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https://api.github.com/repos/huggingface/transformers/issues/8021 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8021/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8021/comments | https://api.github.com/repos/huggingface/transformers/issues/8021/events | https://github.com/huggingface/transformers/issues/8021 | 728,822,358 | MDU6SXNzdWU3Mjg4MjIzNTg= | 8,021 | [bart] SinusoidalPositionalEmbedding breaks under pytorch-nightly | {
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```
FAILED tests/test_modeling_bart.py::TestSinusoidalPositionalEmbeddings::test_odd_embed_dim - RuntimeError: a view of a leaf Variable that requires...
FAILED tests/test_modeling_bart.py::TestSinusoidalPositionalEmbeddings::test_positional_emb_cache_logic - RuntimeError: a view of a l... | {
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https://api.github.com/repos/huggingface/transformers/issues/8020 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8020/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8020/comments | https://api.github.com/repos/huggingface/transformers/issues/8020/events | https://github.com/huggingface/transformers/issues/8020 | 728,814,000 | MDU6SXNzdWU3Mjg4MTQwMDA= | 8,020 | sentencepiece 0.1.94 causing segmentation fault | {
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"This can be worked around, for anyone hitting this issue, by setting `sentencepiece==0.1.91` explicitly.",
"Maybe we could set `sentencepiece==0.1.91` in the setup.py to prevent this from happening, as we already had the issue with the 0.1.92.\r\n\r\nDo you want to open a PR for that?",
"This should also be fi... | 1,603 | 1,610 | 1,610 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.4.0 and 3.3.1
- Platform: Linux/Sagemaker
- Python version: 3.7
- PyTorch version (GPU?): 1.4
- Tens... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"Had the same issue. Found a trim_batch implementation on the transformers repo, used it, didn't face any issues so far.\r\n\r\n[Link to... | 1,603 | 1,613 | 1,609 | NONE | null | from transformers.tokenization_utils import trim_batch
ImportError: cannot import name 'trim_batch'
Any solutions? Thanks a lot. | {
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"You're correct! @patrickvonplaten, git blame shows you as the author, want to fix?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,603 | 1,609 | 1,609 | NONE | null | In the Translation section in https://huggingface.co/transformers/task_summary.html
"
Here is an example of doing translation using a model and a tokenizer. The process is the following:
1.Instantiate a tokenizer and a model from the checkpoint name. Summarization is usually done using an encoder-decoder model, such... | {
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This PR adds Trainer integration with [MLflow](https://mlflow.org/).
It is implemented in roughly the same way as other integration callbacks (CometML, wandb) and gets added to the list of Trainer callbacks automatically when mlflow is installed. All the mlflow parameters are configured w... | {
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"One probably related issue is that if I try to use `model.evaluate` I get an error with the following traceback:\r\n```\r\n\r\n---------------------------------------------------------------------------\r\nValueError Traceback (most recent call last)\r\n<ipython-input-125-3f03cbe29a6... | 1,603 | 1,603 | 1,603 | NONE | null | I'm trying to fine-tune `TFDistilBertForSequenceClassification` for multi-class classification (100 classes) on a custom dataset following the tutorial at https://huggingface.co/transformers/custom_datasets.html.
I'm following the workflow for fine-tuning in native tensorflow, i.e.:
```
from transformers import... | {
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@sshleifer | {
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"### Solution\r\n\r\nIf you encounter the same, here is how to fix it:\r\n\r\n```\r\npip uninstall -y tensorflow-gpu tensorflow\r\npip install tensorflow-gpu -U \r\n```\r\n(I assume you want the gpu version - adjust if not)\r\n",
"I think that for the last few versions, when installing `tensorflow` you get a `ten... | 1,603 | 1,668 | 1,603 | CONTRIBUTOR | null | Problem and solution:
This happened several times as of recent. Some env gets messed up and I end up with most tests failing with:
```____________________________________________________ ERROR collecting tests/test_benchmark_tf.py ____________________________________________________
tests/test_benchmark_tf.py:6: i... | {
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"is self.generate?",
"Hello! Could you provide all the information relative to your environment as asked in the template, as well as the code that generates the error? Thanks!",
"Thanks for your replying!\r\n\r\noutputs = self(**model_inputs)\r\nThis code appear in function _generate_beam_search and _generate_... | 1,603 | 1,609 | 1,609 | NONE | null | Traceback (most recent call last):
File "D:\Program Files\JetBrains\PyCharm 2018.3.2\helpers\pydev\pydevd.py", line 1741, in <module>
main()
File "D:\Program Files\JetBrains\PyCharm 2018.3.2\helpers\pydev\pydevd.py", line 1735, in main
globals = debugger.run(setup['file'], None, None, is_module)
File... | {
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Add a script that does some styling on the doc files and docstrings.
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"Hi! Could you put the whole stack trace here? I fear it might be an internal sentencepiece error, for which we'll be unable to help and you would have more luck opening an issue on the sentencepiece repo directly.",
"This issue has been automatically marked as stale because it has not had recent activity. It wil... | 1,603 | 1,609 | 1,609 | NONE | null | - `transformers` version: 3.0.2
- Platform: Linux-4.4.0-137-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No
### Who can help
@mfuntow... | {
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"`tests/test_tokenization_fsmt.py::FSMTTokenizationTest::test_match_encode_decode` fixed in https://github.com/huggingface/transformers/pull/8031\r\n\r\nI checked it off in your list.",
"@patrickvonplaten can you take a look at the failing TF-Longformer and TF-T5 tests?",
"> @patrickvonplaten can you take a loo... | 1,603 | 1,604 | 1,604 | MEMBER | null | Enable the slow TF suite on GPU. Below are the current failing tests.
Investigating whether they're actually failing or if it's for some other reason.
- [x] ~FAILED tests/test_modeling_marian.py::ModelManagementTests::test_model_names~
- [x] ~FAILED tests/test_modeling_prophetnet.py::ProphetNetModelIntegrationT... | {
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Fixes #8001
Now the tokenizers classes have to send all the keyword arguments of the `__init__` up to the base class of the tokenizer (by `super().__init__`) were they are stored in `init_kwargs` for serialized saving/reloading with `save_pretrained/from_pretrained`.
Adding a test on to... | {
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https://api.github.com/repos/huggingface/transformers/issues/8005 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8005/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8005/comments | https://api.github.com/repos/huggingface/transformers/issues/8005/events | https://github.com/huggingface/transformers/issues/8005 | 728,312,850 | MDU6SXNzdWU3MjgzMTI4NTA= | 8,005 | Differences between facebook/bart-base and facebook/bart-large? | {
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"If you look at\r\n\r\nhttps://s3.amazonaws.com/models.huggingface.co/bert/facebook/bart-large/config.json\r\nand \r\nhttps://s3.amazonaws.com/models.huggingface.co/bert/facebook/bart-base/config.json\r\n(how to do this for any model: go to [model hub](https://s3.amazonaws.com/models.huggingface.co/) and click see ... | 1,603 | 1,641 | 1,610 | NONE | null | # ❓ Questions & Help
Is there some more difference between `facebook/bart-base` and `facebook/bart-large` (other than dimensions, heads and layers)?
## Who can help
@sshleifer @WiseDoge
## Environment info
- transformers version: 3.3.1
- Python version: 3.6.12
- PyTorch version (GPU?): 1.4.0 GPU-versio... | {
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"Closed in favor of #8002 "
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"Oh! I'll take a look, thanks for the report @tholor ",
"Thanks for the fast fix @thomwolf ! Very much appreciated!"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 3.4.0
- Platform: Linux-5.4.0-52-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.6
- PyTorch version (GPU?): 1.5.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
... | {
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https://api.github.com/repos/huggingface/transformers/issues/8000 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8000/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8000/comments | https://api.github.com/repos/huggingface/transformers/issues/8000/events | https://github.com/huggingface/transformers/issues/8000 | 728,031,905 | MDU6SXNzdWU3MjgwMzE5MDU= | 8,000 | How to load tokenizer for models without vocab.txt? | {
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"Hello! In order to use the xlm-roberta-large model, why don't you use the `from_pretrained` method?\r\n\r\n```py\r\nfrom transformers import XLMRobertaModel\r\n\r\nmodel = XLMRobertaModel.from_pretrained(\"xlm-roberta-large\")\r\n```",
"> Hello! In order to use the xlm-roberta-large model, why don't you use the ... | 1,603 | 1,609 | 1,609 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to the Hugging Face forum: https://discuss.huggingface.co/ .
You can also try Stack Overflow (SO) where a wh... | {
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Add model cards for DynaBERT. | {
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https://api.github.com/repos/huggingface/transformers/issues/7998 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7998/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7998/comments | https://api.github.com/repos/huggingface/transformers/issues/7998/events | https://github.com/huggingface/transformers/pull/7998 | 727,916,290 | MDExOlB1bGxSZXF1ZXN0NTA4NzIwMzA1 | 7,998 | update version for scipy | {
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"Let's wait for Victor to answer on that issue before merging.",
"looks good!"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | # What does this PR do?
updating version requirement for scipy in 'examples\\distillation\\requirements.txt'.
fix [https://github.com/huggingface/transformers/issues/7967](url)
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/7996 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7996/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7996/comments | https://api.github.com/repos/huggingface/transformers/issues/7996/events | https://github.com/huggingface/transformers/pull/7996 | 727,840,507 | MDExOlB1bGxSZXF1ZXN0NTA4NjU2MTY1 | 7,996 | Added model cards for Tagalog ELECTRA models | {
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"@jcblaisecruz02 looks like your config.json files do not contain a `architectures` field nor a `model_type`, so your models might be incorrectly categorized – any way you could add those? Thank you!",
"> @jcblaisecruz02 looks like your config.json files do not contain a `architectures` field nor a `model_type`, ... | 1,603 | 1,603 | 1,603 | NONE | null | # What does this PR do?
Added model cards for eight ELECTRA Tagalog models (four generators and four discriminators). | {
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https://api.github.com/repos/huggingface/transformers/issues/7995 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7995/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7995/comments | https://api.github.com/repos/huggingface/transformers/issues/7995/events | https://github.com/huggingface/transformers/pull/7995 | 727,838,660 | MDExOlB1bGxSZXF1ZXN0NTA4NjU0NzQ5 | 7,995 | [CI] generate separate report files as artifacts | {
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"This looks good but I only see `test_output.txt` in the artifacts, for some reason?",
"you must be looking at the wrong job? As I said I only did it for one job at the moment - this one:\r\nhttps://app.circleci.com/pipelines/github/huggingface/transformers/14359/workflows/b38c8e8c-2867-4366-a907-a202da9bc9ee/job... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | This PR solves https://github.com/huggingface/transformers/issues/7887 to produce easier to use reports on CIs.
* [x] adds an optional `--make_reports=id` to `pytest`- e.g. `--make_reports=examples`. It then uses that id to generate `report_{id}_{reports}.txt` - this was needed since some jobs like on scheduled jobs... | {
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https://api.github.com/repos/huggingface/transformers/issues/7994 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7994/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7994/comments | https://api.github.com/repos/huggingface/transformers/issues/7994/events | https://github.com/huggingface/transformers/issues/7994 | 727,804,903 | MDU6SXNzdWU3Mjc4MDQ5MDM= | 7,994 | BertTokenizer's add_token won't add token | {
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"It seems not work until I save the new tokenizer. I close the issue.\r\n```\r\ntokenizer.save_pretrained('/path/to/tokenizer')\r\ntokenizer = BertTokenizer.from_pretrained('/path/to/tokenizer')\r\n```",
"looks like tokenizer.vocab_size does not update after add tokens. but len(tokenizer) shows correct number ",
... | 1,603 | 1,603 | 1,603 | NONE | null | `add_token` actually won't add token. Please refer to the code below:
```
from transformers import BertTokenizer
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased', do_lower_case=True)
tokenizer.vocab_size
>>30522
tokenizer.add_tokens(new_tokens=['[SUBJ]', '[OBJ]'], special_tokens=True)
>>2
token... | {
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https://api.github.com/repos/huggingface/transformers/issues/7993 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7993/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7993/comments | https://api.github.com/repos/huggingface/transformers/issues/7993/events | https://github.com/huggingface/transformers/pull/7993 | 727,731,547 | MDExOlB1bGxSZXF1ZXN0NTA4NTY3NjQ1 | 7,993 | [docs] [testing] distributed training | {
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"One followup is to update the `test_trainer_distributed` to work with pytest. Then ideally, if we could have one command to run all those tests, that would be awesome (maybe we can use a pytest marker to mark all distributed-specific tests so it's easy to select them all?)",
"I will port `test_trainer_distribute... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | We figured out how to support distributed training with `pytest`, this is a preliminary doc snippet to help those in need to find the current implementation. I'm sure it will evolve as we have more tests with varying needs, but for now that's all we have.
@sgugger | {
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Just changing bart's zero shot widget example. | {
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The `crime-and-punishment` tokenizer actually does not have a `pad_token_id` - check with this [notebook](https://colab.research.google.com/github/google/trax/blob/master/trax/models/reformer/text_generation.ipynb#scrollTo=iDgvKNa_DDIq). Since this is our only tokenizer for Reformer, we shoul... | {
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https://api.github.com/repos/huggingface/transformers/issues/7990 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7990/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7990/comments | https://api.github.com/repos/huggingface/transformers/issues/7990/events | https://github.com/huggingface/transformers/pull/7990 | 727,693,335 | MDExOlB1bGxSZXF1ZXN0NTA4NTM1OTIw | 7,990 | Handling longformer model_type | {
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"cc @patil-suraj @patrickvonplaten @xixiaoyao"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | Updating the run_squad training script to handle the "longformer" `model_type`. The longformer is trained in the same was as RoBERTa, so I've added the "longformer" `model_type` (that's the right hugginface name for the LongFormer model, right?) everywhere there was a "roberta" `model_type` reference. The longformer (l... | {
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https://api.github.com/repos/huggingface/transformers/issues/7989 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7989/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7989/comments | https://api.github.com/repos/huggingface/transformers/issues/7989/events | https://github.com/huggingface/transformers/pull/7989 | 727,681,964 | MDExOlB1bGxSZXF1ZXN0NTA4NTI2NTMy | 7,989 | [gh ci] less output ( --durations=50) | {
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"Thank you for the heads up - I will be working on all these related issues shortly - too much data indeed, but not just that.",
"I'd say remove them complete for now and also -rA - I need to experiment and see how to make this data available w/o making logs unusable. ",
"More context on github actions:\r\n\r\n... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | Way too much output in [this](https://github.com/huggingface/transformers/pull/7989)
This will make it slightly better.
cc @stas00
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https://api.github.com/repos/huggingface/transformers/issues/7988 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7988/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7988/comments | https://api.github.com/repos/huggingface/transformers/issues/7988/events | https://github.com/huggingface/transformers/issues/7988 | 727,668,194 | MDU6SXNzdWU3Mjc2NjgxOTQ= | 7,988 | [Good first issue] Documentation links in older docs versions | {
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"Hi, has anyone picked this up? I can give it a go in the coming week or two when I have some let off from releases at work if no-one is doing this. ",
"Nobody has picked this up yet, would love to see such a contribution!",
"Awesome, have our last release till year end freeze this week at work. I'll get in th... | 1,603 | 1,609 | 1,609 | MEMBER | null | # 🚀 Feature request
This is a documentation request in order to make it easier to find corresponding examples in the documentation.
Good first issue if you want to get acquainted with the docs and how to build docs using Sphinx!
## Current issue
Here's the issue: currently, if one goes to an older documen... | {
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"@patrickvonplaten \r\n+ I deleted the `_force_token_id` function, replaced with faster `tf.where` one-liner. (+ added regression test). \r\n+ Replaced unneeded `TFSharedEmbedding` with `tf.keras.layers.Embedding`\r\n+ switched all `.shape` to `shape_list`\r\n\r\nWDYT?"
] | 1,603 | 1,604 | 1,604 | CONTRIBUTOR | null | ### Notes:
- add `TFSinusoidalPositionalEmbeddings`.
- Code structure identical to the corresponding pytorch code -- same classes, implementations differ only slightly.
- Integration tests and common tests, rst updates, for all 4 children. All 4 children run the same common tests as TFBart and at least 1 integration... | {
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https://api.github.com/repos/huggingface/transformers/issues/7986 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7986/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7986/comments | https://api.github.com/repos/huggingface/transformers/issues/7986/events | https://github.com/huggingface/transformers/issues/7986 | 727,656,041 | MDU6SXNzdWU3Mjc2NTYwNDE= | 7,986 | T5 Decoder Inputs | {
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"your 2nd option is correct here: \r\n\r\n```python\r\n# pad_token prepended, eos_token unmasked in attention\r\ndecoder_input_ids: tensor([[0, 2018, 55, 1, 0, 0, 0]])\r\ndecoder_attention_mask: tensor([[1, 1, 1, 1, 0, 0, 0]])\r\n```\r\n\r\n1) You have to start with `decoder_start_token_id = pad_token_id` in T5 and... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | # ❓ Questions & Help
Just confirming that my data preprocessing is perfect for T5. I added a print statement in `T5ConditionalGeneration` for the `decoder_input_ids` and `decoder_attention_mask` just before they're passed to the decoder. Which of these is right?
```
# pad_token prepended, eos_token is not in the s... | {
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https://api.github.com/repos/huggingface/transformers/issues/7985 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7985/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7985/comments | https://api.github.com/repos/huggingface/transformers/issues/7985/events | https://github.com/huggingface/transformers/pull/7985 | 727,642,768 | MDExOlB1bGxSZXF1ZXN0NTA4NDk0Njgz | 7,985 | [setup] require torch>=1.4 | {
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"@patrickvonplaten @sshleifer @sgugger Could we solve the errors here to have `torch>=1.3` instead?",
"May be it's simpler to set it to 1.4+ and only if someone asks for it to bother with 1.3?",
"After discussion with the team, we'll take a look at supporting v1.3+ in the coming days, and if it requires too man... | 1,603 | 1,622 | 1,622 | CONTRIBUTOR | null | I run the non-slow test suite on lower torch versions:
* torch-1.2 and below is definitely a no go - a gazillion of errors in the test suite.
* torch-1.3+ is mostly OK, but:
```
FAILED tests/test_modeling_bart.py::BartHeadTests::test_generate_fp16 - RuntimeError: "argmax_cuda" not implemented for 'Half'
FAILED... | {
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This PR fixes a few bugs linked to resuming training from a checkpoint, mainly:
- the progress was not properly displayed (beginning at 0 instead of the step from the checkpoint)
- reloading the optimizer state and scheduler state on TPU was causing an error
Tested on TPU, single-GPU and... | {
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https://api.github.com/repos/huggingface/transformers/issues/7983 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7983/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7983/comments | https://api.github.com/repos/huggingface/transformers/issues/7983/events | https://github.com/huggingface/transformers/pull/7983 | 727,604,487 | MDExOlB1bGxSZXF1ZXN0NTA4NDY0MjU3 | 7,983 | add zero shot pipeline tags & examples | {
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Adds the zero shot pipeline tag as well as default examples for a selection of pre-trained MNLI models. cc @patil-suraj | {
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https://api.github.com/repos/huggingface/transformers/issues/7982 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7982/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7982/comments | https://api.github.com/repos/huggingface/transformers/issues/7982/events | https://github.com/huggingface/transformers/issues/7982 | 727,575,895 | MDU6SXNzdWU3Mjc1NzU4OTU= | 7,982 | [s2s test] examples/seq2seq/test_finetune_trainer.py::TestFinetuneTrainer::test_finetune_trainer_slow fails on GPU | {
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"I would fix this by training on much more data (like 1000 obs) and getting the loss down much further.",
"I used more iterations - 6 was enough for 1 gpu, 10 for 2, so I went with 10.\r\n\r\nThis issue will be resolved by https://github.com/huggingface/transformers/pull/7965"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | This works (cpu / any pytorch):
```
CUDA_VISIBLE_DEVICES="" RUN_SLOW=1 pytest -sv examples/seq2seq/test_finetune_trainer.py::TestFinetuneTrainer::test_finetune_trainer_slow
```
This fails torch-1.5/gpu or 1.6, or nightly:
```
CUDA_VISIBLE_DEVICES="0" RUN_SLOW=1 pytest -sv examples/seq2seq/test_finetune_trainer.py... | {
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This PR removes the addition of `total_flos` at each (and every) log, since this kind of pollutes them, and only logs it once and for all at the end of training. Users can still define their own callbacks and do more with that value if they really want to, but from what I understood. @TevenLe... | {
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"Could you provide the information related to your environment, as well as the code that outputs this error, like it is asked in the issue template?",
"I am facing same issue as the given issu 'DistributedDataParallel' is custom class created by coder that is having base model available in Transformer repo\r\n\r\... | 1,603 | 1,667 | 1,609 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to the Hugging Face forum: https://discuss.huggingface.co/ .
You can also try Stack Overflow (SO) where a wh... | {
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"Hey @yhznb, \r\n\r\nWe try to mainly use the github issues for bugs in the library. For more customized questions it would be great if you could use https://discuss.huggingface.co/ instead.\r\n\r\nRegarding your question I would just add a layer to `BertLMHeadModel` wherever you want to and then build your `Encode... | 1,603 | 1,604 | 1,604 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to the Hugging Face forum: https://discuss.huggingface.co/ .
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https://api.github.com/repos/huggingface/transformers/issues/7977 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7977/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7977/comments | https://api.github.com/repos/huggingface/transformers/issues/7977/events | https://github.com/huggingface/transformers/pull/7977 | 727,349,039 | MDExOlB1bGxSZXF1ZXN0NTA4MjU3Nzgy | 7,977 | GPT2 - Remove else branch adding 0 to the hidden state if token_type_embeds is None. | {
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This can be simplified to:
- avoid summing 0 over many elements
- avoid using raw Python scalar value which cannot be traced by TorchScript / ONNX when exporting.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/7976 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7976/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7976/comments | https://api.github.com/repos/huggingface/transformers/issues/7976/events | https://github.com/huggingface/transformers/issues/7976 | 727,334,859 | MDU6SXNzdWU3MjczMzQ4NTk= | 7,976 | [XLA] Cannot restore from checkpoint on TPU | {
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"Pinging @sgugger "
] | 1,603 | 1,603 | 1,603 | NONE | null | ## Environment info
- `transformers` version: 3.4.0
- Platform: Linux-4.9.0-13-amd64-x86_64-with-debian-9.13
- Python version: 3.6.10
- PyTorch version (GPU?): 1.8.0a0+e5ed037 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No (but using TPU)
- Using distributed or parallel set-up... | {
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https://api.github.com/repos/huggingface/transformers/issues/7975 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7975/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7975/comments | https://api.github.com/repos/huggingface/transformers/issues/7975/events | https://github.com/huggingface/transformers/pull/7975 | 727,308,847 | MDExOlB1bGxSZXF1ZXN0NTA4MjI0OTAz | 7,975 | Fixing the "translation", "translation_XX_to_YY" pipelines. | {
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"But If 1 models implies 1 task, how should we cope with models that are able to do multiple things (like `t5-base`) ? \r\n\r\nI think `datasets` does it correctly in that it does not make any choice on your behalf, but instead raises an Exception with your available choices.",
"> But If 1 models implies 1 task, ... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | # What does this PR do
Actually make the "translation", "translation_XX_to_YY" task behave correctly.
Background:
- Currently "translation_cn_to_ar" does not work. (only 3 pairs are
supported)
- Some models, contain in their config the correct values for the (src,
tgt) pair they can translate. It's usually ju... | {
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"It was recently added, so you may need to upgrade your version of transformers.",
"> It was recently added, so you may need to upgrade your version of transformers.\r\n\r\nThanks,it works!\r\nI use transformers in \r\n\r\n> kaggle notebook\r\n\r\n , maybe there is some bug in such online applications. I once tri... | 1,603 | 1,656 | 1,609 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
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https://api.github.com/repos/huggingface/transformers/issues/7973 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7973/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7973/comments | https://api.github.com/repos/huggingface/transformers/issues/7973/events | https://github.com/huggingface/transformers/pull/7973 | 727,289,812 | MDExOlB1bGxSZXF1ZXN0NTA4MjA5Nzk5 | 7,973 | support relative path for best_model_checkpoint | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/7972 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7972/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7972/comments | https://api.github.com/repos/huggingface/transformers/issues/7972/events | https://github.com/huggingface/transformers/issues/7972 | 727,261,885 | MDU6SXNzdWU3MjcyNjE4ODU= | 7,972 | Unable to load UnifiedQA models, tf throws DataLossError | {
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"As far as I can see, the model you are trying load doesn't have a compliant format. We cannot help more without the full error stack.",
"Edit, added the full error stack.\r\nAlso, this is fairly easy to reproduce."
] | 1,603 | 1,603 | 1,603 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.4.0
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/7971 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7971/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7971/comments | https://api.github.com/repos/huggingface/transformers/issues/7971/events | https://github.com/huggingface/transformers/pull/7971 | 727,255,674 | MDExOlB1bGxSZXF1ZXN0NTA4MTgxNzcz | 7,971 | FillMaskPipeline: support passing top_k on __call__ | {
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"Ok so should be ready to merge after a quick review @LysandreJik @sgugger!"
] | 1,603 | 1,603 | 1,603 | MEMBER | null | Also change name from topk to top_k for more consistency with the TextGenerationPipeline | {
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https://api.github.com/repos/huggingface/transformers/issues/7970 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7970/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7970/comments | https://api.github.com/repos/huggingface/transformers/issues/7970/events | https://github.com/huggingface/transformers/pull/7970 | 727,243,776 | MDExOlB1bGxSZXF1ZXN0NTA4MTcxOTMz | 7,970 | [tests|tokenizers] Refactoring pipelines test backbone - Small tokenizers improvements - General tests speedups | {
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"Tagging a few people working on the pipelines and @sshleifer because I've added additional imports of TF Bart in `modeling_tf_auto` to make the pipelines happy.",
"Ok. great, thanks @sgugger and @sshleifer.\r\n\r\nI took the occasion to speed up the CI test suite (cc @stas00) by:\r\n- spinning out the pipeline t... | 1,603 | 1,603 | 1,603 | MEMBER | null | # What does this PR do?
This PR refactor the pipeline tests to split them in smaller parts more easy to iterate on.
There is now:
- one common backbone for testing pipelines in `test_pipeline_common.py` with two Mixin that can be used depending on the test: `CustomInputPipelineCommonMixin` and `MonoInputPipeline... | {
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"I think we should also add some meta-information (see [here](https://github.com/huggingface/model_card)) to the models:\r\n\r\n```\r\n---\r\nlanguage: de\r\nlicense: mit\r\ndatasets:\r\n- wikipedia\r\n---\r\n```\r\n\r\nAnd maybe we need to add `masked-lm` to the `tags` array, so that we can use the inference widge... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | Add model cards for new German language models. Paper [here](https://arxiv.org/abs/2010.10906) | {
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https://api.github.com/repos/huggingface/transformers/issues/7968 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7968/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7968/comments | https://api.github.com/repos/huggingface/transformers/issues/7968/events | https://github.com/huggingface/transformers/pull/7968 | 727,219,499 | MDExOlB1bGxSZXF1ZXN0NTA4MTUyMjUw | 7,968 | Herbert tokenizer auto load | {
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Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/... | {
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https://api.github.com/repos/huggingface/transformers/issues/7967 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7967/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7967/comments | https://api.github.com/repos/huggingface/transformers/issues/7967/events | https://github.com/huggingface/transformers/issues/7967 | 727,169,267 | MDU6SXNzdWU3MjcxNjkyNjc= | 7,967 | Should update version requirement for scipy in 'examples\\distillation\\requirements.txt'? | {
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"@VictorSanh what do you think?"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | There are inconsistent version requirements for scipy in 'examples\\distillation\\requirements.txt' and 'examples\\movement-pruning\\requirements.txt'. Fixed version **1.3.1** in 'examples\\distillation\\requirements.txt' is not in the version range in **'>=1.4.1'** in 'examples\\movement-pruning\\requirements.txt'.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/7966 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7966/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7966/comments | https://api.github.com/repos/huggingface/transformers/issues/7966/events | https://github.com/huggingface/transformers/issues/7966 | 727,090,997 | MDU6SXNzdWU3MjcwOTA5OTc= | 7,966 | T5 with allowing model changes | {
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"Hey @rabeehk - for more specific cases we recommend that you fork master and tweak the model however you would like to so that it fits your purpose. \r\nI didn't understand 100% what kind of script you are looking for, but here you can browse some of the T5 scripts, we have collected: https://github.com/huggingfac... | 1,603 | 1,608 | 1,608 | NONE | null | Hi
I would like to be able to change the model of T5, in addition to training on multiple tasks, I think currently the script can work for summarization only. Do you know possible other scripts allowing training on multiple tasks?
One more question that in T5 in tensorflow repo, they have a small example for using y... | {
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https://api.github.com/repos/huggingface/transformers/issues/7965 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7965/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7965/comments | https://api.github.com/repos/huggingface/transformers/issues/7965/events | https://github.com/huggingface/transformers/pull/7965 | 727,068,000 | MDExOlB1bGxSZXF1ZXN0NTA4MDMwOTk2 | 7,965 | [s2s trainer] tests to use distributed on multi-gpu machine | {
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"@sshleifer, the slow test isn't working for me prior to this PR with 0 or 1 gpu:\r\n\r\n```\r\nCUDA_VISIBLE_DEVICES=\"\" RUN_SLOW=1 pytest -sv examples/seq2seq/test_finetune_trainer.py::TestFinetuneTrainer::test_finetune_trainer_slow \r\n[...]\r\n\r\nself = <seq2seq.test_finetune_trainer.TestFinetuneTrainer test... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | This PR:
* [x] abstracts the async forking io into local `utils.py`
* [x] deploys distributed training with special async io forking for `examples/seq2seq/test_finetune_trainer.py`
So now this works (2 gpus):
```
CUDA_VISIBLE_DEVICES="0,1" RUN_SLOW=1 pytest -sv examples/seq2seq/test_finetune_trainer.py
```
a... | {
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https://api.github.com/repos/huggingface/transformers/issues/7964 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7964/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7964/comments | https://api.github.com/repos/huggingface/transformers/issues/7964/events | https://github.com/huggingface/transformers/pull/7964 | 727,058,304 | MDExOlB1bGxSZXF1ZXN0NTA4MDIyNjk0 | 7,964 | adding beginner-friendly notebook on text classification with DistilBERT/TF | {
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Looking at the current community notebooks, it seems that few are targeted for absolute beginners and even fewer are written with TensorFlow. This notebook describes absolutely everything a beginner would need to know, including how to save/load their model and use it for new predictions (this ... | {
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https://api.github.com/repos/huggingface/transformers/issues/7963 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7963/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7963/comments | https://api.github.com/repos/huggingface/transformers/issues/7963/events | https://github.com/huggingface/transformers/issues/7963 | 727,002,341 | MDU6SXNzdWU3MjcwMDIzNDE= | 7,963 | Load tuned model without downloading from huggingface | {
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" Instead of doing `self.base = DistilBertModel(DistilBertConfig())` you can do `self.base = DistilBertModel(DistilBertConfig(vocab_size=119547))`.\r\n"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | I have the following model which I have tuned for a classification task.
```python
BASE_MODEL = "distilbert-base-multilingual-cased"
class Model(nn.Module):
def __init__(self, nc, p=0.1):
super().__init__()
self.base = AutoModel.from_pretrained(BASE_MODEL)
in_features = 768 # self.b... | {
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https://api.github.com/repos/huggingface/transformers/issues/7962 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7962/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7962/comments | https://api.github.com/repos/huggingface/transformers/issues/7962/events | https://github.com/huggingface/transformers/issues/7962 | 726,988,544 | MDU6SXNzdWU3MjY5ODg1NDQ= | 7,962 | xla_spawn and run_language_modeling slow on TPUs | {
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"The only difference I'm seeing between our script and yours is the data loading, here using `datasets`. Are we aware of TPU slowdown when using `datasets` @lhoestq, @thomwolf?",
"I haven't tested `datasets` with TPU yet. I know @sgugger tried once, did you notice slowdowns ?",
"Not for the new run_glue script ... | 1,603 | 1,604 | 1,604 | NONE | null | ## Environment info
- `transformers` version: 3.4.0
- Platform: Linux-4.9.0-13-amd64-x86_64-with-debian-9.13
- Python version: 3.6.10
- PyTorch version (GPU?): 1.8.0a0+e5ed037 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No (but using TPU)
- Using distributed or parallel set-... | {
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https://api.github.com/repos/huggingface/transformers/issues/7961 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7961/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7961/comments | https://api.github.com/repos/huggingface/transformers/issues/7961/events | https://github.com/huggingface/transformers/issues/7961 | 726,986,169 | MDU6SXNzdWU3MjY5ODYxNjk= | 7,961 | A question about shift_tokens_right in BART model | {
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"It's correct, copied from fairseq (authors code).\r\nyou can think of `shift_tokens_right` as `shift_tokens_right_and_wrap_eos_to_position0`.\r\nIf you have empirical evidence that there is a change that improves fine-tuning, I'd be happy to incorporate it.\r\n",
"After I updated my version for this one, I'm als... | 1,603 | 1,603 | 1,603 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.10
- Platform: Ubuntu 16.04
- Python version: 3.7.3
- PyTorch version (GPU?): 1.6 GPU-version
### ... | {
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https://api.github.com/repos/huggingface/transformers/issues/7960 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7960/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7960/comments | https://api.github.com/repos/huggingface/transformers/issues/7960/events | https://github.com/huggingface/transformers/pull/7960 | 726,962,855 | MDExOlB1bGxSZXF1ZXN0NTA3OTQ2OTEx | 7,960 | RoBERTa convert-script modified to support mapping of bpe tokens | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,603 | 1,619 | 1,619 | NONE | null | # Reordering of embeddings possible when converting roberta with dict file
When RoBERTa is trained using fairseq the preprocessing pipeline bpe encodes tokens and stores a mapping of token ids to bpe-token ids in a dict.txt file. This is mostly just a re-ordering of the tokens (potentially with a few missing ones if... | {
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https://api.github.com/repos/huggingface/transformers/issues/7959 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7959/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7959/comments | https://api.github.com/repos/huggingface/transformers/issues/7959/events | https://github.com/huggingface/transformers/issues/7959 | 726,958,493 | MDU6SXNzdWU3MjY5NTg0OTM= | 7,959 | T5-large on multiple gpus. | {
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"For OOM errors, I guess you need to reduce batch_size or parallelize over more GPUs.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,603 | 1,609 | 1,609 | NONE | null | Hi! I'm trying to fine-tune a T5-large on multiple gpus, so I basically use `torch.nn.DataParallel`, but when I get the output of the model which contains the loss and I do `loss.mean().backward()` I run into `cuda out of memory` as I think the loss is just on the first gpu and that's taken. What should I do? | {
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https://api.github.com/repos/huggingface/transformers/issues/7958 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7958/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7958/comments | https://api.github.com/repos/huggingface/transformers/issues/7958/events | https://github.com/huggingface/transformers/pull/7958 | 726,954,715 | MDExOlB1bGxSZXF1ZXN0NTA3OTQwMjMx | 7,958 | added qg evaluation notebook | {
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"Thanks Patrick :)\r\n\r\nThank you for sharing this @zolekode !",
"@patrickvonplaten thanks for the correction"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | @patrickvonplaten, @TevenLeScao
I added a notebook to evaluate question generation models. Could you please take a look ? | {
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https://api.github.com/repos/huggingface/transformers/issues/7957 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7957/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7957/comments | https://api.github.com/repos/huggingface/transformers/issues/7957/events | https://github.com/huggingface/transformers/issues/7957 | 726,924,716 | MDU6SXNzdWU3MjY5MjQ3MTY= | 7,957 | dropping "," in date because of Tokenization | {
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"Hi, I'm sorry but I really don't understand what the issue is. Could you clarify?",
"I think this comes from the original Albert tokenization, maybe you want to ask on google repository about this?\r\nhttps://github.com/google-research/albert/blob/master/tokenization.py#L67",
"This issue has been automatically... | 1,603 | 1,609 | 1,609 | NONE | null | I had my model where "May 7, 2020" is split like this
`['▁may', b'\xe2\x96\x818', ',', '▁2017']`
I saw that this is a problem here. Any reason why this code was thrown in for bytes string insertion where we have a comma in the token of len > 1?
```
for piece in pieces:
if len(piece) > 1 and piece[-1]... | {
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"pinging the T5 master @patrickvonplaten ",
"Hey @rabeehk - not sure about that. You can check the T5 notebooks we provide or `https://discuss.huggingface.co/`.",
"Hi\nI could not find notebooks in the link you said.\nI am looking for a way to train multiple tasks at once in T5, similar to\nthis script:\nhttps:... | 1,603 | 1,609 | 1,609 | NONE | null | Hi Everyone,
Is there an example showing how to run T5 on multiple datasets? Greatly appreciated.
thanks.
Best
Rabeeh | {
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"Also what does `extras[\"all\"]` stand for? Is it a vestige of something?\r\nhttps://github.com/huggingface/transformers/blob/master/setup.py#L94\r\n\r\nI'd put it last and really put everything into `all` unless I'm missing a special purpose here.",
"Does `transformers` really work `torch==1.0` or would we rea... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | This PR
* [x] does a major revamp to how targets are specified and merged into groups. it lists all the dependencies vertically and allows you to write comments next to them, if needed - or completely comment them out
* [x] adds `docs` to `dev`, since we need to have the tools to run `make docs`
* [x] adds `flax`... | {
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https://api.github.com/repos/huggingface/transformers/issues/7954 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7954/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7954/comments | https://api.github.com/repos/huggingface/transformers/issues/7954/events | https://github.com/huggingface/transformers/issues/7954 | 726,833,255 | MDU6SXNzdWU3MjY4MzMyNTU= | 7,954 | TF: Faster to way to set one column/all but one column of a tensor to -inf | {
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"Solution: https://stackoverflow.com/questions/64575346/tensorflow-set-column-of-tensor-to-infinity"
] | 1,603 | 1,604 | 1,604 | CONTRIBUTOR | null | in `_force_token_id_to_be_generated` we have much simpler torch code:
```python
scores[:, [x for if x != token_id]] = -float("inf")
```
Is it possible to make the TF Code simpler? TF doesn't support assignment, but maybe to and from `numpy` could be faster. Would definitely be simpler.
```python
@staticmeth... | {
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https://api.github.com/repos/huggingface/transformers/issues/7953 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7953/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7953/comments | https://api.github.com/repos/huggingface/transformers/issues/7953/events | https://github.com/huggingface/transformers/issues/7953 | 726,825,608 | MDU6SXNzdWU3MjY4MjU2MDg= | 7,953 | 'EncoderDecoderModel' object has no attribute '_init_weights' after `model.resize_token_embeddings(len(tokenizer))` | {
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"Hello @XinXia2019, sadly `resize_token_embeddings` is not supported yet for `EncoderDecoderModel`. Instead you could just manually instantiate the encoder and decoder and apply `resize_token_embeddings` on each part before wrapping them into the `EncoderDecoderModel` framework.",
"Thanks!",
"(for anyone that m... | 1,603 | 1,623 | 1,603 | NONE | null | ## Details
Version transformers==3.4.0
torch==1.6.0
torchvision==0.7.0
>>> tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
>>>tokenizer.add_special_tokens({"additional_special_tokens": ['extra1', 'extra2']})
1
>>> model = EncoderDecoderModel.from_encoder_decoder_pretrained('bert-base-uncased', '... | {
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"Heya - Are there any concerns to merge this PR? Please let me know.\r\n\r\nMany thanks, Philip"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | - new model card for "German RoBERTa for Sentence Embeddings V2"
- marked old model as outdated | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"> This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity oc... | 1,603 | 1,621 | null | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.1.0
- Platform: Linux-5.4.0-52-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyTorch versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/7950 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7950/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7950/comments | https://api.github.com/repos/huggingface/transformers/issues/7950/events | https://github.com/huggingface/transformers/issues/7950 | 726,755,907 | MDU6SXNzdWU3MjY3NTU5MDc= | 7,950 | Code bug in tokenization_utils.py? | {
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"Pinging @mfuntowicz, @n1t0 for their opinions",
"I think we should delegate to the underlying tokenization algorithm and never strip like we do here. This what is done in `tokenizers` and thus one of the source of discrepancies between fast and slow tokenizers.\n\nFor most tokenizers this is not a problem since ... | 1,603 | 1,609 | 1,609 | NONE | null | In the function split_on_tokens in tokenization_utils.py, it contains the following logic:
if not text.strip():
return []
if not tok_list:
return self._tokenize(text)
So if the text contains just white space, '[]' will be returned. However, if the text contains white space and visible characters, the w... | {
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Fixes the docstring for `encode_plus`.
<!--
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https://api.github.com/repos/huggingface/transformers/issues/7948 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7948/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7948/comments | https://api.github.com/repos/huggingface/transformers/issues/7948/events | https://github.com/huggingface/transformers/issues/7948 | 726,685,551 | MDU6SXNzdWU3MjY2ODU1NTE= | 7,948 | Error: should have a 'get_encoder' function defined when running model.generate() | {
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"Don't see that in the docs.\r\nthe docs use `BartForConditionalGeneration`.\r\nYou could also use `AutoModelForSeq2SeqLM`.\r\n\r\n"
] | 1,603 | 1,603 | 1,603 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.4.0
- Platform: Windows-10-10.0.17134-SP0
- Python version: 3.8.4
- PyTorch version (GPU?): 1.5.1+cpu... | {
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https://api.github.com/repos/huggingface/transformers/issues/7947 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7947/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7947/comments | https://api.github.com/repos/huggingface/transformers/issues/7947/events | https://github.com/huggingface/transformers/pull/7947 | 726,685,358 | MDExOlB1bGxSZXF1ZXN0NTA3NzExNzIx | 7,947 | [GPT2 batch generation] Make test clearer. `do_sample=True` is not deterministic. | {
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https://api.github.com/repos/huggingface/transformers/issues/7946 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7946/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7946/comments | https://api.github.com/repos/huggingface/transformers/issues/7946/events | https://github.com/huggingface/transformers/issues/7946 | 726,643,549 | MDU6SXNzdWU3MjY2NDM1NDk= | 7,946 | EncoderDecoderModel loss function | {
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"Hello, this depends on the decoder you use to initialize the encoder-decoder model. What decoder do you use?",
"I use 'bert-base-uncased'. just like this \r\nmodel = EncoderDecoderModel.from_encoder_decoder_pretrained('bert-base-uncased', 'bert-base-uncased')",
"I'm not sure this is the recommended way to load... | 1,603 | 1,603 | 1,603 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to the Hugging Face forum: https://discuss.huggingface.co/ .
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https://api.github.com/repos/huggingface/transformers/issues/7945 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7945/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7945/comments | https://api.github.com/repos/huggingface/transformers/issues/7945/events | https://github.com/huggingface/transformers/pull/7945 | 726,582,386 | MDExOlB1bGxSZXF1ZXN0NTA3NjIyODg0 | 7,945 | Move NoLayerEmbedTokens | {
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"`TFWrappedEmbeddings` is definitely way better, but as a user, I still don't understand what this means. Do you think we could add a comment where it's used? Maybe something along the lines of:\r\n\r\n```\r\n# Wraps layer to avoid problems with weight restoring and ensuring we're in the correct TF scope.\r\n```",
... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | As agreed upon with @patrickvonplaten , this moves the very useful, very model agnostic, `NoLayerEmbedTokens` to `modeling_tf_utils.py`, where it can be used by `TFBart` and `TFT5`.
`TFProphetNet` and other seq2seq may also eventually need. | {
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https://api.github.com/repos/huggingface/transformers/issues/7944 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7944/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7944/comments | https://api.github.com/repos/huggingface/transformers/issues/7944/events | https://github.com/huggingface/transformers/pull/7944 | 726,522,230 | MDExOlB1bGxSZXF1ZXN0NTA3NTc0MDcz | 7,944 | [ProphetNet] Correct Doc string example | {
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"Can we have the examples take less than 119 chars (i'd even settle for 200 honestly)?\r\n\r\n",
"> Can we have the examples take less than 119 chars (i'd even settle for 200 honestly)?\r\n\r\nCan I break lines while using `>>>` ? Or just use a smaller inp... | 1,603 | 1,603 | 1,603 | MEMBER | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/7943 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7943/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7943/comments | https://api.github.com/repos/huggingface/transformers/issues/7943/events | https://github.com/huggingface/transformers/pull/7943 | 726,384,868 | MDExOlB1bGxSZXF1ZXN0NTA3NDU3MjQy | 7,943 | [PretrainedConfig] Fix save pretrained config for edge case | {
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"Any reason not to look at just the config class? At a first glance, I'd say we want to compare the defaults to the class we instantiated, not to the superclass `PretrainedConfig`.",
"> Any reason not to look at just the config class? At a first glance, I'd say we want to compare the defaults to the class we inst... | 1,603 | 1,603 | 1,603 | MEMBER | null | # What does this PR do?
There is an edge case for which the "diff" save method for `PretrainedConfig` fails. We decided a while ago in this PR: https://github.com/huggingface/transformers/pull/3797 that we wanted to have more readable configs and thus tweaked the `save_pretrained()` method so that only parameters th... | {
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https://api.github.com/repos/huggingface/transformers/issues/7942 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7942/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7942/comments | https://api.github.com/repos/huggingface/transformers/issues/7942/events | https://github.com/huggingface/transformers/pull/7942 | 726,294,063 | MDExOlB1bGxSZXF1ZXN0NTA3MzgyMjUz | 7,942 | [ProphetNet] Add Question Generation Model + Test | {
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https://api.github.com/repos/huggingface/transformers/issues/7941 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7941/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7941/comments | https://api.github.com/repos/huggingface/transformers/issues/7941/events | https://github.com/huggingface/transformers/pull/7941 | 726,281,029 | MDExOlB1bGxSZXF1ZXN0NTA3MzcxNzAw | 7,941 | [RAG] Handle the case when title is None while loading own datasets | {
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"@lhoestq Can you please check"
] | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/7940 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7940/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7940/comments | https://api.github.com/repos/huggingface/transformers/issues/7940/events | https://github.com/huggingface/transformers/issues/7940 | 726,161,843 | MDU6SXNzdWU3MjYxNjE4NDM= | 7,940 | Access bert output with output_hidden_states=True of TFBertForSequenceClassification fails | {
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"Hello! Could you provide your software versions so that I may investigate?\r\n\r\nI get an error earlier: `print(bert_model.get_layer(\"bert\").output)`:\r\n```\r\nTraceback (most recent call last):\r\n File \"<input>\", line 4, in <module>\r\n File \"/home/lysandre/Workspaces/Python/transformers/.env/lib/python... | 1,603 | 1,603 | 1,603 | NONE | null | Hey,
I want to access the output of the main bert model inside the TFBertForSequenceClassification model with output_hidden_states :
`bert_model = TFBertForSequenceClassification.from_pretrained('bert-base-german-cased', output_hidden_states=True)
`
then
```
print(bert_model.summary())
print(bert_model.ge... | {
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https://api.github.com/repos/huggingface/transformers/issues/7939 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7939/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7939/comments | https://api.github.com/repos/huggingface/transformers/issues/7939/events | https://github.com/huggingface/transformers/pull/7939 | 725,980,243 | MDExOlB1bGxSZXF1ZXN0NTA3MTI2MTA1 | 7,939 | Fix BatchEncoding.word_to_tokens for removed tokens | {
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... | [] | closed | false | null | [] | [] | 1,603 | 1,603 | 1,603 | MEMBER | null | Fixes https://github.com/huggingface/tokenizers/issues/343
Copied from issue on `tokenizers` repo:
> I'm working with pre-tokenized data (UD-Treebanks) for a sequence-tagging task, since I don't want to inflate the importance of a training example based on the number of word-pieces the token gets split into, I ne... | {
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https://api.github.com/repos/huggingface/transformers/issues/7938 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7938/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7938/comments | https://api.github.com/repos/huggingface/transformers/issues/7938/events | https://github.com/huggingface/transformers/pull/7938 | 725,978,079 | MDExOlB1bGxSZXF1ZXN0NTA3MTI0MzUz | 7,938 | PPL guide code snippet minor fix | {
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Minor fix to the code snippet in the [perplexity guide](https://huggingface.co/transformers/perplexity.html), as discussed in [this thread](https://discuss.huggingface.co/t/guide-the-best-way-to-calculate-the-perplexity-of-fixed-length-models/193).
Previously the snippet didn't take into a... | {
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https://api.github.com/repos/huggingface/transformers/issues/7937 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7937/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7937/comments | https://api.github.com/repos/huggingface/transformers/issues/7937/events | https://github.com/huggingface/transformers/issues/7937 | 725,912,113 | MDU6SXNzdWU3MjU5MTIxMTM= | 7,937 | Your example code for WNUT NER produces array indexing ValueError | {
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"Hi,\r\nnot a HuggingFace developer but I came across the same problem. I think this is this is due to the fact that the Tokenizer is truncating sequences longer than 64 so there is a mismatch in length between `tags` and `encodings`. This is also why it's fixed when you increase the max_lenght. Another reason may ... | 1,603 | 1,636 | 1,636 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.4
- Platform: Google Colab
- Python version: 3.6.9
- PyTorch version (GPU?): 1.6.0
- Tensorflow vers... | {
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https://api.github.com/repos/huggingface/transformers/issues/7936 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7936/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7936/comments | https://api.github.com/repos/huggingface/transformers/issues/7936/events | https://github.com/huggingface/transformers/issues/7936 | 725,827,360 | MDU6SXNzdWU3MjU4MjczNjA= | 7,936 | cannot load customized tokenizer with modified vocabulary | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,603 | 1,609 | 1,609 | NONE | null | I have customized a tokenizer saved as tokenization_new.py and modified the vocab.txt from s3 server. I tried
`from transformers import NewBertTokenizer`
`tokenizer = NewBertTokenizer.from_pretrained('bert-base-uncased', do_lower_case=True)`
where I modified `PRETRAINED_VOCAB_FILES_MAP = {"vocab_file":{"bert-base-un... | {
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https://api.github.com/repos/huggingface/transformers/issues/7935 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7935/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7935/comments | https://api.github.com/repos/huggingface/transformers/issues/7935/events | https://github.com/huggingface/transformers/pull/7935 | 725,800,379 | MDExOlB1bGxSZXF1ZXN0NTA2OTc3NDY2 | 7,935 | TensorBoard/Wandb/optuna/raytune integration improvements. | {
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Improves TensorBoard/optuna model hyper-parameters logging.
Improves optuna and Ray/tune integration, and provides model hyper-parameter naming.
Test (and sample code) is provided in test_trainer.TrainerHyperParamet... | {
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https://api.github.com/repos/huggingface/transformers/issues/7934 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7934/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7934/comments | https://api.github.com/repos/huggingface/transformers/issues/7934/events | https://github.com/huggingface/transformers/pull/7934 | 725,782,061 | MDExOlB1bGxSZXF1ZXN0NTA2OTYyMzcx | 7,934 | [s2s] create doc for pegasus/fsmt replication | {
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* created a dedicated doc for getting eval data
* move the existing entries to the new doc
* add FSMT
* add pegasus
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https://api.github.com/repos/huggingface/transformers/issues/7933 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7933/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7933/comments | https://api.github.com/repos/huggingface/transformers/issues/7933/events | https://github.com/huggingface/transformers/pull/7933 | 725,779,991 | MDExOlB1bGxSZXF1ZXN0NTA2OTYwNzAw | 7,933 | Fix comet_ml import and add ensure availability | {
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"FYI: @stas00 ",
"> but I agree with @stas00: I wouldn't want to see warnings about cometml or wandb if I don't have the libraries installed.\r\n\r\nThis is not the case already. We were talking about the odd case where some other package installed one of these as its auto-dependencies. So the user now unwittingl... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | # What does this PR do?
1. Adds a better check to make sure comet_ml is ready to use
2. Moves the integration imports above the ML imports. This is required to use comet_ml
The current version 3.4.0 is broken, and can not be used with comet_ml without a workaround. This PR fixes that.
## Before submitting
- ... | {
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] | 1,603 | 1,610 | 1,610 | NONE | null | # 🚀 Feature request
Hugging Face does a great job of including popular decoding strategies such as nucleus sampling, top-k, and temperature. There are also other really interesting decoding strategies for chatbots to fix the response "blandness" or "I don't know" problem, such as using the **Maximum Mutual Informat... | {
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"This technique looks really cool! Unfortunately running `generate` with two models will break lots of our assumptions, so maybe you could write a standalone:\r\n\r\n```python\r\ndef generate_anti_lm(model, lm_model, **kwargs):\r\n\t... logic ...\r\n return generated_ids\r\n```\r\n\r\n,put it in `examples/anti_m... | 1,603 | 1,614 | 1,614 | NONE | null | # What does this PR do?
Implements **Maximum Mutual Information anti-Language Model objective (MMI anti-LM)** decoding from [A Diversity-Promoting Objective Function for Neural Conversation Models](https://www.aclweb.org/anthology/N16-1014.pdf).
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Updates models cards of Illuin uploaded models to provide various informations.
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"The only Reformer tokenizer we have actually doesn't have a PAD Token which is why this leads to problems. The PR attached below removes the PAD token. Before padding one should set \r\n\r\n```python\r\ntokenizer.pad_token = tokenizer.eos_token\r\n```\r\n\r\nSimilar to GPT2 this won't cause any problems thanks to ... | 1,603 | 1,603 | 1,603 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.4.0
- Platform: Linux
- Python version: 3.8.5
- PyTorch version (GPU?): 1.6.0 (No)
- Tensorflow vers... | {
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<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/7926 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7926/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7926/comments | https://api.github.com/repos/huggingface/transformers/issues/7926/events | https://github.com/huggingface/transformers/issues/7926 | 725,558,658 | MDU6SXNzdWU3MjU1NTg2NTg= | 7,926 | Validation loop gives OOM when finetuning T5 | {
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"Maybe @sshleifer or @patil-suraj can help here? :-) ",
"We can't help without:\r\n\r\n1) a command that used to work and now OOMs.\r\n2) Some notion of when it worked. (Ideally version numbers but a guess is fine.)\r\n3) current `transformers-cli env` and `pip freeze | grep torch` outputs.",
"Maybe colab alloc... | 1,603 | 1,614 | 1,614 | NONE | null | While finetuning T5-base on summarization task, using `--sortish_sampler` it gives an OOM error starting from a particular index during the validation loop. After removing those indices and training again, I still get the OOM error, but in the second validation loop, whereas the validation loop worked well the first ti... | {
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https://api.github.com/repos/huggingface/transformers/issues/7925 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7925/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7925/comments | https://api.github.com/repos/huggingface/transformers/issues/7925/events | https://github.com/huggingface/transformers/pull/7925 | 725,438,040 | MDExOlB1bGxSZXF1ZXN0NTA2NjcwODIw | 7,925 | # Add whole word mask support for lm fine-tune | {
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"Seem all test passed( expect the format problem), @sgugger @stas00 Could you help me review these PR ? ",
"And I wonder which version of black you use in **check_code_quality**.\r\nI got errors as follows:\r\n```\r\nwould reformat /home/circleci/transformers/examples/language-modeling/run_language_modeling.py\... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | This PR add support for **wwm** (whole word mask) proxy when fine-tune BERT like model.
And it can be divided into two part : English Model Support and Chinese Model Support
For English, it's simple. The original tokenizer res contains symbols like '##ing'.
I just use the same mask proxy in [data_collator.py](http... | {
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https://api.github.com/repos/huggingface/transformers/issues/7924 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7924/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7924/comments | https://api.github.com/repos/huggingface/transformers/issues/7924/events | https://github.com/huggingface/transformers/issues/7924 | 725,266,119 | MDU6SXNzdWU3MjUyNjYxMTk= | 7,924 | EncoderDecoderModel not working with DDP | {
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"@sgugger @patrickvonplaten Can someone please help me?",
"I tried running @patrickvonplaten `bert-bert` Encoder-Decoder summarization script using DDP but got same error. \r\nBelow is the script. Have modified script a bit to skip some download for fast experimentation.\r\n\r\n``` patrick_script.py\r\n#!/usr/bi... | 1,603 | 1,619 | 1,619 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 3.3.1
- Platform: Linux-3.10.0-1127.19.1.el7.x86_64-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.8
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in sc... | {
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https://api.github.com/repos/huggingface/transformers/issues/7923 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7923/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7923/comments | https://api.github.com/repos/huggingface/transformers/issues/7923/events | https://github.com/huggingface/transformers/issues/7923 | 725,236,623 | MDU6SXNzdWU3MjUyMzY2MjM= | 7,923 | Loading a pytorch quantized model | {
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"Hello @amanpreet692 \r\nAre you making sure you are reloading the saved (quantized) weights into a quantized model?\r\nA dense checkpoint and its quantized counterpart have two different state dicts and I suspect you are re-initializing random matrices because when loading into from_pretrained it doesn't find the ... | 1,603 | 1,609 | 1,609 | CONTRIBUTOR | null | Hi, I quantized a pre-trained model via **torch.quantization.quantize_dynamic** and saved it using **save_pretrained**.
based on https://colab.research.google.com/github/pytorch/tutorials/blob/gh-pages/_downloads/dynamic_quantization_bert_tutorial.ipynb#scrollTo=foe-dVxHIgOC .
On reloading it using **from_pretrained... | {
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https://api.github.com/repos/huggingface/transformers/issues/7922 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/7922/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/7922/comments | https://api.github.com/repos/huggingface/transformers/issues/7922/events | https://github.com/huggingface/transformers/issues/7922 | 725,229,649 | MDU6SXNzdWU3MjUyMjk2NDk= | 7,922 | Is it possible to recommend the deployment method for implementing trained mode | {
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"I find this https://pytorch.org/blog/model-serving-in-pyorch . It is very useful! "
] | 1,603 | 1,603 | 1,603 | NONE | null | # ❓ Questions & Help
I trained a model the Class Trainer. Could you recommend some high performance deployment proposal ？ | {
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