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https://github.com/guillaume-be/rust-bert.git
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Formatting and dependencies update
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@ -1,6 +1,6 @@
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[package]
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name = "rust-bert"
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version = "0.7.12"
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version = "0.8.0"
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authors = ["Guillaume Becquin <guillaume.becquin@gmail.com>"]
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edition = "2018"
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description = "Ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)"
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@ -30,8 +30,8 @@ all-tests = []
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features = ["doc-only"]
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[dependencies]
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rust_tokenizers = { version = "~4.0.0", path = "E:/Coding/backup-rust/rust-tokenizers/main" }
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tch = {version = "~0.2.0", path = "E:/Coding/tch-rs"}
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rust_tokenizers = "~4.0.0"
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tch = "~0.2.0"
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serde_json = "1.0.56"
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serde = { version = "1.0.114", features = ["derive"] }
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dirs = "3.0.1"
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@ -1,8 +1,8 @@
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pub(crate) mod activations;
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pub mod config;
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pub(crate) mod dropout;
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pub mod error;
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pub(crate) mod linear;
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pub mod resources;
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pub mod error;
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pub use config::Config;
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@ -44,6 +44,7 @@
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//! # Disclaimer
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//! The authors of this repository are not responsible for any generation
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//! from the 3rd party utilization of the pretrained system.
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use crate::common::error::RustBertError;
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use crate::common::resources::{RemoteResource, Resource};
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use crate::gpt2::{
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Gpt2ConfigResources, Gpt2MergesResources, Gpt2ModelResources, Gpt2VocabResources,
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@ -55,7 +56,6 @@ use rust_tokenizers::Tokenizer;
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use std::collections::HashMap;
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use tch::{Device, Tensor};
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use uuid::Uuid;
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use crate::common::error::RustBertError;
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/// # Configuration for multi-turn classification
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/// Contains information regarding the model to load, mirrors the GenerationConfig, with a
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@ -591,7 +591,9 @@ impl ConversationModel {
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/// # Ok(())
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/// # }
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/// ```
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pub fn new(conversation_config: ConversationConfig) -> Result<ConversationModel, RustBertError> {
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pub fn new(
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conversation_config: ConversationConfig,
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) -> Result<ConversationModel, RustBertError> {
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let generate_config = GenerateConfig {
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model_resource: conversation_config.model_resource,
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config_resource: conversation_config.config_resource,
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@ -117,8 +117,8 @@
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//! Spanish| XLM_ROBERTA_NER_ES |
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//! Dutch| XLM_ROBERTA_NER_NL |
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use crate::pipelines::token_classification::{TokenClassificationConfig, TokenClassificationModel};
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use crate::common::error::RustBertError;
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use crate::pipelines::token_classification::{TokenClassificationConfig, TokenClassificationModel};
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#[derive(Debug)]
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/// # Entity generated by a `NERModel`
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@ -54,6 +54,7 @@
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//! # ;
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//! ```
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use crate::common::error::RustBertError;
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use crate::pipelines::sequence_classification::{
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SequenceClassificationConfig, SequenceClassificationModel,
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};
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@ -61,7 +62,6 @@ use serde::Deserialize;
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use std::error::Error;
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use std::fs;
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use std::path::PathBuf;
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use crate::common::error::RustBertError;
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#[derive(Debug, PartialEq)]
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/// Enum with the possible sentiment polarities. Note that the pre-trained SST2 model does not include neutral sentiment.
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