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https://api.github.com/repos/huggingface/transformers/issues/5120 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5120/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5120/comments | https://api.github.com/repos/huggingface/transformers/issues/5120/events | https://github.com/huggingface/transformers/issues/5120 | 641,487,035 | MDU6SXNzdWU2NDE0ODcwMzU= | 5,120 | AutoTokenizer.from_pretrained('facebook/mbart-large-en-ro') fails | {
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Need to make separate MBartConfig.
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https://api.github.com/repos/huggingface/transformers/issues/5119 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5119/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5119/comments | https://api.github.com/repos/huggingface/transformers/issues/5119/events | https://github.com/huggingface/transformers/pull/5119 | 641,478,472 | MDExOlB1bGxSZXF1ZXN0NDM2NzA0MTYx | 5,119 | [cleanup] remove redundant code in SummarizationDataset | {
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"@patrickvonplaten, do you want to take a look?",
"Hey @chrisdoyleIE ,\r\n\r\nUsing your code example above (I corrected some typos and missing imports), I am not able to reproduce the error. If a longer input is need to produce this error, please provide all necessary code to reproduce this error. Ideally, I sho... | 1,592 | 1,618 | 1,593 | NONE | null | # 🐛 Bug
I have pre-trained GPT2 on a summarisation dataset such that summarisation is a language modelling task i.e. input = concat( padded_to_max_len(body , "TL;DR:" , summary)).
For some reason, this error occurs when I try to generate via beam search using GPT2's with language modelling head. Here is my code:... | {
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https://api.github.com/repos/huggingface/transformers/issues/5117 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5117/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5117/comments | https://api.github.com/repos/huggingface/transformers/issues/5117/events | https://github.com/huggingface/transformers/issues/5117 | 641,377,781 | MDU6SXNzdWU2NDEzNzc3ODE= | 5,117 | An Implementation of ERNIE For Language Understanding (including Pre-training models and Fine-tuning tools) | {
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"Can we update to add this into transformers",
"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"
] | 1,592 | 1,597 | 1,597 | NONE | null | # 🌟 New model addition
ERNIE 2.0 is a continual pre-training framework for language understanding in which pre-training tasks can be incrementally built and learned through multi-task learning. ERNIE 2.0 builds a strong basic for nearly every NLP tasks: Text Classification, Ranking, NER, machine reading comprehension... | {
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https://api.github.com/repos/huggingface/transformers/issues/5116 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5116/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5116/comments | https://api.github.com/repos/huggingface/transformers/issues/5116/events | https://github.com/huggingface/transformers/pull/5116 | 641,367,749 | MDExOlB1bGxSZXF1ZXN0NDM2NjA4NTEw | 5,116 | support local_files_only option for tf models | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5116?src=pr&el=h1) Report\n> Merging [#5116](https://codecov.io/gh/huggingface/transformers/pull/5116?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/355954ffca798bb81d9db8886e30ce10f11e8a40&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5115 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5115/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5115/comments | https://api.github.com/repos/huggingface/transformers/issues/5115/events | https://github.com/huggingface/transformers/pull/5115 | 641,361,386 | MDExOlB1bGxSZXF1ZXN0NDM2NjAyODg1 | 5,115 | [cleanup] generate_beam_search comments | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5115?src=pr&el=h1) Report\n> Merging [#5115](https://codecov.io/gh/huggingface/transformers/pull/5115?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/355954ffca798bb81d9db8886e30ce10f11e8a40&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | This PR does two small things:
1) try to make `generate_beam_search`'s inline comments work with the code, and fix some typos.
2) make the `cur_len` argument to `BeamHypothesis.is_done` mandatory, since it is always specified. This simplifies the logic a tiny bit.
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## Information
Model I am using (Bert, XLNet ...): Distilbert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on ... | {
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"Did you try to train with half precision using the apex/amp package?",
"No, I didn't. Anyway, this was only evaluating the pretrained model.",
"I now have installed nvidia apex and tried training a new model with fp16. It ran out of memory after around 10% of the evaluation loop. I didn't expect it, since the ... | 1,592 | 1,599 | 1,598 | CONTRIBUTOR | null | # ❓ Questions & Help
I'm trying to run the pretrained model `google/reformer-enwik8` but I'm getting CUDA out of memory errors unless I limit the sequences to one-fourth of the model capacity (~16k instead of the 65k).
This happens with a Titan Xp with 12GB RAM; I expected all the tricks of the Reformer to make t... | {
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https://api.github.com/repos/huggingface/transformers/issues/5112 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5112/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5112/comments | https://api.github.com/repos/huggingface/transformers/issues/5112/events | https://github.com/huggingface/transformers/issues/5112 | 641,293,709 | MDU6SXNzdWU2NDEyOTM3MDk= | 5,112 | Strange exception | {
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"The notebook is not using the collation function from `transformers` but the `T2TDataCollator` it defines. Apart from stopping subclassing `DataCollator` (as it's not a class anymore on master) this shouldn't be a problem.",
"Hi, @antoniomastro1996 , if you are using transformers from master branch then there ar... | 1,592 | 1,598 | 1,598 | NONE | null | # ❓ Questions & Help
Hi everybody,
I'm keeping experiment with the following colab:
https://colab.research.google.com/github/patil-suraj/exploring-T5/blob/master/T5_on_TPU.ipynb#scrollTo=X9_Go99fvW-z
however I got a new error after the fine-tuning starts:
Exception in thread Thread-20:
Traceback (most r... | {
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https://api.github.com/repos/huggingface/transformers/issues/5111 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5111/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5111/comments | https://api.github.com/repos/huggingface/transformers/issues/5111/events | https://github.com/huggingface/transformers/issues/5111 | 641,287,244 | MDU6SXNzdWU2NDEyODcyNDQ= | 5,111 | [Marian] Run predictions on GPU? RuntimeError: Expected object of device type cuda but got device type cpu for argument #3 'index' in call to _th_index_select` | {
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"Is your `batch` on the correct device too?",
"Thank you, I moved `batch` to the GPU and it works.\r\n`batch = tokenizer.prepare_translation_batch(sentences).to('cuda')`",
"More generally: `batch.to(model.device)`."
] | 1,592 | 1,617 | 1,592 | NONE | null | Is it possible to run the Marian NMT model predictions on GPU, should not it be faster? Once I try to move the model to GPU I get the error described below. Is there any quick fix to the code to achieve this?
```
torch.__version__
Out[15]: '1.5.0'
```
The code to reproduce:
```
from transformers import Maria... | {
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https://api.github.com/repos/huggingface/transformers/issues/5110 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5110/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5110/comments | https://api.github.com/repos/huggingface/transformers/issues/5110/events | https://github.com/huggingface/transformers/pull/5110 | 641,278,345 | MDExOlB1bGxSZXF1ZXN0NDM2NTMyMzI4 | 5,110 | XLMForMultipleChoice | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5110?src=pr&el=h1) Report\n> Merging [#5110](https://codecov.io/gh/huggingface/transformers/pull/5110?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/355954ffca798bb81d9db8886e30ce10f11e8a40&el=desc) will **increase... | 1,592 | 1,598 | 1,598 | MEMBER | null | This PR adds `XLMForMultipleChoice`. One of the missing models in this [project](https://github.com/huggingface/transformers/projects/17)
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/5109 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5109/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5109/comments | https://api.github.com/repos/huggingface/transformers/issues/5109/events | https://github.com/huggingface/transformers/issues/5109 | 641,266,116 | MDU6SXNzdWU2NDEyNjYxMTY= | 5,109 | Flaky tests sometimes caused by S3 failures | {
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"I can't replicate (I understand that's the point :)) \r\n\r\nThe traceback from your link is:\r\n\r\n```python\r\nOSError: Can't load weights for 'sshleifer/tiny-distilroberta-base'. Make sure that:\r\nE \r\nE - 'sshleifer/tiny-distilroberta-base' is a correct model identifier listed on... | 1,592 | 1,599 | 1,599 | MEMBER | null | # 🐛 Bug
## Information
The test: `tests/test_pipelines.py::MonoColumnInputTestCase::test_torch_fill_mask` is flaky on circle ci: https://app.circleci.com/pipelines/github/huggingface/transformers/7734/workflows/7c51cfcf-5425-4172-aa15-ed677e37f7fc/jobs/49891/steps
## To reproduce
Not sure. It pops up from ti... | {
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https://api.github.com/repos/huggingface/transformers/issues/5108 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5108/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5108/comments | https://api.github.com/repos/huggingface/transformers/issues/5108/events | https://github.com/huggingface/transformers/pull/5108 | 641,255,717 | MDExOlB1bGxSZXF1ZXN0NDM2NTEzMzY3 | 5,108 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5108?src=pr&el=h1) Report\n> Merging [#5108](https://codecov.io/gh/huggingface/transformers/pull/5108?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/355954ffca798bb81d9db8886e30ce10f11e8a40&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5107 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5107/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5107/comments | https://api.github.com/repos/huggingface/transformers/issues/5107/events | https://github.com/huggingface/transformers/pull/5107 | 641,217,204 | MDExOlB1bGxSZXF1ZXN0NDM2NDgxMjc4 | 5,107 | Create README.md | {
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"> @julien-c check out that dataset meta tag is right\r\n\r\nIt seems everythigs is right"
] | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | @julien-c check out that dataset meta tag is right | {
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https://api.github.com/repos/huggingface/transformers/issues/5106 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5106/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5106/comments | https://api.github.com/repos/huggingface/transformers/issues/5106/events | https://github.com/huggingface/transformers/issues/5106 | 641,211,104 | MDU6SXNzdWU2NDEyMTExMDQ= | 5,106 | How can I initialize RobertaForSequenceClassification empty? | {
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"Hi! If you want to initialize a new `RobertaForSequenceClassification` model you can do so as such:\r\n\r\n```py\r\nfrom transformers import RobertaForSequenceClassification, RobertaConfig\r\n\r\nconfig = RobertaConfig(\r\n # put the args you need, like the vocab size\r\n vocab_size=100\r\n)\r\n\r\nmodel = R... | 1,592 | 1,599 | 1,592 | NONE | null | I am having my own custom dataset which is completely different from the one with roberta. Now using ByteLevelBPETokenizer, I am creating vocab.json and merges.txt . I am using these two to files to initialize RobertaTokenizerFast for encoding my corpus. Now I am training a RobertaForSequenceClassification for a binary... | {
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https://api.github.com/repos/huggingface/transformers/issues/5105 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5105/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5105/comments | https://api.github.com/repos/huggingface/transformers/issues/5105/events | https://github.com/huggingface/transformers/issues/5105 | 641,195,120 | MDU6SXNzdWU2NDExOTUxMjA= | 5,105 | Is there a helper script to randomly mask spans of text for T5 pretraining? | {
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"Not yet -> on the roadmap :-) ",
"any updates here?"
] | 1,592 | 1,671 | 1,592 | NONE | null | Hello team,
If I have an input text like
```The cute dog walks in the park```
Is there a library within HuggingFace that can output the following for me by masking random spans of text by (optional) taking an input masking probability?
```
masked input: The <extra_id_1> walks in <extra_id_2> park
target... | {
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https://api.github.com/repos/huggingface/transformers/issues/5104 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5104/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5104/comments | https://api.github.com/repos/huggingface/transformers/issues/5104/events | https://github.com/huggingface/transformers/issues/5104 | 641,162,417 | MDU6SXNzdWU2NDExNjI0MTc= | 5,104 | Trainer evaluation doesn't return eval loss for question-answering. | {
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"I solved it editing trainer.py, in this line https://github.com/huggingface/transformers/blob/master/src/transformers/trainer.py#L765 . I added start_positions and end_positions to that \"possible labels names\" list, and it worked. Review the bug, please.",
"Thanks @alexvaca0 !\r\n\r\ncc @julien-c , @sgugger ",... | 1,592 | 1,627 | 1,598 | NONE | null | As mentioned in this issue:
"""
Just a note that I tried `python run_squad_trainer.py --model_name_or_path bert-base-uncased --model_type bert --data_dir squad --output_dir /tmp/debug_squad/ --overwrite_output_dir --do_train --do_eval --evaluate_during_training --logging_steps 100`.
For some reason I don't get any... | {
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https://api.github.com/repos/huggingface/transformers/issues/5103 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5103/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5103/comments | https://api.github.com/repos/huggingface/transformers/issues/5103/events | https://github.com/huggingface/transformers/pull/5103 | 641,130,420 | MDExOlB1bGxSZXF1ZXN0NDM2NDA4Nzk4 | 5,103 | Tokenizers API developments | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5103?src=pr&el=h1) Report\n> Merging [#5103](https://codecov.io/gh/huggingface/transformers/pull/5103?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/417e492f1e832c0b93512600d3385aa4c8a887c9&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | MEMBER | null | Some developments on the tokenizer's API to make it more flexible and easy to use for dynamic/uniform size batching.
- add `return_lengths` methods to both slow and fast tokenizer to have a column with input lengths (useful to sort them afterward)
- make `tokenizer.pad()` accept a list of dicts so it can be used as... | {
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https://api.github.com/repos/huggingface/transformers/issues/5102 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5102/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5102/comments | https://api.github.com/repos/huggingface/transformers/issues/5102/events | https://github.com/huggingface/transformers/issues/5102 | 641,070,807 | MDU6SXNzdWU2NDEwNzA4MDc= | 5,102 | Loading Fine Tuned BERT Sequence Model after Training | {
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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"
] | 1,592 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
Loading Fine Tuned BERT Sequence Model after Training
## Information
Hi All,
iam facing following issue while loading pretrained BERT Sequence model with my own data
RuntimeError: Error(s) in loading state_dict for DataParallel:
Missing key(s) in state_dict: "module.out.weight", "module.out.bias".... | {
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https://api.github.com/repos/huggingface/transformers/issues/5101 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5101/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5101/comments | https://api.github.com/repos/huggingface/transformers/issues/5101/events | https://github.com/huggingface/transformers/issues/5101 | 641,060,842 | MDU6SXNzdWU2NDEwNjA4NDI= | 5,101 | OpenAIGPTDoubleHeadsModel Don't have the "labels" attributes as it is described in the documentation | {
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"Hi @ghsama `lm_labels` is changed to `labels` after 2.11.0. So if you are using version <=2.11.0 use `lm_labels` and if you're using master branch then use `labels`",
"Yes ! i just figure it out . Thank you @patil-suraj :D "
] | 1,592 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
Model I am using OpenAIGPTDoubleHeadsModel:
Language I am using the model on English:
The problem arises when using:
* The official example scripts:
I'm using transformer version : '2.11.0'
In the documentation i found that i can pass a "labels" attribute to the OpenAIGPTDouble... | {
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https://api.github.com/repos/huggingface/transformers/issues/5100 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5100/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5100/comments | https://api.github.com/repos/huggingface/transformers/issues/5100/events | https://github.com/huggingface/transformers/issues/5100 | 641,017,173 | MDU6SXNzdWU2NDEwMTcxNzM= | 5,100 | Update Conda Release | {
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"This might provide more information: https://github.com/conda-forge/transformers-feedstock/issues/3\r\n\r\nIn short, the conda-forge update is blocked by `sentencepiece` not being available through conda.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be clos... | 1,592 | 1,610 | 1,610 | NONE | null | When trying to get started with transformers using some examples from the model cards, the installation with conda results in an outdated version (2.1.1).
As a result, the example cannot run. However, when using pip to install transformers the newest version (2.11) is correctly used.
I would suggest updating the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5099 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5099/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5099/comments | https://api.github.com/repos/huggingface/transformers/issues/5099/events | https://github.com/huggingface/transformers/pull/5099 | 640,913,885 | MDExOlB1bGxSZXF1ZXN0NDM2MjMzNTYy | 5,099 | Fix TF WarmUp class | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5099?src=pr&el=h1) Report\n> Merging [#5099](https://codecov.io/gh/huggingface/transformers/pull/5099?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/efeb75b8054cc299698cf8bc09f395ada2660745&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | This commit fixes the TF WarmUp learning rate scheduler.
The LR shape was wrong due to warmup steps. See linked issue for more details.
Fix #5098 | {
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When using `create_optimizer`, 2 learning rate schedulers are placed on top of each other (WarmUp and keras Polynomial Decay) :
https://github.com/huggingface/transformers/blob/efeb75b8054cc299698cf8bc09f395ada2660745/src/transformers/optimization_tf.py#L70-L80
But the step in Warmup scheduler is not ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5097 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5097/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5097/comments | https://api.github.com/repos/huggingface/transformers/issues/5097/events | https://github.com/huggingface/transformers/issues/5097 | 640,908,566 | MDU6SXNzdWU2NDA5MDg1NjY= | 5,097 | Training the BERTSUM model | {
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"Hi, as seen with @sshleifer, you can train for summarization using the [summarization script](https://github.com/huggingface/transformers/tree/master/examples/summarization). The models supported right now are all BART variants and t5-small. More to come!"
] | 1,592 | 1,593 | 1,593 | NONE | null | Hi, I find that the script can only predict the summaries using the BERTSUM model. Is it possible to train the BERTSUM model using this script? | {
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https://api.github.com/repos/huggingface/transformers/issues/5096 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5096/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5096/comments | https://api.github.com/repos/huggingface/transformers/issues/5096/events | https://github.com/huggingface/transformers/issues/5096 | 640,903,149 | MDU6SXNzdWU2NDA5MDMxNDk= | 5,096 | Can I training a bart model from scratch by transformers? | {
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"Yes",
"> Yes\r\n\r\nThat' s awesome!Can you give a code to show? I'm grateful!",
"So from the paper: https://arxiv.org/pdf/1910.13461.pdf, you can see that Bart is trained on denoising input sequences in almost any possible way. \r\n\r\nOne way could be for `BartForConditionalGeneration`:\r\n\r\n```python \r\n... | 1,592 | 1,676 | 1,592 | CONTRIBUTOR | null | Can I training a bart model from scratch by transformers? | {
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https://api.github.com/repos/huggingface/transformers/issues/5095 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5095/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5095/comments | https://api.github.com/repos/huggingface/transformers/issues/5095/events | https://github.com/huggingface/transformers/issues/5095 | 640,768,610 | MDU6SXNzdWU2NDA3Njg2MTA= | 5,095 | Addition of VisualBERT | {
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"This is very interesting!",
"This has been proposed before as a separate issue but no action was taken. Hence, I thought I'll start implementing some of the multi-modal models one by one.",
"Please let @liunian-harold-li and me know if you need any help. We can also provide the pre-trained models. ",
"This i... | 1,592 | 1,614 | 1,599 | CONTRIBUTOR | null | # 🌟 New model addition
## Model description
The VisualBERT model is used for multi-modal processing when the modes of images and text are present. It takes in object detection features from images, and combines them with textual embeddings from the pre-trained BERT models, pre-trained the whole thing on COCO image c... | {
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https://api.github.com/repos/huggingface/transformers/issues/5094 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5094/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5094/comments | https://api.github.com/repos/huggingface/transformers/issues/5094/events | https://github.com/huggingface/transformers/issues/5094 | 640,740,906 | MDU6SXNzdWU2NDA3NDA5MDY= | 5,094 | Different output from model on CPU and GPU | {
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"Hi! I don't think it's possible to have two different hardware perform *exactly* the same. A 1e-7 precision is already very high. Out of curiosity, why do you need such a high precision?\r\n\r\nNevertheless, this is more of a pytorch-specific question rather than transformers-related. I'll close the issue here but... | 1,592 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
I trained models using the `run_glue.py` script and uploaded them to the model hub. I've realized that their output slightly differs between when I do inference on the CPU and the GPU.
Absolute errors are small – on the order of `1e-7` – but that turns out to be too much for my use case.
## Informatio... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5093?src=pr&el=h1) Report\n> Merging [#5093](https://codecov.io/gh/huggingface/transformers/pull/5093?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/90c833870c78bb3d5d807a9a3e6a40d24bf2302b&el=desc) will **not chan... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | Need to add pandas to setup.cfg. Otherwise, for people that have pandas installed locally isort tries to change `eli5_utils.py` everytime.
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5092?src=pr&el=h1) Report\n> Merging [#5092](https://codecov.io/gh/huggingface/transformers/pull/5092?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/20fa82898495f516b221115fc3ef9ec8ebf50b1e&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | Attempt at fixing #4491 using @jpcorb20 's solution | {
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"What tokenizer are you using? Is it one already trained? If so, which? If not, on what did you train your tokenizer? What is your code? What is your output?\r\n\r\nIf possible, please fill the template. It's much easier to help you if you provide all the information we need.",
"1. Trained using a pretrained biob... | 1,592 | 1,600 | 1,600 | NONE | null | When I used a the bio dataset (linnaeus-IOB) to train bert on, the dataset includes the symbol (>=) [greater than or equal], the tokenizer is separating them into two tokens
**Expected output is either**:
`>`
`##=`
**or**
`>= `
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https://api.github.com/repos/huggingface/transformers/issues/5090 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5090/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5090/comments | https://api.github.com/repos/huggingface/transformers/issues/5090/events | https://github.com/huggingface/transformers/pull/5090 | 640,708,393 | MDExOlB1bGxSZXF1ZXN0NDM2MDY4MTQw | 5,090 | minor spelling correction in script execution command - movement pruning | {
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https://api.github.com/repos/huggingface/transformers/issues/5089 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5089/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5089/comments | https://api.github.com/repos/huggingface/transformers/issues/5089/events | https://github.com/huggingface/transformers/issues/5089 | 640,703,022 | MDU6SXNzdWU2NDA3MDMwMjI= | 5,089 | Is there a helper script to preprocess data for T5 for masked language modeling? | {
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"Not yet sadly - it's on my ToDo list. Hope to be able to work on it soon",
"I am working on a script for T5 based upon the current run_language_modeling.py, maybe I can share that once I am done and someone can confirm if it works as expected?",
"This issue has been automatically marked as stale because it has... | 1,592 | 1,601 | 1,598 | NONE | null | Hi Team
Thanks for the wonderful HuggingFace library !
I am now working with T5 on my own dataset. I want to know if there is any helper script that can automatically take text and mask a random set of tokens and also generate the expected output sequence for the pretraining unsupervised language modeling tas... | {
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https://api.github.com/repos/huggingface/transformers/issues/5088 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5088/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5088/comments | https://api.github.com/repos/huggingface/transformers/issues/5088/events | https://github.com/huggingface/transformers/issues/5088 | 640,677,523 | MDU6SXNzdWU2NDA2Nzc1MjM= | 5,088 | Image GPT | {
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"I'd like a google colab of it ",
"Hey @minimaxir! Here's a [colab](https://colab.research.google.com/github/apeguero1/image-gpt/blob/master/Transformers_Image_GPT.ipynb) which loads the weights into a subclass of `GPT2LMHeadModel` and demonstrates unconditional image generation and conditional image completion. ... | 1,592 | 1,604 | 1,604 | NONE | null | # 🌟 New model addition
## Model description
OpenAI just announced Image GPT: https://openai.com/blog/image-gpt/
Although image rendering would be out of scope for Transformers, the RGB generation would still be in scope and it would be best to port the weights to a `GPT2LMModel`.
However, it's not immediat... | {
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https://api.github.com/repos/huggingface/transformers/issues/5087 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5087/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5087/comments | https://api.github.com/repos/huggingface/transformers/issues/5087/events | https://github.com/huggingface/transformers/issues/5087 | 640,651,743 | MDU6SXNzdWU2NDA2NTE3NDM= | 5,087 | Why does the T5Tokenizer prepend and '_' to every token? | {
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"Hi, the T5 tokenizer is a SentencePiece tokenizer, and that's the way SentencePiece works. This underscore means that it's the start of a word. When it's not the start of a word, it's not prepended by anything.\r\n\r\nI think you're thinking of the # symbol because you're used to the BertTokenizer (wordpiece). Sen... | 1,592 | 1,592 | 1,592 | NONE | null | I am using the T5Tokenizer as follows:
```
In [119]: tokenizer = T5Tokenizer.from_pretrained('t5-small')
In [120]: input_ids = tokenizer.encode_plus('I love my dog', return_tensors='pt')
In [121]: [tokenizer.convert_ids_to_tokens([ele]) for ele in input_ids['input_ids'][0]]
Out[121]: [['▁I'], ['▁love'], ['▁m... | {
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https://api.github.com/repos/huggingface/transformers/issues/5086 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5086/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5086/comments | https://api.github.com/repos/huggingface/transformers/issues/5086/events | https://github.com/huggingface/transformers/pull/5086 | 640,638,197 | MDExOlB1bGxSZXF1ZXN0NDM2MDEwMzkw | 5,086 | SummarizationPipeline: init required task name | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5086?src=pr&el=h1) Report\n> Merging [#5086](https://codecov.io/gh/huggingface/transformers/pull/5086?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/70bc3ead4f0b08e8cadd1805ada2a22f0c302399&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | MEMBER | null | Otherwise, can't do:
```python
tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn")
model = AutoModelWithLMHead.from_pretrained("facebook/bart-large-cnn")
p = SummarizationPipeline(model=model, tokenizer=tokenizer)
p("Long boring text to summarize, etc. etc.")
``` | {
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https://api.github.com/repos/huggingface/transformers/issues/5085 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5085/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5085/comments | https://api.github.com/repos/huggingface/transformers/issues/5085/events | https://github.com/huggingface/transformers/pull/5085 | 640,543,849 | MDExOlB1bGxSZXF1ZXN0NDM1OTM1MjM4 | 5,085 | Add missing arg in 02-transformers notebook | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5085?src=pr&el=h1) Report\n> Merging [#5085](https://codecov.io/gh/huggingface/transformers/pull/5085?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7291ea0bff57a017e71b1ea8ec01ff19da298bf0&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | Add missing `from_tf=True` arg when creating the model `AutoModel.from_pretrained()` to avoid an OSError from loading a PyTorch model from a TF 2.0 checkpoint.
Also fixed two small typos in markdown text. | {
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https://api.github.com/repos/huggingface/transformers/issues/5084 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5084/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5084/comments | https://api.github.com/repos/huggingface/transformers/issues/5084/events | https://github.com/huggingface/transformers/pull/5084 | 640,510,103 | MDExOlB1bGxSZXF1ZXN0NDM1OTA3NDg0 | 5,084 | Update installation page and add contributing to the doc | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5084?src=pr&el=h1) Report\n> Merging [#5084](https://codecov.io/gh/huggingface/transformers/pull/5084?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7291ea0bff57a017e71b1ea8ec01ff19da298bf0&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | This PR simplifies the installation page, adds the mention of TF/PT installation with one command only (for CPU) and adds a test that the installation was successful.
The tests mention is moved to CONTRIBUTING. The mention of the tokenization process for OpenAI GPT is moved to that model doc page.
It also adds th... | {
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https://api.github.com/repos/huggingface/transformers/issues/5083 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5083/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5083/comments | https://api.github.com/repos/huggingface/transformers/issues/5083/events | https://github.com/huggingface/transformers/pull/5083 | 640,473,621 | MDExOlB1bGxSZXF1ZXN0NDM1ODc3NDgy | 5,083 | updated hans eval instructions | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5083?src=pr&el=h1) Report\n> Merging [#5083](https://codecov.io/gh/huggingface/transformers/pull/5083?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7291ea0bff57a017e71b1ea8ec01ff19da298bf0&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | I've updated the info regarding how hans evaluation can be carried out.
I've also renamed `run_hans.py` to `test_hans.py` to restore the previous file convention and also indicate that HANS only supports evaluation. | {
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https://api.github.com/repos/huggingface/transformers/issues/5082 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5082/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5082/comments | https://api.github.com/repos/huggingface/transformers/issues/5082/events | https://github.com/huggingface/transformers/pull/5082 | 640,471,377 | MDExOlB1bGxSZXF1ZXN0NDM1ODc1NTk5 | 5,082 | Add header and fix command | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5082?src=pr&el=h1) Report\n> Merging [#5082](https://codecov.io/gh/huggingface/transformers/pull/5082?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7291ea0bff57a017e71b1ea8ec01ff19da298bf0&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | This finishes to fix #4742 | {
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https://api.github.com/repos/huggingface/transformers/issues/5081 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5081/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5081/comments | https://api.github.com/repos/huggingface/transformers/issues/5081/events | https://github.com/huggingface/transformers/issues/5081 | 640,419,497 | MDU6SXNzdWU2NDA0MTk0OTc= | 5,081 | 01_how-to-train.ipynb broken | {
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"@orestisfl thanks for raising this, I also was scratching my head as the same tokenizer.save(\"EsperBERTo\") worked for me a few days ago and not anymore. I could save the tokenizer using tokenizer.save(\"EsperBERTo/vocab.txt\"), but then I can't load it. If I try to load I get:\r\n```\r\nTypeError: sep_token not... | 1,592 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## To reproduce
Steps to reproduce the behavior:
1. Go to https://github.com/huggingface/transformers/tree/master/examples
2. Click the colab for `language-modeling`: https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb
3. Run notebook
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https://api.github.com/repos/huggingface/transformers/issues/5080 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5080/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5080/comments | https://api.github.com/repos/huggingface/transformers/issues/5080/events | https://github.com/huggingface/transformers/pull/5080 | 640,367,093 | MDExOlB1bGxSZXF1ZXN0NDM1Nzg4ODIz | 5,080 | [docs] fix T5 training doc | {
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"Great thanks @patil-suraj ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5080?src=pr&el=h1) Report\n> Merging [#5080](https://codecov.io/gh/huggingface/transformers/pull/5080?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ebab096e864a619717a497089d864d10e... | 1,592 | 1,592 | 1,592 | MEMBER | null | This PR fixes T5 training doc. In a recent commit `lm_labels` is changed to `labels`. Made the doc changes accordingly. Regarding issue #5079
@patrickvonplaten | {
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https://api.github.com/repos/huggingface/transformers/issues/5079 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5079/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5079/comments | https://api.github.com/repos/huggingface/transformers/issues/5079/events | https://github.com/huggingface/transformers/issues/5079 | 640,337,532 | MDU6SXNzdWU2NDAzMzc1MzI= | 5,079 | How do I pre-train the T5 model in HuggingFace library using my own text corpus? | {
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"Hi, @abhisheknovoic this might help you https://huggingface.co/transformers/model_doc/t5.html#training\r\ncheck the Unsupervised denoising training section",
"@patil-suraj , do you mean this class? - T5ForConditionalGeneration \r\n\r\nAlso, at the top of the page, there is the following code:\r\n\r\n```input_ids... | 1,592 | 1,678 | 1,599 | NONE | null | Hello,
I understand how the T5 architecture works and I have my own large corpus where I decide to mask a sequence of tokens and replace them with sentinel tokens.
I also understand about the tokenizers in HuggingFace, specially the T5 tokenizer.
Can someone point me to a document or refer me to the class th... | {
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https://api.github.com/repos/huggingface/transformers/issues/5078 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5078/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5078/comments | https://api.github.com/repos/huggingface/transformers/issues/5078/events | https://github.com/huggingface/transformers/pull/5078 | 640,315,320 | MDExOlB1bGxSZXF1ZXN0NDM1NzQ1MTQy | 5,078 | Add BERT Loses Patience (Patience-based Early Exit) | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5078?src=pr&el=h1) Report\n> Merging [#5078](https://codecov.io/gh/huggingface/transformers/pull/5078?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e4aaa4580515446cd5a2972ab42fec0b95819c84&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | Add BERT Loses Patience (Patience-based Early Exit) based on the paper https://arxiv.org/abs/2006.04152 and the official implementation https://github.com/JetRunner/PABEE
It's impossible to make PABEE's ALBERT and BERT compatible with the standard API (e.g., `run_glue.py` so I keep the modeling files in a separate d... | {
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https://api.github.com/repos/huggingface/transformers/issues/5077 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5077/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5077/comments | https://api.github.com/repos/huggingface/transformers/issues/5077/events | https://github.com/huggingface/transformers/issues/5077 | 640,296,368 | MDU6SXNzdWU2NDAyOTYzNjg= | 5,077 | Several problems with named entites predicted with the ner pipeline | {
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"@Nighthyst thanks for summarizing these issues as I also ran into them.\r\nI was digging on this last weekend and I think maybe this could help:\r\n\r\nhttps://github.com/huggingface/tokenizers/pull/200\r\n\r\n\r\n>> Provide some more mappings on the Encoding in order to easily identify words after tokenization.\r... | 1,592 | 1,602 | 1,602 | NONE | null | # 🐛 Bug
## Information
Hello,
I am using the `bert-base-cased` model to predict named entities for a bunch of sentences (around 29 900). I am facing 3 main issues :
1. Residual '##' in grouped entities' word field (So they are not well grouped)
2. [UNK] (or [CLS]) tokens inside word fields
3. Missing syll... | {
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https://api.github.com/repos/huggingface/transformers/issues/5076 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5076/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5076/comments | https://api.github.com/repos/huggingface/transformers/issues/5076/events | https://github.com/huggingface/transformers/issues/5076 | 640,239,297 | MDU6SXNzdWU2NDAyMzkyOTc= | 5,076 | Colab session crashes on transformers | {
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"The same thing for me. Colab (using TPU) crashes when importing transformers package.\r\n\r\n\r\n where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/5075 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5075/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5075/comments | https://api.github.com/repos/huggingface/transformers/issues/5075/events | https://github.com/huggingface/transformers/issues/5075 | 640,229,333 | MDU6SXNzdWU2NDAyMjkzMzM= | 5,075 | Converting to ONNX doesn't apply to all models | {
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"Here is a related PyTorch issue: https://github.com/pytorch/pytorch/issues/32968.\r\n\r\nHere is a list of pretraineds model that can be exported to ONNX:\r\nbert-base-cased, distilbert-base-uncased, roberta-base, gpt2, distilgpt2, openai-gpt, albert-base-v2, xlnet-base-cased\r\n\r\nSo far, the following models ha... | 1,592 | 1,691 | 1,599 | NONE | null | Is it possible to list or highlight which models are ONNX convertible?
On a fresh python environment:
```
python -m pip install -U transformers
python -m pip install mosestokenizer
```
The transformer version on the machine is `2.11.0`
When trying to convert the https://huggingface.co/transformers/mo... | {
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https://api.github.com/repos/huggingface/transformers/issues/5074 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5074/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5074/comments | https://api.github.com/repos/huggingface/transformers/issues/5074/events | https://github.com/huggingface/transformers/issues/5074 | 640,220,185 | MDU6SXNzdWU2NDAyMjAxODU= | 5,074 | how to get complete URLs to weights in 2.11.0 | {
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"They are the same as Roberta's \r\n\r\n```python\r\nvocab_url = \"https://s3.amazonaws.com/models.huggingface.co/bert/roberta-large-vocab.json\"\r\nmerges_url = \"https://s3.amazonaws.com/models.huggingface.co/bert/roberta-large-merges.txt\"\r\n```\r\n\r\nIs your question more general than just `bart-large`? (Feel... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | # ❓ Questions & Help
Since it is related to the newest release, I would like to raise the question here. As our servers in the company are not able to access the HF url, we have to download the models locally and upload to the servers. Now seems I couldn't find the links to download `pytorch_model.bin`, `config.json... | {
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https://api.github.com/repos/huggingface/transformers/issues/5073 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5073/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5073/comments | https://api.github.com/repos/huggingface/transformers/issues/5073/events | https://github.com/huggingface/transformers/pull/5073 | 640,181,307 | MDExOlB1bGxSZXF1ZXN0NDM1NjM1MDI4 | 5,073 | fix typo | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5073?src=pr&el=h1) Report\n> Merging [#5073](https://codecov.io/gh/huggingface/transformers/pull/5073?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e4aaa4580515446cd5a2972ab42fec0b95819c84&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5072 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5072/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5072/comments | https://api.github.com/repos/huggingface/transformers/issues/5072/events | https://github.com/huggingface/transformers/issues/5072 | 640,071,313 | MDU6SXNzdWU2NDAwNzEzMTM= | 5,072 | 🐛 [TFTrainer] Wrong number of optimization steps | {
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"You are right, the number of optimization steps is already fixed in an another PR (#5051). And indeed the batch size for TPUs has to take into account the gradient accumulation, but I put this for later because we don't have yet a proper way to differenciate a run on TPU/CPU/GPU. Also the `unbatch` then `batch` is... | 1,592 | 1,598 | 1,598 | CONTRIBUTOR | null | # 🐛 Bug
It seems TFTrainer compute the wrong number of optimization steps :
https://github.com/huggingface/transformers/blob/e4aaa4580515446cd5a2972ab42fec0b95819c84/src/transformers/trainer_tf.py#L79
**It does not take into account the gradient accumulation**.
---
I believe this line should be changed ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5071 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5071/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5071/comments | https://api.github.com/repos/huggingface/transformers/issues/5071/events | https://github.com/huggingface/transformers/issues/5071 | 640,056,524 | MDU6SXNzdWU2NDAwNTY1MjQ= | 5,071 | glue.py Data Processor Index Error for Large Data | {
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"Hi Ali!\r\nBased on your error info, it seems that a line in your `train.tsv` does not follow the MRPC format. Or more specifically, that line may contain an empty field. Could you add a try-except to catch and print that line? It'll look like:\r\n\r\n```python\r\ntry:\r\n text_a = line[3]\r\nexcept:\r\n pri... | 1,592 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
I am using `bert-base-uncase` and `roberta-base` for sentence pair classification, following the same exact example concept and data processing as MRPC. I have a large collection of private data that is in the _exact same format of MRPC_, and I am using `run_glue.py`as a base code for runn... | {
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https://api.github.com/repos/huggingface/transformers/issues/5070 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5070/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5070/comments | https://api.github.com/repos/huggingface/transformers/issues/5070/events | https://github.com/huggingface/transformers/issues/5070 | 639,973,345 | MDU6SXNzdWU2Mzk5NzMzNDU= | 5,070 | Errors while running pytest | {
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"Hi, could you provide the versions of your software, like asked in the issue template?\r\n\r\nNamely tansformer version, python version, pytorch version, tensorflow version ...",
"updated",
"I still don't know what's your transformer version, which is arguably the most important version of the list :sweat_smil... | 1,592 | 1,599 | 1,599 | NONE | null | # ❓ Questions & Help
Hi!
I followed the installation procedures from source for a conda environment.
`make test-examples` returns with the following error:
```
FAILED examples/token-classification/test_ner_examples.py::ExamplesTests::test_run_ner - AssertionError: 2.1329751014709473 not less than 1.5
FAIL... | {
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https://api.github.com/repos/huggingface/transformers/issues/5069 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5069/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5069/comments | https://api.github.com/repos/huggingface/transformers/issues/5069/events | https://github.com/huggingface/transformers/pull/5069 | 639,960,176 | MDExOlB1bGxSZXF1ZXN0NDM1NDU2ODUw | 5,069 | Typo | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5068?src=pr&el=h1) Report\n> Merging [#5068](https://codecov.io/gh/huggingface/transformers/pull/5068?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/439aa1d6e9c953069f75fc23c737221d0df2c977&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | This PR touches a lot of files but nothing that should break anything, it's just there to fix all sphynx warnings. Why? Well some of them are just there to annoy us and don't have any effect, but for roughly half of them, there is something wrong going on in the docs so it's best to fix them all, especially to make it ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5067 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5067/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5067/comments | https://api.github.com/repos/huggingface/transformers/issues/5067/events | https://github.com/huggingface/transformers/issues/5067 | 639,921,212 | MDU6SXNzdWU2Mzk5MjEyMTI= | 5,067 | Modify BERT/BERT-descendants to be TorchScript-able (not just traceable) | {
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"Hi! This is interesting. Could you resume what are the changes that would be needed in order to have our models scriptable?",
"Sure, mostly my changes fall into these categories:\r\n\r\n### 1. Class members can only be basic types, None, nn.Modules, or list or tuple thereof\r\n- Solution: don't save whole config... | 1,592 | 1,667 | 1,609 | NONE | null | # 🚀 Feature request
Modify BERT models (src/transformers/modeling_bert.py) to conform to TorchScript requirements, so they can be ``jit.script()``-ed, not just ``jit.trace()``-ed (as is [currently the only supported option](https://huggingface.co/transformers/torchscript.html))
*Note:* I have a working version i... | {
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https://api.github.com/repos/huggingface/transformers/issues/5066 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5066/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5066/comments | https://api.github.com/repos/huggingface/transformers/issues/5066/events | https://github.com/huggingface/transformers/issues/5066 | 639,915,872 | MDU6SXNzdWU2Mzk5MTU4NzI= | 5,066 | Tokenization+Transformers works with PyTorch but not TensorFlow on TPU | {
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"This makes sense! Do you have some examples of some tokenization that can happen on TPUs with TensorFlow, so that we may consider what we have to do to enable this?",
"I am not totally sure, but one thing to look at would probably be TF's native `tf.keras.preprocessing.text.Tokenizer`, which (I think) works when... | 1,592 | 1,605 | 1,605 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): RoBERTa
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
... | {
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https://api.github.com/repos/huggingface/transformers/issues/5065 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5065/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5065/comments | https://api.github.com/repos/huggingface/transformers/issues/5065/events | https://github.com/huggingface/transformers/pull/5065 | 639,879,912 | MDExOlB1bGxSZXF1ZXN0NDM1MzkwNTg3 | 5,065 | [WIP] TF Trainer with TPUs | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5065?src=pr&el=h1) Report\n> Merging [#5065](https://codecov.io/gh/huggingface/transformers/pull/5065?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/fc24a93e6493c2689e5585d12b7c43730ad9b3ea&el=desc) will **decrease... | 1,592 | 1,600 | 1,599 | CONTRIBUTOR | null | This PR is to make the TF trainer fully compliant with the TPUs.
Should fix #5042, #4996 and #4994. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5064?src=pr&el=h1) Report\n> Merging [#5064](https://codecov.io/gh/huggingface/transformers/pull/5064?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d5477baf7d87b9bdad386f2f317732b85277b06b&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | This PR does two things:
- reorganize the doc topics in five sections
- complete the model list in the index
Also I cut all lines at 119 chars (like the code) otherwise it's not readable in visual studio code (and I imagine other viewers), removed the stars from authors since it wasn't pointing to anything (can ad... | {
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https://api.github.com/repos/huggingface/transformers/issues/5063 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5063/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5063/comments | https://api.github.com/repos/huggingface/transformers/issues/5063/events | https://github.com/huggingface/transformers/issues/5063 | 639,812,340 | MDU6SXNzdWU2Mzk4MTIzNDA= | 5,063 | Non-deterministic training issue on GPU: TF-BERT | {
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"Hi! [This StackOverflow issue](https://datascience.stackexchange.com/questions/14812/making-keras-tensorflow-code-execution-deterministic-on-a-gpu) might be of interest to you.\r\n\r\nNamely:\r\n\r\n> In fact, the randomness(non-determinstic) is a behavior of GPU.\r\n> \r\n> The reason behind is that cuDNN(and oth... | 1,592 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
TF-BERT
Language I am using the model on (English, Chinese ...):
English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
... | {
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"I added a description of `d_kv`. `d_model` is as you say the size of the embedding. `d_kv` is the size of the key, query, value projections. \r\n\r\nIf you look at this blog post: http://jalammar.github.io/illustrated-transformer/\r\n\r\n`d_model` corresponds to the size of a vector `x_1` and `d_kv` of a vector `q... | 1,592 | 1,592 | 1,592 | NONE | null | Hello,
I am aware of the general Transformer model and I believe it is the same model used in T5 architecture.
I know we have the input vocab_size which is the total number of vocabulary size. Besides this, the important parameters would be the embedding size (the size of the embedding of each token), the numb... | {
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"Yeah I agree with the motivations here. From my experience I like to initialize wandb as soon as the main script starts which has benefits like \r\n- Capturing all the console logs, so if something failed before the execution reached the trainer class one could debug the issue through Wandb. This is specially usef... | 1,592 | 1,593 | 1,593 | NONE | null | # 🚀 Feature request
**A.** Make it possible to initialize wandb outside Trainer class.
**B.** Add `use_wandb` argument to the Trainer arguments.
## Motivation
**A.** Currently, wandb inside Trainer configuration if very limited. There are only three environment variables `WANDB_WATCH`, `WANDB_PROJECT`, and `... | {
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- avoid breaking changes when people had a custom `DataCollator` with a `collate_batch` method (there is still the breaking change with `DataCollator` not being a class anymore)
- makes `default_data_collator` more flexible by handling dicts on top of `InputExamples` classes coming from our... | {
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https://api.github.com/repos/huggingface/transformers/issues/5059 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5059/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5059/comments | https://api.github.com/repos/huggingface/transformers/issues/5059/events | https://github.com/huggingface/transformers/pull/5059 | 639,637,030 | MDExOlB1bGxSZXF1ZXN0NDM1MTkxMDEy | 5,059 | [cleanup] examples test_run_squad uses tiny model | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5059?src=pr&el=h1) Report\n> Merging [#5059](https://codecov.io/gh/huggingface/transformers/pull/5059?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d5477baf7d87b9bdad386f2f317732b85277b06b&el=desc) will **not chan... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | This speeds up the examples tests from 120s to 70s.
Note that this probably understates the difference, since all the relevant models are cached on my local machine.
We can also improve `test_run_glue` in a future PR.
I made an issue discussing improvements this PR does not fix: #5059
### More detail:
Befor... | {
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https://api.github.com/repos/huggingface/transformers/issues/5058 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5058/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5058/comments | https://api.github.com/repos/huggingface/transformers/issues/5058/events | https://github.com/huggingface/transformers/issues/5058 | 639,636,718 | MDU6SXNzdWU2Mzk2MzY3MTg= | 5,058 | Error when loading Flaubert model | {
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"Hi! Could you show what command you used to launch the script?",
"I was runing the token classification example : https://github.com/huggingface/transformers/blob/master/examples/token-classification/run.sh with flaubert-large-cased as model name. \r\n\r\nI tried to use the downloaded model from https://huggin... | 1,592 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
## Information
I am trying to run the example run_ner.pl using the Flaubert model.
But I got this error:
Traceback (most recent call last):
File "/py37/lib/python3.7/site-packages/torch/serialization.py", line 191, in _check_seekable
f.seek(f.tell())
AttributeError: 'NoneType' object has no... | {
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https://api.github.com/repos/huggingface/transformers/issues/5057 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5057/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5057/comments | https://api.github.com/repos/huggingface/transformers/issues/5057/events | https://github.com/huggingface/transformers/issues/5057 | 639,635,502 | MDU6SXNzdWU2Mzk2MzU1MDI= | 5,057 | Examples tests improvements | {
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"Hi, @sshleifer I would like to work on this issue. Shall I take this up.\r\n\r\n",
"Yes, I would pick one item from the list to start with.\r\nMake sure you pull first, I just merged some improvements.",
"@sshleifer I will work on the first one.\r\n\r\nJust to be clear I will note down what I have understood a... | 1,592 | 1,601 | 1,601 | CONTRIBUTOR | null | There are a few things about the `examples/` tests that are suboptimal:
1. They never use cuda or fp16, even if they are available.
2. The `@slow` decorator used in the main tests is not importable, so there are no @slow tests.
3. `test_run_glue` uses distilbert-case-cased. It should use a smaller model, one of th... | {
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https://api.github.com/repos/huggingface/transformers/issues/5056 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5056/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5056/comments | https://api.github.com/repos/huggingface/transformers/issues/5056/events | https://github.com/huggingface/transformers/pull/5056 | 639,605,373 | MDExOlB1bGxSZXF1ZXN0NDM1MTY0ODU1 | 5,056 | Add more tests on tokenizers serialization - fix bugs | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5056?src=pr&el=h1) Report\n> Merging [#5056](https://codecov.io/gh/huggingface/transformers/pull/5056?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b28b53713161a6299c757c32f7179a2cb2d8cbd7&el=desc) will **increase... | 1,592 | 1,593 | 1,593 | MEMBER | null | Adds more tests on tokenizer serialization (test when adding tokens, special tokens, etc).
Tokenizer's serialization was not thoroughly tested and actually had quite some holes and bugs. Fix related issues. | {
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https://api.github.com/repos/huggingface/transformers/issues/5055 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5055/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5055/comments | https://api.github.com/repos/huggingface/transformers/issues/5055/events | https://github.com/huggingface/transformers/issues/5055 | 639,600,385 | MDU6SXNzdWU2Mzk2MDAzODU= | 5,055 | How can I load the finetuned BART model to memory? | {
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"Duplicate of #4144 ",
"Thanks!"
] | 1,592 | 1,592 | 1,592 | NONE | null | I have finetuned a `facebook/bart-large` model following the example here: https://github.com/huggingface/transformers/blob/master/examples/summarization/finetune.py
As an output I got a `checkpointcheckpoint_ckpt_epoch_0.ckpt` file. How can I create a BartForConditionalGeneration instance with updated weights? | {
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https://api.github.com/repos/huggingface/transformers/issues/5054 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5054/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5054/comments | https://api.github.com/repos/huggingface/transformers/issues/5054/events | https://github.com/huggingface/transformers/pull/5054 | 639,594,388 | MDExOlB1bGxSZXF1ZXN0NDM1MTU2MDM2 | 5,054 | Add pad_to_multiple_of on tokenizers (reimport) | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5054?src=pr&el=h1) Report\n> Merging [#5054](https://codecov.io/gh/huggingface/transformers/pull/5054?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/24f46ea3f3e5006ca38735306753a846a0823174&el=desc) will **increase... | 1,592 | 1,593 | 1,593 | MEMBER | null | Reimported from #4731.
Introduce `pad_to_multiple_of` on both slow and fast tokenizers. This parameter introduces the "bucketizaton behaviour" also refered as Shape Polymorphism.
This is especially usefull when targetting NN dedicated accelerators such as:
- NVidia Tensor Core (on >= Volta Architecture)
- XLA... | {
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https://api.github.com/repos/huggingface/transformers/issues/5053 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5053/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5053/comments | https://api.github.com/repos/huggingface/transformers/issues/5053/events | https://github.com/huggingface/transformers/issues/5053 | 639,570,483 | MDU6SXNzdWU2Mzk1NzA0ODM= | 5,053 | T5 model for classification doesn't work properly for large number of classes. | {
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"Hi, @HiteshVamshi , what you are trying is highly experimental, I haven't seen anyone using T5 for 100 class classification. So you'll probably need to experiment with it.\r\n\r\nI would like to know few more details\r\n1) What is the size of your dataset\r\n2) which version of t5 are you using (t5-small, t5-base,... | 1,592 | 1,678 | 1,598 | NONE | null | T5 model works properly for 50 class classification but when we try for 100 classes it outputs empty string ("") for a large number of test data. Is this model suitable for multi-class classification with a large number of classes? If yes, what do you think might be the problem with what I am doing. | {
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https://api.github.com/repos/huggingface/transformers/issues/5052 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5052/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5052/comments | https://api.github.com/repos/huggingface/transformers/issues/5052/events | https://github.com/huggingface/transformers/issues/5052 | 639,495,208 | MDU6SXNzdWU2Mzk0OTUyMDg= | 5,052 | How to cosume movement-pruning .h5 models in QnA pipeline | {
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"Hello,\r\nI've only work with PyTorch for all the experiments for movement pruning (even though I've converted the checkpoints in the hub to their TF version).\r\nThe instructions in the notebook show you how you can load a optimized version of the checkpoint (pruning+quantization) which was saved with hdf5 with a... | 1,592 | 1,601 | 1,601 | CONTRIBUTOR | null | # ❓ Questions & Help
## Details
Hi, I am working on the movement pruning method for QnA models. I have performed all the [given steps](https://github.com/huggingface/transformers/tree/master/examples/movement-pruning) in order to generate the pruned model and then used [this notebook](https://github.com/huggingfa... | {
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https://api.github.com/repos/huggingface/transformers/issues/5051 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5051/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5051/comments | https://api.github.com/repos/huggingface/transformers/issues/5051/events | https://github.com/huggingface/transformers/pull/5051 | 639,486,133 | MDExOlB1bGxSZXF1ZXN0NDM1MDY2MDQ1 | 5,051 | Fix LR decay in TF Trainer | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5051?src=pr&el=h1) Report\n> Merging [#5051](https://codecov.io/gh/huggingface/transformers/pull/5051?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9022ef021a56db975d25c7108cbd19d0dd399174&el=desc) will **increase... | 1,592 | 1,593 | 1,593 | CONTRIBUTOR | null | This PR fixes mainly the issue #5045. It also provides a better alignment with the PT trainer with:
- a `set_seed()` function
- use the `logging_first_step` argument
- better logging message when training and load from checkpoint | {
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"I get this error when create datacollator class",
"Could you provide more information? It's a bit hard to help you here. What is the code you're using and what is the stacktrace?",
"thanks you! i have the same problem with this #5049 "
] | 1,592 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
TypeError: function() argument 1 must be code, not str
## Information
@dataclass
class T2TDataCollator(DataCollator):
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"i have the same. It is new bug. i run this week ago and worked",
"try this:\r\n```python\r\nclass T2TDataCollator:\r\n def __call__(self, batch):\r\n```\r\n",
"@abrozso Hi and thanks for the hint, however, it doesn't seem to fix the problem.\r\nI got the following error when the fine-tuning starts:\r\n\r\n0... | 1,592 | 1,610 | 1,592 | NONE | null | # ❓ Questions & Help
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"Hi! What did you use to train your model? Was it the `run_language_modeling` script? Do you happen to have the command you used?",
"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"
] | 1,592 | 1,598 | 1,598 | NONE | null | # ❓ Questions & Help
## Details
I learned albert mlm model.
Often an error occurs (memory exception, ... )
so i resumed learning model from last checkpoint
but, training loss goes back to the beginning.
what do i need to check ?
thank,
![loss ](https://user-images.githubusercontent.com/4244158/84736498-... | {
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"Maybe I don't get it, but can't you simply do:\r\n\r\n```\r\nfrom transformers.modeling_bert import BertConfig, BertModel\r\n\r\nbconfig = BertConfig.from_pretrained('bert-base-uncased')\r\nbconfig.type_vocab_size = 16\r\nmodel = BertModel(bconfig)\r\nmodel.parameters\r\n# ...\r\n# (token_type_embeddings): Embe... | 1,592 | 1,604 | 1,604 | NONE | null | I have a dialogue task and I use token type to distinguish the diffenrent state of the different speeches, but all the pretrained models I can find are of type_vocab_size=2. To accomplish my goal, I have to rewrite many codes in a dirty way. So I want to ask is there an elegant way to restore the pretrained weights and... | {
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"@patrickvonplaten hello, Is there a way to solve this problem",
"Closing since a duplicate of https://github.com/huggingface/transformers/issues/4733. "
] | 1,592 | 1,592 | 1,592 | NONE | null |
# 🐛 Bug
## Information
Model I am using TFBertEncoder:
Language I am using the model on English:
The problem arises when using:
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* [x] my own task or dataset: (give details below)
## To reproduce
Steps to repr... | {
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"This is fixed"
] | 1,592 | 1,594 | 1,594 | CONTRIBUTOR | null | # 🐛 Bug
`TFTrainer` does not consider number of epochs when calculating learning rate
## Information
When using `TFTrainer`, learning rate decreases to 0 at the end of the first epoch, even when we want to train on multiple epochs.
The problem arises when using:
* [X] the official example scripts: (give det... | {
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"Hello !\r\n\r\nThis is because the `--tpu_num_cores` is not taken into account yet. If you want to use TPUs, just fill the TPU name with `--tpu_name` and it will detect automatically the number of cores. For now TPUs with TF Trainer is under development so some use cases might not work properly.",
"Thanks for th... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | # ❓ Questions & Help
I'm trying to run TFTrainer on 8 TPU cores, but I don't understand how to make it work.
I tried running my script with the flags `--tpu_num_cores 8 --per_device_train_batch_size 8`, expecting each core to handle a batch size of 1.
But when I print the shape of my inputs, I have `[8, x]` in... | {
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"Here my intention is to train a BERT binary classifier which classifies if an answer corresponding to a given query is correct. How do I proceed to encode the query, answer pair in the Input?",
"@soumya-ranjan-sahoo You could check the [token type ids](https://huggingface.co/transformers/glossary.html#token-type... | 1,592 | 1,598 | 1,598 | NONE | null | # ❓ Questions & Help
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"I noticed that after saving the pretrained MarianTokenizer to \"my_dir\", the \"source.spm\" file and \"target.spm\" file are actually named as:\r\n\r\n> 1bec78f268e25152d11e6efa41998f2ebebe3ce5452c952c90fc7264c8c45a5b.23f506277c63e64e484c4de9d754a6625e5ba734bb6153470be9b7ffdb7c4ac5\r\n\r\nand\r\n\r\n> 5f95a1efcd8... | 1,592 | 1,642 | 1,592 | NONE | null | # 🐛 Bug
## Information
I want to save MarianConfig, MarianTokenizer, and MarianMTModel to a local directory ("my_dir") and then load them:
> import transformers
>
> transformers.AutoConfig.from_pretrained("Helsinki-NLP/opus-mt-en-de").save_pretrained("my_dir")
> transformers.AutoTokenizer.from_pretrained... | {
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https://api.github.com/repos/huggingface/transformers/issues/5039 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5039/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5039/comments | https://api.github.com/repos/huggingface/transformers/issues/5039/events | https://github.com/huggingface/transformers/pull/5039 | 639,226,874 | MDExOlB1bGxSZXF1ZXN0NDM0ODU1MjI3 | 5,039 | Ability to pickle/unpickle BatchEncoding pickle (reimport) | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5039?src=pr&el=h1) Report\n> Merging [#5039](https://codecov.io/gh/huggingface/transformers/pull/5039?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/36434220fc807c5015bc8f0f1e50ab21f7d34914&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | MEMBER | null | Overrides the methods get_state() & set_state() to (respectively) export the content of the underlying data dictionnary and - if defined - the content of encodings.
Unittests added to covert the serialization & deserialization of all the exported properties.
Reimported from #4515 | {
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https://api.github.com/repos/huggingface/transformers/issues/5038 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5038/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5038/comments | https://api.github.com/repos/huggingface/transformers/issues/5038/events | https://github.com/huggingface/transformers/issues/5038 | 639,221,809 | MDU6SXNzdWU2MzkyMjE4MDk= | 5,038 | Cannot save and load pretrained MarianTokenizer | {
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" #4371 "
] | 1,592 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
I want to save a pretrained MarianTokenizer to a local directory ("my_dir") and then load it:
> import transformers
> transformers.AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-de").save_pretrained("my_dir")
> tokenizer = transformers.AutoTokenizer.from_pretrained("my_dir")
... | {
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https://api.github.com/repos/huggingface/transformers/issues/5037 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5037/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5037/comments | https://api.github.com/repos/huggingface/transformers/issues/5037/events | https://github.com/huggingface/transformers/issues/5037 | 639,221,099 | MDU6SXNzdWU2MzkyMjEwOTk= | 5,037 | The correct way to save and load pretrained MarianTokenizer? | {
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" #4371"
] | 1,592 | 1,592 | 1,592 | NONE | null | I want to save a pretrained MarianTokenizer to a local directory ("my_dir") and then load it:
> import transformers
> transformers.AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-de").save_pretrained("my_dir")
> tokenizer = transformers.AutoTokenizer.from_pretrained("my_dir")
But the above code failed:
... | {
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https://api.github.com/repos/huggingface/transformers/issues/5036 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5036/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5036/comments | https://api.github.com/repos/huggingface/transformers/issues/5036/events | https://github.com/huggingface/transformers/pull/5036 | 639,218,116 | MDExOlB1bGxSZXF1ZXN0NDM0ODQ3Nzkw | 5,036 | Refactor Code samples; Test code samples | {
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- All models now have their docstrings updated.
- Doctest is used for testing
- Fixed a bunch of bugs in all docstrings as well as a few models. All n... | {
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https://api.github.com/repos/huggingface/transformers/issues/5035 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5035/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5035/comments | https://api.github.com/repos/huggingface/transformers/issues/5035/events | https://github.com/huggingface/transformers/pull/5035 | 639,211,774 | MDExOlB1bGxSZXF1ZXN0NDM0ODQyMzQ5 | 5,035 | update for roberta and xlm | {
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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"
] | 1,592 | 1,598 | 1,598 | NONE | null | Two changes are done:
Update the inputs with langs during training and evaluation.
Update the token_type_ids for Roberta otherwise it throws an error while creating features. | {
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https://api.github.com/repos/huggingface/transformers/issues/5034 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5034/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5034/comments | https://api.github.com/repos/huggingface/transformers/issues/5034/events | https://github.com/huggingface/transformers/pull/5034 | 639,203,069 | MDExOlB1bGxSZXF1ZXN0NDM0ODM0NTc2 | 5,034 | Training & fine-tuning quickstart | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5034?src=pr&el=h1) Report\n> Merging [#5034](https://codecov.io/gh/huggingface/transformers/pull/5034?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/24f46ea3f3e5006ca38735306753a846a0823174&el=desc) will **increase... | 1,592 | 1,598 | 1,593 | CONTRIBUTOR | null | This PR adds a short guide to the docs demonstrating how to train & fine-tune models in native PyTorch, native TF2, and using Trainer.
My aim was not to show how to train on every type of task, but simply to communicate the key points along with a couple of very simple and easy-to-follow examples. More involved exam... | {
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https://api.github.com/repos/huggingface/transformers/issues/5033 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5033/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5033/comments | https://api.github.com/repos/huggingface/transformers/issues/5033/events | https://github.com/huggingface/transformers/pull/5033 | 639,199,741 | MDExOlB1bGxSZXF1ZXN0NDM0ODMxNDk2 | 5,033 | update for roberta and xlm | {
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"check_code_quality failed. Updating and sending a new request."
] | 1,592 | 1,592 | 1,592 | NONE | null | Two changes are done:
1. Update the inputs with langs during training and evaluation.
2. Update the token_type_ids for Roberta otherwise it throws an error while creating features. | {
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https://api.github.com/repos/huggingface/transformers/issues/5032 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5032/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5032/comments | https://api.github.com/repos/huggingface/transformers/issues/5032/events | https://github.com/huggingface/transformers/pull/5032 | 639,189,675 | MDExOlB1bGxSZXF1ZXN0NDM0ODIyMjkx | 5,032 | Add DistilBertForMultipleChoice | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5032?src=pr&el=h1) Report\n> Merging [#5032](https://codecov.io/gh/huggingface/transformers/pull/5032?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/bbad4c6989d489097f42bbe38001a3f8ca1c5c11&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | Another missing model | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5031?src=pr&el=h1) Report\n> Merging [#5031](https://codecov.io/gh/huggingface/transformers/pull/5031?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7291ea0bff57a017e71b1ea8ec01ff19da298bf0&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | MEMBER | null | This PR proposes to simplify generation in `modeling_utils.py` in the following ways:
1. Removing some redundant code in `_generate_no_beam_search`: finished sequences are padded at generation time, and do not need to be padded again before returning
2. Initializes the cache in its permanent form directly for both ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5030?src=pr&el=h1) Report\n> Merging [#5030](https://codecov.io/gh/huggingface/transformers/pull/5030?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/bbad4c6989d489097f42bbe38001a3f8ca1c5c11&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | Also fix the values to what's returned. This way we can run
```
python -m doctest README.md
```
to test this codes produces the exact same results. Not sure if we want to include this in our CI in some way.
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https://api.github.com/repos/huggingface/transformers/issues/5029 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5029/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5029/comments | https://api.github.com/repos/huggingface/transformers/issues/5029/events | https://github.com/huggingface/transformers/pull/5029 | 639,127,257 | MDExOlB1bGxSZXF1ZXN0NDM0NzY2MzQ1 | 5,029 | Add reference to NLP (package) dataset | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5029?src=pr&el=h1) Report\n> Merging [#5029](https://codecov.io/gh/huggingface/transformers/pull/5029?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/bbad4c6989d489097f42bbe38001a3f8ca1c5c11&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5028 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5028/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5028/comments | https://api.github.com/repos/huggingface/transformers/issues/5028/events | https://github.com/huggingface/transformers/pull/5028 | 639,124,288 | MDExOlB1bGxSZXF1ZXN0NDM0NzY0MDEx | 5,028 | Add reference to NLP dataset | {
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"I forgot to add the meta tag:\r\ndatasets:\r\n- squad_v2\r\n\r\nSorry",
"same here"
] | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5027 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5027/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5027/comments | https://api.github.com/repos/huggingface/transformers/issues/5027/events | https://github.com/huggingface/transformers/pull/5027 | 639,116,493 | MDExOlB1bGxSZXF1ZXN0NDM0NzU3MTYz | 5,027 | Remove old doc page and add note about cache in installation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5027?src=pr&el=h1) Report\n> Merging [#5027](https://codecov.io/gh/huggingface/transformers/pull/5027?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/bbad4c6989d489097f42bbe38001a3f8ca1c5c11&el=desc) will **increase... | 1,592 | 1,597 | 1,592 | COLLABORATOR | null | As discussed offline, removing the old page "Loading Google AI or OpenAI pre-trained weights or PyTorch dump" and move the not about cache in the installation folder (also, making that up to date ^^). | {
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https://api.github.com/repos/huggingface/transformers/issues/5026 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5026/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5026/comments | https://api.github.com/repos/huggingface/transformers/issues/5026/events | https://github.com/huggingface/transformers/issues/5026 | 639,087,241 | MDU6SXNzdWU2MzkwODcyNDE= | 5,026 | Error while trying to retrieve BERT embeddings for a custom task | {
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"Hi! The error seems to come from your data processing. It's hard to help you without knowing what your inputs are, how `pad_sequence` works, and how you tokenize your inputs.\r\n\r\nIn recent transformers versions, the tokenizer can take care of truncating/padding and do so for input ids, attention masks and token... | 1,592 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
## Information
I am using BERT [base-uncased].
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an offici... | {
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https://api.github.com/repos/huggingface/transformers/issues/5025 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5025/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5025/comments | https://api.github.com/repos/huggingface/transformers/issues/5025/events | https://github.com/huggingface/transformers/pull/5025 | 639,086,544 | MDExOlB1bGxSZXF1ZXN0NDM0NzMxMDc1 | 5,025 | Convert hans to Trainer | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5025?src=pr&el=h1) Report\n> Merging [#5025](https://codecov.io/gh/huggingface/transformers/pull/5025?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1bf4098e03afaed2c6e3671c69fd57e9ac304752&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | This follows up from #4854 (@julien-c I took all your comments into account) and will close #4742. | {
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https://api.github.com/repos/huggingface/transformers/issues/5024 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5024/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5024/comments | https://api.github.com/repos/huggingface/transformers/issues/5024/events | https://github.com/huggingface/transformers/pull/5024 | 639,064,651 | MDExOlB1bGxSZXF1ZXN0NDM0NzEyNTE3 | 5,024 | [Bart] Question Answering Model is added to tests | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5024?src=pr&el=h1) Report\n> Merging [#5024](https://codecov.io/gh/huggingface/transformers/pull/5024?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1bf4098e03afaed2c6e3671c69fd57e9ac304752&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | MEMBER | null | As written in PR #4908, the Bart for QA was not added to the test suite. This PR fixes the output attentions test for encoder decoder QA models.
If we would have named tuples, such a test could be made much much cleaner. | {
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https://api.github.com/repos/huggingface/transformers/issues/5023 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5023/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5023/comments | https://api.github.com/repos/huggingface/transformers/issues/5023/events | https://github.com/huggingface/transformers/issues/5023 | 639,040,670 | MDU6SXNzdWU2MzkwNDA2NzA= | 5,023 | Multi class classification using Reformer Model | {
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"In the reformer projects there is only an card for QA task.\r\nNothing about reformerforsequenceclassification or other model heads.\r\n@patrickvonplaten has assigned the tasks to himself.\r\nAre there any more steps to do when I want to pretrain reformer on larger datasets using the notebook ?\r\nSpecifically we ... | 1,592 | 1,605 | 1,596 | CONTRIBUTOR | 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 Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/5022 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5022/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5022/comments | https://api.github.com/repos/huggingface/transformers/issues/5022/events | https://github.com/huggingface/transformers/issues/5022 | 639,008,090 | MDU6SXNzdWU2MzkwMDgwOTA= | 5,022 | Latest merge [Benchmark] Memory benchmark utils #4198 fails at Windows | {
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"Thanks for noting that - you're 100% correct :-) "
] | 1,592 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
Model I am using: Bert
## To reproduce
Steps to reproduce the behavior:
1. Windows
2. Install transformers from source
## Environment info
python = 3.7.6
pytorch = 1.5
cuda = 10.2
I think the problem happens because in code:
https://github.com/huggingface/transformers/... | {
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https://api.github.com/repos/huggingface/transformers/issues/5021 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5021/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5021/comments | https://api.github.com/repos/huggingface/transformers/issues/5021/events | https://github.com/huggingface/transformers/pull/5021 | 638,999,645 | MDExOlB1bGxSZXF1ZXN0NDM0NjU5OTg3 | 5,021 | Add position_ids in TFElectra models docstring | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5021?src=pr&el=h1) Report\n> Merging [#5021](https://codecov.io/gh/huggingface/transformers/pull/5021?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1affde2f10c653e36601dd7a3e6a2525ae7ced57&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | Just a small thing, but it was forgotten when adding those I guess. | {
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