SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

[t5 doc] make the example work out of the box (#12239)

Browse Source 
* [run_clm.py] restore caching

* style

* [t5 doc] make the example work out of the box

This PR expands the training example to include the correct model type for the example to work, e.g. with `T5Model` this example will break.

* Update docs/source/model_doc/t5.rst

Co-authored-by: Suraj Patil <surajp815@gmail.com>

* expand the other example

Co-authored-by: Suraj Patil <surajp815@gmail.com>
This commit is contained in:
Stas Bekman
2021-06-18 10:00:19 -07:00
committed by GitHub
parent f3558bbcfd
commit 2e5dbdf2db
1 changed files with 8 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
docs/source/model_doc/t5.rst
View File

@@ -74,6 +74,10 @@ token. T5 can be trained / fine-tuned both in a supervised and unsupervised fash
.. code-block:: .. code-block::
from transformers import T5ForConditionalGeneration, T5Tokenizer
model = T5ForConditionalGeneration.from_pretrained("t5-small")
tokenizer = T5Tokenizer.from_pretrained("t5-small")
input_ids = tokenizer('The <extra_id_0> walks in <extra_id_1> park', return_tensors='pt').input_ids input_ids = tokenizer('The <extra_id_0> walks in <extra_id_1> park', return_tensors='pt').input_ids
labels = tokenizer('<extra_id_0> cute dog <extra_id_1> the <extra_id_2>', return_tensors='pt').input_ids labels = tokenizer('<extra_id_0> cute dog <extra_id_1> the <extra_id_2>', return_tensors='pt').input_ids
# the forward function automatically creates the correct decoder_input_ids # the forward function automatically creates the correct decoder_input_ids
@@ -87,6 +91,10 @@ token. T5 can be trained / fine-tuned both in a supervised and unsupervised fash
.. code-block:: .. code-block::
from transformers import T5ForConditionalGeneration, T5Tokenizer
model = T5ForConditionalGeneration.from_pretrained("t5-small")
tokenizer = T5Tokenizer.from_pretrained("t5-small")
input_ids = tokenizer('translate English to German: The house is wonderful.', return_tensors='pt').input_ids input_ids = tokenizer('translate English to German: The house is wonderful.', return_tensors='pt').input_ids
labels = tokenizer('Das Haus ist wunderbar.', return_tensors='pt').input_ids labels = tokenizer('Das Haus ist wunderbar.', return_tensors='pt').input_ids
# the forward function automatically creates the correct decoder_input_ids # the forward function automatically creates the correct decoder_input_ids