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https://api.github.com/repos/huggingface/transformers/issues/8521 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8521/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8521/comments | https://api.github.com/repos/huggingface/transformers/issues/8521/events | https://github.com/huggingface/transformers/issues/8521 | 742,481,553 | MDU6SXNzdWU3NDI0ODE1NTM= | 8,521 | Tagged versions of model in new model hub don't work | {
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"Looking into it right now (cc @Pierrci)",
"looks like we were supporting lightweight tags but not annotated ones. ",
"Should be fixed: https://huggingface.co/deepset/roberta-base-squad2/tree/v2.0",
"That fixed the problem! Thanks very much",
"Thanks, and please keep the feedback coming! <3"
] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | Our model, deepset/roberta-base-squad2 was originally uploaded under the old style model hub.
I have committed a new version of the deepset/roberta-base-squad2 model onto the model hub using the new git based system introduced in transformers 3.5.0. I have 2 tags (v1.0 and v2.0) that I have also pushed to the repo. ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8520 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8520/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8520/comments | https://api.github.com/repos/huggingface/transformers/issues/8520/events | https://github.com/huggingface/transformers/pull/8520 | 742,465,173 | MDExOlB1bGxSZXF1ZXN0NTIwNTk0MDk0 | 8,520 | Model sharing doc: more tweaks | {
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"feel free to merge this when it's a good time!"
] | 1,605 | 1,605 | 1,605 | MEMBER | null | cc @Pierrci | {
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https://api.github.com/repos/huggingface/transformers/issues/8519 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8519/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8519/comments | https://api.github.com/repos/huggingface/transformers/issues/8519/events | https://github.com/huggingface/transformers/issues/8519 | 742,402,860 | MDU6SXNzdWU3NDI0MDI4NjA= | 8,519 | MLflowCallback to log run_name argument | {
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"Please don't hesitate to suggest a PR, `run_name` is there just for this reason!",
"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",
"It will be useful to have this, and it will organ... | 1,605 | 1,643 | 1,611 | NONE | null | # 🚀 Feature request
When using the MLflowCallback (set as default for Trainer), I would like to log the `run_name` argument passed to TrainingArguments as the Run Name on the MLflow dashboard. Currently runs are being logged as nameless.
E.g. see below.
![Screenshot 2020-11-13 at 10 29 32](https://user-images.git... | {
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https://api.github.com/repos/huggingface/transformers/issues/8518 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8518/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8518/comments | https://api.github.com/repos/huggingface/transformers/issues/8518/events | https://github.com/huggingface/transformers/pull/8518 | 742,388,374 | MDExOlB1bGxSZXF1ZXN0NTIwNTI5OTY2 | 8,518 | [T5] Bug correction & Refactor | {
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"I have tested both \"refactor_t5\" and \"major_t5_refactor\" branches using \"T5ForConditionalGeneration\".\r\n\r\nI didn't re-convert the Tensorflow to Pytorch, since you already told me the conversion process is not the problem.\r\n\r\nDoesn't seem it solved our issue yet, but it gives different rubbish output. ... | 1,605 | 1,620 | 1,605 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/8517 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8517/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8517/comments | https://api.github.com/repos/huggingface/transformers/issues/8517/events | https://github.com/huggingface/transformers/issues/8517 | 742,321,290 | MDU6SXNzdWU3NDIzMjEyOTA= | 8,517 | XLM-RoBERTa tokenizer changes characters during tokenization | {
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"Hi, this is unfortunately a limit of this tokenizer. We try to stay as close as possible to the original implementation, so we will not be able to change this behavior.",
"I see. Well, it's not a big deal, as the characters it replaces are quite rare and not really important, at least not for my application. So,... | 1,605 | 1,605 | 1,605 | NONE | null | I'm using `transformers` 3.5.0.
Whenever the XLM-RoBERTa tokenizer encounters some characters such as '²' (super-script 2, `ord('²')` is 178), it converts them to other characters (in this example, to the plain '2', with `ord('2')` being 50).
That is, with `tokenizer = AutoTokenizer.from_pretrained('xlm-roberta-l... | {
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https://api.github.com/repos/huggingface/transformers/issues/8516 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8516/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8516/comments | https://api.github.com/repos/huggingface/transformers/issues/8516/events | https://github.com/huggingface/transformers/pull/8516 | 742,314,800 | MDExOlB1bGxSZXF1ZXN0NTIwNDcwMzE3 | 8,516 | SWA | {
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/8515 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8515/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8515/comments | https://api.github.com/repos/huggingface/transformers/issues/8515/events | https://github.com/huggingface/transformers/pull/8515 | 742,299,562 | MDExOlB1bGxSZXF1ZXN0NTIwNDYwNTAx | 8,515 | Adding the prepare_seq2seq_batch function to ProphetNet | {
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"For fixing the check_code_quality failure, I run `make style` in the repository, but it tries to re-format so many files.\r\nShould I check some settings for `black`?",
"I changed the environment and made it work again according to the instructions, and it seems that formatting with black works appropriately. So... | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
I tried to use ProphetNet with Seq2SeqTrainer, but it failed.
The error message told me: this is because the collator uses `prepare_seq2seq_batch()` in `_encode()`, but `prepare_seq2seq_batch()` is not implemented in ProphetNet Tokenizer.
I've gotten kind advices in the HuggingFace forum,... | {
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https://api.github.com/repos/huggingface/transformers/issues/8514 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8514/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8514/comments | https://api.github.com/repos/huggingface/transformers/issues/8514/events | https://github.com/huggingface/transformers/issues/8514 | 742,265,651 | MDU6SXNzdWU3NDIyNjU2NTE= | 8,514 | How to pretrain the model (like Roberta) again? | {
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"The authors of the Transformers library wrote a script for this. You can find it under the examples folder -> language modeling [here](https://github.com/huggingface/transformers/tree/master/examples/language-modeling#robertabertdistilbert-and-masked-language-modeling). ",
"> The authors of the Transformers libr... | 1,605 | 1,611 | 1,611 | NONE | null | I don't want to pretrain the model from scratch. I have some dataset related to my task. I want to pretrain the model from transformers the second time. Could someone give me some advice on how to do it or which document to read? Thank you! | {
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https://api.github.com/repos/huggingface/transformers/issues/8513 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8513/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8513/comments | https://api.github.com/repos/huggingface/transformers/issues/8513/events | https://github.com/huggingface/transformers/issues/8513 | 742,205,852 | MDU6SXNzdWU3NDIyMDU4NTI= | 8,513 | Using Pretrained BERT model to add additional words that are not recognized by the model | {
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"You don't need to do either of those things! You should add tokens to your tokenizer by leveraging the `add_tokens()` method, and then resize your model's embedding matrix.\r\n\r\nThen, you should train your model on a dataset that has those entities so that it understands the meaning of these entities. It seems t... | 1,605 | 1,605 | 1,605 | NONE | null | Hello,
I want some help regarding adding additional words in the existing BERT model. I have two quires kindly guide me:
I am working on NER task for a domain:
There are few words (not sure the exact numbers) that BERT recognized as [UNK], but those entities are required for the model to recognize. The pretrai... | {
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https://api.github.com/repos/huggingface/transformers/issues/8512 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8512/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8512/comments | https://api.github.com/repos/huggingface/transformers/issues/8512/events | https://github.com/huggingface/transformers/issues/8512 | 742,152,232 | MDU6SXNzdWU3NDIxNTIyMzI= | 8,512 | Issue while model sharing and uploading on huggingface | {
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"You cannot save directly remotely like this (though it could be nice to be able to do this in the future, cc @madlag).\r\n\r\nYou need to first create a repo with `transformers-cli repo create`, or directly on the website.\r\n\r\nThen clone it locally and add your files, then push.\r\n\r\nHopefully #8520 makes it ... | 1,605 | 1,614 | 1,605 | NONE | null |
The model I am using (Bert, XLNet ...): Roberta for questionanswering
I am trying to follow the tutorial given in https://huggingface.co/transformers/model_sharing.html and while I am able to load my model in the local repository, I am unable to save my model and tokenizer using "model.save_pretrained("https://hug... | {
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https://api.github.com/repos/huggingface/transformers/issues/8511 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8511/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8511/comments | https://api.github.com/repos/huggingface/transformers/issues/8511/events | https://github.com/huggingface/transformers/issues/8511 | 742,073,991 | MDU6SXNzdWU3NDIwNzM5OTE= | 8,511 | Adding Confusion matrix support in Trainer | {
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"Hi there! We love contributions, but metrics should now be implemented directly in the datasets library, not inside Transformers. So you should check there if it does not already exist, and if not, suggest a Pr on that repository :-)",
"Okay then, I will close it."
] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | I want to add confusion matrix support in Trainer. It would be a useful addition. The only dependency would be `sklearn` which this library already uses for metrics. It can allow users to better understand about predictions coming from model. @sgugger Let me know if this is something you want to add.
| {
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https://api.github.com/repos/huggingface/transformers/issues/8510 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8510/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8510/comments | https://api.github.com/repos/huggingface/transformers/issues/8510/events | https://github.com/huggingface/transformers/issues/8510 | 742,039,909 | MDU6SXNzdWU3NDIwMzk5MDk= | 8,510 | Finetune TFBertForMaskedLM model.fit() ValueError | {
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"Maybe @jplu has an idea!",
"Hello @MarsSu0618 \r\n\r\nThe bad news is that it is currently not possible to train an LM from scratch or fine tune it with `.fit()`. The good one is that we are heavily working on it and should be feasible soon.\r\n\r\nSorry for the inconvenience.",
"@jplu \r\nSo i can not fine tu... | 1,605 | 1,614 | 1,614 | NONE | null | ## The Problem
I have been trying to train TFBertForMaskedLM model with tensorflow. But when i use model.fit() always encounter some question.Hope someone can help and propose some solution.
## Reference Paper and sample output
The Paper title is "Conditional Bert for Contextual Augmentation". In short, just chang... | {
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https://api.github.com/repos/huggingface/transformers/issues/8509 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8509/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8509/comments | https://api.github.com/repos/huggingface/transformers/issues/8509/events | https://github.com/huggingface/transformers/pull/8509 | 741,920,203 | MDExOlB1bGxSZXF1ZXN0NTIwMTUxMjc3 | 8,509 | Model templates encoder only | {
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"Thank you both for your reviews!"
] | 1,605 | 1,605 | 1,605 | MEMBER | null | Only merge the encoder part, not the encoder-decoder part of #7636.
Will work on a decoder in the future.
Applied your comments @sgugger @patrickvonplaten, but opened a new PR on a new branch so that we can keep the old one for reference when integrating the encoder-decoder model. | {
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https://api.github.com/repos/huggingface/transformers/issues/8508 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8508/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8508/comments | https://api.github.com/repos/huggingface/transformers/issues/8508/events | https://github.com/huggingface/transformers/issues/8508 | 741,916,532 | MDU6SXNzdWU3NDE5MTY1MzI= | 8,508 | TPU issue: possible memory leak in eval loop | {
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"The problem is that you are aggregating all your predictions on the TPU host, with a big evaluation set. You should use the `eval_accumulation_steps` argument to pass the predictions back to the CPU every, let's say 20 evaluation steps for instance to avoid the OOM.",
"Thanks for the response!\r\nI started a ver... | 1,605 | 1,606 | 1,606 | CONTRIBUTOR | null | I am running into a HBM OOM during the eval loop of xlnet (`--model_name_or_path xlnet-large-cased`) when running on TPUs. No matter which batch size I use, the behavior is the same:
1. training loop succeeds
2. eval loop starts, makes it about halfway, then the TPU runs out of HBM memory and eval loop dies
All th... | {
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https://api.github.com/repos/huggingface/transformers/issues/8507 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8507/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8507/comments | https://api.github.com/repos/huggingface/transformers/issues/8507/events | https://github.com/huggingface/transformers/issues/8507 | 741,894,466 | MDU6SXNzdWU3NDE4OTQ0NjY= | 8,507 | Fill-mask pipeline removes space after token prediction when loading pre-training model based on roberta-base | {
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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",
"Could this be reopened. I'm facing the same issue.",
"@sk- Same. Still getting this with `distilroberta-base`",
"Could you solve it... | 1,605 | 1,706 | 1,611 | NONE | null | ## Environment info
- `transformers` version: 3.5.0
- Platform: Linux-4.15.0-122-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.5
- PyTorch version (GPU?): 1.7.0+cu101 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: False
- Using distributed or parallel set-up in scr... | {
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https://api.github.com/repos/huggingface/transformers/issues/8506 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8506/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8506/comments | https://api.github.com/repos/huggingface/transformers/issues/8506/events | https://github.com/huggingface/transformers/issues/8506 | 741,855,259 | MDU6SXNzdWU3NDE4NTUyNTk= | 8,506 | DPR model: FileNotFoundError: Couldn't find file | {
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"Thanks for reporting !\r\nIndeed the index was renamed recently. I fixed it, it should be good now",
"Got it. Upon re-trying the code, it works fine. "
] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | I am using DPR model:
```python
from transformers import DPRQuestionEncoderTokenizer, DPRQuestionEncoder
from datasets import load_dataset
question_tokenizer = DPRQuestionEncoderTokenizer.from_pretrained('facebook/dpr-question_encoder-single-nq-base')
question_encoder = DPRQuestionEncoder.from_pretrained('face... | {
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https://api.github.com/repos/huggingface/transformers/issues/8505 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8505/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8505/comments | https://api.github.com/repos/huggingface/transformers/issues/8505/events | https://github.com/huggingface/transformers/issues/8505 | 741,855,059 | MDU6SXNzdWU3NDE4NTUwNTk= | 8,505 | Unexpected behavior when using PubMedBERT with AutoModelForMaskedLM | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I know it's an old issue but I just came across this page.\r\n\r\nThe original PubMedBERT checkpoint didn't have the mask prediction he... | 1,605 | 1,658 | 1,611 | CONTRIBUTOR | null | ## Information
I'm getting some strange behavior when using `AutoModelForMaskedLM` with PubMedBERT to impute masked tokens. The screenshot below shows a simple example where I would expect PubMedBERT to give reasonable values, but the suggested tokens are really strange. As shown just below this, `bert-base-uncased`... | {
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"And `git-lfs` is already installed in my local.\r\n```bash\r\n$ git lfs install\r\nUpdated git hooks.\r\nGit LFS initialized.\r\n```\r\n\r\nWhat should I do?",
"Well, it's magical. It works if I clone it again. But this time is different from the first time.\r\n\r\n- The first time, the model file seems not comp... | 1,605 | 1,643 | 1,605 | CONTRIBUTOR | null | Hi, when I upload my model to hub as the [new document](https://huggingface.co/transformers/model_sharing.html) say, I got this error:
```
Delta compression using up to 16 threads.
Compressing objects: 100% (3/3), done.
Writing objects: 100% (4/4), 1.07 GiB | 3.08 MiB/s, done.
Total 4 (delta 0), reused 1 (delta 0)... | {
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https://api.github.com/repos/huggingface/transformers/issues/8503 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8503/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8503/comments | https://api.github.com/repos/huggingface/transformers/issues/8503/events | https://github.com/huggingface/transformers/issues/8503 | 741,786,838 | MDU6SXNzdWU3NDE3ODY4Mzg= | 8,503 | Training the TFGPT2LMHeadModel with model.fit produces error | {
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"Hello!\r\n\r\nYour way of computing the loss is wrong. I suggest you to look at how we compute it [here](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_tf_gpt2.py#L650) and [here](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_tf_utils.py#L125).... | 1,605 | 1,618 | 1,618 | NONE | null | MWE:
```python
from transformers.modeling_tf_gpt2 import TFGPT2LMHeadModel
from transformers.configuration_gpt2 import GPT2Config
from tensorflow.data import Dataset
import tensorflow as tf
data = tf.random.uniform(shape=[10000], dtype = tf.int32, maxval = 100)
src = tf.constant(data)
def split_input_target(c... | {
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"Hello!\r\n\r\nUnfortunately this is a known bug we have with few of the TF models. We are currently reworking all the TF models to solve this issue among others.",
"@jplu I tried the same thing with Pytorch model also. It is also giving error. Any idea if I can get the attentions with pytorch?",
"You get the ... | 1,605 | 1,620 | 1,610 | NONE | null | - `transformers` version: 2.11
- Platform: Multiple
- Python version: multiple
### Who can help
T5: @patrickvonplaten
tensorflow: @jplu
## Information
Model I am using (Bert, XLNet ...): T5
The problem arises when t5-small is loaded from pretrain with output_hidden_states=True, output_attentions=True... | {
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https://api.github.com/repos/huggingface/transformers/issues/8501 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8501/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8501/comments | https://api.github.com/repos/huggingface/transformers/issues/8501/events | https://github.com/huggingface/transformers/issues/8501 | 741,717,309 | MDU6SXNzdWU3NDE3MTczMDk= | 8,501 | Why is the XLM-RoBERTa sometimes producing a standalone start of the word character (the special underscore with ord = 9601) | {
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"Ah, I guess I figured that out. Does it happen when the training data set of the tokenizer never had this token at the beginning of a word but only inside a word?"
] | 1,605 | 1,607 | 1,607 | NONE | null | I'm using the `transformers` library 3.4.0.
The XLM-RoBERTa tokenizer produces in certain cases standalone start of the word characters. Is that intended?
For example:
```
tokenizer.tokenize('amerikanische')
['▁', 'amerikanische']
```
while
```
tokenizer.tokenize('englische')
['▁englische']
```
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https://api.github.com/repos/huggingface/transformers/issues/8500 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8500/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8500/comments | https://api.github.com/repos/huggingface/transformers/issues/8500/events | https://github.com/huggingface/transformers/pull/8500 | 741,710,834 | MDExOlB1bGxSZXF1ZXN0NTE5OTc2NTEw | 8,500 | Fix doc bug | {
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"Thanks for the fix!"
] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | Fix the example of Trainer, hope it help.
@sgugger
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https://api.github.com/repos/huggingface/transformers/issues/8499 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8499/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8499/comments | https://api.github.com/repos/huggingface/transformers/issues/8499/events | https://github.com/huggingface/transformers/issues/8499 | 741,699,107 | MDU6SXNzdWU3NDE2OTkxMDc= | 8,499 | Unable to install Transformers | {
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"I guess the issue is that you're using `anaconda` here. Until version v4.0.0, we're not entirely compatible with anaconda as SentencePiece is not on a conda channel.\r\n\r\nIn the meantime, we recommend installing `transformers` in a pip virtual env:\r\n\r\n```shell-script\r\npython -m venv .env\r\nsource .env/bin... | 1,605 | 1,655 | 1,605 | NONE | null | Hi all - I'm unable to install transformers from source. I need this for a project, it's really annoying not be able to use your amazing work. Could you please help me? :) Thank you so much.
**Issue**
pip install is blocked at **sentencepiece-0.1.91** install and crashes
**What I tried**
- I tried to find a wor... | {
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https://api.github.com/repos/huggingface/transformers/issues/8498 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8498/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8498/comments | https://api.github.com/repos/huggingface/transformers/issues/8498/events | https://github.com/huggingface/transformers/pull/8498 | 741,690,925 | MDExOlB1bGxSZXF1ZXN0NTE5OTU5Nzg1 | 8,498 | Model sharing doc | {
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This PR expands the model sharing doc with some instructions specific to colab.
Unrelated: some fixes in marian.rst that I thought I had pushed directly to master but had not. | {
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https://api.github.com/repos/huggingface/transformers/issues/8497 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8497/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8497/comments | https://api.github.com/repos/huggingface/transformers/issues/8497/events | https://github.com/huggingface/transformers/issues/8497 | 741,688,291 | MDU6SXNzdWU3NDE2ODgyOTE= | 8,497 | Error when loading a model cloned without git-lfs is quite cryptic | {
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"Yep, they way I would go about this would be to programmatically check whether the file is text-only (non-binary) and between 100 and 200 bytes. If it is (and we expected a weights file), it's probably a lfs pointer file.",
"This issue has been automatically marked as stale because it has not had recent activity... | 1,605 | 1,631 | 1,631 | MEMBER | null | # 🚀 Error message request
If you forget to install git-LFS (e.g. on Google Colab) and you just do:
```python
!git clone https://huggingface.co/facebook/bart-base
from transformers import AutoModel
model = AutoModel.from_pretrained('./bart-base')
```
The cloning seems to work well but the model weights are... | {
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https://api.github.com/repos/huggingface/transformers/issues/8496 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8496/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8496/comments | https://api.github.com/repos/huggingface/transformers/issues/8496/events | https://github.com/huggingface/transformers/pull/8496 | 741,672,876 | MDExOlB1bGxSZXF1ZXN0NTE5OTQ0NjAw | 8,496 | Created ModelCard for Hel-ach-en MT model | {
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"This is really cool @Pogayo, thanks for sharing.\r\n\r\nIf you can, please consider adding sample inputs for the inference widget, either in DefaultWidget.ts (see https://huggingface.co/docs#how-can-i-control-my-models-widgets-example-inputs) or in this model card.\r\n\r\nWill also add Acholi to the list in https:... | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/8495 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8495/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8495/comments | https://api.github.com/repos/huggingface/transformers/issues/8495/events | https://github.com/huggingface/transformers/issues/8495 | 741,646,503 | MDU6SXNzdWU3NDE2NDY1MDM= | 8,495 | Allow tensorflow tensors as input to Tokenizer | {
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"I believe @jplu has already used TF Serving. Do you know if it's possible to include tokenization in it?",
"Hello!\r\n\r\nUnfortunately it is currently not possible to integrate our tokenizer directly inside a model due to some TensorFlow limitations. Nevertheless, there might be a solution by trying to create ... | 1,605 | 1,631 | 1,605 | NONE | null | Firstly thanks so much for all the amazing work!
I'm trying to package a model for use in TF Serving. The problem is that everywhere I see this done, the tokenisation step happens outside of the server. I want to include this step inside the server so the user can just provide raw text as the input and not need to k... | {
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https://api.github.com/repos/huggingface/transformers/issues/8494 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8494/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8494/comments | https://api.github.com/repos/huggingface/transformers/issues/8494/events | https://github.com/huggingface/transformers/issues/8494 | 741,552,250 | MDU6SXNzdWU3NDE1NTIyNTA= | 8,494 | error occurs when trainning transformer-xl by ddp | {
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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"
] | 1,605 | 1,611 | 1,611 | NONE | null | my env is as below:
- `transformers` version: 3.4.0
- Platform: 1Ubuntu-18.04
- Python version: 3.6.9
- PyTorch version (GPU?): 1.6.0+cu101 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>
I am trainning the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8493 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8493/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8493/comments | https://api.github.com/repos/huggingface/transformers/issues/8493/events | https://github.com/huggingface/transformers/issues/8493 | 741,521,290 | MDU6SXNzdWU3NDE1MjEyOTA= | 8,493 | I meet the zero gradient descent | {
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"Hi @Sniper970119 do you mind posting this on the forum rather? It's here: https://discuss.huggingface.co\r\n\r\nWe are trying to focus the issues on bug reports and features/model requests.\r\n\r\nThanks a lot.",
"> \r\n> \r\n> Hi @Sniper970119 do you mind posting this on the forum rather? It's here: https://dis... | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | I want use transformers to do text classification, I want code myself rather than use `TFBertForSequenceClassification`,so I write the model with `TFBertModel` and `tf.keras.laters.Dense`,but this is no gradient descent in my code, I try to find what wrong with my code but I can't. So I submit this issues to ask for s... | {
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https://api.github.com/repos/huggingface/transformers/issues/8492 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8492/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8492/comments | https://api.github.com/repos/huggingface/transformers/issues/8492/events | https://github.com/huggingface/transformers/pull/8492 | 741,511,540 | MDExOlB1bGxSZXF1ZXN0NTE5ODExMzc4 | 8,492 | Rework some TF tests | {
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Rework some TF tests to make them compliant with dict returns, and simplify some of them. | {
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https://api.github.com/repos/huggingface/transformers/issues/8491 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8491/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8491/comments | https://api.github.com/repos/huggingface/transformers/issues/8491/events | https://github.com/huggingface/transformers/pull/8491 | 741,491,150 | MDExOlB1bGxSZXF1ZXN0NTE5Nzk0MzQy | 8,491 | Fix check scripts for Windows | {
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"It doesn't make any change on Linux, and you've tested it on Windows. Could we get someone using MacOS to double-check it doesn't break anything for them before merging?",
"I think @LysandreJik is on MacOS?",
"I'm actually between Manjaro and EndeavourOS, but I'll check on a Mac."
] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
The current check-X scripts are reading/writing with `os.linesep` as the newline separator. On Windows it makes the overwritten files in CRLF instead of LF. Same logic is applied on Mac with CR. Now, Python will always use LF to read and write in the files. | {
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https://api.github.com/repos/huggingface/transformers/issues/8490 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8490/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8490/comments | https://api.github.com/repos/huggingface/transformers/issues/8490/events | https://github.com/huggingface/transformers/pull/8490 | 741,473,603 | MDExOlB1bGxSZXF1ZXN0NTE5Nzc5NzUz | 8,490 | New TF loading weights | {
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"I have added a lot of comments in the method to make it clearer, I removed a small part of the code that was due to the moment where I was updating to the new names in same time. @LysandreJik @sgugger it should be easier to understand now.",
"It's a lot clearer, thanks. There are still unaddressed comments howev... | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
This PR improves the way we load the TensorFlow weights. Before we had to go through the instantiated model + the checkpoint twice:
- once for loading the weights from the checkpoints into the instantiated model
- once for computing the missing and unexpected keys
Now both are done simul... | {
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https://api.github.com/repos/huggingface/transformers/issues/8489 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8489/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8489/comments | https://api.github.com/repos/huggingface/transformers/issues/8489/events | https://github.com/huggingface/transformers/pull/8489 | 741,467,565 | MDExOlB1bGxSZXF1ZXN0NTE5Nzc0ODM1 | 8,489 | Fix typo in roberta-base-squad2-v2 model card | {
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Simply adding `-v2` for Haystack API model loading. Furthermore, I've also changed `model` in `model_name_or_path` due to breaking change in Haystack (https://github.com/deepset-ai/haystack/pull/510).
## Who can review?
Model Cards: @julien-c | {
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https://api.github.com/repos/huggingface/transformers/issues/8488 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8488/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8488/comments | https://api.github.com/repos/huggingface/transformers/issues/8488/events | https://github.com/huggingface/transformers/pull/8488 | 741,445,821 | MDExOlB1bGxSZXF1ZXN0NTE5NzU2OTcx | 8,488 | [WIP] T5v1.1 & MT5 | {
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"Maybe wrong model config for T5.1.1. For instance, T5.1.1.small should have num_layers=8 and num_heads=6.\r\n\r\nSee https://github.com/google-research/text-to-text-transfer-transformer/blob/master/t5/models/gin/models/t5.1.1.small.gin",
"> Maybe wrong model config for T5.1.1. For instance, T5.1.1.small should h... | 1,605 | 1,605 | 1,605 | MEMBER | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/8487 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8487/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8487/comments | https://api.github.com/repos/huggingface/transformers/issues/8487/events | https://github.com/huggingface/transformers/issues/8487 | 741,432,522 | MDU6SXNzdWU3NDE0MzI1MjI= | 8,487 | `log_history` does not contain metrics anymore | {
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"`evaluate` calls `log` which appends the results to `log_history`. So the code is there. Without a reproducer to investigate, there is nothing we can do to help.",
"Here is the demo code that shows the bug: https://colab.research.google.com/drive/1dEzkDoMampL-VVrQeO924HQmHXffya0Z?usp=sharing\r\n\r\nThe last line... | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | Since version 3.5.0 the `log_history` of the trainer does not contain the metrics anymore. Version 3.4.0 works...
My trainer uses a `compute_metrics` callback. It avaluates after each epoch. At version 3.4.0 after the training I am extracting the last epoch results: `trainer.state.log_history[-1]` to log the metrics... | {
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https://api.github.com/repos/huggingface/transformers/issues/8486 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8486/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8486/comments | https://api.github.com/repos/huggingface/transformers/issues/8486/events | https://github.com/huggingface/transformers/issues/8486 | 741,390,993 | MDU6SXNzdWU3NDEzOTA5OTM= | 8,486 | Gradient accumulation averages over gradients | {
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"Hi @MarktHart do you mind posting this on the forum rather? It's here: https://discuss.huggingface.co\r\n\r\nWe are trying to focus the issues on bug reports and features/model requests.\r\n\r\nThanks a lot.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be c... | 1,605 | 1,611 | 1,611 | NONE | null | https://github.com/huggingface/transformers/blob/121c24efa4453e4e726b5f0b2cf7095b14b7e74e/src/transformers/trainer.py#L1118
So I have been looking at this for the past day and a half. Please explain to me. Gradient accumulation should accumulate the gradient, not average it, right? That makes this scaling plain wron... | {
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https://api.github.com/repos/huggingface/transformers/issues/8485 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8485/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8485/comments | https://api.github.com/repos/huggingface/transformers/issues/8485/events | https://github.com/huggingface/transformers/pull/8485 | 741,300,497 | MDExOlB1bGxSZXF1ZXN0NTE5NjM3ODMz | 8,485 | Prediction loop: work with batches of variable length (fixed per batch) | {
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"Please feel free to modify this in any shape or form of course.",
"This will cause a regression for code expecting a NumPy output, obviously :/",
"I don't have much time, if any, to dedicate to this. If you're not interested by the idea, it's completely fine, I will close.",
"I think @jplu is redesigning the... | 1,605 | 1,605 | 1,605 | NONE | null | In the current form, the `prediction_loop` doesn't handle batches with samples of varying lengths (but fixed length per batch). This patch adds this capability.
This is great because it can save a lot of time during training and inference, where using the full length every time is a big sacrifice, knowing self-attenti... | {
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https://api.github.com/repos/huggingface/transformers/issues/8484 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8484/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8484/comments | https://api.github.com/repos/huggingface/transformers/issues/8484/events | https://github.com/huggingface/transformers/issues/8484 | 741,286,414 | MDU6SXNzdWU3NDEyODY0MTQ= | 8,484 | automodel | {
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform:
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in s... | {
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"Created pull request https://github.com/huggingface/transformers/pull/8485",
"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",
"Hello @JulesGM \r\nRegarding [#8483](https://github.com... | 1,605 | 1,620 | 1,611 | NONE | null | Hello,
It seems like `np.append` in `TFTrainer.prediction_loop` is the only thing that prevent TFTrainer from being able to deal with batches of variable sequence length (between the batches, not inside the batches themselves). Indeed, `np.append` requires the batches to be of the same sequence length.
Alternatives:... | {
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"Thank you! \r\n\r\n❗ This is a preliminary review, I'm not finished with it. 2 important things for now:\r\n\r\n1) I am also testing the Colab demo's with this branch. Currently I'm getting an error when providing `answer_coordinates` and `answer_texts` to the tokenizer: \r\n\r\nSQA: https://colab.research.google.... | 1,605 | 1,651 | 1,605 | MEMBER | null | This PR aims to implement the tokenizer API for the TAPAS model, as well as the tests. It is based on `tapas-style` which contains all the changes done by black & isort on top of the `nielsrogge/tapas_v3` branch in https://github.com/huggingface/transformers/pull/8113.
The API is akin to our other tokenizers': it is... | {
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https://api.github.com/repos/huggingface/transformers/issues/8480 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8480/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8480/comments | https://api.github.com/repos/huggingface/transformers/issues/8480/events | https://github.com/huggingface/transformers/issues/8480 | 741,208,845 | MDU6SXNzdWU3NDEyMDg4NDU= | 8,480 | Error when upload models: "LFS: Client error" | {
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"Since `git push` by itself is not so informative, I retried it with more verbose output (sorry for the long output): \r\n```\r\n$ GIT_TRACE=1 GIT_CURL_VERBOSE=1 git push\r\n18:07:20.246678 git.c:440 trace: built-in: git push\r\n18:07:20.247908 run-command.c:663 trace: run_command: GIT_DIR=.git ... | 1,605 | 1,611 | 1,611 | CONTRIBUTOR | null | I am using the most recent release to upload a model.
Like the new instructions suggested, I am using git to upload my files:
```bash
$ git add --all
Encountered 1 file(s) that may not have been copied correctly on Windows:
pytorch_model.bin
$ git status
On branch main
Your branch is up to date with 'ori... | {
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https://api.github.com/repos/huggingface/transformers/issues/8479 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8479/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8479/comments | https://api.github.com/repos/huggingface/transformers/issues/8479/events | https://github.com/huggingface/transformers/pull/8479 | 741,189,946 | MDExOlB1bGxSZXF1ZXN0NTE5NTQ4NjQ4 | 8,479 | Fix SqueezeBERT for masked language model | {
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] | closed | false | null | [] | [] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
This corrects a mistake in the implementation of SqueezeBertForMaskedLM.
Fixes #8277
## Before submitting
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests),
Pull Request sectio... | {
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https://api.github.com/repos/huggingface/transformers/issues/8478 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8478/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8478/comments | https://api.github.com/repos/huggingface/transformers/issues/8478/events | https://github.com/huggingface/transformers/pull/8478 | 741,183,012 | MDExOlB1bGxSZXF1ZXN0NTE5NTQzMzQz | 8,478 | [s2s] finetune.py: specifying generation min_length | {
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"LGTM, but will break CI. no idea why it's not running.\r\nYou will need to update the tests. I bet `pytest examples/seq2seq/test_seq2seq_examples.py` will fail ( you should fix that).\r\n",
"Yeah, here is the error I am seeing. \r\n\r\n```\r\n$ pytest examples/seq2seq/test_seq2seq_examples.py\r\ncomet_ml is inst... | 1,605 | 1,606 | 1,606 | CONTRIBUTOR | null | # What does this PR do?
Adds an argument to `finetune.py` to specify min length for text generation.
Related to:
https://github.com/huggingface/transformers/issues/5142#issuecomment-724938595
https://github.com/huggingface/transformers/issues/7796#issuecomment-709348940
## Who can review?
@patrickvonpl... | {
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https://api.github.com/repos/huggingface/transformers/issues/8477 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8477/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8477/comments | https://api.github.com/repos/huggingface/transformers/issues/8477/events | https://github.com/huggingface/transformers/issues/8477 | 741,170,843 | MDU6SXNzdWU3NDExNzA4NDM= | 8,477 | How to print out the probability for each bean search result in gpt2 text generator? | {
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"Take a look at https://github.com/huggingface/transformers/issues/5164",
"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"
] | 1,605 | 1,611 | 1,611 | NONE | null | # 🚀 I want to see the probability for the text result generated by gpt2 model
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
See a sample code as below, when we used a pre-trained model, can we also print out the probabili... | {
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https://api.github.com/repos/huggingface/transformers/issues/8476 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8476/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8476/comments | https://api.github.com/repos/huggingface/transformers/issues/8476/events | https://github.com/huggingface/transformers/issues/8476 | 741,166,156 | MDU6SXNzdWU3NDExNjYxNTY= | 8,476 | Trainer runs out of memory when computing eval score | {
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"I'm not sure what the bug is: by requiring the complete predictions for your `compute_metrics` function, you are asking for an array of 4,057 by 200 by vocab_size (which for the base CamemBERT model is 30,522 I believe). This does not fit easily in RAM.\r\n",
"Is there another way to compute the metrics (or an e... | 1,605 | 1,660 | 1,605 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.5.0
- Platform: Linux-3.10.0-1127.19.1.el7.x86_64-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.... | {
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https://api.github.com/repos/huggingface/transformers/issues/8474 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8474/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8474/comments | https://api.github.com/repos/huggingface/transformers/issues/8474/events | https://github.com/huggingface/transformers/pull/8474 | 741,102,627 | MDExOlB1bGxSZXF1ZXN0NTE5NDc2ODUw | 8,474 | Fix on "examples/language-modeling" to support more datasets | {
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"Great fix, thanks!"
] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
Fix on "run_clm.py", "run_mlm.py", "run_plm.py", so that they can support datasets with more than one features. Before they will fail on datasets with more than one features.
<!--
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https://api.github.com/repos/huggingface/transformers/issues/8473 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8473/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8473/comments | https://api.github.com/repos/huggingface/transformers/issues/8473/events | https://github.com/huggingface/transformers/issues/8473 | 741,070,726 | MDU6SXNzdWU3NDEwNzA3MjY= | 8,473 | Support fp16 for inference | {
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"I imagine this only happens when the `generate()` method is used under the hood? ",
"Hi there! It's true you can't just do `model.half()` for generation. There is nothing in Trainer/Seq2SeqTrainer right now for FP16-inference, only training, but we're looking at it right now through #8403. So stay tuned!",
"T... | 1,605 | 1,633 | 1,614 | NONE | null | # 🚀 Feature request - support fp16 inference
Right now most models support mixed precision for model training, but not for inference. Naively calling `model= model.haf()` makes the model generate junk instead of valid results for text generation, even though mixed-precision works fine in training.
If there's a ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8472 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8472/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8472/comments | https://api.github.com/repos/huggingface/transformers/issues/8472/events | https://github.com/huggingface/transformers/issues/8472 | 741,068,616 | MDU6SXNzdWU3NDEwNjg2MTY= | 8,472 | GPT2 (pre-trained not fine-tuned) only generates additional special tokens | {
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"@g-karthik ",
"Was able to reproduce this as well.\r\n\r\nFrom the observation, I suspect the random weights being initialized for the added tokens in the final `Linear` and/or `SequenceSummary` head are such that no matter what hidden state is sent in, a special token gets the highest final scalar score. Haven'... | 1,605 | 1,698 | 1,605 | NONE | null | ## Environment info
- `transformers` version: 3.5.0
- Platform: Darwin-19.6.0-x86_64-i386-64bit
- Python version: 3.6.3
- PyTorch version (GPU?): 1.7.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### Who can help
@pa... | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,605 | 1,605 | 1,605 | NONE | null | I'm using TFBertForTokenClassification to perform a NER task on the annotated corpus fo NER:
[https://www.kaggle.com/abhinavwalia95/entity-annotated-corpus](https://www.kaggle.com/abhinavwalia95/entity-annotated-corpus).
The problem is that the O-Labels are the majority of all labels, then the accuracy is quite high ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8470 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8470/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8470/comments | https://api.github.com/repos/huggingface/transformers/issues/8470/events | https://github.com/huggingface/transformers/pull/8470 | 740,902,522 | MDExOlB1bGxSZXF1ZXN0NTE5MzEyMjM0 | 8,470 | Add pretraining loss computation for TF Bert pretraining | {
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This PR adds the loss computation for the pretraining TF BERT model. The loss computation test is also more robust on variable call signature lengths. | {
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https://api.github.com/repos/huggingface/transformers/issues/8469 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8469/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8469/comments | https://api.github.com/repos/huggingface/transformers/issues/8469/events | https://github.com/huggingface/transformers/issues/8469 | 740,896,538 | MDU6SXNzdWU3NDA4OTY1Mzg= | 8,469 | Pegasus models load very slowly or do not load at all on initial execution of from_pretrained() when Python is spawned from within a Node.js process | {
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"maybe @julien-c or @Pierrci can answer this question better",
"This seems very environment-specific. @wehriam in case paid support is an option, we have a technical support program in beta at api-enterprise@huggingface.co (cc @clmnt @jeffboudier)",
"This issue has been automatically marked as stale because it ... | 1,605 | 1,611 | 1,611 | NONE | null | ## Description
We are using Node.js to coordinate processes, including a Python web server that loads a pretrained model in CPU mode.
The model files are downloaded and cached prior to execution during a container build process.
On initial execution, it appears the model stalls while loading the primary weight... | {
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# What does this PR do?
Fix an error with run_ner.py at the prediction step on a custom dataset
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https://api.github.com/repos/huggingface/transformers/issues/8467 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8467/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8467/comments | https://api.github.com/repos/huggingface/transformers/issues/8467/events | https://github.com/huggingface/transformers/issues/8467 | 740,837,112 | MDU6SXNzdWU3NDA4MzcxMTI= | 8,467 | Fine tuning a classification model with engineered features | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discuss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,605 | 1,605 | 1,605 | NONE | null | # 🚀 Feature request
When fine-tuning a BERT model for text classification, it would be useful to be able to add some engineered features to improve accuracy.
## Motivation
For example:
- if there are any dates on the text (based on NER);
- if the text starts with a punctuation;
- if the font size is l... | {
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https://api.github.com/repos/huggingface/transformers/issues/8466 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8466/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8466/comments | https://api.github.com/repos/huggingface/transformers/issues/8466/events | https://github.com/huggingface/transformers/pull/8466 | 740,809,139 | MDExOlB1bGxSZXF1ZXN0NTE5MjMzODU2 | 8,466 | Fix TF next sentence output | {
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Make the loss optional in the TF next sentence prediction output. | {
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https://api.github.com/repos/huggingface/transformers/issues/8465 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8465/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8465/comments | https://api.github.com/repos/huggingface/transformers/issues/8465/events | https://github.com/huggingface/transformers/issues/8465 | 740,798,832 | MDU6SXNzdWU3NDA3OTg4MzI= | 8,465 | Pytorch Vs Onnx: Pytorch is faster and provides different output | {
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"I also got different results 🤦",
"I have figured out the problem, but I don't have the solution.\r\nWhen you use a single sample per batch it works correctly, but when you use more than one sample per batch, the results are totally different.",
"@mfuntowicz and @LysandreJik , it will be great if you could sh... | 1,605 | 1,614 | 1,614 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 3.5.0
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101 (True)
- Tensorflow version (GPU?): 2.3.0 (True)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No
###... | {
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https://api.github.com/repos/huggingface/transformers/issues/8464 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8464/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8464/comments | https://api.github.com/repos/huggingface/transformers/issues/8464/events | https://github.com/huggingface/transformers/pull/8464 | 740,792,864 | MDExOlB1bGxSZXF1ZXN0NTE5MjIwMjUz | 8,464 | Add model card for ai4bharat/indic-bert | {
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"really cool, thanks for sharing"
] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
This PR adds model card for IndicBERT model (shortcut name: `ai4bharat/indic-bert`)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/tr... | {
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"cc @patrickvonplaten ",
"No, 2 character language codes are not covered. However `>>.{2}<<|>>.{3}<<|>>.{3}\\_.{4}<<` can be used.\r\n\r\nI can try writing tests. Is these somewhere where I could find an exhaustive set of language codes? I had written the regex to cover the 194 language code in `'Helsinki-NLP/opu... | 1,605 | 1,614 | 1,614 | NONE | null | # Better regex expression for extracting language code in tokenization_marian.py
In `tokenization_marian.py`, the regex `>>.+<<` is used to extract the language token from the sentences leading to the following incorrect tokenization.
```
Example Sentence:
>>hin<< We use cout<< function to print a line in C++.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/8462 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8462/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8462/comments | https://api.github.com/repos/huggingface/transformers/issues/8462/events | https://github.com/huggingface/transformers/pull/8462 | 740,748,367 | MDExOlB1bGxSZXF1ZXN0NTE5MTgyODcz | 8,462 | Add next sentence prediction loss computation | {
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This PR adds the loss computation for the next sentence prediction task in TF BERT and MobileBERT. | {
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https://api.github.com/repos/huggingface/transformers/issues/8461 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8461/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8461/comments | https://api.github.com/repos/huggingface/transformers/issues/8461/events | https://github.com/huggingface/transformers/issues/8461 | 740,709,364 | MDU6SXNzdWU3NDA3MDkzNjQ= | 8,461 | multiple hard-coded paths in transformers/file_utils.py | {
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"will report this in datasets repo. "
] | 1,605 | 1,605 | 1,605 | NONE | null | Hi
I need to run the codes on a machine not having access to internet, I am running finetune_trainer.py on a dataset from datasets repo, due to these hardcoded paths I cannot get the code running without access to internet, could you please make any hard-coded path a parameter, so if user do not have access to interne... | {
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https://api.github.com/repos/huggingface/transformers/issues/8460 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8460/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8460/comments | https://api.github.com/repos/huggingface/transformers/issues/8460/events | https://github.com/huggingface/transformers/pull/8460 | 740,704,981 | MDExOlB1bGxSZXF1ZXN0NTE5MTQ2NzIy | 8,460 | Fix TF Longformer | {
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Fix TF Longformer model outputs. | {
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https://api.github.com/repos/huggingface/transformers/issues/8459 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8459/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8459/comments | https://api.github.com/repos/huggingface/transformers/issues/8459/events | https://github.com/huggingface/transformers/issues/8459 | 740,679,846 | MDU6SXNzdWU3NDA2Nzk4NDY= | 8,459 | Question Answering Documentation Example Bug | {
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"Hi! That sounds good, do you want to open a PR?",
"Yes, I am on it. Thanks!\r\n",
"+1\r\nany updates?",
"@iremnasir can you please let me know how exactly you managed to solve it? I am having the same issue. \r\n: 1.7.0 (... | {
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https://api.github.com/repos/huggingface/transformers/issues/8458 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8458/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8458/comments | https://api.github.com/repos/huggingface/transformers/issues/8458/events | https://github.com/huggingface/transformers/pull/8458 | 740,647,359 | MDExOlB1bGxSZXF1ZXN0NTE5MDk4NDQ2 | 8,458 | Fix logging in the examples | {
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"The five examples scripts mentioned above all already use the huggingface logger, and already set it to the correct verbosity level. Seeing as the example scripts are *examples*, they really should be as straightforward as possible, and should not repeat unnecessary statements.\r\n\r\nPlease update the following f... | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
This PR updates all the examples to use the Transformers logging util. Before no logs was displayed. | {
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"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n\nIf you think this still needs to be addressed please comment on this thread."
] | 1,605 | 1,614 | 1,614 | CONTRIBUTOR | null | I correct the mark down grammar about WWM readme, in order to keep all things right. | {
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https://api.github.com/repos/huggingface/transformers/issues/8456 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8456/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8456/comments | https://api.github.com/repos/huggingface/transformers/issues/8456/events | https://github.com/huggingface/transformers/issues/8456 | 740,525,316 | MDU6SXNzdWU3NDA1MjUzMTY= | 8,456 | ValueError: No gradients provided for any variable: ['tf_bert_for_masked_lm_6/bert/embeddings/word_embeddings/weight:0', 'tf_bert_for_masked_lm_6/bert/embeddings/position_embeddings/embeddings:0'...... | {
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"change other questions.",
"How did u solve this issue?",
"How did u solve this problem? I got same problem like yours"
] | 1,605 | 1,621 | 1,605 | NONE | null | Hi! Everyone.
I encounter some problems with TFBertForMaskedLM.
I modify TFBertForMaskedLM layer according to "Condition-Bert Contextual Augmentation" paper.
In short, my dataset sentences have 5 labels, then change type_token_ids to label_ids.
so, i change bert.embeddings.token_type_embeddings .
my model cod... | {
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https://api.github.com/repos/huggingface/transformers/issues/8455 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8455/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8455/comments | https://api.github.com/repos/huggingface/transformers/issues/8455/events | https://github.com/huggingface/transformers/issues/8455 | 740,515,573 | MDU6SXNzdWU3NDA1MTU1NzM= | 8,455 | Can't down models from huggingface.cn! | {
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"Duplicate of #8449 "
] | 1,605 | 1,605 | 1,605 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform:
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in s... | {
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https://api.github.com/repos/huggingface/transformers/issues/8454 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8454/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8454/comments | https://api.github.com/repos/huggingface/transformers/issues/8454/events | https://github.com/huggingface/transformers/issues/8454 | 740,506,768 | MDU6SXNzdWU3NDA1MDY3Njg= | 8,454 | Add POINTER model | {
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"Thanks @patrickvonplaten for taking this. It's nice to work with you again :)",
"Really interesting approach :hugs: \r\n\r\n@dreasysnail Do you think it is possible to pre-train a model from scratch on **one** GPU in a reasonable time? Could you say something about your used hardware setup and training time for ... | 1,605 | 1,631 | null | CONTRIBUTOR | null | # 🌟 New model addition
## Model description
[POINTER](https://github.com/dreasysnail/POINTER) is a progressive and non-autoregressive text generation pre-training approach, published on EMNLP 2020 by Microsoft Research. POINTER generates fluent text in a progressive and parallel manner. With empirical logarithmi... | {
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https://api.github.com/repos/huggingface/transformers/issues/8453 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8453/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8453/comments | https://api.github.com/repos/huggingface/transformers/issues/8453/events | https://github.com/huggingface/transformers/issues/8453 | 740,457,445 | MDU6SXNzdWU3NDA0NTc0NDU= | 8,453 | _pickle.PicklingError: Can't pickle typing.Union[str, NoneType]: it's not the same object as typing.Union | {
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"Maybe @sgugger has an idea",
"This is a duplicate of #8212 which gives the workaround (install python 3.7) while waiting for the new release of datasets, which will fix that bug.",
"Maybe we should do a quick patch release of `datasets` just for this one @lhoestq?",
"It seems an issue ´till Python 3.6 on Pic... | 1,605 | 1,611 | 1,611 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:3.4.0
- Platform:linux
- Python version:3.6
- PyTorch version (GPU?):1.6 cuda10
- Tensorflow version (G... | {
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https://api.github.com/repos/huggingface/transformers/issues/8452 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8452/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8452/comments | https://api.github.com/repos/huggingface/transformers/issues/8452/events | https://github.com/huggingface/transformers/issues/8452 | 740,445,596 | MDU6SXNzdWU3NDA0NDU1OTY= | 8,452 | Fine-tuning GPT: problems with padding | {
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"Another suspicious flag in the config for GPT is `predict_special_tokens` which is set to `True` (no such thing for GPT2 config). I did a grep on this flag and it seems to be present only in the config class and not used anywhere else. Somewhat strange. ",
"I might have found a problem in my scripts/code. I've b... | 1,605 | 1,685 | 1,614 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.4.0
- Platform: Linux-3.10.0-957.el7.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyTorch v... | {
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https://api.github.com/repos/huggingface/transformers/issues/8451 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8451/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8451/comments | https://api.github.com/repos/huggingface/transformers/issues/8451/events | https://github.com/huggingface/transformers/issues/8451 | 740,442,985 | MDU6SXNzdWU3NDA0NDI5ODU= | 8,451 | config.attention_head_size for structured pruning out-of-box | {
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"@dsindex FYI, I am working on creating a PR including this feature for the effort of #8083 .",
"@ykim362 great! closing issue here."
] | 1,605 | 1,605 | 1,605 | NONE | null | # 🚀 Feature request
## Motivation
for structured pruning like `fastformers`, https://github.com/microsoft/fastformers#pruning-models ,
we should modify the source code of transformers for `attention_head_size.
for example,
1. configuration_bert.py
https://github.com/microsoft/fastformers/blob/main/src/... | {
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https://api.github.com/repos/huggingface/transformers/issues/8450 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8450/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8450/comments | https://api.github.com/repos/huggingface/transformers/issues/8450/events | https://github.com/huggingface/transformers/issues/8450 | 740,420,659 | MDU6SXNzdWU3NDA0MjA2NTk= | 8,450 | A layman wants to train DistilBERT | {
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"[https://github.com/google-research/bert](url)\r\n\r\nIn this url, I find some files.\r\n\r\n\r\nBut I don't whether they are the data which used to be the training data of distilbert.\r\nAnd the distilber... | 1,605 | 1,611 | 1,611 | NONE | null | I want to train DistilBERT, but I don't know how to get the training data.
In the article, it describes the training data as a concatenation of Toronto Book Corpus and English Wikipedia (same training data as the English version of BERT). So how can I get it?
![image](https://user-images.githubusercontent.com/38... | {
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https://api.github.com/repos/huggingface/transformers/issues/8449 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8449/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8449/comments | https://api.github.com/repos/huggingface/transformers/issues/8449/events | https://github.com/huggingface/transformers/issues/8449 | 740,414,070 | MDU6SXNzdWU3NDA0MTQwNzA= | 8,449 | Can't find model to down | {
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"I encountered the same problem",
"Will release a new version of that UX tomorrow",
"We just added file sizes, and download links, to the lists of model files, see for instance:\r\n\r\n<img width=\"1592\" alt=\"Screenshot 2020-11-13 at 22 55 23\" src=\"https://user-images.githubusercontent.com/326577/99125288-b... | 1,605 | 1,619 | 1,619 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
<!-- Please outline the motivation for the proposal. Is your feature request
related to a problem? e.g., I'm always frustrated when [.... | {
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https://api.github.com/repos/huggingface/transformers/issues/8448 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8448/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8448/comments | https://api.github.com/repos/huggingface/transformers/issues/8448/events | https://github.com/huggingface/transformers/issues/8448 | 740,197,842 | MDU6SXNzdWU3NDAxOTc4NDI= | 8,448 | Make sure the slot variables are created under the same strategy scope. | {
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"I think i already got an answer to my question from this page https://github.com/huggingface/transformers/blob/master/examples/token-classification/run_tf_ner.py :)\r\n\r\nwith training_args.strategy.scope():\r\n model = TFBertForTokenClassification.from_pretrained(bert_model,\r\n ... | 1,605 | 1,605 | 1,605 | NONE | null | - `transformers` version: 3.5.0
- Platform: jupyter notebook
- Python version: 3.6.9
- Tensorflow version (GPU?): 2.3.1
- Using GPU in script?: Single RTX 2080TI
- Model: "distilbert-base-multilingual-cased"
with tf.device('/device:GPU:0'):
model.compile(optimizer=optimizer, loss=loss_fn)
model.fit(tr... | {
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"Hi, I have a related issue. This happen to `\"facebook/rag-token-base\"` and `\"facebook/rag-token-nq\"` and `\"facebook/rag-sequence-nq\"` as well.\r\n\r\nBasic loading failed (was able to do it until around 2 days ago -- I use version 3.5.0)\r\nBoth\r\n\r\n`tokenizer = RagTokenizer.from_pretrained(\"facebook/ra... | 1,605 | 1,606 | 1,605 | NONE | null | ## Environment info
- `transformers` version: 3.3.1
- Platform: Linux-4.15.0-38-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: True
- Using distributed or parallel set-up in scri... | {
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* `multiple_gpu`
* `multigpu`
with `multi_gpu` for consistency
There is no functionality change otherwise.
I did repo-wide:
```
find . -type d -name ".git" -prune -o -type f -exec perl -pi -e '... | {
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https://api.github.com/repos/huggingface/transformers/issues/8445 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8445/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8445/comments | https://api.github.com/repos/huggingface/transformers/issues/8445/events | https://github.com/huggingface/transformers/pull/8445 | 740,127,323 | MDExOlB1bGxSZXF1ZXN0NTE4NjY4NjE4 | 8,445 | [marian.rst] remove combined lines | {
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"I already did that in a commit to master, thanks for fixing too! :-)"
] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/8444 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8444/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8444/comments | https://api.github.com/repos/huggingface/transformers/issues/8444/events | https://github.com/huggingface/transformers/pull/8444 | 740,070,005 | MDExOlB1bGxSZXF1ZXN0NTE4NjIxMTM2 | 8,444 | Add missing import | {
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... | [] | closed | false | null | [] | [] | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
Fix a missing import for TF auto. | {
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https://api.github.com/repos/huggingface/transformers/issues/8443 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8443/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8443/comments | https://api.github.com/repos/huggingface/transformers/issues/8443/events | https://github.com/huggingface/transformers/issues/8443 | 740,047,270 | MDU6SXNzdWU3NDAwNDcyNzA= | 8,443 | Dropout p is changing after loading | {
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"Hi, this is not the best way to update the dropout value as it will get overridden by the configuration value on load.\r\n\r\nThe classifier in `BertForSequenceClassification` is a linear layer, that has no dropout. If you want to change the dropout which is applied before the linear layer, you should update the `... | 1,605 | 1,610 | 1,610 | NONE | null | ## Environment info
- `transformers` version: 3.5.0
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101 (True)
- Tensorflow version (GPU?): 2.3.0 (True)
- Using GPU in script?:
- Using distributed or parallel set-up in script?: No
### ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8442 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8442/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8442/comments | https://api.github.com/repos/huggingface/transformers/issues/8442/events | https://github.com/huggingface/transformers/issues/8442 | 740,002,461 | MDU6SXNzdWU3NDAwMDI0NjE= | 8,442 | Models fine-tuned with gradient checkpointing (=True) fails to export to ONXX | {
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"Indeed, I see why this would fail. I don't have access to your notebook, but as a temporary workaround you could do:\r\n\r\n```py\r\nmodel.save_pretrained(\"here\")\r\nmodel = ModelClass.from_pretrained(\"here\", gradient_checkpointing=False)\r\n```\r\n\r\nYou should be able to convert that model to ONNX then.",
... | 1,605 | 1,610 | 1,610 | NONE | null | ## Environment info
- `transformers` version: 3.5.0
- Platform: Linux-5.4.0-52-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.9
- PyTorch version (GPU?): 1.7.0 (True)
- Tensorflow version (GPU?): 2.3.1 (False)
- Using GPU in script?: False
- Using distributed or parallel set-up in script?: False
... | {
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https://api.github.com/repos/huggingface/transformers/issues/8441 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8441/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8441/comments | https://api.github.com/repos/huggingface/transformers/issues/8441/events | https://github.com/huggingface/transformers/issues/8441 | 739,954,560 | MDU6SXNzdWU3Mzk5NTQ1NjA= | 8,441 | CUDA out of memory (ALBERT)!! | {
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"Hi there. Questions like this should be asked on the forum. In your code example, you are using different variable names for each of your three call, so it's logical to get more memory consumption. Python will only release the memory if you reuse the same variable name.",
"Hi,friends.\r\n`you are using different... | 1,605 | 1,605 | 1,605 | NONE | null | # ❓ Questions & Help
While using `albert-base-v2` to train my model, I got the following problem:
```
#first call
outputs = self.albert(input_ids,
attention_mask=attention_mask,
token_type_ids=token_type_ids,
position_ids... | {
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https://api.github.com/repos/huggingface/transformers/issues/8440 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8440/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8440/comments | https://api.github.com/repos/huggingface/transformers/issues/8440/events | https://github.com/huggingface/transformers/pull/8440 | 739,948,596 | MDExOlB1bGxSZXF1ZXN0NTE4NTIwNzk5 | 8,440 | Question template | {
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"<img width=\"1402\" alt=\"image\" src=\"https://user-images.githubusercontent.com/7353373/98936078-c3bcb600-24e4-11eb-9ae3-6894af553004.png\">\r\n\r\nFor some reason I don't see the \"Question and Help\" option when I try to open an issue @sgugger @LysandreJik ",
"Mmm, guess the metadata at the top doesn't like ... | 1,605 | 1,605 | 1,605 | COLLABORATOR | null | # What does this PR do?
This PR updates the question template to insist a bit more on users using the forum for questions. | {
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https://api.github.com/repos/huggingface/transformers/issues/8439 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8439/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8439/comments | https://api.github.com/repos/huggingface/transformers/issues/8439/events | https://github.com/huggingface/transformers/pull/8439 | 739,907,146 | MDExOlB1bGxSZXF1ZXN0NTE4NDg3MTcz | 8,439 | Model sharing rst | {
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"Merging it now with Julien's offline approval."
] | 1,605 | 1,605 | 1,605 | MEMBER | null | Update the model sharing RST for the new model versioning. | {
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https://api.github.com/repos/huggingface/transformers/issues/8438 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8438/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8438/comments | https://api.github.com/repos/huggingface/transformers/issues/8438/events | https://github.com/huggingface/transformers/issues/8438 | 739,893,503 | MDU6SXNzdWU3Mzk4OTM1MDM= | 8,438 | login to huggingface forum | {
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"Maybe @julien-c or @Pierrci knows!",
"can you try again, just in case it was an intermittent issue?",
"Wonderful, i login with another email and it works. Thanks."
] | 1,605 | 1,605 | 1,605 | NONE | null | hey.
I'm not sure where to post it, so my apologise in advance.
I'm trying to login to huggingface forum, but it return me the message: "Unauthorized".
what can I do?
(I created a user..)
thanks. | {
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https://api.github.com/repos/huggingface/transformers/issues/8437 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8437/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8437/comments | https://api.github.com/repos/huggingface/transformers/issues/8437/events | https://github.com/huggingface/transformers/pull/8437 | 739,848,228 | MDExOlB1bGxSZXF1ZXN0NTE4NDM4MTQw | 8,437 | [T5Tokenizer] fix t5 token type ids | {
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/8436 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8436/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8436/comments | https://api.github.com/repos/huggingface/transformers/issues/8436/events | https://github.com/huggingface/transformers/pull/8436 | 739,819,087 | MDExOlB1bGxSZXF1ZXN0NTE4NDEzMzU2 | 8,436 | Windows dev section in the contributing file | {
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This PR adds a section for people who wants to contribute from a Windows environment. | {
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https://api.github.com/repos/huggingface/transformers/issues/8435 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8435/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8435/comments | https://api.github.com/repos/huggingface/transformers/issues/8435/events | https://github.com/huggingface/transformers/pull/8435 | 739,815,048 | MDExOlB1bGxSZXF1ZXN0NTE4NDA5OTk4 | 8,435 | [T5 Tokenizer] Fix t5 special tokens | {
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"Fixes #7796 "
] | 1,605 | 1,605 | 1,605 | MEMBER | null | # What does this PR do?
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/8434 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8434/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8434/comments | https://api.github.com/repos/huggingface/transformers/issues/8434/events | https://github.com/huggingface/transformers/pull/8434 | 739,803,612 | MDExOlB1bGxSZXF1ZXN0NTE4NDAwMzg0 | 8,434 | Support serialized tokenizer in AutoTokenizer | {
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"I'm having an issue that could be fixed by this PR. I trained a BPETokinizer using the Tokenizers library, uploaded the tokenizer generated JSON file to [my HF repository](https://huggingface.co/jonatasgrosman/bartuque-bart-large-mefmt/blob/main/vocab.json) and this command:\r\n\r\n```python\r\nfrom transformers i... | 1,605 | 1,619 | 1,619 | NONE | null | # What does this PR do?
Addresses issue: https://github.com/huggingface/transformers/issues/7293
With these changes, the `AutoTokenizer.from_pretrained()` supports also loading a tokenizer, which was saved with [🤗 Tokenizers](https://github.com/huggingface/tokenizers) library.
Example:
```python
from tokenize... | {
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https://api.github.com/repos/huggingface/transformers/issues/8433 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8433/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8433/comments | https://api.github.com/repos/huggingface/transformers/issues/8433/events | https://github.com/huggingface/transformers/pull/8433 | 739,778,809 | MDExOlB1bGxSZXF1ZXN0NTE4Mzc5NjA1 | 8,433 | Replaced unnecessary iadd operations on lists in tokenization_utils.py with proper list methods | {
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"Thanks for the quick reviews both of you!\r\n\r\n@LysandreJik \r\nI just searched the whole code and I found many more list append operations than updates through `__iadd__`. So I actually think that for consistency over the whole project scope, it may be better to use list append whenever it's applicable. If you ... | 1,605 | 1,605 | 1,605 | CONTRIBUTOR | null | # Replaced unnecessary iadd operations on lists in tokenization_utils.py with proper list methods
@mfuntowicz
Previously, unnecessarily many list objects are created because of list updates through iadd operations.
This is bad for the following reasons.
* It slows down the program.
* It's a substandard style.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/8432 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8432/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8432/comments | https://api.github.com/repos/huggingface/transformers/issues/8432/events | https://github.com/huggingface/transformers/pull/8432 | 739,748,175 | MDExOlB1bGxSZXF1ZXN0NTE4MzU0NzQx | 8,432 | Add auto next sentence prediction | {
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This PR adds auto models for the next sentence prediction task.
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"Maybe @sgugger or @jplu have an idea",
"`seqeval` can return you more information, for instance the version in the Datasets library returns all the metrics per label IIRC. The code is [here](https://github.com/huggingface/datasets/blob/8005fed0887236804a07bfdc7dc69298e15dac7c/metrics/seqeval/seqeval.py#L96), you... | 1,604 | 1,605 | 1,605 | NONE | null | I'm running the run_ner.py script to use the bert-base-german-cased transformer model in the token classification task to train it on custom NE labels and make predictions for German documents. I have 11 labels in total.
I wondered if there is any way to get prediction results (meaning loss, accuracy, precision, etc... | {
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https://api.github.com/repos/huggingface/transformers/issues/8430 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8430/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8430/comments | https://api.github.com/repos/huggingface/transformers/issues/8430/events | https://github.com/huggingface/transformers/issues/8430 | 739,531,342 | MDU6SXNzdWU3Mzk1MzEzNDI= | 8,430 | RAG: Explanation on Retriever Variables. | {
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"Hey @shamanez - could you please forward this question to the forum: https://discuss.huggingface.co/ . We try to keep the issues for bug reports."
] | 1,604 | 1,605 | 1,605 | CONTRIBUTOR | null | Can you please explain what these terms in the RAG retrieval mean?
1. config.index_name
2. config.index_path | {
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The... | {
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https://api.github.com/repos/huggingface/transformers/issues/8428 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8428/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8428/comments | https://api.github.com/repos/huggingface/transformers/issues/8428/events | https://github.com/huggingface/transformers/pull/8428 | 739,508,433 | MDExOlB1bGxSZXF1ZXN0NTE4MTU3MzAy | 8,428 | Add missing tasks to `pipeline` docstring | {
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Also, I fixed some typos I found. | {
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https://api.github.com/repos/huggingface/transformers/issues/8427 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8427/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8427/comments | https://api.github.com/repos/huggingface/transformers/issues/8427/events | https://github.com/huggingface/transformers/issues/8427 | 739,364,906 | MDU6SXNzdWU3MzkzNjQ5MDY= | 8,427 | Set num_beams=4 for all Helsinki-NLP models | {
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"I can do the change! Will wait until the new git model hub is merged and then apply it :-) ",
"Thanks!\n",
"Should be decently easy to do it @patrickvonplaten let me know when you get to it :)",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no... | 1,604 | 1,610 | 1,610 | CONTRIBUTOR | null | Currently it is 6. Empirically, I tested 77 random models and num_beams=4 was about 50% faster and on average slightly higher BLEU (22.5 vs 22.4).
We also have @jorgtied 's approval for the change.
On slack, he wrote
> Again, no systematic evaluation - more like a feeling. I had the impression that 1 or 2 is w... | {
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https://api.github.com/repos/huggingface/transformers/issues/8426 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8426/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8426/comments | https://api.github.com/repos/huggingface/transformers/issues/8426/events | https://github.com/huggingface/transformers/issues/8426 | 739,308,783 | MDU6SXNzdWU3MzkzMDg3ODM= | 8,426 | Wrong files names in model list for "xlm-roberta-large-finetuned-conll03-german" | {
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"Hi, what do you mean they're incorrect? Are you having issues loading the files in your `transformers` objects?",
"Hi, click on [https://huggingface.co/xlm-roberta-large-finetuned-conll03-german](https://huggingface.co/xlm-roberta-large-finetuned-conll03-german) and then on _List all files in model_ and move the... | 1,604 | 1,604 | 1,604 | NONE | null | Hi, the names of the model files for "xlm-roberta-large-finetuned-conll03-german" are incorrect and have to model name as prefix.
Example:
xlm-roberta-large-finetuned-conll03-german-config.json instead of config.json
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https://api.github.com/repos/huggingface/transformers/issues/8425 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8425/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8425/comments | https://api.github.com/repos/huggingface/transformers/issues/8425/events | https://github.com/huggingface/transformers/pull/8425 | 739,306,488 | MDExOlB1bGxSZXF1ZXN0NTE3OTkyMjYz | 8,425 | Check all models are in an auto class | {
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Following up from @patrickvonplaten fixes, this PR adds a script to check all models are in an auto class. This way we will get a CI error if a newly added model ends up forgotten :-) | {
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] | closed | false | null | [] | [
"That would depend of the training script. All of our models are `nn.Module`s so all can be trained on multi-GPU, it just depends on the script. What script are you using?",
"@LysandreJik Hi, thanks for your reply, i am not pretty sure about script, what I am doing now is using TensorFlow google Electra, but it ... | 1,604 | 1,610 | 1,610 | NONE | null | Hi, I am pretraining the Electra model with my own data, for now, I am pretraining using one GPU in my machine. Can we use multi GPUs to pretrain Electra? Thanks for your reply
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https://api.github.com/repos/huggingface/transformers/issues/8423 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8423/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8423/comments | https://api.github.com/repos/huggingface/transformers/issues/8423/events | https://github.com/huggingface/transformers/pull/8423 | 739,245,173 | MDExOlB1bGxSZXF1ZXN0NTE3OTQxNzAw | 8,423 | Fix bart shape comment | {
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Before transpose , shape of x and encoder_hidden_states are both (BS, seq_len, model_dim) to me.
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https://api.github.com/repos/huggingface/transformers/issues/8422 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8422/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8422/comments | https://api.github.com/repos/huggingface/transformers/issues/8422/events | https://github.com/huggingface/transformers/pull/8422 | 739,241,861 | MDExOlB1bGxSZXF1ZXN0NTE3OTM4OTk5 | 8,422 | [docs] [testing] gpu decorators table | {
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"Thanks Stas!"
] | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | This PR adds a table of gpu requirement decorators that perhaps is easier to grasp quickly in addition to the prose version.
(based on the discussion [here](https://github.com/huggingface/transformers/pull/8341#issuecomment-723705104))
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