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Update transfomers install docs
* Recommend installing PyTorch separately * Add instructions for `sentencepiece`
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@ -204,14 +204,25 @@ drop-in replacements that let you achieve **higher accuracy** in exchange for
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> downloaded: 3GB CUDA runtime, 800MB PyTorch, 400MB CuPy, 500MB weights, 200MB
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> downloaded: 3GB CUDA runtime, 800MB PyTorch, 400MB CuPy, 500MB weights, 200MB
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> spaCy and dependencies.
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> spaCy and dependencies.
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Once you have CUDA installed, you'll need to install two pip packages,
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Once you have CUDA installed, we recommend installing PyTorch separately
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[`cupy`](https://docs.cupy.dev/en/stable/install.html) and
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following the
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[`spacy-transformers`](https://github.com/explosion/spacy-transformers). `cupy`
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[PyTorch installation guidelines](https://pytorch.org/get-started/locally/) for
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is just like `numpy`, but for GPU. The best way to install it is to choose a
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your package manager and CUDA version. If you skip this step, pip will install
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wheel that matches the version of CUDA you're using. You may also need to set
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PyTorch as a dependency below, but it may not find the best version for your
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the `CUDA_PATH` environment variable if your CUDA runtime is installed in a
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setup.
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non-standard location. Putting it all together, if you had installed CUDA 10.2
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in `/opt/nvidia/cuda`, you would run:
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```bash
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### Example: Install PyTorch 1.7.1 for CUDA 10.1 with pip
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$ pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
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```
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Next, install spaCy with the extras for your CUDA version and transformers. The
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CUDA extra (e.g., `cuda92`, `cuda102`, `cuda111`) installs the correct version
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of [`cupy`](https://docs.cupy.dev/en/stable/install.html#installing-cupy), which
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is just like `numpy`, but for GPU. You may also need to set the `CUDA_PATH`
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environment variable if your CUDA runtime is installed in a non-standard
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location. Putting it all together, if you had installed CUDA 10.2 in
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`/opt/nvidia/cuda`, you would run:
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```bash
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```bash
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### Installation with CUDA
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### Installation with CUDA
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@ -219,6 +230,16 @@ $ export CUDA_PATH="/opt/nvidia/cuda"
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$ pip install -U %%SPACY_PKG_NAME[cuda102,transformers]%%SPACY_PKG_FLAGS
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$ pip install -U %%SPACY_PKG_NAME[cuda102,transformers]%%SPACY_PKG_FLAGS
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```
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```
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For [`transformers`](https://huggingface.co/transformers/) v4.0.0+ and models
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that require [`SentencePiece`](https://github.com/google/sentencepiece) (e.g.,
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ALBERT, CamemBERT, XLNet, Marian, and T5), install the additional dependencies
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with:
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```bash
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### Install sentencepiece
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$ pip install transformers[sentencepiece]
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```
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### Runtime usage {#transformers-runtime}
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### Runtime usage {#transformers-runtime}
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Transformer models can be used as **drop-in replacements** for other types of
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Transformer models can be used as **drop-in replacements** for other types of
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