23 releases (5 breaking)
0.9.5 | Nov 22, 2024 |
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0.9.2 | Sep 10, 2024 |
0.9.0 | Jul 22, 2024 |
#170 in Machine learning
320 downloads per month
11MB
207K
SLoC
ctranslate2-rs
This library provides Rust bindings for OpenNMT/CTranslate2. At this time, it has only been tested and confirmed to work on macOS and Linux. Windows support is available experimentally, but it has not been thoroughly tested and may have limitations or require additional configuration.
Supported Models
The ct2rs crate has been tested and confirmed to work with the following models:
- BART
- BLOOM
- FALCON
- Marian-MT
- MPT
- NLLB
- GPT-2
- GPT-J
- OPT
- T5
- Whisper
Please see the respective examples for each model.
Stream API
This crate also offers a streaming API that utilizes callback closures. Please refer to the example code for more information.
Compilation
If you plan to use GPU acceleration, CUDA and cuDNN are available.
Please enable the cuda
or cudnn
feature and set the CUDA_TOOLKIT_ROOT_DIR
environment variable appropriately.
Several backends are available for use: OpenBLAS, Intel MKL, Ruy, and Apple Accelerate.
- OpenBLAS: To use OpenBLAS, enable the
openblas
feature and add the path to the directory containinglibopenblas.a
to theLIBRARY_PATH
environment variable. - Intel MKL: To use Intel MKL, enable the
mkl
feature and set the path to the Intel libraries in theMKLROOT
environment variable (default is/opt/intel
). - Ruy: To use Ruy, enable the
ruy
feature. - Apple Accelerate: Available only on macOS, enable the
accelerate
feature to use Apple Accelerate.
The installation of CMake is required to compile the library.
Additional notes for Windows:
it is necessary to add RUSTFLAGS=-C target-feature=+crt-static
to the environment variables for compilation.
Model Conversion for CTranslate2
To use model files with CTranslate2, they must first be converted.
Below is an example of how to convert the nllb-200-distilled-600M
model:
pip install ctranslate2 huggingface_hub torch transformers
ct2-transformers-converter --model facebook/nllb-200-distilled-600M --output_dir nllb-200-distilled-600M \
--copy_files tokenizer.json
For more details, please refer to the CTranslate2's docs.
License
This application is released under the MIT License. For details, see the LICENSE file.
Dependencies
~18–33MB
~484K SLoC