Torch version update

Cargo.toml

@@ -76,14 +76,14 @@ features = ["doc-only"]
 
 [dependencies]
 rust_tokenizers = "8.1.1"
-tch = { version = "0.16.0", features = ["download-libtorch"] }
+tch = { version = "0.17.0", features = ["download-libtorch"] }
 serde_json = "1"
 serde = { version = "1", features = ["derive"] }
 ordered-float = "4.2.0"
 uuid = { version = "1", features = ["v4"] }
 thiserror = "1"
 half = "2"
-regex = "1.6"
+regex = "1.10"
 
 cached-path = { version = "0.6", default-features = false, optional = true }
 dirs = { version = "5", optional = true }
@@ -92,7 +92,7 @@ ort = { version = "1.16.3", optional = true, default-features = false, features
     "half",
 ] }
 ndarray = { version = "0.15", optional = true }
-tokenizers = { version = "0.19.1", optional = true, default-features = false, features = [
+tokenizers = { version = "0.20", optional = true, default-features = false, features = [
     "onig",
 ] }
 

README.md

@@ -103,7 +103,7 @@ models used by this library are in the order of the 100s of MBs to GBs.
    package requires `v2.2`: if this version is no longer available on the "get
    started" page, the file should be accessible by modifying the target link,
    for example
-   `https://download.pytorch.org/libtorch/cu121/libtorch-cxx11-abi-shared-with-deps-2.2.0%2Bcu121.zip`
+   `https://download.pytorch.org/libtorch/cu124/libtorch-cxx11-abi-shared-with-deps-2.4.0%2Bcu124.zip`
    for a Linux version with CUDA12. **NOTE:** When using `rust-bert` as
    dependency from [crates.io](https://crates.io), please check the required
    `LIBTORCH` on the published package
@@ -140,7 +140,7 @@ Alternatively, you can let the `build` script automatically download the
 `libtorch` library for you. The `download-libtorch` feature flag needs to be
 enabled. The CPU version of libtorch will be downloaded by default. To download
 a CUDA version, please set the environment variable `TORCH_CUDA_VERSION` to
-`cu118`. Note that the libtorch library is large (order of several GBs for the
+`cu124`. Note that the libtorch library is large (order of several GBs for the
 CUDA-enabled version) and the first build may therefore take several minutes to
 complete.
 

src/lib.rs

@@ -90,8 +90,8 @@
 //!
 //! ### Manual installation (recommended)
 //!
-//! 1. Download `libtorch` from <https://pytorch.org/get-started/locally/>. This package requires `v2.2`: if this version is no longer available on the "get started" page,
-//!     the file should be accessible by modifying the target link, for example `https://download.pytorch.org/libtorch/cu121/libtorch-cxx11-abi-shared-with-deps-2.2.0%2Bcu121.zip` for a Linux version with CUDA12.
+//! 1. Download `libtorch` from <https://pytorch.org/get-started/locally/>. This package requires `v2.4`: if this version is no longer available on the "get started" page,
+//!     the file should be accessible by modifying the target link, for example `https://download.pytorch.org/libtorch/cu124/libtorch-cxx11-abi-shared-with-deps-2.4.0%2Bcu124.zip` for a Linux version with CUDA12.
 //! 2. Extract the library to a location of your choice
 //! 3. Set the following environment variables
 //! ##### Linux:
@@ -109,7 +109,7 @@
 //! ### Automatic installation
 //!
 //! Alternatively, you can let the `build` script automatically download the `libtorch` library for you. The `download-libtorch` feature flag needs to be enabled.
-//! The CPU version of libtorch will be downloaded by default. To download a CUDA version, please set the environment variable `TORCH_CUDA_VERSION` to `cu118`.
+//! The CPU version of libtorch will be downloaded by default. To download a CUDA version, please set the environment variable `TORCH_CUDA_VERSION` to `cu124`.
 //! Note that the libtorch library is large (order of several GBs for the CUDA-enabled version) and the first build may therefore take several minutes to complete.
 //!
 //! ## ONNX Support (Optional)