Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Wrong model is used in example, should be character instead of subword model #12676

Merged
merged 6 commits into from
Jul 13, 2021
Merged

Wrong model is used in example, should be character instead of subword model #12676

Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
18af50e
Wrong model is used, should be character instead of subword
jsteggink Jul 13, 2021
657a7c2
canine.rst style fix
jsteggink Jul 13, 2021
1be1892
Update docs/source/model_doc/canine.rst
jsteggink Jul 13, 2021
ad6e4fb
Styling canine.rst
jsteggink Jul 13, 2021
346340b
Added links to model cards.
jsteggink Jul 13, 2021
33fb60e
Fixed links to model cards.
jsteggink Jul 13, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 9 additions & 3 deletions docs/source/model_doc/canine.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -48,6 +48,12 @@ Tips:
(which has a predefined Unicode code point). For token classification tasks however, the downsampled sequence of
tokens needs to be upsampled again to match the length of the original character sequence (which is 2048). The
details for this can be found in the paper.
- Models:

- `google/canine-c <https://huggingface.co/google/canine-c>`__: Pre-trained with autoregressive character loss,
12-layer, 768-hidden, 12-heads, 121M parameters (size ~500 MB).
- `google/canine-s <https://huggingface.co/google/canine-s>`__: Pre-trained with subword loss, 12-layer,
768-hidden, 12-heads, 121M parameters (size ~500 MB).

This model was contributed by `nielsr <https://huggingface.co/nielsr>`__. The original code can be found `here
<https://github.com/google-research/language/tree/master/language/canine>`__.
Expand All @@ -63,7 +69,7 @@ CANINE works on raw characters, so it can be used without a tokenizer:
from transformers import CanineModel
import torch

model = CanineModel.from_pretrained('google/canine-s') # model pre-trained with autoregressive character loss
model = CanineModel.from_pretrained('google/canine-c') # model pre-trained with autoregressive character loss

text = "hello world"
# use Python's built-in ord() function to turn each character into its unicode code point id
Expand All @@ -81,8 +87,8 @@ sequences to the same length):

from transformers import CanineTokenizer, CanineModel

model = CanineModel.from_pretrained('google/canine-s')
tokenizer = CanineTokenizer.from_pretrained('google/canine-s')
model = CanineModel.from_pretrained('google/canine-c')
tokenizer = CanineTokenizer.from_pretrained('google/canine-c')

inputs = ["Life is like a box of chocolates.", "You never know what you gonna get."]
encoding = tokenizer(inputs, padding="longest", truncation=True, return_tensors="pt")
Expand Down