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https://api.github.com/repos/huggingface/transformers/issues/3912 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3912/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3912/comments | https://api.github.com/repos/huggingface/transformers/issues/3912/events | https://github.com/huggingface/transformers/issues/3912 | 605,252,709 | MDU6SXNzdWU2MDUyNTI3MDk= | 3,912 | ImportError: cannot import name 'DataCollatorForLanguageModeling'_File "run_language_modeling.py" | {
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"Unfortunatelly I have the same error\r\n\r\nTraceback (most recent call last):\r\n File \"run_language_modeling.py\", line 29, in <module>\r\n from transformers import (\r\nImportError: cannot import name 'DataCollatorForLanguageModeling' from 'transformers' (E:\\PycharmProjects\\Ancient_BERT\\venv\\lib\\site-... | 1,587 | 1,657 | 1,587 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
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we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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If possible, check your work with an automated tool and tell us how you did it! | {
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"These `next_token_logits[batch_idx, banned_tokens[batch_idx]]` are logits in the `range(-inf, inf)` not probabilities. You can try to set all other logits except your banned_tokens to `-float(\"inf\")`"
] | 1,587 | 1,591 | 1,591 | 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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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3909?src=pr&el=h1) Report\n> Merging [#3909](https://codecov.io/gh/huggingface/transformers/pull/3909?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cb3c2212c79d7ff0a4a4e84c3db48371ecc1c15d&el=desc) will **increase... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | Fix #3892
@sshleifer | {
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https://api.github.com/repos/huggingface/transformers/issues/3908 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3908/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3908/comments | https://api.github.com/repos/huggingface/transformers/issues/3908/events | https://github.com/huggingface/transformers/pull/3908 | 605,119,098 | MDExOlB1bGxSZXF1ZXN0NDA3NTg0MTA3 | 3,908 | MarianMTModel.from_pretrained('Helsinki-NLP/opus-marian-en-de') | {
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"I think that's awesome! Such little code changes to include that many models is amazing :-) \r\nDoes the model with the pre-trained weights produce 1-to-1 the same results as the official Marian models in C++?",
"@patrickvonplaten the generations are very sensible, but not identical to marian, due to slightly di... | 1,587 | 1,592 | 1,588 | CONTRIBUTOR | null | Adds support for `opus/marian-en-de` translation models:
- There are 900 models with this `MarianSentencePieceTokenizer`, `MarianMTModel` setup. - This PR only adds en-de to avoid massive S3 maintenance if names/other things change.
- There is no formal connection to the bart authors, but the bart code is well-tested... | {
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https://api.github.com/repos/huggingface/transformers/issues/3907 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3907/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3907/comments | https://api.github.com/repos/huggingface/transformers/issues/3907/events | https://github.com/huggingface/transformers/pull/3907 | 605,105,346 | MDExOlB1bGxSZXF1ZXN0NDA3NTcyNzYw | 3,907 | Fix TF optimization classes and apply the changes in the NER TF script | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3907?src=pr&el=h1) Report\n> Merging [#3907](https://codecov.io/gh/huggingface/transformers/pull/3907?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cb3c2212c79d7ff0a4a4e84c3db48371ecc1c15d&el=desc) will **not chan... | 1,587 | 1,589 | 1,589 | CONTRIBUTOR | null | This PR fix the AdamW and GradientAccumulator optimization classes for Tensorflow. Furthermore, we apply these new changes in the NER TF script. | {
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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"
] | 1,587 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
Model conversion succeeds but inputs and outputs are not recognized.
## Information
Model I am using (Bert, XLNet ...): BERT (`bert-base-uncased`)
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
- TensorFlow 2.1.0 + Transformers 2.8.0 - has no probl... | {
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https://api.github.com/repos/huggingface/transformers/issues/3904 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3904/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3904/comments | https://api.github.com/repos/huggingface/transformers/issues/3904/events | https://github.com/huggingface/transformers/issues/3904 | 605,041,334 | MDU6SXNzdWU2MDUwNDEzMzQ= | 3,904 | how i pass from an AutoModelWithLMHead to a GPT2DoubleHeadsModel ? | {
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"It will load the weights, but will not load the multiple choice head as it's not in the checkpoint. That's why fine-tuning it is a good idea, so that this head's weights get trained!"
] | 1,587 | 1,589 | 1,589 | NONE | null | I used your script of run_language_modeling.py to train a gpt2 model from scratch. Here i save it and upload:
from transformers import AutoModelWithLMHead, AutoTokenizer
import os
directory = "./checkpoint"
model = AutoModelWithLMHead.from_pretrained(directory)
tokenizer = AutoTokenizer.from_pretrained(directory... | {
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https://api.github.com/repos/huggingface/transformers/issues/3903 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3903/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3903/comments | https://api.github.com/repos/huggingface/transformers/issues/3903/events | https://github.com/huggingface/transformers/issues/3903 | 604,996,755 | MDU6SXNzdWU2MDQ5OTY3NTU= | 3,903 | T5 shows weird behaviour in a sanity check of its pre-training task. | {
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"Hi @yuvalkirstain,\r\n\r\n\r\nThanks for your message! \r\n\r\nWhen you put in `input_ids` and `lm_labels` at the some time the following happens:\r\nthe `decoder_input_ids` are created automatically depending on the `lm_labels` (shift `lm_labels` to the right and pre-prend `<PAD>`) and look as follows: \r\n`<PAD>... | 1,587 | 1,588 | 1,587 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): T5
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* no script, just a few simple commands. watch below.
## To reproduce
Steps to reproduce the behavior:
1.
```
from transformers import T... | {
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https://api.github.com/repos/huggingface/transformers/issues/3902 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3902/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3902/comments | https://api.github.com/repos/huggingface/transformers/issues/3902/events | https://github.com/huggingface/transformers/issues/3902 | 604,995,241 | MDU6SXNzdWU2MDQ5OTUyNDE= | 3,902 | RuntimeError: index out of range at /pytorch/aten/src/TH/generic/THTensorEvenMoreMath.cpp:237 | {
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"How big are your batches? BERT can only accept tensors of maximum length of 512. Is it possible one of your inputs is longer than 512?",
"I had the same issue while my `per_gpu_eval_batch_size=8` and `per_gpu_train_batch_size=8 `. ",
"Yes, it's unrelated to batch size. Is your sequence length longer than 512?"... | 1,587 | 1,612 | 1,605 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert-base-uncased
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ x] my own modified scripts: (give details below)
The tasks I am work... | {
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https://api.github.com/repos/huggingface/transformers/issues/3901 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3901/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3901/comments | https://api.github.com/repos/huggingface/transformers/issues/3901/events | https://github.com/huggingface/transformers/issues/3901 | 604,975,183 | MDU6SXNzdWU2MDQ5NzUxODM= | 3,901 | How to only use part of pretrained model | {
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"How did you obtain your pre-trained model? Does your pre-train model have a classification head? What is `model_class`? Is it `BertForSequenceClassification`?",
"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 fo... | 1,587 | 1,595 | 1,595 | NONE | null | Hi
I am using BERT for classification, I have a pretrained model, and my question is when I load the model like this:
model = model_class.from_pretrained(
args.model_name_or_path,
from_tf=bool(".ckpt" in args.model_name_or_path),
config=config,
cache_dir=args.cache_dir if args.... | {
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https://api.github.com/repos/huggingface/transformers/issues/3900 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3900/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3900/comments | https://api.github.com/repos/huggingface/transformers/issues/3900/events | https://github.com/huggingface/transformers/pull/3900 | 604,949,987 | MDExOlB1bGxSZXF1ZXN0NDA3NDQ1OTg5 | 3,900 | quick fix wording readme for community models | {
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https://api.github.com/repos/huggingface/transformers/issues/3899 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3899/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3899/comments | https://api.github.com/repos/huggingface/transformers/issues/3899/events | https://github.com/huggingface/transformers/issues/3899 | 604,832,353 | MDU6SXNzdWU2MDQ4MzIzNTM= | 3,899 | NLQ application | {
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"I assume you concatenate all paragraphs in a single text string, encode it with your question, and give the string as an input to your QA model (or pipeline). What you get back, is an answer span: indexes of the first and last character of the answer in the input text. To find a paragraph it belongs to, compute i... | 1,587 | 1,594 | 1,594 | NONE | null | # ❓ Questions & Help
I have a pdf extractor and from this I got a dataframe with 2 columns (sections,paragraphs).
Is there any easy way to do a question and get answer like: (example)
Question: "where is the book?"
Answer: "It's on the bookshelf."
Section: "1.2.3 The Book"
Paragraph: "(Full section paragraph)"
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3898 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3898/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3898/comments | https://api.github.com/repos/huggingface/transformers/issues/3898/events | https://github.com/huggingface/transformers/pull/3898 | 604,827,892 | MDExOlB1bGxSZXF1ZXN0NDA3MzQ3OTQx | 3,898 | Bump tokenizers version to final 0.7.0 | {
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https://api.github.com/repos/huggingface/transformers/issues/3897 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3897/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3897/comments | https://api.github.com/repos/huggingface/transformers/issues/3897/events | https://github.com/huggingface/transformers/issues/3897 | 604,774,339 | MDU6SXNzdWU2MDQ3NzQzMzk= | 3,897 | How to fine-tune DialoGPT with your own data? | {
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"DialoGPT is fine-tuned in the same way GPT2 in fine-tuned. Please take a look at the paper: \r\nhttps://arxiv.org/pdf/1911.00536.pdf . \r\n\r\nI will also add some training tips to the doc string."
] | 1,587 | 1,588 | 1,588 | NONE | null | # 🚀 How to fine-tune DialoGPT with your own data?
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
I really liked the new DialoGPT that allows to make chatbots, but how do i fine-tune this for own dataset?
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3896 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3896/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3896/comments | https://api.github.com/repos/huggingface/transformers/issues/3896/events | https://github.com/huggingface/transformers/issues/3896 | 604,681,806 | MDU6SXNzdWU2MDQ2ODE4MDY= | 3,896 | ImportError: cannot import name 'DataCollatorForLanguageModeling' in run_language_modeling.py | {
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"Duplicate of #3893 \r\n\r\nPlease install from source until we release a new version of the library on PyPI"
] | 1,587 | 1,587 | 1,587 | NONE | null | # 🐛 Bug ImportError: cannot import name 'DataCollatorForLanguageModeling' in run_language_modeling.py
## Information
> Traceback (most recent call last):
> File "transformers/examples/run_language_modeling.py", line 29, in <module>
> from transformers import (
> ImportError: cannot import name 'DataCollat... | {
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https://api.github.com/repos/huggingface/transformers/issues/3895 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3895/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3895/comments | https://api.github.com/repos/huggingface/transformers/issues/3895/events | https://github.com/huggingface/transformers/issues/3895 | 604,659,995 | MDU6SXNzdWU2MDQ2NTk5OTU= | 3,895 | run_bertology: AttributeError: 'NoneType' object has no attribute 'abs' | {
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"Sorry, I think it is the same issue as #4103. ",
"Please don't open duplicate issues. If you have more info about this issue, post it here. Also, please use [code blocks](https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks).",
"> Please don't open duplicate issues. If you ... | 1,587 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
One more question did run_bertology also support albert model?
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)
run_bertology.py
* [ ] my ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3894 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3894/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3894/comments | https://api.github.com/repos/huggingface/transformers/issues/3894/events | https://github.com/huggingface/transformers/issues/3894 | 604,647,290 | MDU6SXNzdWU2MDQ2NDcyOTA= | 3,894 | FileNotFoundError: [Errno 2] No such file or directory: 'mnli/dev_matched.tsv' | {
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"Well, it looks like you don't have the \"mnli/dev_matched.tsv\" file downloaded? You can download the GLUE datasets using [utils/download_glue_data.py](https://github.com/huggingface/transformers/blob/master/utils/download_glue_data.py)"
] | 1,587 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
## Information
A strange error：
INFO:transformers.data.datasets.glue:Creating features from dataset file at mnli
Traceback (most recent call last):
File "run_bertology.py", line 426, in <module>
main()
File "run_bertology.py", line 407, in main
eval_dataset = GlueDataset(args, tokenizer=t... | {
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https://api.github.com/repos/huggingface/transformers/issues/3893 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3893/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3893/comments | https://api.github.com/repos/huggingface/transformers/issues/3893/events | https://github.com/huggingface/transformers/issues/3893 | 604,468,068 | MDU6SXNzdWU2MDQ0NjgwNjg= | 3,893 | Can not import DataCollatorForLanguageModeling | {
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"I was installing from pip and it isn't updated yet. Building from source solved this.",
"I am trying to run this from source and still I am getting the same error! \r\nPlease have a look at this [here](https://github.com/huggingface/transformers/issues/3896#issue-604681806)",
"It's because the pip package hasn... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (ALBERT):
Language I am using the model on (Sanskrit, Hindi):
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQUaD ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3892 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3892/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3892/comments | https://api.github.com/repos/huggingface/transformers/issues/3892/events | https://github.com/huggingface/transformers/issues/3892 | 604,404,617 | MDU6SXNzdWU2MDQ0MDQ2MTc= | 3,892 | ❓ Summarization example : Why no shuffling ? | {
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"No good reason.\r\nDo you feel comfortable sending a PR that shuffles for train loader only?\r\n"
] | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | # ❓ Questions & Help
Usually, when loading using Dataloader, data is shuffled for the training set. But in the case of the summarization example, data is not shuffled for training set :
https://github.com/huggingface/transformers/blob/1dc9b3c7847269961458c059ad8ad443b26bf60d/examples/summarization/bart/finetune.p... | {
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"Hi @aced125, I agree that this functionality should be provided :-) \r\n\r\nI think in the PR, one has to include a `output_attention` argument to the `generate()` function and then make sure that the output idx are correct! \r\nBefore starting this PR, this PR should probably be solved before: https://github.com/... | 1,587 | 1,608 | 1,608 | NONE | null | # 🚀 Feature request
Please could we have the ability to return attention weights from the decoded generated tokens to the encoded source?
## Motivation
To attribute the decoded text. E.g in the summarization task we want to see where the decoder was paying attention to in the source.
## Your contribution
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3890 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3890/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3890/comments | https://api.github.com/repos/huggingface/transformers/issues/3890/events | https://github.com/huggingface/transformers/pull/3890 | 604,297,515 | MDExOlB1bGxSZXF1ZXN0NDA2OTE4MzM4 | 3,890 | Create model card | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3890?src=pr&el=h1) Report\n> Merging [#3890](https://codecov.io/gh/huggingface/transformers/pull/3890?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/eb5601b0a5a88824a2598956f96e06e7f2422bce&el=desc) will **decrease... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | Model: TinyBERT-spanish-uncased-finetuned-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"
] | 1,587 | 1,593 | 1,593 | NONE | null | https://github.com/huggingface/transformers/blob/d32585a304107cb9f42ccb0e1278405aa3eb6c9c/examples/summarization/bertabs/utils_summarization.py#L130
Hi,
Could you please take a look at this part of the codes? I think this part might not act the function to separate the sentences. The function doesn't actually ad... | {
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"I get the below error:\r\n\r\n```\r\nValidation sanity check: 0%| | 0/5 [00:00<?, ?it/s]Traceback (most recent call last):\r\n File \"run_pl_glue.py\", line 186, in <module>\r\n trainer = generic_tr... | 1,587 | 1,603 | 1,603 | 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:
* [x] the official example scripts: run_pl.sh (run_pl_glue.py)
The tasks I am working on is:
* [x] an official GLUE/SQUaD task: Glue
## To ... | {
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"It won't be that easy since some words will be split into multiple tokens so you have to make two forward passes. \r\n\r\nIf you limit your `original_word` to just one token words (you can check that simply with `len(tokenizer.encode(original_word))==1`. Then your idea here should work. \r\n\r\nIf not it's gonna ... | 1,587 | 1,593 | 1,593 | NONE | null | Hi,
I would like to calculate at which place correct word option lies in the top 5 predicted words from GPT-2 model?
For this purpose, I am using following code snippet:
```
subseq = "The car moves very" #sample sequence
orignal_word="fast"
sequence = tokenizer.encode(subseq, retur... | {
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] | 1,587 | 1,593 | 1,593 | NONE | null | @julien-c @patrickvonplaten
I want to pretrain a model from scratch by utilizing Google Cloud TPU offered in kaggle. I can train the model without TPU but I want to train it on a TPU. Any help will be much appreciated.
Also what options do I have, if there is no straight forward approach ? | {
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"Seems fixed now--delete transformers installed via pip and install by cloning this repo."
] | 1,587 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): AlbertForMaskedLM
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [X ] the official example scripts: (give details below)
* [X ] my own modified scripts: (give details below)
The tasks I am wor... | {
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"Never mind; this was an issue with the colab. It's sorted now."
] | 1,587 | 1,587 | 1,587 | NONE | null | A few months ago, I was able to run GPT2 on a Google Colab notebook. This was using the following script, which is based on the provided docs:
```
!git clone https://github.com/huggingface/transformers
%cd transformers
!pip install .
!pip install -r ./examples/requirements.txt
!python /content/transformers/ex... | {
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"I there any problem with this card?"
] | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3881 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3881/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3881/comments | https://api.github.com/repos/huggingface/transformers/issues/3881/events | https://github.com/huggingface/transformers/pull/3881 | 604,065,612 | MDExOlB1bGxSZXF1ZXN0NDA2NzI5NTMz | 3,881 | Fix Torch.hub + Integration test | {
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"(Hmm, GitHub was failing earlier today, and now it seems to have posted my comment multiple times. Sorry about that.)",
"See cbbb3c43c55d2d93a156fc80bd12f31ecbac8520"
] | 1,587 | 1,587 | 1,587 | MEMBER | null | - Torch.hub doesn't use pip-installed versions of modules, but uses a [custom importer instead](https://github.com/pytorch/pytorch/blob/master/torch/hub.py#L70-L83) (it imports `hubconf.py`) which means that:
- all imports from hubconf.py refer to src.transformers instead of transformers
- all imports inside the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3880 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3880/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3880/comments | https://api.github.com/repos/huggingface/transformers/issues/3880/events | https://github.com/huggingface/transformers/issues/3880 | 604,022,389 | MDU6SXNzdWU2MDQwMjIzODk= | 3,880 | Replace `config.output_attentions` parameter with function argument `output_attentions` | {
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"Hi, I would like to work on this issue.",
"That's great :-) Do you want to open a PR and do the changes analogous to PR: #3734 ? ",
"Is this still be worked on? If not, I'd be happy to make a first contribution here",
"First PR first serve ;-) Still an open issue",
"Any tips on how I should proceed? I was ... | 1,587 | 1,591 | 1,591 | MEMBER | null | # 🚀 Feature request
Currently the user has to decide whether the model should output the attentions when she/he creates the config of a model: config.output_attentions = True/False. It would be nice if the user can decide this when calling the models `forward()` / `call()` with a flag `output_attentions`. This shou... | {
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https://api.github.com/repos/huggingface/transformers/issues/3879 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3879/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3879/comments | https://api.github.com/repos/huggingface/transformers/issues/3879/events | https://github.com/huggingface/transformers/issues/3879 | 604,020,219 | MDU6SXNzdWU2MDQwMjAyMTk= | 3,879 | Replace `config.output_hidden_states` parameter with function argument `output_hidden_states` | {
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"Hi, @patrickvonplaten I want to take up this issue. Can I move forward with it? ",
"I think this could have side effects for libraries that use `config.output_hidden_states`, so I'm cc'ing @Timoeller and @brandenchan, because this parameter is used in [FARM](https://github.com/deepset-ai/FARM).",
"> Hi, @patri... | 1,587 | 1,595 | 1,595 | MEMBER | null | # 🚀 Feature request
Currently the user has to decide whether the model should output the hidden states when she/he creates the config of a model: `config.output_hidden_states = True/False`. It would be nice if the user can decide this when calling the models `forward()` / `call()` with a flag `output_hidden_states... | {
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https://api.github.com/repos/huggingface/transformers/issues/3878 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3878/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3878/comments | https://api.github.com/repos/huggingface/transformers/issues/3878/events | https://github.com/huggingface/transformers/issues/3878 | 603,976,902 | MDU6SXNzdWU2MDM5NzY5MDI= | 3,878 | When will ELECTRA pretraining from scratch will be available? | {
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"Working on it as we speak :).\r\n\r\nI'd say it will be out in a few weeks at most.",
"Is Albert pretraining from scratch is available? @LysandreJik \r\n",
"@LysandreJik do you think the update will be available by the end of the month ? Maybe it has been postponed due to the recent addition of the Trainer and... | 1,587 | 1,620 | 1,605 | 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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"Should be fixed on master, please share if it does/your results"
] | 1,587 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
## Information
I try to run the latest versions of the examples and got the error message(I have installed the main README mentioned procedure from source):
Traceback (most recent call last):
File "run_bertology.py", line 33, in <module>
from run_glue import ALL_MODELS, MODEL_CLASSES, load_and_c... | {
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"BART is used as a model for abstractive summarization so it can use different words than those used in the original text. But it should not go *off-topic*. You could use an extractive summarization model instead which does not generate new nouns. Also you might be interested in the methods from [*Controlling the A... | 1,587 | 1,593 | 1,593 | NONE | null | Currently BART model trained on CNN dataset is generating summaries which consist of new nouns which are not present in the input text.
How to control the randomness of these summaries. Is there any parameter like temperature in GPT-2 model which can control the degree to which the model can go off-topic?
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"Why do you use `decoder_start_token_id = tokenizer.eos_token_id` ? Is that stated in the examples somewhere? \r\n\r\nIf you do:\r\n```\r\nfrom transformers import T5Tokenizer, T5ForConditionalGeneration\r\ntokenizer = T5Tokenizer.from_pretrained('t5-base')\r\nmodel = T5ForConditionalGeneration.from_pretrained('t5-... | 1,587 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
## Information
Model I am using (T5-base):
Language I am using the model on (T5-base):
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
```
from transformers import T5Tokenizer, T5ForConditionalGenerat... | {
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"It is! (though ideally you would add an example of use + details about training)\r\n\r\nWill merge this unless you add more in the next 24 hours.",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3874?src=pr&el=h1) Report\n> Merging [#3874](https://codecov.io/gh/huggingface/transformers/pull/387... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | sorry, not sure if this is the right way to do this | {
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"I think you are correct. Any way you'd open a PR? Otherwise we'll get on it in the next few days/weeks"
] | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | # 🐛 Bug
## Information
I am running the GPT2 pytest and it fails to load in [PyTorch Glow](https://github.com/pytorch/glow) because the model calls _torch.pow()_ with an integer for the _exponent_ parameter.
Per the PyTorch documentation (https://pytorch.org/docs/master/torch.html?highlight=torch%20pow#torch.... | {
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https://api.github.com/repos/huggingface/transformers/issues/3872 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3872/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3872/comments | https://api.github.com/repos/huggingface/transformers/issues/3872/events | https://github.com/huggingface/transformers/issues/3872 | 603,593,929 | MDU6SXNzdWU2MDM1OTM5Mjk= | 3,872 | torchscript tests fail with RuntimeError: normal_ expects std > 0.0, but found std=0 | {
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## Information
I am running the gpt2 torchscript test from master and a call to _normal_()_ fails because the _std_ parameter is zero. The error is not limited to the GPT2 model.
## To reproduce
Steps to reproduce the behavior:
1. python -m pytest -v -k 'test_torchscript and not test_torchscri... | {
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https://api.github.com/repos/huggingface/transformers/issues/3871 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3871/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3871/comments | https://api.github.com/repos/huggingface/transformers/issues/3871/events | https://github.com/huggingface/transformers/issues/3871 | 603,581,467 | MDU6SXNzdWU2MDM1ODE0Njc= | 3,871 | Tokenizer could accept a string tensor | {
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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"
] | 1,587 | 1,593 | 1,593 | NONE | null | Currently, the [`batch_encode_plus`](https://huggingface.co/transformers/main_classes/tokenizer.html#transformers.PreTrainedTokenizer.batch_encode_plus) method from tokenizer, can return a Tensorflow tensor.
It can be done assigning `tf` to the optional parameter `return_tensors`.
It would be great if this method ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3870 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3870/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3870/comments | https://api.github.com/repos/huggingface/transformers/issues/3870/events | https://github.com/huggingface/transformers/issues/3870 | 603,579,780 | MDU6SXNzdWU2MDM1Nzk3ODA= | 3,870 | bert summarizer module import error | {
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"HELLO eeegnu, I'm also facing the same issue.\r\n\r\n**Environment Info :**\r\nPlatform: Windows 10 64bit\r\nPython version: 3.6.10\r\nPyTorch version (GPU?): 1.4.0 \r\nTensorflow version (GPU?): not inst... | 1,587 | 1,597 | 1,597 | NONE | null | # 🐛
Running bert summarizer ([run_summarization.py](https://github.com/huggingface/transformers/blob/master/examples/summarization/bertabs/run_summarization.py)) gives the following error
```
Traceback (most recent call last):
File "run_summarization.py", line 15, in <module>
from .utils_summarization im... | {
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https://api.github.com/repos/huggingface/transformers/issues/3869 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3869/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3869/comments | https://api.github.com/repos/huggingface/transformers/issues/3869/events | https://github.com/huggingface/transformers/issues/3869 | 603,479,766 | MDU6SXNzdWU2MDM0Nzk3NjY= | 3,869 | ImportError: cannot import name 'HfArgumentParser' from 'transformers' | {
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"Hi, \r\n\r\nAs mentioned [here](https://github.com/huggingface/transformers/tree/master/examples#examples) and in the main README you need to install from source in order to run the latest versions of the examples"
] | 1,587 | 1,587 | 1,587 | NONE | null | Hi,
I installed tokenizers-0.5.2 transformers-2.8.0.
When I try to run run_bertology.py in the example dir calling it with
export TASK_NAME=mnli
python ./run_bertology.py --data_dir $GLUE_DIR/$TASK_NAME
--model_name bert-base-uncased
--ta... | {
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https://api.github.com/repos/huggingface/transformers/issues/3868 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3868/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3868/comments | https://api.github.com/repos/huggingface/transformers/issues/3868/events | https://github.com/huggingface/transformers/issues/3868 | 603,410,942 | MDU6SXNzdWU2MDM0MTA5NDI= | 3,868 | unable to load model 'bert', tensor 'input_ids': the model expects 1 dimensions but the model configuration specified 2 dimensions | {
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"I'm assuming you read https://blog.einstein.ai/benchmarking-tensorrt-inference-server/ ?",
"> \r\n> \r\n> I'm assuming you read https://blog.einstein.ai/benchmarking-tensorrt-inference-server/ ?\r\nok: torch.jit.trace(bert)\r\nFailed :torch.jit.script\r\nFailed:torch.jit.trace(bert+after)\r\nFailed: to onnx: \r\... | 1,587 | 1,587 | 1,587 | 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/3867 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3867/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3867/comments | https://api.github.com/repos/huggingface/transformers/issues/3867/events | https://github.com/huggingface/transformers/issues/3867 | 603,382,590 | MDU6SXNzdWU2MDMzODI1OTA= | 3,867 | Tokenization issue with RoBERTa and DistilRoBERTa. | {
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">Furthermore, I am also curious about what these 'Ġ' characters are in the RoBERTa encoding?\r\n\r\nIt's a feature of byte-level BPE (an encoded space character)\r\n[Ref-bart-fairseq](https://github.com/pytorch/fairseq/issues/1716), [Ref-openai-gpt](https://github.com/openai/gpt-2/issues/80)",
"This issue has be... | 1,587 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
RoBERTa (roberta-base), DistilRoBERTa (distilroberta-base)
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... | {
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https://api.github.com/repos/huggingface/transformers/issues/3866 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3866/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3866/comments | https://api.github.com/repos/huggingface/transformers/issues/3866/events | https://github.com/huggingface/transformers/pull/3866 | 603,287,310 | MDExOlB1bGxSZXF1ZXN0NDA2MTAzMjAw | 3,866 | [examples] fix summarization do_predict | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3866?src=pr&el=h1) Report\n> Merging [#3866](https://codecov.io/gh/huggingface/transformers/pull/3866?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a21d4fa410dc3b4c62f93aa0e6bbe4b75a101ee9&el=desc) will **increase... | 1,587 | 1,590 | 1,587 | CONTRIBUTOR | null | - by copying NER
- add type hints | {
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https://api.github.com/repos/huggingface/transformers/issues/3865 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3865/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3865/comments | https://api.github.com/repos/huggingface/transformers/issues/3865/events | https://github.com/huggingface/transformers/issues/3865 | 603,223,777 | MDU6SXNzdWU2MDMyMjM3Nzc= | 3,865 | Summarisation tuning | {
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"Great, thanks @sshleifer ",
"(Duplicate of https://github.com/huggingface/transformers/issues/3853)\r\n",
"sorry, mentioned wrong issue"
] | 1,587 | 1,588 | 1,587 | CONTRIBUTOR | null | Hi everybody,
I’ve tried using BART summarisation code, and I had a question about finetune.py
Can SummarisationTrainer checkpoint be loaded as a BartForConditionalGeneration model from the evaluation script? | {
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https://api.github.com/repos/huggingface/transformers/issues/3864 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3864/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3864/comments | https://api.github.com/repos/huggingface/transformers/issues/3864/events | https://github.com/huggingface/transformers/pull/3864 | 603,131,626 | MDExOlB1bGxSZXF1ZXN0NDA1OTc3NDY0 | 3,864 | Add language and license information to model cards | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3864?src=pr&el=h1) Report\n> Merging [#3864](https://codecov.io/gh/huggingface/transformers/pull/3864?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a21d4fa410dc3b4c62f93aa0e6bbe4b75a101ee9&el=desc) will **increase... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Should fix issues #3397 and #3357 | {
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https://api.github.com/repos/huggingface/transformers/issues/3863 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3863/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3863/comments | https://api.github.com/repos/huggingface/transformers/issues/3863/events | https://github.com/huggingface/transformers/issues/3863 | 602,979,654 | MDU6SXNzdWU2MDI5Nzk2NTQ= | 3,863 | Cannot convert RoBERTa to tflite model | {
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"I believe this is because `tf.Cumsum` is not a supported operation and not an issue relating to this repo. Here is a link to the tensorflow documentation on supported ops. [https://www.tensorflow.org/lite/guide/ops_compatibility]\r\nIn the past, I've been able to get around unsupported ops by reimplementing the o... | 1,587 | 1,606 | 1,587 | NONE | null | # 🐛 Bug
## Information
Model I am using:
RoBERTa (roberta-base)
Language I am using the model on:
English
The problem arises when using:
Conversion based on https://github.com/huggingface/tflite-android-transformers/blob/master/models_generation/distilbert.py
The tasks I am working on is:
It is irre... | {
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https://api.github.com/repos/huggingface/transformers/issues/3862 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3862/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3862/comments | https://api.github.com/repos/huggingface/transformers/issues/3862/events | https://github.com/huggingface/transformers/pull/3862 | 602,888,730 | MDExOlB1bGxSZXF1ZXN0NDA1NzgzOTQ0 | 3,862 | New model added | {
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"Thanks! [model page](https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-english)",
"A few things to add to the model card if you can (happy to help!)\r\n\r\n- which language(s) is it trained on?\r\n- How can one use it, i.e. is this a sequence classifier? "
] | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | The first model added to the repo | {
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https://api.github.com/repos/huggingface/transformers/issues/3861 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3861/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3861/comments | https://api.github.com/repos/huggingface/transformers/issues/3861/events | https://github.com/huggingface/transformers/issues/3861 | 602,881,156 | MDU6SXNzdWU2MDI4ODExNTY= | 3,861 | How to do parameter sharing between two BERT models | {
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"You could do it very simply by passing the reference around:\r\n\r\n```py\r\nfrom transformers import BertModel\r\n\r\nmodel = BertModel.from_pretrained(\"bert-base-cased\")\r\nmodel2 = BertModel.from_pretrained(\"bert-base-cased\")\r\n\r\nmodel2.embeddings = model.embeddings\r\n\r\nprint(model2.embeddings.word_em... | 1,587 | 1,593 | 1,593 | NONE | null | # ❓ Questions & Help
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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/3860 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3860/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3860/comments | https://api.github.com/repos/huggingface/transformers/issues/3860/events | https://github.com/huggingface/transformers/pull/3860 | 602,779,094 | MDExOlB1bGxSZXF1ZXN0NDA1NzA1NjMz | 3,860 | Update README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3860?src=pr&el=h1) Report\n> Merging [#3860](https://codecov.io/gh/huggingface/transformers/pull/3860?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a21d4fa410dc3b4c62f93aa0e6bbe4b75a101ee9&el=desc) will **not chan... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | Improved results from new hardware | {
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https://api.github.com/repos/huggingface/transformers/issues/3859 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3859/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3859/comments | https://api.github.com/repos/huggingface/transformers/issues/3859/events | https://github.com/huggingface/transformers/issues/3859 | 602,762,083 | MDU6SXNzdWU2MDI3NjIwODM= | 3,859 | ValueError: Unable to set proper padding strategy as the tokenizer does not have a padding token. | {
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"\r\n",
"tokenizer.pad_token = 0",
"You have to set the pad_token_id yourself as it's stated in the error message ;-). I would recommend using the `eos_token_id` as the `pad_token_id` for GPT... | 1,587 | 1,603 | 1,588 | NONE | null | # ❓ Questions & Help
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"Hi! We run on K80 and V100 GPUs. Running the 1.5B params model was very costly and hard to maintain, so we're not running it anymore, however. It should run fine on a single V100/Titan RTX however.\r\n\r\nDid you have issues with the T4 GPU because of memory?",
"Thanks for you response. This is really beneficial... | 1,587 | 1,589 | 1,589 | NONE | null | Hi,
Your package is great and your demo is cool too. I was wondering what kind of hardware does it take to generate text with the large language models. I've had a difficult time running GPT-2 with 1.5B params on a Tesla T4 GPU.
Any pointers will be greatly appreciated.
Thanks in advance,
Barak | {
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https://api.github.com/repos/huggingface/transformers/issues/3857 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3857/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3857/comments | https://api.github.com/repos/huggingface/transformers/issues/3857/events | https://github.com/huggingface/transformers/pull/3857 | 602,704,576 | MDExOlB1bGxSZXF1ZXN0NDA1NjU3Njcx | 3,857 | [Pipelines] Encode to max length of input not max length of tokenizer for batch input | {
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"Update: rm'ed inaccurate comment"
] | 1,587 | 1,588 | 1,587 | MEMBER | null | I don't see a reason why we have to pad to `tokenizer.max_length` when encoding. Tokenizers automatically encode until the longest `input_ids` which is much more efficient IMO. | {
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https://api.github.com/repos/huggingface/transformers/issues/3856 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3856/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3856/comments | https://api.github.com/repos/huggingface/transformers/issues/3856/events | https://github.com/huggingface/transformers/issues/3856 | 602,686,416 | MDU6SXNzdWU2MDI2ODY0MTY= | 3,856 | Bug in optimization_tf create_optimizer | {
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"I have raised https://github.com/huggingface/transformers/pull/4940, waiting for approval.",
"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"
] | 1,587 | 1,597 | 1,597 | CONTRIBUTOR | null | # 🐛 Bug
## Information
WHEN I am using optimization_tf(create_optimizer):
Problems with learning rate schedule
## To reproduce
```
from transformers.optimization_tf import create_optimizer
import matplotlib.pyplot as plt
%matplotlib inline
opt = create_optimizer(init_lr=5e-5, num_train_steps=100, num_warm... | {
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https://api.github.com/repos/huggingface/transformers/issues/3855 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3855/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3855/comments | https://api.github.com/repos/huggingface/transformers/issues/3855/events | https://github.com/huggingface/transformers/pull/3855 | 602,681,067 | MDExOlB1bGxSZXF1ZXN0NDA1NjQxNzgz | 3,855 | Fix Documentation issue in BertForMaskedLM forward | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3855?src=pr&el=h1) Report\n> Merging [#3855](https://codecov.io/gh/huggingface/transformers/pull/3855?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a21d4fa410dc3b4c62f93aa0e6bbe4b75a101ee9&el=desc) will **increase... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | Fix #3066 by interchanging positions of `ltr_lm_loss` and `masked_lm_loss` | {
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https://api.github.com/repos/huggingface/transformers/issues/3854 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3854/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3854/comments | https://api.github.com/repos/huggingface/transformers/issues/3854/events | https://github.com/huggingface/transformers/pull/3854 | 602,661,527 | MDExOlB1bGxSZXF1ZXN0NDA1NjI4NjMx | 3,854 | Added electra-bahasa README | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3854?src=pr&el=h1) Report\n> Merging [#3854](https://codecov.io/gh/huggingface/transformers/pull/3854?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a21d4fa410dc3b4c62f93aa0e6bbe4b75a101ee9&el=desc) will **increase... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | {
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"Facing a similar type of issue for T5. @sshleifer ",
"The last ckpt file should be loaded into a `pl.LightningModule` if the --do_predict flag is specified.\r\n\r\nThere is a bug on master that messes up the loading, but it's fixed in #3866\r\n\r\nTo use that code immediately, you can run:\r\n```\r\ngit fetch\r\... | 1,587 | 1,612 | 1,597 | NONE | null | # ❓ Questions & Help
## Details
I fine-tuned the BART model on a custom summarization dataset using the **transformers/examples/summarization/bart/finetune.py** and **transformers/examples/summarization/bart/run_train.sh** files in the repository for training (which generated three _checkpointepoch=*.ckpt_ files) a... | {
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"From what I'm seeing, the `TFT5Model` **does** have [documentation](https://huggingface.co/transformers/model_doc/t5.html#transformers.TFT5Model.get_input_embeddings) for `get_input_embeddings` and `get_output_embeddings`.\r\n\r\nI believe the output embeddings and input embeddings should actually be the same. The... | 1,587 | 1,661 | 1,591 | CONTRIBUTOR | null | In class TFT5Model
1. The get_input_embeddings() and get_output_embeddings() methods do not have any documentation provided in them
2. Furthermore, the get_output_embeddings provides the same output as the get_input embeddings. This needs to be resolved. Or flagged with a NotImplementedError | {
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https://api.github.com/repos/huggingface/transformers/issues/3851 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3851/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3851/comments | https://api.github.com/repos/huggingface/transformers/issues/3851/events | https://github.com/huggingface/transformers/issues/3851 | 602,529,109 | MDU6SXNzdWU2MDI1MjkxMDk= | 3,851 | How properly apply a tokenizer map function to a Tensorflow batched dataset? | {
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"This seems like more of a TF-related question rather than a Transformers-related question. The issue seems to stem from your code trying to get the value of a tensor which is not eager, using numpy. I believe the `tf.data.Dataset.map` method must trace inputs, resulting in the Tensors not being eager.\r\n\r\nCould... | 1,587 | 1,639 | 1,591 | NONE | null | Considering the following `batched_dataset`:
```python3
samples = ([{"query": "this is a query 1", "doc": "this is one relevant document regarding query 1"},
{"query": "this is a query 2", "doc": "this is one relevant document regarding query 2"},
{"query": "this is a query 3", "doc"... | {
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https://api.github.com/repos/huggingface/transformers/issues/3850 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3850/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3850/comments | https://api.github.com/repos/huggingface/transformers/issues/3850/events | https://github.com/huggingface/transformers/issues/3850 | 602,484,854 | MDU6SXNzdWU2MDI0ODQ4NTQ= | 3,850 | 'pad_to_max_length' in Pipeline should be set to True by default | {
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"Hi @Akashdesarda, thanks for reporting this.\r\nYou should be able to pass `pad_to_max_length=True` when calling your pipeline: \r\n\r\n`pipe(train_data['comment_text'][:100].values.tolist(), pad_to_max_length=True)`\r\n\r\nCan you let us know if it works in your case ?\r\n",
"Yes it worked, thanks for the solut... | 1,587 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
pad_to_max_length is set by default False in Piplene class' _parse_and_tokenize() function
## Information
Model I am using (Bert):
Language I am using the model on (English):
The problem arises when using: my own modified scripts:
```
import numpy as np
from transformers import AutoTokenizer, pi... | {
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"You need to install from source as specified in the README."
] | 1,587 | 1,587 | 1,587 | NONE | null | Hi
I am getting this error when running run_glue.py
ImportError: cannot import name 'TrainingArguments' from 'transformers' (/idiap/user/rkarimi/libs/anaconda3/envs/iborn/lib/python3.7/site-packages/transformers/__init__.py)
Traceback (most recent call last):
File "run_glue.py", line 34, in <module>
fro... | {
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https://api.github.com/repos/huggingface/transformers/issues/3848 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3848/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3848/comments | https://api.github.com/repos/huggingface/transformers/issues/3848/events | https://github.com/huggingface/transformers/issues/3848 | 602,359,819 | MDU6SXNzdWU2MDIzNTk4MTk= | 3,848 | Electra for question answering | {
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"You can basically copy+paste the code from BertForQuestionAnswering and just change it for ELECTRA. However, the original ELECTRA implementation to fine-tune on squad looks a bit different (it's more like in XLNet). \r\n\r\nIf you want to reproduce the official implementation it's probably best you take a look at ... | 1,587 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🚀 Feature request
Electra for question answering
## Motivation
Electra is the highest rated single model (non essemble) on the Squad leaderboard
## Your contribution
I am not sure if I have the skills, but I'm willing to take a crack at it! Looking the other QA architectures, it seems that I'll need t... | {
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https://api.github.com/repos/huggingface/transformers/issues/3847 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3847/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3847/comments | https://api.github.com/repos/huggingface/transformers/issues/3847/events | https://github.com/huggingface/transformers/issues/3847 | 602,246,881 | MDU6SXNzdWU2MDIyNDY4ODE= | 3,847 | Share more details on fine-tuning GPT-2 on WikiText-2 ? | {
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"@xihui-wu To get the hyperparameters specific to the model (in this case `gpt2`), you can check the config file of `gpt2` with the code below:\r\n\r\n```\r\nfrom transformers import GPT2Config\r\nprint(GPT2Config())\r\n```\r\n\r\nSome higher level hyperparameters are still not included here (e.g. \"epochs\"). Thes... | 1,587 | 1,605 | 1,598 | NONE | null | Hello! Regarding https://github.com/huggingface/transformers/tree/master/examples#gpt-2gpt-and-causal-language-modeling, would you mind sharing what hyper-parameters you use to get this result ? How many epochs, what's the batch size? etc... | {
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"For anyone coming across this issue, you can disable all such transformations in `decode` by passing `clean_up_tokenization_spaces=False`. However, I maintain that this decoding behavior is not a sensible default.",
"fixed with #4024 "
] | 1,587 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Roberta
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
... | {
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"Hi, have you fixed this error? I just got the same error. Any help will be grateful!",
"Hi, I have already fixed it. I made a mistake on tsv files. After converting them to correct format by using LibreOffice, glue.py ran correctly. \r\nI hope this could help you!",
"Thanks! I fixed this error. There were some... | 1,587 | 1,590 | 1,587 | NONE | null | Hi, I am new to transformers, and I got a list index out of range error when I execute a command for examples/run_glue.py.
I want to do Fine-Turning to classify Japanese words, and I modified some files following a web site.
**The process was:**
**1. I used these commands below to install transformers and to u... | {
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"Merging this, though it will be rendered obsolete (for a subset of the script initially) by #3800 "
] | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | This bug is present in several scripts in `examples`:
* `examples/run_language_modeling.py`
* `examples/run_multiple_choice.py`
* `examples/run_xnli.py`
* `examples/ner/run_ner.py`
* `examples/mm-imdb/run_mmimdb.py`
* `examples/hans/test_hans.py`
The problem is exactly the same as it was in #1801 and in #1504:... | {
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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"
] | 1,587 | 1,592 | 1,592 | NONE | null | # ❓ Questions & Help
Hello all,
first of all, thanks for the library that is very helpful. There have been several discussions regarding XLM-Roberta and questions answering (#3732 #3694 ). On my side, I added a TFXLMRobertaForQuestionAnswering but never reproduced a decent squad score (I was always below 50% f1... | {
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https://api.github.com/repos/huggingface/transformers/issues/3840 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3840/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3840/comments | https://api.github.com/repos/huggingface/transformers/issues/3840/events | https://github.com/huggingface/transformers/issues/3840 | 601,912,906 | MDU6SXNzdWU2MDE5MTI5MDY= | 3,840 | Decoding predictions for masked language modeling task using custom BPE | {
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"Maybe @mfuntowicz ? :-) ",
"Bump",
"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"
] | 1,587 | 1,593 | 1,593 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
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https://api.github.com/repos/huggingface/transformers/issues/3839 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3839/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3839/comments | https://api.github.com/repos/huggingface/transformers/issues/3839/events | https://github.com/huggingface/transformers/issues/3839 | 601,746,519 | MDU6SXNzdWU2MDE3NDY1MTk= | 3,839 | Different output encode and encode_plus | {
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"I made a mistake in my code. The output is the same."
] | 1,587 | 1,587 | 1,587 | NONE | null | Hi everyone,
I'm struggling with the following scenario:
I have the following input:
```
sentence = "Sheldon : If a photon is directed through a plane with two slits in it and either is observed . Sheldon : . it will not go through both . If unobserved , it will . UNKNAME : If it 's observed after it left the... | {
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https://api.github.com/repos/huggingface/transformers/issues/3838 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3838/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3838/comments | https://api.github.com/repos/huggingface/transformers/issues/3838/events | https://github.com/huggingface/transformers/issues/3838 | 601,711,222 | MDU6SXNzdWU2MDE3MTEyMjI= | 3,838 | Cutom tokenizer not loaded in AutoTokenizer | {
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"If it's a BPETokenizer, you can load it with `RobertaTokenizer.from_pretrained(\"vocab.json\", \"merges.json\")`",
"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"
] | 1,587 | 1,592 | 1,592 | NONE | null | I am training a language model from scratch. I trained **ByteLevelBPETokenizer** and then when I am trying to load this tokenizer using **AutoTokenizer**, it is giving me the following error.
OSError: Model name './MyRobertaConfig/' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3837 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3837/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3837/comments | https://api.github.com/repos/huggingface/transformers/issues/3837/events | https://github.com/huggingface/transformers/pull/3837 | 601,694,215 | MDExOlB1bGxSZXF1ZXN0NDA0OTE1NTMx | 3,837 | PretrainedTokenizer cleanup: Typehints, decode_batch | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3837?src=pr&el=h1) Report\n> Merging [#3837](https://codecov.io/gh/huggingface/transformers/pull/3837?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f399c00610506325bc1690f0e68c6885e73395ec&el=desc) will **decrease... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | This is very very minor cleanup
- adds `decode_batch` which calls `.decode` on every entry in a list.
- A few cosmetic changes to tokenization_utils.py (type hints using defaultdict)
- adds type hints in files I touched. | {
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https://api.github.com/repos/huggingface/transformers/issues/3836 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3836/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3836/comments | https://api.github.com/repos/huggingface/transformers/issues/3836/events | https://github.com/huggingface/transformers/pull/3836 | 601,656,875 | MDExOlB1bGxSZXF1ZXN0NDA0ODg2MjAw | 3,836 | Update camembert-base-README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3836?src=pr&el=h1) Report\n> Merging [#3836](https://codecov.io/gh/huggingface/transformers/pull/3836?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f0c96fafd16d206b22a74fe76b251414f7314703&el=desc) will **increase... | 1,587 | 1,588 | 1,587 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3835 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3835/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3835/comments | https://api.github.com/repos/huggingface/transformers/issues/3835/events | https://github.com/huggingface/transformers/issues/3835 | 601,435,600 | MDU6SXNzdWU2MDE0MzU2MDA= | 3,835 | Transfo-XL cannot generate long texts. Using run_generation.py to generate texts | {
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"What is the error?",
"So, first, it does not generate long texts. It usually generates texts with\nabout 10 tokens. And I think it is because of the warning:\nWARNING - transformers.modeling_utils - Setting `pad_token_id` to 0 (first\n`eos_token_id`) to generate sequence\n\nOther generators in run_generation.py ... | 1,587 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
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https://api.github.com/repos/huggingface/transformers/issues/3834 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3834/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3834/comments | https://api.github.com/repos/huggingface/transformers/issues/3834/events | https://github.com/huggingface/transformers/issues/3834 | 601,381,666 | MDU6SXNzdWU2MDEzODE2NjY= | 3,834 | i want help to create saved model(.pth) from Pytorch Dump(pytorch_model.bin) if possible! | {
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"i used `transformers-cli convert` to make `python_model.bin` from checkpoints",
"Did you try to put in in quotes? If you have a model you should do `torch.save(model.state_dict(), PATH)`.\r\n\r\nPlease take a look at the [PyTorch documentation](https://pytorch.org/tutorials/beginner/saving_loading_models.html). ... | 1,587 | 1,587 | 1,587 | NONE | null | i have, PROJECT(folder)
├── pytorch_model.bin
├── bert_config.json
└── vocab.txt
i tried saving it with
`torch.save( pytorch_model.bin , PATH)`
but came with error
`-bash: syntax error near unexpected token `pytorch_model.bin,'`
what am i ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3833 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3833/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3833/comments | https://api.github.com/repos/huggingface/transformers/issues/3833/events | https://github.com/huggingface/transformers/pull/3833 | 601,245,894 | MDExOlB1bGxSZXF1ZXN0NDA0NTM0NDY3 | 3,833 | Remove tqdm logging when using pipelines. | {
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Introduce `tqdm_enabled` parameter on `squad_convert_examples_to_features()` default to `True` and set to `False` in QA pipelines. | {
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https://api.github.com/repos/huggingface/transformers/issues/3832 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3832/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3832/comments | https://api.github.com/repos/huggingface/transformers/issues/3832/events | https://github.com/huggingface/transformers/issues/3832 | 601,244,776 | MDU6SXNzdWU2MDEyNDQ3NzY= | 3,832 | The issue I met when do the NER task for Universal language by using XLM-R | {
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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"
] | 1,587 | 1,592 | 1,592 | NONE | null | # ❓ Questions & Help
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https://api.github.com/repos/huggingface/transformers/issues/3831 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3831/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3831/comments | https://api.github.com/repos/huggingface/transformers/issues/3831/events | https://github.com/huggingface/transformers/issues/3831 | 601,224,342 | MDU6SXNzdWU2MDEyMjQzNDI= | 3,831 | AlbertModel output is not HalfTensor when using apex fp16 | {
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"Hi @rasoolims, \r\n\r\nThis seems correct. Basically, using `opt_level=\"O1\"` means apex will add some downcasting to `float16` from a set of whitelisted operations, such as GEMM or Conv. This way, these operations will benefit from using Tensor Cores on latest devices, achieving higher throughput.. \r\n\r\nIn th... | 1,587 | 1,593 | 1,587 | NONE | null | # 🐛 Bug
Despite the fact that I turned the model to fp16 with apex, the hidden representation output is not half tensor (see code snippet for details) while class heads are half tensors.
## Information
Model I am using AlbertModel.
Language I am using the model on arbitrary:
The problem arises when using:... | {
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https://api.github.com/repos/huggingface/transformers/issues/3830 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3830/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3830/comments | https://api.github.com/repos/huggingface/transformers/issues/3830/events | https://github.com/huggingface/transformers/issues/3830 | 601,196,542 | MDU6SXNzdWU2MDExOTY1NDI= | 3,830 | Faster mask computation | {
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"Hi @rasoolims ,\r\n\r\nThat sounds reasonable what you are saying! I wanted to take a look into masking optimization in a couple of weeks. If you feel like it, you could also open a PR and we take a look together :-) ",
"Feel free to open a PR for this :-) Closing for now"
] | 1,587 | 1,591 | 1,591 | NONE | null | # 🚀 Feature request
Currently, the masking is done using the full prediction matrix which is both memory and computation inefficient. One example is in [here](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_albert.py#L675). I think with Pytorch indexing, first and foremost, we don'... | {
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https://api.github.com/repos/huggingface/transformers/issues/3829 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3829/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3829/comments | https://api.github.com/repos/huggingface/transformers/issues/3829/events | https://github.com/huggingface/transformers/issues/3829 | 601,180,126 | MDU6SXNzdWU2MDExODAxMjY= | 3,829 | Can't install transformers in conda environment | {
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"Looking at the error message, you seem to be running into an error with the sentencepiece package, not transformers.\r\n\r\nI looked at the sentencepiece GitHub repo and there is an open issue on this here:\r\nhttps://github.com/google/sentencepiece/issues/452",
"Looks like this issue can be closed now. @chen-bo... | 1,587 | 1,603 | 1,596 | NONE | null | # 🐛 Bug
I tried to install transformers into a conda environment
```
pip install transformers
Collecting transformers
Using cached transformers-2.8.0-py3-none-any.whl (563 kB)
Collecting tokenizers==0.5.2
Downloading tokenizers-0.5.2-cp38-cp38-macosx_10_15_x86_64.whl (1.1 MB)
|████████████████████... | {
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https://api.github.com/repos/huggingface/transformers/issues/3828 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3828/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3828/comments | https://api.github.com/repos/huggingface/transformers/issues/3828/events | https://github.com/huggingface/transformers/pull/3828 | 601,164,041 | MDExOlB1bGxSZXF1ZXN0NDA0NDYzOTg5 | 3,828 | Tanh torch warnings | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3828?src=pr&el=h1) Report\n> Merging [#3828](https://codecov.io/gh/huggingface/transformers/pull/3828?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b1e2368b32f3af88a920dac47cfc02a869409b20&el=desc) will **not chan... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | This pull request the warning generated by using torch.nn.functional.tanh (which is deprecated). This pull request changes it to torch.tanh to remove the warning. | {
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https://api.github.com/repos/huggingface/transformers/issues/3827 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3827/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3827/comments | https://api.github.com/repos/huggingface/transformers/issues/3827/events | https://github.com/huggingface/transformers/issues/3827 | 601,133,560 | MDU6SXNzdWU2MDExMzM1NjA= | 3,827 | ModuleNotFoundError: No module named '__main__.utils_summarization'; '__main__' is not a package | {
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"closing the issue \r\nchanged the from `.utils_summarization import ( `\r\nto ` from utils_summarization import ( `\r\nin run_summarization.py\r\nand solved the issue "
] | 1,587 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
## Information
I am using ./examples/summarization/bertabs/
`python run_summarization.py \
--documents_dir $data_dir\
--summaries_output_dir$output_dir \
--no_cuda true \
--batch_size 4 \
--min_length 50 \
--max_length 200 \
--beam_size 5 \
--alpha 0.95 \
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/3826 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3826/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3826/comments | https://api.github.com/repos/huggingface/transformers/issues/3826/events | https://github.com/huggingface/transformers/issues/3826 | 601,129,719 | MDU6SXNzdWU2MDExMjk3MTk= | 3,826 | [readability] consolidate examples/summarization/bart and examples/summarization/t5 | {
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"Hey @sshleifer !\r\nI would like to work on the issue. It's my first issue so I appreciate any help!",
"Awesome, helpful command to get quick feedback on whether your change is working:\r\n\r\n```bash\r\npytest --tb=short -p no:warnings examples/summarization/bart\r\n```\r\n\r\nMake sure you tag @sshleifer when ... | 1,587 | 1,591 | 1,591 | CONTRIBUTOR | null | This involves
- [ ] consolidating README.md
- [ ] consolidating evaluate_cnn.py scripts.
- [ ] evaluate_wmt.py should also work
- [ ] consolidating unittests
- [ ] updating bash scripts
- [ ] checking that consolidated stuff works, adding appropriate test coverage.
the resulting code should probably ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3825 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3825/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3825/comments | https://api.github.com/repos/huggingface/transformers/issues/3825/events | https://github.com/huggingface/transformers/issues/3825 | 601,125,823 | MDU6SXNzdWU2MDExMjU4MjM= | 3,825 | [readability] Consolidate prune_heads logic to PretrainedModel. | {
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"Hi @sshleifer , \r\nI am new to opensource and would like to help out with this issue. Could you please point me to some guide to setting up the project locally.\r\nThanks.",
"I got the contributing.md file. Thanks anyways. :)",
"Hi @sshleifer \r\nI am looking for a contribution. Is the issue is still open?\r\... | 1,587 | 1,594 | 1,594 | CONTRIBUTOR | null | Many models have identical implementations of `prune_heads` it would be nice to store that implementation as a method on `PretrainedModel` and reduce the redundancy. | {
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https://api.github.com/repos/huggingface/transformers/issues/3824 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3824/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3824/comments | https://api.github.com/repos/huggingface/transformers/issues/3824/events | https://github.com/huggingface/transformers/pull/3824 | 601,121,396 | MDExOlB1bGxSZXF1ZXN0NDA0NDI3Mjc2 | 3,824 | [examples] summarization/bart/finetune.py supports t5 | {
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"Super! LGTM",
"Thanks @sshleifer for the quick fix. Just a small query where it will save the output sentences. A file is generated in output_dir with only losses specified when --do_predict is passed in Argument.\r\nWhat if I want to generate for unknown inputs using fine-tuned model."
] | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | - we were passing attention_mask as an arg, not a kwarg, causing `test_step` to break.
- That case is now covered in the unittest, unittests also cover the t5 model.
- renamed run_bart_sum.py to finetune.py since it is model agnostic.
- The `bart/` and `t5` subdirectories should be consolidated in a future PR.
T... | {
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https://api.github.com/repos/huggingface/transformers/issues/3823 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3823/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3823/comments | https://api.github.com/repos/huggingface/transformers/issues/3823/events | https://github.com/huggingface/transformers/issues/3823 | 601,070,523 | MDU6SXNzdWU2MDEwNzA1MjM= | 3,823 | lowercasing on LM with cased models | {
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"Unfortunately, this is because these models didn't get uploaded with the `tokenizer_config.json` specifying they shouldn't be lowercased.\r\n\r\ncc @julien-c ",
"I see. Thanks for the explanation. I think it would be helpful to mention that in the instruction or somewhere for newbies like me though. They may ove... | 1,587 | 1,593 | 1,593 | 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:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3822 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3822/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3822/comments | https://api.github.com/repos/huggingface/transformers/issues/3822/events | https://github.com/huggingface/transformers/issues/3822 | 601,065,394 | MDU6SXNzdWU2MDEwNjUzOTQ= | 3,822 | getting random results when running run_glue | {
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"Hi\r\nAny comment on this? I also tested with these versions, run_glue with BERT gets fully random results. Like this I cannot run experiments, could you please have a look?\r\n \r\npython 3.6.9 h265db76_0 \r\npytorch 1.2.0 py3.6_cuda10.0.130_cudnn7.6... | 1,587 | 1,592 | 1,592 | NONE | null | Hi
I am running run_glue.py script on RTE dataset with BERT base model, on different gpus and I am getting very random results, like changing a lot by changing the gpu. I am using python 3.6 and transformer version 2.5.0. I tried with two gpu types like
Kepler , GTX1080ti and P40, ...
such randomness really affects... | {
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https://api.github.com/repos/huggingface/transformers/issues/3821 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3821/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3821/comments | https://api.github.com/repos/huggingface/transformers/issues/3821/events | https://github.com/huggingface/transformers/pull/3821 | 601,027,248 | MDExOlB1bGxSZXF1ZXN0NDA0MzQ4MDI0 | 3,821 | Typo fix | {
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https://api.github.com/repos/huggingface/transformers/issues/3820 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3820/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3820/comments | https://api.github.com/repos/huggingface/transformers/issues/3820/events | https://github.com/huggingface/transformers/pull/3820 | 600,995,719 | MDExOlB1bGxSZXF1ZXN0NDA0MzIxNTMx | 3,820 | #3787 Fixing the pip install issue by installing from git | {
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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"
] | 1,587 | 1,594 | 1,594 | CONTRIBUTOR | null | #3787 | {
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https://api.github.com/repos/huggingface/transformers/issues/3819 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3819/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3819/comments | https://api.github.com/repos/huggingface/transformers/issues/3819/events | https://github.com/huggingface/transformers/issues/3819 | 600,871,020 | MDU6SXNzdWU2MDA4NzEwMjA= | 3,819 | Tokenizers Notebook Issue | {
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"pip version of installation has a problem, dependencies are not defined so it installs tokenizers-0.5.2 with transformers 2.8.0. \r\nDownload from source and don't care warning of dependency, works fine :) "
] | 1,587 | 1,587 | 1,587 | 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/3818 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3818/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3818/comments | https://api.github.com/repos/huggingface/transformers/issues/3818/events | https://github.com/huggingface/transformers/issues/3818 | 600,849,737 | MDU6SXNzdWU2MDA4NDk3Mzc= | 3,818 | What are the GPU RAM requirements of popular models? | {
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"Hi @r0levrai,\r\n\r\nGood question! We are actually thinking about a good visualization for exactly that. Maybe in 2,3 weeks :-) \r\n\r\nWe already have a very useful script to test RAM requirements which you can find here: \r\n`https://github.com/huggingface/transformers/blob/master/examples/benchmarks.py`",
"I... | 1,587 | 1,661 | 1,587 | NONE | null | # ❓ Questions & Help
What are the GPU RAM requirement of `gpt2`, `gpt2-medium`, `distilgpt2`, `bert-base-uncased` and/or `distilroberta-base`
* for training?
* for inference?
Additionally, how do you calculate or find this information for other models?
original StackOverflow question: https://stackoverflow... | {
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https://api.github.com/repos/huggingface/transformers/issues/3817 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3817/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3817/comments | https://api.github.com/repos/huggingface/transformers/issues/3817/events | https://github.com/huggingface/transformers/pull/3817 | 600,815,036 | MDExOlB1bGxSZXF1ZXN0NDA0MTcyMzA1 | 3,817 | [Examples, T5] Change newstest2013 to newstest2014 and clean up | {
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https://api.github.com/repos/huggingface/transformers/issues/3816 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3816/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3816/comments | https://api.github.com/repos/huggingface/transformers/issues/3816/events | https://github.com/huggingface/transformers/issues/3816 | 600,788,894 | MDU6SXNzdWU2MDA3ODg4OTQ= | 3,816 | Aborted (core dumped) or Kernel dies | {
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"Do you mind showing us the lines that crash? Do you have a reproducible example?",
"+1. @yashwatwani do you have resolved it? I have the same problem too.\r\n\r\nIf I install transformers 2.8.0, it will produce error:\r\n```\r\n[1] 11267 segmentation fault (core dumped) PYTHONPATH=. python apps/absa/main.py\... | 1,587 | 1,597 | 1,597 | NONE | null | Whenever I am trying to import tranfomers my kernel dies off in jupyter notebook .
tranformer version - 2.8.0
python version -3.7.7
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https://api.github.com/repos/huggingface/transformers/issues/3815 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3815/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3815/comments | https://api.github.com/repos/huggingface/transformers/issues/3815/events | https://github.com/huggingface/transformers/issues/3815 | 600,764,359 | MDU6SXNzdWU2MDA3NjQzNTk= | 3,815 | How to speed up getting answers? | {
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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"
] | 1,587 | 1,592 | 1,592 | NONE | null | Hi ,
I'm facing the issues using BertForQuestionAnswering ,can you please help me fixing these:
1. I'm trying to use BertForQuestionAnswering pretrained model to get answers from news,
answer_question is the function where in you pass the context and the question and get the relevant answers,but if I have 100 co... | {
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https://api.github.com/repos/huggingface/transformers/issues/3814 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3814/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3814/comments | https://api.github.com/repos/huggingface/transformers/issues/3814/events | https://github.com/huggingface/transformers/issues/3814 | 600,642,093 | MDU6SXNzdWU2MDA2NDIwOTM= | 3,814 | A bug in the padding of input examples in the NER fine-tuning example | {
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"This PR https://github.com/huggingface/transformers/pull/3803 might be related to the bug but my initial thought is that it will not fix it.",
"Hello! Why do you think it should return 3 for RoBERTa models?\r\n\r\nIt should return 2, single sequences for RoBERTa are built like: \r\n\r\n`<s> tok_0 ... tok_n </s>`... | 1,586 | 1,594 | 1,594 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Roberta
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [X] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3813 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3813/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3813/comments | https://api.github.com/repos/huggingface/transformers/issues/3813/events | https://github.com/huggingface/transformers/issues/3813 | 600,622,906 | MDU6SXNzdWU2MDA2MjI5MDY= | 3,813 | T5 prediction using fine-tuned model | {
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"@sshleifer @patrickvonplaten ",
"Hi, I am curious about how you fine-tined T5. Did you used the run_bart_sum.py script by changing the model type from bart to T5? Thanks!",
"@sshleifer - could you take a look at this if you find some time? `T5` should more or less work out-of-the-box with the `run_bart_sum` sc... | 1,586 | 1,587 | 1,587 | NONE | null | After fine-tuning the T5 model on my own dataset, when I use the fine-tuned model to predict for test set using the following command:
python '/content/transformers-master/examples/summarization/bart/run_bart_sum.py' --data_dir='/content/drive/My Drive/two_keywords/' --model_type=t5 --output_dir=/content/t5 --do_pre... | {
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