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Merge pull request #6855 from adrianeboyd/docs/trf-sentencepiece [ci skip]

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