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Update docs [ci skip]

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This commit is contained in:
Ines Montani 2020-10-08 11:56:50 +02:00
parent 064575d79d
commit d1602e1ece
1 changed files with 4 additions and 4 deletions
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website/docs/usage/embeddings-transformers.md
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@ -235,7 +235,7 @@ The `Transformer` component sets the
which lets you access the transformers outputs at runtime.
```cli
$ python -m spacy download en_core_trf_lg
$ python -m spacy download en_core_web_trf
```
```python
@ -249,7 +249,7 @@ from thinc.api import use_pytorch_for_gpu_memory, require_gpu
use_pytorch_for_gpu_memory()
require_gpu(0)
nlp = spacy.load("en_core_trf_lg")
nlp = spacy.load("en_core_web_trf")
for doc in nlp.pipe(["some text", "some other text"]):
tokvecs = doc._.trf_data.tensors[-1]
```
@ -269,7 +269,7 @@ def custom_annotation_setter(docs, trf_data):
for doc, data in zip(docs, doc_data):
doc._.custom_attr = data
nlp = spacy.load("en_core_trf_lg")
nlp = spacy.load("en_core_web_trf")
nlp.get_pipe("transformer").set_extra_annotations = custom_annotation_setter
doc = nlp("This is a text")
assert isinstance(doc._.custom_attr, TransformerData)
@ -286,7 +286,7 @@ of objects by referring to creation functions, including functions you register
yourself. For details on how to get started with training your own model, check
out the [training quickstart](/usage/training#quickstart).
<!-- TODO: <Project id="en_core_trf_lg">
<!-- TODO: <Project id="pipelines/transformers">
The easiest way to get started is to clone a transformers-based project
template. Swap in your data, edit the settings and hyperparameters and train,