PyTorch
Learn about PyTorch conda environments.
A description of the PyTorch 2.4.0 for GPU on Python 3.10 with CUDA 12.4 (version 1.0) conda environment.
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Released |
August 23, 2024 |
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Description |
PyTorch is a machine learning library that's used for applications in computer vision and natural language processing. It provides high level features for tensor computing and deep neural networks. Use oracle-ads to speed up your data science workflow with tools that automate common tasks. This environment includes CUDA toolkit and libraries commonly used in training large language models (LLMs). To get started with the PyTorch environment, open and review the notebook example getting-started.ipynb, using the Launcher. |
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Python Version |
3.10 |
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| Object Storage Path |
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Top Libraries |
For a complete list of preinstalled Python libraries, see pytorch24_p310_gpu_x86_64_v1.txt. |
A description of the PyTorch 2.3.1 for GPU on Python 3.10 with CUDA 12.1 (version 1.0) conda environment.
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Released |
August 23, 2024 |
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Description |
PyTorch is a machine learning library that's used for applications in computer vision and natural language processing. It provides high level features for tensor computing and deep neural networks. Use oracle-ads to speed up your data science workflow with tools that automate common tasks. This environment includes CUDA toolkit and libraries commonly used in training large language models (LLMs). To get started with the PyTorch environment, open and review the notebook example getting-started.ipynb, using the Launcher. |
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Python Version |
3.10 |
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| Object Storage Path |
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Top Libraries |
For a complete list of preinstalled Python libraries, see pytorch23_p310_gpu_x86_64_v1.txt. |
A description of the PyTorch 2.1 for GPU on Python 3.9 with CUDA 11.8 (version 1.0) conda environment.
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Released |
February 9, 2024 |
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Description |
PyTorch is a machine learning library that's used for applications in computer vision and natural language processing. It provides high level features for tensor computing and deep neural networks. Use oracle-ads to speed up your data science workflow with tools that automate common tasks. This environment includes CUDA 11.8 and libraries commonly used in training large language models (LLMs). To get started with the PyTorch environment, open and review the notebook example getting-started.ipynb, using the Launcher. |
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Python Version |
3.9 |
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| Object Storage Path |
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Top Libraries |
For a complete list of preinstalled Python libraries, see pytorch21_p39_gpu_v1.txt. |
A description of the PyTorch 2.0 for GPU on Python 3.9 with CUDA 11.8 (version 2.0) conda environment.
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Released |
September 12, 2023 |
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Description |
PyTorch is a machine learning library that's used for applications in computer vision and natural language processing. It provides high level features for tensor computing and deep neural networks. Use oracle-ads to speed up Data Science workflows with tools that automate common tasks. This environment includes CUDA 11.8 and libraries commonly used in training large language models (LLMs). To get started with this conda environment, review the Getting Started notebook, using the Launcher. |
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Python Version |
3.8 |
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| Object Storage Path |
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Top Libraries |
For a complete list of preinstalled Python libraries, see pytorch20_p39_gpu_v2.txt. |