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hipdnn
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mattwill-a
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c3fb922973 | ||
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fcc0fa5f98 | ||
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74032b9ecc |
@@ -349,7 +349,7 @@ with ROCm.
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you need to explicitly move audio data (waveform tensor) to GPU using
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you need to explicitly move audio data (waveform tensor) to GPU using
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``.to('cuda')``.
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``.to('cuda')``.
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* - `torchtune <https://docs.pytorch.org/torchtune/stable/index.html>`_
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* - `torchtune <https://meta-pytorch.org/torchtune/stable/index.html>`_
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- PyTorch-native library designed for fine-tuning large language models
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- PyTorch-native library designed for fine-tuning large language models
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(LLMs). Provides supports the full fine-tuning workflow and offers
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(LLMs). Provides supports the full fine-tuning workflow and offers
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compatibility with popular production inference systems.
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compatibility with popular production inference systems.
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@@ -366,7 +366,7 @@ with ROCm.
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constructing flexible and performant data pipelines, with features still
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constructing flexible and performant data pipelines, with features still
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in prototype stage.
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in prototype stage.
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* - `torchrec <https://docs.pytorch.org/torchrec/>`_
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* - `torchrec <https://meta-pytorch.org/torchrec/>`_
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- PyTorch domain library for common sparsity and parallelism primitives
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- PyTorch domain library for common sparsity and parallelism primitives
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needed for large-scale recommender systems, enabling authors to train
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needed for large-scale recommender systems, enabling authors to train
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models with large embedding tables shared across many GPUs.
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models with large embedding tables shared across many GPUs.
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@@ -130,7 +130,7 @@ After loading the model in this way, the model is fully ready to use the resourc
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torchtune for fine-tuning and inference
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torchtune for fine-tuning and inference
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=============================================
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=============================================
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`torchtune <https://pytorch.org/torchtune/main/>`_ is a PyTorch-native library for easy single and multi-GPU
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`torchtune <https://meta-pytorch.org/torchtune/main/>`_ is a PyTorch-native library for easy single and multi-GPU
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model fine-tuning and inference with LLMs.
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model fine-tuning and inference with LLMs.
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#. Install torchtune using pip.
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#. Install torchtune using pip.
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@@ -240,7 +240,7 @@ The following models are pre-optimized for performance on the AMD Instinct MI325
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- `Hugging Face Datasets <https://huggingface.co/docs/datasets/v3.2.0/en/index>`_ 3.2.0
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- `Hugging Face Datasets <https://huggingface.co/docs/datasets/v3.2.0/en/index>`_ 3.2.0
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* - ``torchdata``
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* - ``torchdata``
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- `TorchData <https://pytorch.org/data/beta/index.html>`_
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- `TorchData <https://meta-pytorch.org/data/beta/index.html>`_
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* - ``tomli``
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* - ``tomli``
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- `Tomli <https://pypi.org/project/tomli/>`_
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- `Tomli <https://pypi.org/project/tomli/>`_
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