Transformers cuda, 3 markupsafe 3. Trainer class using pytorch will automatically use the cuda (GPU) version without any additional specification. The programs are designed to leverage the parallel processing capabilities of GPUs to perform these operations more efficiently than traditional CPU-based implementations. 1. 3 environment at: uv_venvs/transformers-v4576 Package Version ------------------------ --------- accelerate 1. 4 filelock 3. 0 cuda-bindings 12. 12. I had the same issue - to answer this question, if pytorch + cuda is installed, an e. 3. 9. Installation Prerequisites Linux x86_64 CUDA 12. 4 compressed-tensors 0. 0 certifi 2026. Complete setup guide with PyTorch configuration and performance optimization tips. Feb 9, 2022 · Transformers: How to use CUDA for inferencing? Ask Question Asked 4 years ago Modified 1 year, 11 months ago 4 days ago · Install CUDA 12. 4. 11 jinja2 3. Transformer Engine in NGC Containers Transformer Engine library is preinstalled in the Feb 20, 2026 · Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada, and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference. within CUDA_HOME, set NVTE_CUDA_INCLUDE_PATH in the environment. FasterTransformer This repository provides a script and recipe to run the highly optimized transformer-based encoder and decoder component, and it is tested and maintained by NVIDIA. Feb 9, 2022 · Transformers: How to use CUDA for inferencing? Ask Question Asked 4 years ago Modified 1 year, 11 months ago This repository contains a collection of CUDA programs that perform various mathematical operations on matrices and vectors. 3 or later. 1 or later. 7. The CUDA_DEVICE_ORDER is especially useful if your training setup consists of an older and newer GPU, where the older GPU appears first, but you cannot physically swap the cards to make the newer GPU appear first. If the CUDA Toolkit headers are not available at runtime in a standard installation path, e. 0. Click to redirect to the main version of the documentation. 0 hf-xet 1. The documentation page PERF_INFER_GPU_ONE doesn't exist in v5. 8. 4 days ago · Install CUDA 12. 0 for Transformers GPU acceleration. 3 mpmath 1. g. 4 cuda-pathfinder 1. cuDNN 9. These operations include matrix multiplication, matrix scaling, softmax function implementation, vector addition, matrix addition, and dot product calculation. 2. 0 huggingface-hub 0. Fast and memory-efficient exact attention. . 4 charset-normalizer 3. 1+ (12. transformers. 3 fsspec 2026. 0, but exists on the main version. 13. 0 annotated-types 0. 6 loguru 0. Using Python 3. Contribute to Dao-AILab/flash-attention development by creating an account on GitHub. 8+ for Blackwell support) NVIDIA Driver supporting CUDA 12. 2 idna 3. 24. 36.


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