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

Updates the default branch from master to main (#16326)

Browse Source 
* Updates the default branch from master to main

* Links from `master` to `main`

* Typo

* Update examples/flax/README.md

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
This commit is contained in:
Lysandre Debut
2022-03-23 08:46:59 +01:00
committed by GitHub
parent 7732148124
commit eca77f4719
101 changed files with 401 additions and 402 deletions
Download Patch File Download Diff File Expand all files Collapse all files

18
templates/adding_a_new_model/ADD_NEW_MODEL_PROPOSAL_TEMPLATE.md
View File

@@ -562,12 +562,12 @@ Cookiecutter!
**Use the Cookiecutter to automatically generate the model's code**
To begin with head over to the [🤗 Transformers
templates](https://github.com/huggingface/transformers/tree/master/templates/adding_a_new_model)
templates](https://github.com/huggingface/transformers/tree/main/templates/adding_a_new_model)
to make use of our `cookiecutter` implementation to automatically
generate all the relevant files for your model. Again, we recommend only
adding the PyTorch version of the model at first. Make sure you follow
the instructions of the `README.md` on the [🤗 Transformers
templates](https://github.com/huggingface/transformers/tree/master/templates/adding_a_new_model)
templates](https://github.com/huggingface/transformers/tree/main/templates/adding_a_new_model)
carefully.
**Open a Pull Request on the main huggingface/transformers repo**
@@ -580,7 +580,7 @@ Transformers.
You should do the following:
1. Create a branch with a descriptive name from your master branch
1. Create a branch with a descriptive name from your main branch
```
git checkout -b add_[lowercase name of model]
@@ -593,11 +593,11 @@ You should do the following:
git commit
```
3. Fetch and rebase to current master
3. Fetch and rebase to current main
```
git fetch upstream
git rebase upstream/master
git rebase upstream/main
```
4. Push the changes to your account using:
@@ -617,10 +617,10 @@ You should do the following:
In the following, whenever you have done some progress, don't forget to
commit your work and push it to your account so that it shows in the
pull request. Additionally, you should make sure to update your work
with the current master from time to time by doing:
with the current main from time to time by doing:
git fetch upstream
git merge upstream/master
git merge upstream/main
In general, all questions you might have regarding the model or your
implementation should be asked in your PR and discussed/solved in the
@@ -703,7 +703,7 @@ similar already existing conversion script for your model.
[here](https://github.com/huggingface/transformers/blob/7acfa95afb8194f8f9c1f4d2c6028224dbed35a2/src/transformers/models/bert/modeling_bert.py#L91)
- If you are porting a model from PyTorch to PyTorch, a good starting
point might be BART's conversion script
[here](https://github.com/huggingface/transformers/blob/master/src/transformers/models/bart/convert_bart_original_pytorch_checkpoint_to_pytorch.py)
[here](https://github.com/huggingface/transformers/blob/main/src/transformers/models/bart/convert_bart_original_pytorch_checkpoint_to_pytorch.py)
In the following, we'll quickly explain how PyTorch models store layer
weights and define layer names. In PyTorch, the name of a layer is
@@ -1122,7 +1122,7 @@ for the community.
**14. Submit your finished PR**
You're done programming now and can move to the last step, which is
getting your PR merged into master. Usually, [name of mentor]
getting your PR merged into main. Usually, [name of mentor]
should have helped you already at this point, but it is worth taking
some time to give your finished PR a nice description and eventually add
comments to your code, if you want to point out certain design choices

18
templates/adding_a_new_model/open_model_proposals/ADD_BIG_BIRD.md
View File

@@ -254,7 +254,7 @@ You should have understood the following aspects of BigBird by now:
- BigBird's self-attention layer is composed of three mechanisms: block sparse (local) self-attention, global self-attention, random self-attention
- BigBird's block sparse (local) self-attention is different from Longformer's local self-attention. How so? Why does that matter? => Can be deployed on TPU much easier this way
- BigBird can be implemented for both an encoder-only model **and**
for an encoder-decoder model, which means that we can reuse lots of [code from RoBERTa](https://github.com/huggingface/transformers/blob/master/src/transformers/models/roberta/modeling_roberta.py) and [from PEGASUS](https://github.com/huggingface/transformers/blob/master/src/transformers/models/pegasus/modeling_pegasus.py) at a later stage.
for an encoder-decoder model, which means that we can reuse lots of [code from RoBERTa](https://github.com/huggingface/transformers/blob/main/src/transformers/models/roberta/modeling_roberta.py) and [from PEGASUS](https://github.com/huggingface/transformers/blob/main/src/transformers/models/pegasus/modeling_pegasus.py) at a later stage.
If any of the mentioned aspects above are **not** clear to you, now is a great time to talk to Patrick.
@@ -569,12 +569,12 @@ Cookiecutter!
**Use the Cookiecutter to automatically generate the model's code**
To begin with head over to the [🤗 Transformers
templates](https://github.com/huggingface/transformers/tree/master/templates/adding_a_new_model)
templates](https://github.com/huggingface/transformers/tree/main/templates/adding_a_new_model)
to make use of our `cookiecutter` implementation to automatically
generate all the relevant files for your model. Again, we recommend only
adding the PyTorch version of the model at first. Make sure you follow
the instructions of the `README.md` on the [🤗 Transformers
templates](https://github.com/huggingface/transformers/tree/master/templates/adding_a_new_model)
templates](https://github.com/huggingface/transformers/tree/main/templates/adding_a_new_model)
carefully.
Since you will first implement the Encoder-only/RoBERTa-like version of BigBird you should
select the `is_encoder_decoder_model = False` option in the cookiecutter. Also, it is recommended
@@ -591,7 +591,7 @@ Transformers.
You should do the following:
1. Create a branch with a descriptive name from your master branch
1. Create a branch with a descriptive name from your main branch
```
git checkout -b add_big_bird
@@ -604,11 +604,11 @@ You should do the following:
git commit
```
3. Fetch and rebase to current master
3. Fetch and rebase to current main
```
git fetch upstream
git rebase upstream/master
git rebase upstream/main
```
4. Push the changes to your account using:
@@ -627,10 +627,10 @@ You should do the following:
In the following, whenever you have done some progress, don't forget to
commit your work and push it to your account so that it shows in the
pull request. Additionally, you should make sure to update your work
with the current master from time to time by doing:
with the current main from time to time by doing:
git fetch upstream
git merge upstream/master
git merge upstream/main
In general, all questions you might have regarding the model or your
implementation should be asked in your PR and discussed/solved in the
@@ -1129,7 +1129,7 @@ for the community.
**14. Submit your finished PR**
You're done programming now and can move to the last step, which is
getting your PR merged into master. Usually, Patrick
getting your PR merged into main. Usually, Patrick
should have helped you already at this point, but it is worth taking
some time to give your finished PR a nice description and eventually add
comments to your code, if you want to point out certain design choices