"unstyled","key":"ejcl1"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"dlsjd"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Добавьте pyo3к Cargo.tomlдля прямого вызова функций Python.","type":"unstyled","key":"au4sd"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"[dependencies]","type":"unstyled","key":"d6gsl"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"pyo3 = { version = \"0.16.4\", features = [\"extension-module\"] }","type":"unstyled","key":"dutnj"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"6ph1n"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":48,"offset":3,"style":"BOLD"}],"text":"5. Обучение внедрению с помощью моделей Rust и ONNX","type":"header-three","key":"4ggbp"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"2b6tv"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":21,"offset":0,"style":"BOLD"}],"text":"Пример с ONNX Runtime :","type":"unstyled","key":"fncjh"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":78,"offset":0,"style":"BOLD"}],"text":"use ort::{environment::Environment, tensor::OrtOwnedTensor, session::Session};","type":"unstyled","key":"1d313"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":54,"offset":0,"style":"BOLD"}],"text":" fn main() -> Result<(), Box> {","type":"unstyled","key":"5607b"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":55,"offset":0,"style":"BOLD"}],"text":"\n let environment = Environment::builder().build()?;","type":"unstyled","key":"5ela1"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":19,"offset":0,"style":"BOLD"}],"text":"\n let session = ","type":"unstyled","key":"afvkl"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":71,"offset":0,"style":"BOLD"}],"text":"environment.new_session_builder()?.with_model_from_file(\"model.onnx\")?;","type":"unstyled","key":"89or2"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":38,"offset":0,"style":"BOLD"}],"text":"\n let input = vec![1.0, 2.0, 3.0]; ","type":"unstyled","key":"8or6t"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":72,"offset":0,"style":"BOLD"}],"text":" let outputs: Vec> = session.run(vec![input])?;","type":"unstyled","key":"7m12b"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":45,"offset":0,"style":"BOLD"}],"text":"\n println!(\"Embedding: {:?}\", outputs[0]);","type":"unstyled","key":"fn1o8"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":13,"offset":0,"style":"BOLD"}],"text":"\n Ok(()) }","type":"unstyled","key":"tnmp"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Добавьте ort для Cargo.tomlзапуска моделей в формате ONNX.","type":"unstyled","key":"7ceuh"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"[dependencies]","type":"unstyled","key":"1j77b"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"ort = \"0.8.1\"","type":"unstyled","key":"8j2ra"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"5pbgu"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":53,"offset":3,"style":"BOLD"}],"text":"6. Использование моделей TensorFlow или PyTorch с Tch-rs","type":"header-three","key":"ffger"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"8gh0"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":15,"offset":0,"style":"BOLD"}],"text":"Пример с Tch-rs :","type":"unstyled","key":"769kc"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":71,"offset":0,"style":"BOLD"}],"text":"use tch::{Tensor, nn, nn::Module}; fn load_model() -> nn::Sequential {","type":"unstyled","key":"878vq"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":53,"offset":0,"style":"BOLD"}],"text":"\n let vs = nn::VarStore::new(tch::Device::Cpu); ","type":"unstyled","key":"4mdal"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":16,"offset":0,"style":"BOLD"}],"text":" nn::seq() ","type":"unstyled","key":"9am08"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":63,"offset":0,"style":"BOLD"}],"text":" .add(nn::linear(&vs.root(), 100, 50, Default::default())) ","type":"unstyled","key":"4g8vr"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":78,"offset":0,"style":"BOLD"}],"text":" .add_fn(|x| x.relu()) } fn generate_embedding(model: &nn::Sequential, ","type":"unstyled","key":"f1bv1"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":67,"offset":0,"style":"BOLD"}],"text":"input: Tensor) -> Tensor { model.forward(&input) } fn main() {","type":"unstyled","key":"230q1"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":30,"offset":0,"style":"BOLD"}],"text":"\n let model = load_model();","type":"unstyled","key":"8rkbk"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":54,"offset":0,"style":"BOLD"}],"text":"\n let input = Tensor::of_slice(&[0.5, 1.0, -0.5]); ","type":"unstyled","key":"9em3h"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":54,"offset":0,"style":"BOLD"}],"text":" let embedding = generate_embedding(&model, input);","type":"unstyled","key":"3b531"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[{"length":46,"offset":0,"style":"BOLD"}],"text":"\n println!(\"Embedding: {:?}\", embedding); }","type":"unstyled","key":"c6usa"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"djpen"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"Добавьте tch в Cargo.toml:","type":"unstyled","key":"9hrlk"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"[dependencies]","type":"unstyled","key":"8rsf2"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"tch = { version = \"0.6.1\", features = [\"libtorch-sys\"] }","type":"unstyled","key":"5kqop"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"unstyled","key":"evivc"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"header-three","key":"bt2vn"},{"data":{},"depth":0,"entityRanges":[],"inlineStyleRanges":[],"text":"","type":"marker","key":"4WDnVhNQ7J5jU8EDqQfi"}],"entityMap":{"0":{"data":{"url":"http://t.me/oneRustnoqRust"},"mutability":"MUTABLE","type":"LINK"}}},"mentions":[]}