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https://api.github.com/repos/huggingface/transformers/issues/5620 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5620/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5620/comments | https://api.github.com/repos/huggingface/transformers/issues/5620/events | https://github.com/huggingface/transformers/pull/5620 | 653,833,523 | MDExOlB1bGxSZXF1ZXN0NDQ2Njc0Mzc5 | 5,620 | Fix re-tokenization (ignoring is_pretokenized=True) when passing a pretokenized batch to both batch_encode_plus and tokenizer.__call__ methods | {
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> Fix unexpected behavior when passing already tokenized tokens (ignoring `is_pretokenized=True`) using `batch_encode_plus` and `self.__call__()`
```python
tokenizer = BertTokenizer.from_pretrained("bert-base-cased")
batch_sentences = ['The rapid expansion of the current COVID - 19 pandemic.',
... | {
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https://api.github.com/repos/huggingface/transformers/issues/5619 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5619/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5619/comments | https://api.github.com/repos/huggingface/transformers/issues/5619/events | https://github.com/huggingface/transformers/issues/5619 | 653,830,607 | MDU6SXNzdWU2NTM4MzA2MDc= | 5,619 | Should t5-small generate coherent text as summaries without finetuning? | {
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"Hi @marton-avrios can you share with me the example? Let me try them out as well and see if I found any edge cases where it is not coherent (subjectively). Can you also point out the dataset?\r\n\r\nWill be appreciated if you can share the example reference, dataset link, or your example source code.",
"just go ... | 1,594 | 1,600 | 1,600 | NONE | null | I am following the summarization example and if I run `run_eval.py` for `t5-small` and `xsum` without finetuning I still get coherent, new (similar to source but not the same) and meaningful texts as summaries. The doc does not mention that it was pretrained on any kind of summarization task. | {
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https://api.github.com/repos/huggingface/transformers/issues/5618 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5618/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5618/comments | https://api.github.com/repos/huggingface/transformers/issues/5618/events | https://github.com/huggingface/transformers/pull/5618 | 653,824,548 | MDExOlB1bGxSZXF1ZXN0NDQ2NjY3MDYx | 5,618 | Generate up to max_target_length sequences | {
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* Previous to this commit, implementation caps generation at 20 tokens and may result in poor performance.
* See related recent generation_utils.py commit: https://github.com/huggingface/transf... | {
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https://api.github.com/repos/huggingface/transformers/issues/5617 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5617/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5617/comments | https://api.github.com/repos/huggingface/transformers/issues/5617/events | https://github.com/huggingface/transformers/pull/5617 | 653,796,023 | MDExOlB1bGxSZXF1ZXN0NDQ2NjQzNzAy | 5,617 | Update README.md | {
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https://api.github.com/repos/huggingface/transformers/issues/5615 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5615/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5615/comments | https://api.github.com/repos/huggingface/transformers/issues/5615/events | https://github.com/huggingface/transformers/issues/5615 | 653,700,819 | MDU6SXNzdWU2NTM3MDA4MTk= | 5,615 | 🐛 Bart Tokenization difference between 2.11.0 and 3.0.2 | {
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"This line :\r\n\r\nhttps://github.com/huggingface/transformers/blob/b42586ea560a20dcadb78472a6b4596f579e9043/src/transformers/tokenization_utils.py#L1709\r\n\r\nwas changed to :\r\n\r\nhttps://github.com/huggingface/transformers/blob/b0892fa0e8df02d683e05e625b3903209bff362d/src/transformers/tokenization_utils.py#L... | 1,594 | 1,600 | 1,600 | CONTRIBUTOR | null | # 🐛 Bug
Running this code :
```python
from transformers import BartTokenizer
tokenizer = BartTokenizer.from_pretrained("facebook/bart-large")
print(tokenizer.batch_encode_plus(["This is an example"]))
```
in `transformers` `2.11.0` and `3.0.2` gives different results.
`transformers` `2.11.0` :
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https://api.github.com/repos/huggingface/transformers/issues/5614 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5614/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5614/comments | https://api.github.com/repos/huggingface/transformers/issues/5614/events | https://github.com/huggingface/transformers/pull/5614 | 653,677,115 | MDExOlB1bGxSZXF1ZXN0NDQ2NTUwNzQw | 5,614 | [WIP] Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleC… | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5614?src=pr&el=h1) Report\n> Merging [#5614](https://codecov.io/gh/huggingface/transformers/pull/5614?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8a8ae27617e3c4dafb34bcbbaadf4ceee28583bd&el=desc) will **increase... | 1,594 | 1,596 | 1,596 | MEMBER | null | …hoice} models and tests
The remaining TF tests pass with TF2.3. Waiting to unpin TF before merge. | {
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https://api.github.com/repos/huggingface/transformers/issues/5613 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5613/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5613/comments | https://api.github.com/repos/huggingface/transformers/issues/5613/events | https://github.com/huggingface/transformers/pull/5613 | 653,661,500 | MDExOlB1bGxSZXF1ZXN0NDQ2NTM4MDg5 | 5,613 | doc fixes | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5613?src=pr&el=h1) Report\n> Merging [#5613](https://codecov.io/gh/huggingface/transformers/pull/5613?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7d0ef0042042899b67867a4e2962d8e97fb5c6f5&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | a few minor doc improvements. | {
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https://api.github.com/repos/huggingface/transformers/issues/5612 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5612/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5612/comments | https://api.github.com/repos/huggingface/transformers/issues/5612/events | https://github.com/huggingface/transformers/issues/5612 | 653,610,640 | MDU6SXNzdWU2NTM2MTA2NDA= | 5,612 | Did the run_language_model support TPU? | {
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"I totally agree with you that the transformers team needs to address this issue from a long time ago. I am also struggle to run token classification using TPU. Google gives TPUv3-8 as a part of google collab for only 9$ which equivalent to 8xV100 GPU. Yet until now, we can't run transformers using TPU. This should... | 1,594 | 1,604 | 1,604 | NONE | null | # ❓ Questions & Help
I try to using own dataset on tpu with running run_language_model.py, the command is I use below:
python examples/xla_spawn.py --num_cores 8 examples/language-modeling/run_language_modeling.py --model_name_or_path hfl/chinese-bert-wwm --output_dir model/tpu --train_data_file /Language_masked_m... | {
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"how did you solve this problem. Can you share your solution.",
"Most likely there is mismatch between vocabulary size of tokenizer and bert model ( in bert config). Try setting vocab size of your tokenizer in bert config while initializing your model.",
"@zhunipingan I had to trim the length of the sentence t... | 1,594 | 1,665 | 1,596 | NONE | null | # 🐛 Bug
## Information
The model I am using Bert ('bert-large-uncased') and I am facing two issues related to this model
The language I am using the model on English
The problem arises when using:
When I am trying to encode a large sentence ( sentence length 500 words ), I am getting this error :
`I... | {
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https://api.github.com/repos/huggingface/transformers/issues/5610 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5610/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5610/comments | https://api.github.com/repos/huggingface/transformers/issues/5610/events | https://github.com/huggingface/transformers/pull/5610 | 653,482,406 | MDExOlB1bGxSZXF1ZXN0NDQ2MzkyNjE3 | 5,610 | create model cards for qg models | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5610?src=pr&el=h1) Report\n> Merging [#5610](https://codecov.io/gh/huggingface/transformers/pull/5610?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/40d98ebf50c4662bcd6dce6395bbed0b2142ea52&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | MEMBER | null | cc @julien-c , @danielduckworth | {
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https://api.github.com/repos/huggingface/transformers/issues/5609 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5609/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5609/comments | https://api.github.com/repos/huggingface/transformers/issues/5609/events | https://github.com/huggingface/transformers/issues/5609 | 653,429,077 | MDU6SXNzdWU2NTM0MjkwNzc= | 5,609 | Duplicate grouped entities when using 'ner' pipeline | {
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"Can you check whether this still occurs after recently merged #4987? ",
"Thanks for the response.\r\n\r\nIs there a special repo I have to pull from or can I just update transformers. Assuming the latter, I just re-ran `pip install --upgrade transformers`. After doing this, the bug persists.",
"No, you would... | 1,594 | 1,601 | 1,601 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): 'ner' pipeline
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 ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5608 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5608/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5608/comments | https://api.github.com/repos/huggingface/transformers/issues/5608/events | https://github.com/huggingface/transformers/issues/5608 | 653,428,433 | MDU6SXNzdWU2NTM0Mjg0MzM= | 5,608 | Is there an implementation of BERT architecture in PyTorch that I can modify here? | {
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"Hi! Yes, you can modify the BERT architecture as you please, it's self contained. It's in the [modeling_bert.py](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_bert.py) file.",
"Thanks @LysandreJik , can you also confirm if this implementation supports multi gpu training? ",
... | 1,594 | 1,594 | 1,594 | NONE | null | Hello Team,
Firstly, thanks for this amazing repo.
I am doing my own research and I want access to a native implementation of BERT in PyTorch so I can modify the architecture and play with it by including a few of my own modules.
Is that possible with the codebase in HuggingFace repo here?
Thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/5607 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5607/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5607/comments | https://api.github.com/repos/huggingface/transformers/issues/5607/events | https://github.com/huggingface/transformers/pull/5607 | 653,419,435 | MDExOlB1bGxSZXF1ZXN0NDQ2MzQyNTU5 | 5,607 | docs(wandb): explain how to use W&B integration | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5607?src=pr&el=h1) Report\n> Merging [#5607](https://codecov.io/gh/huggingface/transformers/pull/5607?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/40d98ebf50c4662bcd6dce6395bbed0b2142ea52&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | Documentation on how to use W&B integration has been added to clear up confusion on how to customize logging.
fix #5262 | {
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https://api.github.com/repos/huggingface/transformers/issues/5606 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5606/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5606/comments | https://api.github.com/repos/huggingface/transformers/issues/5606/events | https://github.com/huggingface/transformers/issues/5606 | 653,366,047 | MDU6SXNzdWU2NTMzNjYwNDc= | 5,606 | OSError using FlauBERT | {
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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"
] | 1,594 | 1,600 | 1,600 | NONE | null | Hello everyone,
I'm trying to run Flaubert model on my data using ktrain.
# 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): flaubert/flaubert_base_cased
Language I am using the model on (English, Chinese ...): French
The problem arises when using:
* [x] the official example scripts: (giv... | {
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https://api.github.com/repos/huggingface/transformers/issues/5605 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5605/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5605/comments | https://api.github.com/repos/huggingface/transformers/issues/5605/events | https://github.com/huggingface/transformers/issues/5605 | 653,362,662 | MDU6SXNzdWU2NTMzNjI2NjI= | 5,605 | Here maybe a bug, when we load staged checkpoint | {
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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",
"I'm also puzzled by this. The calculations here seems incorrect.",
"To me these calculations are not incorrect if we take `step` as o... | 1,594 | 1,605 | 1,600 | NONE | null | ERROR: type should be string, got "https://github.com/huggingface/transformers/blob/40d98ebf50c4662bcd6dce6395bbed0b2142ea52/src/transformers/trainer.py#L458\r\n\r\nI met this bug when I used the setting below:\r\n\r\nglobal_steps = 2748\r\nlen(train_dataloader) = 27484\r\ngradient_accumulation_steps = 4\r\n\r\nIn the original code, \"steps_trained_in_current_epoch\" will be 2748 ! BUT this variable should be 2748*4 = 10,992\r\n\r\nthe code I suggested is below:\r\n\r\n```\r\nepochs_trained = (self.global_step * self.args.gradient_accumulation_steps) // len(train_dataloader)\r\nsteps_trained_in_current_epoch = (self.global_step * self.args.gradient_accumulation_steps) % len(train_dataloader)\r\n```" | {
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https://api.github.com/repos/huggingface/transformers/issues/5604 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5604/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5604/comments | https://api.github.com/repos/huggingface/transformers/issues/5604/events | https://github.com/huggingface/transformers/issues/5604 | 653,331,917 | MDU6SXNzdWU2NTMzMzE5MTc= | 5,604 | [Benchmark] TFGPT2LMHeadModel is five times slower than GPT2LMHeadModel | {
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"That's probably because you're in eager mode in your TensorFlow script. You can read about eager mode [here](https://www.tensorflow.org/guide/eager).\r\n\r\n[Here's](https://docs.google.com/spreadsheets/d/1sryqufw2D0XlUH4sq3e9Wnxu5EAQkaohzrJbd5HdQ_w/edit#gid=0) a spreadsheet showcasing several model performances, ... | 1,594 | 1,661 | 1,602 | NONE | null | Here are two scripts I ran.
```python
from time import time
from transformers import TFGPT2LMHeadModel, GPT2Tokenizer
import tensorflow as tf
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = TFGPT2LMHeadModel.from_pretrained('gpt2')
text = "What are you doing after you have finished working?"
gene... | {
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https://api.github.com/repos/huggingface/transformers/issues/5603 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5603/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5603/comments | https://api.github.com/repos/huggingface/transformers/issues/5603/events | https://github.com/huggingface/transformers/pull/5603 | 653,321,531 | MDExOlB1bGxSZXF1ZXN0NDQ2MjYyNzE4 | 5,603 | Update benchmark notebook | {
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https://api.github.com/repos/huggingface/transformers/issues/5602 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5602/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5602/comments | https://api.github.com/repos/huggingface/transformers/issues/5602/events | https://github.com/huggingface/transformers/issues/5602 | 653,296,621 | MDU6SXNzdWU2NTMyOTY2MjE= | 5,602 | MarianMT: "CUDA out of memory" when translating many times with the MarianMT Model | {
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"@sshleifer The Documentation page said to assign you, but I can only mention you. ",
"how big are your batches?\r\n\r\n```python\r\nsrc = 'en' # source language\r\ntrg = 'de' # target language\r\ndevice='cuda'\r\nmname = f'Helsinki-NLP/opus-mt-{src}-{trg}'\r\nmodel = MarianMTModel.from_pretrained(mname).to(dev... | 1,594 | 1,599 | 1,596 | NONE | null | # 🐛 Bug
RuntimeError('CUDA out of memory. Tried to allocate 26.00 MiB (GPU 0; 4.00 GiB total capacity; 3.03 GiB already allocated; 4.72 MiB free; 3.06 GiB reserved in total by PyTorch)')
## Information
I wrote a python notebook to translate datasets using MarianMT. Therefore I wrote a function, that gets called ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5601 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5601/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5601/comments | https://api.github.com/repos/huggingface/transformers/issues/5601/events | https://github.com/huggingface/transformers/pull/5601 | 653,281,384 | MDExOlB1bGxSZXF1ZXN0NDQ2MjMwMjY3 | 5,601 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5601?src=pr&el=h1) Report\n> Merging [#5601](https://codecov.io/gh/huggingface/transformers/pull/5601?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f82a2a5e8e6827343322a4a9831924c5bb9bd2b2&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5599 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5599/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5599/comments | https://api.github.com/repos/huggingface/transformers/issues/5599/events | https://github.com/huggingface/transformers/pull/5599 | 653,257,870 | MDExOlB1bGxSZXF1ZXN0NDQ2MjEwOTA3 | 5,599 | Add newly trained `calbert-tiny-uncased` | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5599?src=pr&el=h1) Report\n> Merging [#5599](https://codecov.io/gh/huggingface/transformers/pull/5599?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f82a2a5e8e6827343322a4a9831924c5bb9bd2b2&el=desc) will **not chan... | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | Calbert is an open-source ALBERT trained on the Catalan OSCAR dataset. This is the `tiny` version, newly trained from a completely rewrite [in this repo](https://github.com/codegram/calbert), now using SentencePiece which makes everything work much better with pipelines and the default tooling, as demonstrated in the m... | {
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https://api.github.com/repos/huggingface/transformers/issues/5598 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5598/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5598/comments | https://api.github.com/repos/huggingface/transformers/issues/5598/events | https://github.com/huggingface/transformers/pull/5598 | 653,233,476 | MDExOlB1bGxSZXF1ZXN0NDQ2MTkxMTU1 | 5,598 | returned value from parse method of MeCab >= 1.0.0 was changed | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5598?src=pr&el=h1) Report\n> Merging [#5598](https://codecov.io/gh/huggingface/transformers/pull/5598?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f82a2a5e8e6827343322a4a9831924c5bb9bd2b2&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | NONE | null | As shown below, returned value from MeCab's parse method was changed,
we need to fix MecabTokenizer in BertJapaneseTokenizer.
# mecab-python3==1.0.0 (latest version)
```
root@713173e4bace:/# pip freeze | grep mecab
mecab-python3==1.0.0
root@713173e4bace:/# python
Python 3.8.3 (default, Jul 7 2020, 11:33:46... | {
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https://api.github.com/repos/huggingface/transformers/issues/5597 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5597/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5597/comments | https://api.github.com/repos/huggingface/transformers/issues/5597/events | https://github.com/huggingface/transformers/issues/5597 | 653,231,863 | MDU6SXNzdWU2NTMyMzE4NjM= | 5,597 | DPR model examples / notebook / pipeline | {
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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"
] | 1,594 | 1,600 | 1,600 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
An notebook or own script in the examples folders would be pretty nice for the new DPR model, implemented by @lhoestq
Maybe an implementation to the pipeline... | {
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https://api.github.com/repos/huggingface/transformers/issues/5596 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5596/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5596/comments | https://api.github.com/repos/huggingface/transformers/issues/5596/events | https://github.com/huggingface/transformers/pull/5596 | 653,168,270 | MDExOlB1bGxSZXF1ZXN0NDQ2MTM2OTUy | 5,596 | Add data_collator with attention_mask feature | {
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"Add a related issue: #4702",
"I agree that we should handle `attention_mask`, but I don't think adding another class `DataCollatorForMaskedLanguageModeling` is necessary. The class `DataCollatorForLanguageModeling` already handles masked language modeling, and should imo be modified to handle attention masks as ... | 1,594 | 1,602 | 1,602 | NONE | null | For models like BERT, we should mask the padding ids as invalidate to avoid attention on them. Therefore, in addition to `input_ids`, the feature `attention_mask` should also be fed to the model.
Add a data collator `DataCollatorForMaskedLanguageModeling` which will return all of above data, and add a dataset class `... | {
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https://api.github.com/repos/huggingface/transformers/issues/5595 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5595/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5595/comments | https://api.github.com/repos/huggingface/transformers/issues/5595/events | https://github.com/huggingface/transformers/issues/5595 | 653,149,185 | MDU6SXNzdWU2NTMxNDkxODU= | 5,595 | transformer dataset and masked LM | {
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"Should I also put the questions form the stackoverflow post in this issue? Or is there any problem with this issue? Did I overlook something?",
"Posted the solution I found on github."
] | 1,594 | 1,595 | 1,595 | NONE | null | # ❓ Questions & Help
I was wondering about the masked LM models and the Datasets for the transformer library.
<!-- 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) w... | {
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https://api.github.com/repos/huggingface/transformers/issues/5594 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5594/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5594/comments | https://api.github.com/repos/huggingface/transformers/issues/5594/events | https://github.com/huggingface/transformers/pull/5594 | 653,113,306 | MDExOlB1bGxSZXF1ZXN0NDQ2MDkzMzM0 | 5,594 | [Benchmark] Add benchmarks for TF Training | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5594?src=pr&el=h1) Report\n> Merging [#5594](https://codecov.io/gh/huggingface/transformers/pull/5594?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cfbb98297449e09e5a2443b4ba76be52a71ec0f7&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | MEMBER | null | This PR adds train functions to TF benchmarks including tests.
The notebook is updated accordingly as well. | {
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https://api.github.com/repos/huggingface/transformers/issues/5593 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5593/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5593/comments | https://api.github.com/repos/huggingface/transformers/issues/5593/events | https://github.com/huggingface/transformers/issues/5593 | 653,098,510 | MDU6SXNzdWU2NTMwOTg1MTA= | 5,593 | AttributeError: 'Tensor' object has no attribute 'ndim' | {
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"Hi! Do you mind pasting the command you used to run the script? Thank you!",
"Hi @LysandreJik ,\r\nThank you for your quick reply.\r\nFirst, I want to cheer you for your amazing work in HuggingFaces Transformers.\r\nFor that error I used the command \"python run.generation.py --model_type=gpt2 --model_name_or_pa... | 1,594 | 1,595 | 1,595 | NONE | null | # ❓ Questions & Help
Hello,
when I run the run_generation.py file I got this error:
Traceback (most recent call last):
File "C:\Users\imen.benamor\AppData\Local\Programs\Python\Python36\lib\site-packages\transformers\tokenization_utils_base.py", line 507, in convert_to_tensors
if tensor.ndim > 2:
Attr... | {
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https://api.github.com/repos/huggingface/transformers/issues/5592 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5592/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5592/comments | https://api.github.com/repos/huggingface/transformers/issues/5592/events | https://github.com/huggingface/transformers/pull/5592 | 653,023,382 | MDExOlB1bGxSZXF1ZXN0NDQ2MDE5MTEz | 5,592 | Allow to set Adam beta1, beta2 in TrainingArgs | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5592?src=pr&el=h1) Report\n> Merging [#5592](https://codecov.io/gh/huggingface/transformers/pull/5592?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cfbb98297449e09e5a2443b4ba76be52a71ec0f7&el=desc) will **increase... | 1,594 | 1,595 | 1,595 | CONTRIBUTOR | null | In some models, `beta1` and `beta2` in Adam optimizer are set to be different from the default values `(0.9, 0.999)`. For example, RoBERTa set `beta2 = 0.98`. It is thereby necessary to add `beta1` and `beta2` in `TrainingArgs` if the user wants to fine-tune RoBERTa and other similar models. Also, another hyperparamete... | {
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https://api.github.com/repos/huggingface/transformers/issues/5591 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5591/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5591/comments | https://api.github.com/repos/huggingface/transformers/issues/5591/events | https://github.com/huggingface/transformers/issues/5591 | 652,971,055 | MDU6SXNzdWU2NTI5NzEwNTU= | 5,591 | KeyError Issue in Question answering | {
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"I believe this issue has been recurring in other versions due to tokenization related indexing issue. \r\n\r\nI did the following to get the span from the answer. \r\n\r\n```\r\nMODEL_LOC = \"distilbert-base-uncased-distilled-squad\"\r\nTOKENIZER_LOC = \"distilbert-base-uncased-distilled-squad\"\r\nmodel = AutoMod... | 1,594 | 1,594 | 1,594 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Distillbert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* my own modified scripts: (give details below)
## To reproduce
Steps to reproduce the behavior:
1. Just run this code.
```
... | {
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https://api.github.com/repos/huggingface/transformers/issues/5590 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5590/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5590/comments | https://api.github.com/repos/huggingface/transformers/issues/5590/events | https://github.com/huggingface/transformers/issues/5590 | 652,916,593 | MDU6SXNzdWU2NTI5MTY1OTM= | 5,590 | HF Trainer Segmentation Fault | {
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"Hi! Could you paste here the result of `pip list` in your environment ?",
"```\r\nabsl-py 0.9.0\r\napex 0.1\r\nastor 0.8.1\r\nastunparse 1.6.3\r\nbackcall 0.1.0\r\nbeautifulsoup4 4.9.1\r\nblis 0.4.1\r\nBottlenec... | 1,594 | 1,602 | 1,602 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT2-medium & large
Language I am using the model on (English, Chinese ...): Korean (with custom trained tokenizer)
The problem arises when using:
* [ O ] the official example scripts: (give details below)
https://huggingface.co/blog/how-to-train... | {
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https://api.github.com/repos/huggingface/transformers/issues/5589 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5589/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5589/comments | https://api.github.com/repos/huggingface/transformers/issues/5589/events | https://github.com/huggingface/transformers/issues/5589 | 652,823,895 | MDU6SXNzdWU2NTI4MjM4OTU= | 5,589 | Datasets & collators for NER | {
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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"
] | 1,594 | 1,599 | 1,599 | CONTRIBUTOR | null | # 🚀 Feature request
Is there a plan to add a dataset subclass and loader/collator for token classification tasks in the CONLL format? Or has that been deliberately avoided for some reason.
## Motivation
We have TextDatasets and DataCollatorForLanguageModeling. Can we have something similar for token classifi... | {
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https://api.github.com/repos/huggingface/transformers/issues/5588 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5588/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5588/comments | https://api.github.com/repos/huggingface/transformers/issues/5588/events | https://github.com/huggingface/transformers/issues/5588 | 652,810,906 | MDU6SXNzdWU2NTI4MTA5MDY= | 5,588 | [Some weights or buffers of the PyTorch model TFGPT2LMHeadModel were not initialized] convert GPT2 pytorch to tensorflow model | {
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"Hi! The way you converted your model is the recommended way :ok_hand: \r\n\r\nThe warning is irrelevant to this conversion, we should try to make that clearer.",
"The warning is very confusing and can be fixed by pull request #6604.",
"The warning is very confusing and can be fixed by new pull request #6623"
] | 1,594 | 1,597 | 1,594 | NONE | null | # ❓ Questions & Help
How can we convert gpt2 fine tuned model from run_language_model.py from pytorch to tensorflow model? I came into the following warning when importing pytorch model GPT2LMHeadModel into TFGPT2LMHeadModel.
```
WARNING:transformers.modeling_tf_pytorch_utils:Some weights or buffers of the PyTor... | {
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https://api.github.com/repos/huggingface/transformers/issues/5587 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5587/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5587/comments | https://api.github.com/repos/huggingface/transformers/issues/5587/events | https://github.com/huggingface/transformers/issues/5587 | 652,801,008 | MDU6SXNzdWU2NTI4MDEwMDg= | 5,587 | Difference between AutoTokenizer.from_pretrained and BertTokenizer.from_pretrained | {
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"Hi! The [documentation](https://huggingface.co/transformers/model_doc/auto.html) mentions:\r\n\r\n> In many cases, the architecture you want to use can be guessed from the name or the path of the pretrained model you are supplying to the from_pretrained method.\r\n> \r\n> AutoClasses are here to do this job for yo... | 1,594 | 1,691 | 1,594 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to 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/5586 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5586/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5586/comments | https://api.github.com/repos/huggingface/transformers/issues/5586/events | https://github.com/huggingface/transformers/issues/5586 | 652,675,400 | MDU6SXNzdWU2NTI2NzU0MDA= | 5,586 | GPT2 past usage | {
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"Hey @cronoik, \r\n\r\nThanks for your issue. It does not really surprise me that the loss is different. \r\nIn the first case the following loss is calculated:\r\n\r\nloss = CrossEntropy(`input_ids`: \"I like sitting in my new chair and {} about\" vs. `labels`: \"like sitting in my new chair and {} about life\").\... | 1,594 | 1,652 | 1,594 | CONTRIBUTOR | null | Hello everyone,
I tried to answer this [stackoverflow question](https://stackoverflow.com/questions/62703391/estimate-token-probability-logits-given-a-sentence-without-computing-the-entire) and stumbled about a strange beheaviour I can't explain.
The following code will calculate the loss for a sentence with dif... | {
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https://api.github.com/repos/huggingface/transformers/issues/5585 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5585/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5585/comments | https://api.github.com/repos/huggingface/transformers/issues/5585/events | https://github.com/huggingface/transformers/pull/5585 | 652,661,344 | MDExOlB1bGxSZXF1ZXN0NDQ1Njk1MTk2 | 5,585 | Update question template | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5585?src=pr&el=h1) Report\n> Merging [#5585](https://codecov.io/gh/huggingface/transformers/pull/5585?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d6eab53058015483e9cbcbfee4bf900c3a8ab772&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | COLLABORATOR | null | Point people to the forum. | {
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https://api.github.com/repos/huggingface/transformers/issues/5584 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5584/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5584/comments | https://api.github.com/repos/huggingface/transformers/issues/5584/events | https://github.com/huggingface/transformers/issues/5584 | 652,643,644 | MDU6SXNzdWU2NTI2NDM2NDQ= | 5,584 | On running finetune.py for seq2seq, the following error comes up: optimizer_step() got an unexpected keyword argument 'using_native_amp' | {
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"Same issue here on 0.8.4. Downgrading to 0.8.1 works for me.\r\n\r\nRelated to recent pytorch-lightning commits for Apex: https://github.com/PyTorchLightning/pytorch-lightning/commit/0a092f66836912a714804c5103f03c7929ebf774",
"however wandb is not working with 0.8.1",
"Getting the same issue today with 0.8.4. ... | 1,594 | 1,605 | 1,605 | NONE | null | File "finetune.py", line 344, in <module>
main(args)
File "finetune.py", line 322, in main
logger=logger,
File "/content/drive/My Drive/Colab Notebooks/transformers/examples/lightning_base.py", line 336, in generic_train
trainer.fit(model)
File "/usr/local/lib/python3.6/dist-packages/pytorch_lig... | {
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https://api.github.com/repos/huggingface/transformers/issues/5582 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5582/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5582/comments | https://api.github.com/repos/huggingface/transformers/issues/5582/events | https://github.com/huggingface/transformers/pull/5582 | 652,527,771 | MDExOlB1bGxSZXF1ZXN0NDQ1NTc5MDEz | 5,582 | Rename files | {
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"Mmm, guess this change is not possible as long as the file does not support evaluation as well."
] | 1,594 | 1,651 | 1,594 | COLLABORATOR | null | As discussed in #4829 | {
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https://api.github.com/repos/huggingface/transformers/issues/5580 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5580/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5580/comments | https://api.github.com/repos/huggingface/transformers/issues/5580/events | https://github.com/huggingface/transformers/issues/5580 | 652,469,289 | MDU6SXNzdWU2NTI0NjkyODk= | 5,580 | TypeError: 'BertTokenizer' object is not callable | {
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"Hello! It seems you're running on an older `transformers` version. The `__call__` was implemented only in version v3.0.0+. Do you mind pasting your environment information here?\r\n\r\nYou should have a dropdown in the documentation with the different versions, so that you can select the documentation that works f... | 1,594 | 1,690 | 1,594 | NONE | null | ```
from transformers import BertTokenizer
tokenizer = BertTokenizer.from_pretrained("bert-base-cased")
sequence_a = "HuggingFace is based in NYC"
sequence_b = "Where is HuggingFace based?"
encoded_dict = tokenizer(sequence_a, sequence_b)
```
This will produce error 'BertTokenizer' object is not callable. Maybe... | {
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https://api.github.com/repos/huggingface/transformers/issues/5579 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5579/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5579/comments | https://api.github.com/repos/huggingface/transformers/issues/5579/events | https://github.com/huggingface/transformers/issues/5579 | 652,448,887 | MDU6SXNzdWU2NTI0NDg4ODc= | 5,579 | OSError: Model name 'facebook/bart-large-cnn' was not found in tokenizers model name list | {
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"Did you get this solved? I cannot load in t5-large.",
"> Did you get this solved? I cannot load in t5-large.\r\n\r\nsolved simply by reactivating the environment and restarting the program. I installed old version of transformers, after upgrading transformers, I forgot to deactivate the environment. "
] | 1,594 | 1,594 | 1,594 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bart):**facebook/bart-large-cnn**
Language I am using the model on English
The problem arises when using:
* [x] the official example scripts: summarization
## To reproduce
Steps to reproduce the behavior:
run the code below
```python
from transf... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5578?src=pr&el=h1) Report\n> Merging [#5578](https://codecov.io/gh/huggingface/transformers/pull/5578?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8ab565a4be5a7fd96b19ef88d474037ef31f27e5&el=desc) will **decrease... | 1,594 | 1,595 | 1,594 | MEMBER | null | As discussed with the authors in Reformer we cache the hidden states and buckets to speed up inference for language generation. Caching only the hidden states can save at least twice the memory versus caching the key and value output vectors (often more since the `hidden_size` can be smaller than key and query projecti... | {
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https://api.github.com/repos/huggingface/transformers/issues/5577 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5577/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5577/comments | https://api.github.com/repos/huggingface/transformers/issues/5577/events | https://github.com/huggingface/transformers/pull/5577 | 652,363,208 | MDExOlB1bGxSZXF1ZXN0NDQ1NDQ1MDg0 | 5,577 | Fix tokenizers pretrained saving/loading | {
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"Hey @n1t0, great job, saving works now! :)\r\nDo you think `AddedToken` instances should be serialized with additional meta data? \r\n\r\nI managed to tweak JSON (de)serialization with custom hooks to process objects properly but it is difficult to infer the deserializing type from a single set of attributes, pass... | 1,594 | 1,651 | 1,597 | MEMBER | null | Fix #5571
I managed to fix the saving part, but I don't really know what to do for the loading part (in `_from_pretrained`). | {
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https://api.github.com/repos/huggingface/transformers/issues/5576 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5576/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5576/comments | https://api.github.com/repos/huggingface/transformers/issues/5576/events | https://github.com/huggingface/transformers/pull/5576 | 652,355,643 | MDExOlB1bGxSZXF1ZXN0NDQ1NDM5MDE2 | 5,576 | Fix tests imports dpr | {
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"Some tests are failing, please only merge once everything pass.",
"Yep I'm on it",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5576?src=pr&el=h1) Report\n> Merging [#5576](https://codecov.io/gh/huggingface/transformers/pull/5576?src=pr&el=desc) into [master](https://codecov.io/gh/huggingfa... | 1,594 | 1,594 | 1,594 | MEMBER | null | There were changes in the locations of some functions used for tests in #5350.
When #5279 was merged some tests couldn't run.
I fixed the imports of those functions.
When I re-ran the tests I noticed that some didn't pass for the DPRReaderTokenizer so I fixed them.
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https://api.github.com/repos/huggingface/transformers/issues/5575 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5575/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5575/comments | https://api.github.com/repos/huggingface/transformers/issues/5575/events | https://github.com/huggingface/transformers/issues/5575 | 652,353,048 | MDU6SXNzdWU2NTIzNTMwNDg= | 5,575 | Seperating premise and hypothesis in MNLI | {
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"Might be of interest to @joeddav :)",
"I've solved this problem. Thanks a lot @joeddav for even showing interest. You guys are very supportive. I'll post what I did so that if someone is stuck, they can refer.\r\nIn all `SequenceClassification` model, there's a linear layer. So we can straightaway add the loss f... | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | # ❓ Questions & Help
I'm adding it here since I didn't receive any reply on SO. I think this query might be relevant for people who are working in few-shot, contrastive/metric learning space.
I'm trying to implement Siamese like transformer architecture. Similar work has been done in SentenceBERT paper. I'm facin... | {
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"Thank you!"
] | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | Readme file for deepset/electra-base-squad2 | {
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https://api.github.com/repos/huggingface/transformers/issues/5573 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5573/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5573/comments | https://api.github.com/repos/huggingface/transformers/issues/5573/events | https://github.com/huggingface/transformers/issues/5573 | 652,338,186 | MDU6SXNzdWU2NTIzMzgxODY= | 5,573 | MBARTTokenizer set_lang logic will only work for src_lang=en_XX | {
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https://api.github.com/repos/huggingface/transformers/issues/5572 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5572/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5572/comments | https://api.github.com/repos/huggingface/transformers/issues/5572/events | https://github.com/huggingface/transformers/pull/5572 | 652,281,015 | MDExOlB1bGxSZXF1ZXN0NDQ1Mzc5Mjky | 5,572 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5572?src=pr&el=h1) Report\n> Merging [#5572](https://codecov.io/gh/huggingface/transformers/pull/5572?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d2a93991158f15993eba9ab421d82766b892f948&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | {
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"Fixed by #6026",
"> Fixed by #6026\r\n\r\nI am still experiencing this issue when running transformers 3.1\r\n\r\nIf you load from pretrained as follows:\r\n```py\r\ntokenizer = RobertaTokenizer.from_pretrained(\"path/to/tokenizer/folder\")\r\n```\r\nthen the tokenizer init_kwargs will load appropriately. The in... | 1,594 | 1,604 | 1,597 | NONE | null | # 🐛 Bug
## Information
I'm using an instance of `RobertaTokenizerFast` with my custom vocab (pretrained using `tokenizers` library). When I try to save the tokenizer using `tokenizer.save_pretrained(<path>)` method a type error occurs.
I did a bit of investigation why this happens and got a workaround https:... | {
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https://api.github.com/repos/huggingface/transformers/issues/5570 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5570/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5570/comments | https://api.github.com/repos/huggingface/transformers/issues/5570/events | https://github.com/huggingface/transformers/issues/5570 | 652,145,624 | MDU6SXNzdWU2NTIxNDU2MjQ= | 5,570 | Freeze the token embeddings for finetuning | {
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"freezing embedding weights will result in faster training and will also consume less GPU memory. It might result in slightly less performance but I guess it ultimately depends on the task, the dataset etc.",
"A tangent question: is it possible to freeze only a subset of the token embedding weights? Background: I... | 1,594 | 1,658 | 1,603 | NONE | null | Hi ,
I have finetuned the T5 model using the community notebooks given . But when i looked into the code under examples/seq2seq finetuning code token embedding weights are frozen.
Can some one throw some light on how does this effect the finetuning process?
Thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/5569 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5569/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5569/comments | https://api.github.com/repos/huggingface/transformers/issues/5569/events | https://github.com/huggingface/transformers/issues/5569 | 652,111,700 | MDU6SXNzdWU2NTIxMTE3MDA= | 5,569 | BertEmbeddings code for position_embeddings and word_embeddings | {
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"Hi, BERT uses absolute positional embeddings, not based on sinusoidal functions. The positional embeddings are learned. \r\n\r\nYou can check the [XLNet code](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_xlnet.py#L704-L712) or the [TransfoXL code](https://github.com/huggingface... | 1,594 | 1,594 | 1,594 | NONE | null | I am trying to figure out how exactly positions and words are embedded in Bert. I checked the code, and it seems following code is used for the purpose. This implies that both the embedding function are calling same `__init__' function from the class `nn.Embedding`. Where exactly is the code doing the actual pos... | {
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https://api.github.com/repos/huggingface/transformers/issues/5568 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5568/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5568/comments | https://api.github.com/repos/huggingface/transformers/issues/5568/events | https://github.com/huggingface/transformers/issues/5568 | 652,110,887 | MDU6SXNzdWU2NTIxMTA4ODc= | 5,568 | Use pretrained bert withou embedding layers. | {
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"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n\nIf you think this still needs to be addressed please comment on this thread."
] | 1,594 | 1,614 | 1,614 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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https://api.github.com/repos/huggingface/transformers/issues/5567 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5567/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5567/comments | https://api.github.com/repos/huggingface/transformers/issues/5567/events | https://github.com/huggingface/transformers/issues/5567 | 652,018,759 | MDU6SXNzdWU2NTIwMTg3NTk= | 5,567 | How to get gradient wrt to a word embedding layer pytorch? | {
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"Hi, the `word_embeddings` variable is not returned so you won't obtain these except if you modify the file.",
"Thanks!"
] | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
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https://api.github.com/repos/huggingface/transformers/issues/5566 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5566/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5566/comments | https://api.github.com/repos/huggingface/transformers/issues/5566/events | https://github.com/huggingface/transformers/pull/5566 | 652,004,116 | MDExOlB1bGxSZXF1ZXN0NDQ1MTU1MTMw | 5,566 | [docs] fix model_doc links in model summary | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5566?src=pr&el=h1) Report\n> Merging [#5566](https://codecov.io/gh/huggingface/transformers/pull/5566?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1d2332861f5225aef17bd7e75abc670a72239081&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | MEMBER | null | Possible fix for #5561
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/5565 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5565/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5565/comments | https://api.github.com/repos/huggingface/transformers/issues/5565/events | https://github.com/huggingface/transformers/issues/5565 | 651,997,744 | MDU6SXNzdWU2NTE5OTc3NDQ= | 5,565 | ❓ Why multiplying the output of T5 by some scalar before LM head ? | {
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"I think this would be a great question for our new forum, with a title like \"T5 architecture\": https://discuss.huggingface.co/ - would you mind posting it there? This seems like an interesting question people would probably like to see there.",
"This issue has been automatically marked as stale because it has ... | 1,594 | 1,600 | 1,600 | CONTRIBUTOR | null | # ❓ Questions & Help
I'm wondering why multiplying the outputs of T5 by some scalar before inputting in the LM head :
https://github.com/huggingface/transformers/blob/1d2332861f5225aef17bd7e75abc670a72239081/src/transformers/modeling_tf_t5.py#L1147
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https://api.github.com/repos/huggingface/transformers/issues/5564 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5564/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5564/comments | https://api.github.com/repos/huggingface/transformers/issues/5564/events | https://github.com/huggingface/transformers/issues/5564 | 651,961,048 | MDU6SXNzdWU2NTE5NjEwNDg= | 5,564 | Where is the documentation on migrating to the 3.0 tokenizer API? | {
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"Hi @githubrandomuser2017 , AFAIK these methods will still work in v.3.0 as backward compatibility is maintained. This can help\r\nhttps://huggingface.co/transformers/preprocessing.html",
"@patil-suraj The page you mentioned (https://huggingface.co/transformers/preprocessing.html) doesn't mention anything about t... | 1,594 | 1,594 | 1,594 | NONE | null | I see that you folks have completely changed the API to do tokenizing, e.g. for BertTokenizer. I have a lot of code using the two methods `encode_plus()` and `batch_encode_plus()`, and when I went to the [documentation](https://huggingface.co/transformers/main_classes/tokenizer.html) to look up an argument, I found tha... | {
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https://api.github.com/repos/huggingface/transformers/issues/5563 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5563/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5563/comments | https://api.github.com/repos/huggingface/transformers/issues/5563/events | https://github.com/huggingface/transformers/issues/5563 | 651,916,231 | MDU6SXNzdWU2NTE5MTYyMzE= | 5,563 | Bug in Question Answering pipeline when question is weird (unanswerable) | {
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"I believe https://github.com/huggingface/transformers/pull/5542 is trying to fix exactly this.",
"Yes, I see. The pipeline failing on that pull request shows the same error.\r\nBut, I think the fix would lie somewhere in squad feature creation because the `feature.token_to_orig_map` is what gives the `KeyError`.... | 1,594 | 1,594 | 1,594 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): TFDistilBertForQuestionAnswering
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 ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5561 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5561/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5561/comments | https://api.github.com/repos/huggingface/transformers/issues/5561/events | https://github.com/huggingface/transformers/issues/5561 | 651,832,537 | MDU6SXNzdWU2NTE4MzI1Mzc= | 5,561 | [Docs] Incorrect links to models in the Summary of the Models page | {
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"Fixed in #5566 "
] | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | ### Issues with the Summary of the Models page
- Description:
- Clicking on any model documentation located in https://huggingface.co/transformers/model_summary.html leads us to an empty page.
- Possible Fix:
- I've noticed that the GPT link is https://huggingface.co/model_doc/gpt while it should be https://hug... | {
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https://api.github.com/repos/huggingface/transformers/issues/5560 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5560/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5560/comments | https://api.github.com/repos/huggingface/transformers/issues/5560/events | https://github.com/huggingface/transformers/pull/5560 | 651,827,856 | MDExOlB1bGxSZXF1ZXN0NDQ1MDA5NTE2 | 5,560 | [Reformer] Adapt Reformer MaskedLM Attn mask | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5560?src=pr&el=h1) Report\n> Merging [#5560](https://codecov.io/gh/huggingface/transformers/pull/5560?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/58cca47c16149e43d1b516623d59e3c5d97f695e&el=desc) will **decrease... | 1,594 | 1,594 | 1,594 | MEMBER | null | The official trax code added an `attention_mask` to the LSH Attention layer a couple of weeks ago: https://github.com/google/trax/commit/94d7d8643d9a6ea38539486dea9ad16da30ec897#diff-a022408d1029c5cbeac49f4589f1b713R1180 . This PR adapts the Hugging Face code to have equal outputs to the official trax code for masked s... | {
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https://api.github.com/repos/huggingface/transformers/issues/5559 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5559/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5559/comments | https://api.github.com/repos/huggingface/transformers/issues/5559/events | https://github.com/huggingface/transformers/pull/5559 | 651,822,368 | MDExOlB1bGxSZXF1ZXN0NDQ1MDA0OTU3 | 5,559 | Fix #5507 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5558?src=pr&el=h1) Report\n> Merging [#5558](https://codecov.io/gh/huggingface/transformers/pull/5558?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1bbc28bee719120f3b6f73dbe7dfe6f67e2e9fa7&el=desc) will **increase... | 1,594 | 1,594 | 1,594 | MEMBER | null | Fix https://github.com/huggingface/transformers/issues/5486
Fix https://github.com/huggingface/transformers/issues/5482
Fix https://github.com/huggingface/transformers/issues/5393
Fix https://github.com/huggingface/transformers/issues/5490 | {
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"Your learning rate is pretty high and you might be overfitting. Try it again with 3E-5.",
"My question is i have freezed the whole roberta layer. Then why still it needs to be such small lr rather than normal 0.001 as i am training only a classifier head.",
"This issue has been automatically marked as stale be... | 1,594 | 1,599 | 1,599 | NONE | null | The following is my classifier class. I trained it with appropriate code and same tokenizer(roberta-base). It trained well on SST2 2 class sentiment problem. But when i replaced base model with roberta-large (also the tokenizer and dim of linear layer)my classifier is stuck at 50% accuracy and not matter how many epoch... | {
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"What PL version are you on? The unittests should catch this.",
"@sshleifer `pytorch-lightning==0.8.4` which i believe is the latest",
"Got it.\r\nI think you need to run `make style` to get CI to pass.\r\nWe also may need to wait to merge this until https://github.com/huggingface/transformers/pull/5361, which ... | 1,594 | 1,595 | 1,595 | NONE | null | running the example `finetune_bart_tiny.sh` in `seq2seq` fails with:
```
Traceback (most recent call last):
File "finetune.py", line 344, in <module>
main(args)
File "finetune.py", line 322, in main
logger=logger,
File "/root/notebooks/analysis/transformers/examples/lightning_base.py", line 330, in... | {
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"I also find out that every example which uses transformers with `binary_crossentropy` loss changes the pretrained model(i.e. adds some layers). Is it necessary? If so, then what minimal working example for this? ",
"Now I'm just trying to copy [this Kaggle notebook](https://www.kaggle.com/definedennis/pretrained... | 1,594 | 1,600 | 1,600 | NONE | null | I'm trying to fine tune `transformers` with my own dataset in the `csv` file. So, I found [an item in the docs which shows a basic usage example](https://huggingface.co/transformers/training.html#fine-tuning-in-native-tensorflow-2). But the main problem is that this example shows how to use transformers with the `tenso... | {
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https://api.github.com/repos/huggingface/transformers/issues/5554 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5554/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5554/comments | https://api.github.com/repos/huggingface/transformers/issues/5554/events | https://github.com/huggingface/transformers/issues/5554 | 651,723,386 | MDU6SXNzdWU2NTE3MjMzODY= | 5,554 | huggingface optimizer cannot de-serialize | {
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"Great, thanks for your analysis! Do you think you can open a PR with your proposed fix?",
"Sure, will do!",
"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",
"Hi @suhasvk , Did you ... | 1,594 | 1,603 | 1,599 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): 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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"There is some documentation here https://huggingface.co/docs but we will add more later this week.",
"I don't think we want to mask (pun intended) too much in the inference widget what the model actually consumes, but did you see that:\r\n- you can specify your model's widget's example input, by adding metadata ... | 1,594 | 1,600 | 1,600 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
Some models for text generation make use of special tokens or additional initialization text.
It would be useful to add the possibility to pass additional t... | {
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https://api.github.com/repos/huggingface/transformers/issues/5550 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5550/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5550/comments | https://api.github.com/repos/huggingface/transformers/issues/5550/events | https://github.com/huggingface/transformers/pull/5550 | 651,607,438 | MDExOlB1bGxSZXF1ZXN0NDQ0ODMwMzky | 5,550 | Fix the tokenization warning noted in #5505 | {
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https://api.github.com/repos/huggingface/transformers/issues/5549 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5549/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5549/comments | https://api.github.com/repos/huggingface/transformers/issues/5549/events | https://github.com/huggingface/transformers/pull/5549 | 651,599,249 | MDExOlB1bGxSZXF1ZXN0NDQ0ODIzNjQ3 | 5,549 | The `add_space_before_punct_symbol` is only for TransfoXL | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5549?src=pr&el=h1) Report\n> Merging [#5549](https://codecov.io/gh/huggingface/transformers/pull/5549?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1bbc28bee719120f3b6f73dbe7dfe6f67e2e9fa7&el=desc) will **decrease... | 1,594 | 1,594 | 1,594 | MEMBER | null | Same fix as in the [pipelines](https://github.com/huggingface/transformers/blob/master/src/transformers/pipelines.py#L626). Not the cleanest way to do a per-model change, but is bug-free for v3.0.2.
closes https://github.com/huggingface/transformers/issues/5525 | {
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https://api.github.com/repos/huggingface/transformers/issues/5548 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5548/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5548/comments | https://api.github.com/repos/huggingface/transformers/issues/5548/events | https://github.com/huggingface/transformers/issues/5548 | 651,594,737 | MDU6SXNzdWU2NTE1OTQ3Mzc= | 5,548 | Possibility to use WhitespaceSplit as pre_tokenizer instead of BPE/Sentencepiece? | {
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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"
] | 1,594 | 1,599 | 1,599 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to 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/5547 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5547/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5547/comments | https://api.github.com/repos/huggingface/transformers/issues/5547/events | https://github.com/huggingface/transformers/issues/5547 | 651,591,112 | MDU6SXNzdWU2NTE1OTExMTI= | 5,547 | [Feature Request] Extract Predictions from Trainer | {
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"Unless I'm mistaken, Question-answering does support Trainer. Is a specific feature missing for your use case?",
"Hi @julien-c!\r\n\r\nAt the time of writing the PR was not merged yet (and I was not aware of it, my bad). It is great!\r\n\r\nIn any case, the previous example (the one without trainer) outputted bo... | 1,594 | 1,607 | 1,607 | NONE | null | # 🚀 Feature request
Add the possibility to return predictions along with its example id in the new Trainer class.
## Motivation
When working with extractive QA (i.e.: SQuAD), you get back the best predictions, but, the current example for running squad uses the old, plain training/eval script, without the new... | {
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https://api.github.com/repos/huggingface/transformers/issues/5546 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5546/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5546/comments | https://api.github.com/repos/huggingface/transformers/issues/5546/events | https://github.com/huggingface/transformers/pull/5546 | 651,581,766 | MDExOlB1bGxSZXF1ZXN0NDQ0ODA5NDcw | 5,546 | GPT2 tokenizer should not output token type IDs | {
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closes https://github.com/huggingface/transformers/issues/5517
code quality will pass when merged in master.
Edit (@thomwolf):
This will also fix #4922 | {
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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"
] | 1,594 | 1,599 | 1,599 | NONE | null | # 🚀 Feature request
It may be already possible, but I couldn't figure out how, to call TFBertForQuestionAnswering on a batch on context-question pairs rather than just one by one.
## Motivation
I tried out the same code on a machine with 16 cores and a GPU. I could process 22 pairs/sec with the CPUs, but only... | {
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https://api.github.com/repos/huggingface/transformers/issues/5544 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5544/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5544/comments | https://api.github.com/repos/huggingface/transformers/issues/5544/events | https://github.com/huggingface/transformers/issues/5544 | 651,561,976 | MDU6SXNzdWU2NTE1NjE5NzY= | 5,544 | incorrect typehint for PreTrainedTokenizer.convert_ids_to_tokens() return value | {
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"We want to make a clean patched release soon, so I opened #5551 to make sure it's fixed in it.\r\nIn the future, don't hesitate to directly open a PR for an issue with a clear fix like this :-)",
"Closed via #5551"
] | 1,594 | 1,594 | 1,594 | NONE | null | # 🐛 Bug
## Information
The return value of `tokenization_utils.PreTrainedTokenizer.convert_ids_to_tokens()` is declared as `Union[int, List[int]]` while the method clearly returns a `Union[str, List[str]]` object type.
Would you like me to open a PR? ;)
Thanks for the great work!
Andreas
PS: Excuse me ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5543 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5543/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5543/comments | https://api.github.com/repos/huggingface/transformers/issues/5543/events | https://github.com/huggingface/transformers/issues/5543 | 651,544,580 | MDU6SXNzdWU2NTE1NDQ1ODA= | 5,543 | t5-base translation_en_to_de BLEU lower than the paper | {
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"I think the script `evaluate_wmt.py` was never really tested. Note that `t5-base` is not a fine-tuned model, but just a pretrained model. So you would definitely get better results by fine-tuning the model on translation. I'm not 100% sure, but I think the T5 paper shows the \"non-finetuned\" results for translati... | 1,594 | 1,599 | 1,599 | NONE | null | I downloaded the "newstest2014.en" and "newstest2014.de" datasets. Then I used examples/translation/t5/evaluate_wmt.py to evaluate the BLEU value of en_to_de, and the BLEU finally obtained is equal to 22.15, which is much lower than the paper. I used the t5-base model and my transformers version is 2.11.0.
Is there so... | {
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https://api.github.com/repos/huggingface/transformers/issues/5542 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5542/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5542/comments | https://api.github.com/repos/huggingface/transformers/issues/5542/events | https://github.com/huggingface/transformers/pull/5542 | 651,474,427 | MDExOlB1bGxSZXF1ZXN0NDQ0NzIzNDE2 | 5,542 | QA pipeline should mask CLS tokens after handling impossible answer | {
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"Is the pytorch test failure unrelated here @mfuntowicz ?",
"Will check this :)",
"Closed as fix was included in #5496 "
] | 1,594 | 1,651 | 1,594 | MEMBER | null | Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> | {
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https://api.github.com/repos/huggingface/transformers/issues/5541 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5541/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5541/comments | https://api.github.com/repos/huggingface/transformers/issues/5541/events | https://github.com/huggingface/transformers/issues/5541 | 651,465,411 | MDU6SXNzdWU2NTE0NjU0MTE= | 5,541 | High F1 score. But poor accuracy during Inference due to tokenisation | {
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"Hello! Why do you believe the tokenization to be the issue here?",
"@LysandreJik Thanks for reaching out.\r\n\r\nPlease find my observations with the inconsistency in the Tokenizer(possible issue), since I was using the HuggingFace provided script for training the custom NER Model.\r\n\r\n**1. Expected name:**\r... | 1,594 | 1,599 | 1,599 | NONE | null | # 🐛 Bug
## Information
I am using **Bert-Base-cased** model to train my custom Named entity recognition(NER) model with a sequence length of **512**.
Language I am using the model on: **English**
The problem arises when using:
* [ ] the official example scripts: **token-classification/run_ner.py**
The ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5540 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5540/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5540/comments | https://api.github.com/repos/huggingface/transformers/issues/5540/events | https://github.com/huggingface/transformers/issues/5540 | 651,443,634 | MDU6SXNzdWU2NTE0NDM2MzQ= | 5,540 | MobileBert embedding vectors values | {
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"Hi! Firstly, in your code you're using a `MobileBertModel` with tensorflow inputs; does that work? You should either use torch inputs or use `TFMobileBertModel` instead.\r\n\r\nThe model outputs have no reason to be bound between [-1, 1], as they're logits. You can pass them through a softmax layer to get the tota... | 1,594 | 1,600 | 1,600 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): MobileBert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
```py
def BERT_embeddings... | {
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https://api.github.com/repos/huggingface/transformers/issues/5539 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5539/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5539/comments | https://api.github.com/repos/huggingface/transformers/issues/5539/events | https://github.com/huggingface/transformers/issues/5539 | 651,437,349 | MDU6SXNzdWU2NTE0MzczNDk= | 5,539 | Fine Tuning Using /question-answering/run_squad.py | {
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"Hi, there's a [readme](https://github.com/huggingface/transformers/tree/master/examples/question-answering) in `question-answering`!",
"Yes, I've gone through this resource. What I want to achieve is to fine-tune on a custom resource and not on SQuAD dataset. I want to train it on Question-Answer pairs.\r\nYou c... | 1,594 | 1,594 | 1,594 | NONE | null | How do I use `/question-answering/run_squad.py` to fine-tune my own custom dataset?
[StackOverflow][1]
[1]: https://stackoverflow.com/questions/62752709/how-to-fine-tune-bert-for-question-answering | {
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https://api.github.com/repos/huggingface/transformers/issues/5538 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5538/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5538/comments | https://api.github.com/repos/huggingface/transformers/issues/5538/events | https://github.com/huggingface/transformers/issues/5538 | 651,394,176 | MDU6SXNzdWU2NTEzOTQxNzY= | 5,538 | Easier way to download pretrained model files to local | {
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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",
"Any news on this? We have the same problem when running a Docker-container (it takes a while to load the model all the time)",
"Hey!... | 1,594 | 1,650 | 1,599 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarily 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
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https://api.github.com/repos/huggingface/transformers/issues/5537 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5537/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5537/comments | https://api.github.com/repos/huggingface/transformers/issues/5537/events | https://github.com/huggingface/transformers/issues/5537 | 651,392,133 | MDU6SXNzdWU2NTEzOTIxMzM= | 5,537 | Longformer - Compression | {
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"You could check out the example script under distillation: `/home/patrick/hugging_face/transformers/examples/distillation`",
"Did you upload the model to the model hub? I would be great so that we can take a closer look :-) ",
"Hello, thanks for the reply. I checked the train.py script under examples/distillat... | 1,594 | 1,599 | 1,599 | NONE | null | Hello, I have trained a longformer model on my custom question answering dataset, and now I wanted to know if there is a way to compress this trained model?
Thank you! | {
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https://api.github.com/repos/huggingface/transformers/issues/5536 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5536/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5536/comments | https://api.github.com/repos/huggingface/transformers/issues/5536/events | https://github.com/huggingface/transformers/pull/5536 | 651,345,420 | MDExOlB1bGxSZXF1ZXN0NDQ0NjE3NTQ3 | 5,536 | Create README | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5536?src=pr&el=h1) Report\n> Merging [#5536](https://codecov.io/gh/huggingface/transformers/pull/5536?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/58cca47c16149e43d1b516623d59e3c5d97f695e&el=desc) will **decrease... | 1,594 | 1,594 | 1,594 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5535 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5535/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5535/comments | https://api.github.com/repos/huggingface/transformers/issues/5535/events | https://github.com/huggingface/transformers/issues/5535 | 651,321,670 | MDU6SXNzdWU2NTEzMjE2NzA= | 5,535 | How i can set the special token <|endoftext|> to an other id ? | {
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" Now is set to 0 and let's say i want to change it to 50256 for GPT-2 .",
"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"
] | 1,594 | 1,599 | 1,599 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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https://api.github.com/repos/huggingface/transformers/issues/5534 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5534/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5534/comments | https://api.github.com/repos/huggingface/transformers/issues/5534/events | https://github.com/huggingface/transformers/issues/5534 | 651,300,017 | MDU6SXNzdWU2NTEzMDAwMTc= | 5,534 | How-to-fine-tune-bert-for-question-answering? | {
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"Hi, how did you solve this project? I want to do the same in another domain and I want to know what is the best approach."
] | 1,594 | 1,697 | 1,594 | NONE | null | I wish to train two domain-specific models:
Domain 1: Constitution and related Legal Documents
Domain 2: Technical and related documents.
For Domain 1, I've access to a text-corpus with texts from the constitution and no question-context-answer tuples. For Domain 2, I've access to Question-Answer pairs.
Is it p... | {
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"Sounds like your downloads were corrupted.",
"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"
] | 1,593 | 1,599 | 1,599 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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"`from transformers.file_utils import default_cache_path, hf_bucket_url`\r\nI want to import hf_bucket_url on Colab, but I still got the error\r\n\"ImportError: cannot import name 'hf_bucket_url' from 'transformers.file_utils' (/usr/local/lib/python3.9/dist-packages/transformers/file_utils.py)\"\r\nAm I do somethin... | 1,593 | 1,679 | 1,594 | CONTRIBUTOR | null | So I installed the latest version of transformers on Google Colab
!pip install transformers
When trying to invoke the conversion file using
!python /usr/local/lib/python3.6/dist-packages/transformers/convert_pytorch_checkpoint_to_tf2.py .py --help
Or trying to use
from transformers.file... | {
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https://api.github.com/repos/huggingface/transformers/issues/5530 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5530/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5530/comments | https://api.github.com/repos/huggingface/transformers/issues/5530/events | https://github.com/huggingface/transformers/issues/5530 | 651,140,258 | MDU6SXNzdWU2NTExNDAyNTg= | 5,530 | Tabert | {
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"In their readme they say that the implementation to this project is still WIP, but they said this on release.\r\nIt should be really easy to add it here while they are already using this library in their implementation.\r\nDoes the huggingface team has more information about this, if the community can open an PR f... | 1,593 | 1,613 | null | CONTRIBUTOR | null | # 🌟 New model addition
## Model description
a pre-trained language model for learning joint representations of natural language utterances and (semi-)structured tables for semantic parsing. TaBERT is pre-trained on a massive corpus of 26M Web tables and their associated natural language context, and could be used ... | {
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"I must admit that I am confused here. I don't see how this is possible with one of the `0.8.0` version of `tokenizers`, they should have `is_pretokenized` as expected argument of both `encode` and `encode_batch`. Unfortunately, I was not able to reproduce it using the snippet you provided. \r\n\r\nWould it be poss... | 1,593 | 1,594 | 1,594 | NONE | null | # 🐛 Bug
## Information
See title. Does not occur with "slow" tokenizers.
## To reproduce
```python
from transformers import GPT2TokenizerFast
tokenizer = GPT2TokenizerFast.from_pretrained('gpt2')
texts = ['I am a teapot', 'Short and stout']
tokenizer.batch_encode_plus(texts)
```
## Trace
```
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"#Code used to convert from tf to Pytorch\r\n\r\nimport torch\r\n\r\nfrom transformers import (\r\n CONFIG_NAME,\r\n WEIGHTS_NAME,\r\n XLNetConfig,\r\n XLNetForQuestionAnswering,\r\n XLNetForSequenceClassification,\r\n XLNetLMHeadModel,\r\n load_tf_weights_in_xlnet,\r\n XLNetModel\r\n)\r\n\r... | 1,593 | 1,594 | 1,594 | NONE | null | Hi, I have XLNet checkpoint file and want to convert it to pytorch. I have converted the file to pytorch and when I am using the same file with simpletramsformers for text classification. It says the number of labels is not matching. Where should I specify the number of classes while converting from tf to pytorch? | {
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https://api.github.com/repos/huggingface/transformers/issues/5526 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5526/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5526/comments | https://api.github.com/repos/huggingface/transformers/issues/5526/events | https://github.com/huggingface/transformers/pull/5526 | 651,096,185 | MDExOlB1bGxSZXF1ZXN0NDQ0NDI2MjM2 | 5,526 | Fix `RobertaClassificationHead` style consistency. | {
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## Information
Model I am using (Bert, XLNet ...):
ctrl
Language I am using the model on (English, Chinese ...):
English
The problem arises when using:
* [ ] the official example scripts: (give details below)
```
python run_generation.py \
--model_type ctrl \
--model_name ctrl --length... | {
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https://api.github.com/repos/huggingface/transformers/issues/5524 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5524/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5524/comments | https://api.github.com/repos/huggingface/transformers/issues/5524/events | https://github.com/huggingface/transformers/issues/5524 | 651,041,941 | MDU6SXNzdWU2NTEwNDE5NDE= | 5,524 | How to fine-tune tinyBERT for question-asnwering | {
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How do I fine-tune tiny-BERT for question answering on my custom dataset. I've a list of questions and corresponding answers in a csv format, How do I fine-tune tiny-BERT on this dataset.
[You can find it at StackOverFlow here](https://stackoverflow.com/questions/62710931/huggingface-transformer... | {
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https://api.github.com/repos/huggingface/transformers/issues/5523 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5523/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5523/comments | https://api.github.com/repos/huggingface/transformers/issues/5523/events | https://github.com/huggingface/transformers/pull/5523 | 651,041,795 | MDExOlB1bGxSZXF1ZXN0NDQ0Mzg2ODg1 | 5,523 | Create model card | {
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https://api.github.com/repos/huggingface/transformers/issues/5522 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5522/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5522/comments | https://api.github.com/repos/huggingface/transformers/issues/5522/events | https://github.com/huggingface/transformers/pull/5522 | 651,039,176 | MDExOlB1bGxSZXF1ZXN0NDQ0Mzg0OTcy | 5,522 | Added data collator for permutation (XLNet) language modeling and related calls | {
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https://api.github.com/repos/huggingface/transformers/issues/5521 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5521/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5521/comments | https://api.github.com/repos/huggingface/transformers/issues/5521/events | https://github.com/huggingface/transformers/issues/5521 | 650,988,699 | MDU6SXNzdWU2NTA5ODg2OTk= | 5,521 | What should i do if I want a model class similar to BertForSequenceClassification? | {
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"Hi @cloudygoose , \r\nTake a look at the code of `BertForSequenceClassification` https://huggingface.co/transformers/_modules/transformers/modeling_bert.html#BertForSequenceClassification,\r\n\r\nAll it does is, pass the inputs through `BertModel`, which returns the pooled output of bert and the applies the class... | 1,593 | 1,599 | 1,599 | NONE | null | # ❓ Questions & Help
Hi!
For my task I want to implement a class similar to BertForSequenceClassification, but a little different, for example, i may want multiple linear head on top of the bert encoding. Call it BertForMySequenceClassification,
But I still want to use the pretrained bert parameters, and hopeful... | {
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