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https://api.github.com/repos/huggingface/transformers/issues/4513 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4513/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4513/comments | https://api.github.com/repos/huggingface/transformers/issues/4513/events | https://github.com/huggingface/transformers/issues/4513 | 623,010,971 | MDU6SXNzdWU2MjMwMTA5NzE= | 4,513 | Couldn't reach server GPT-2 | {
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"I also created this stack overflow question here: https://stackoverflow.com/questions/61944526/oserror-couldnt-reach-server-gpt2-config-json",
"It is odd that it works from CLI but not from within your script. That does not make a lot of sense. Can you try this?\r\n\r\n```python\r\nscorer = LMScorer.from_pretrai... | 1,590 | 1,590 | 1,590 | NONE | null | I have tried to use gpt2 using ubuntu and vagrant. This is the code:
`
import torch
from lm_scorer.models.auto import AutoLMScorer as LMScorer
scorer = LMScorer.from_pretrained("gpt2")
`
I get this error:
> AH01215: OSError: Couldn't reach server at 'https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-conf... | {
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https://api.github.com/repos/huggingface/transformers/issues/4512 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4512/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4512/comments | https://api.github.com/repos/huggingface/transformers/issues/4512/events | https://github.com/huggingface/transformers/issues/4512 | 623,002,083 | MDU6SXNzdWU2MjMwMDIwODM= | 4,512 | ValueError: TracedModules don't support parameter sharing between modules | {
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"Can you give more information? This is too brief. Please post the full error that you get (also called error or stack trace) and _do not_ post it as a screenshot but use [code blocks](https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks) instead.",
"As I said: _use code block... | 1,590 | 1,596 | 1,596 | NONE | null | # 🐛 Bug
## Information
Language I am using the model on English:
## To reproduce
Steps to reproduce the behavior:
1.run the "Quick tour" code:
```
import torch
from transformers import *
# Transformers has a unified API
# for 10 transformer architectures and 30 pretrained weights.
# Model... | {
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"Please fill out the template. It is there for a reason. It isn't even clear whether you use your own scripts or ours. _Fill out the template._\r\n\r\nSee this question, which might help: https://github.com/lanpa/tensorboardX/issues/502",
"hello when i use \r\n`python run_language_modeling.py \\\r\n --output_d... | 1,590 | 1,595 | 1,590 | NONE | null | # 🐛 Bug
## Information
Traceback (most recent call last):
File "F:/Kaggle/Hug/Colab/main.py", line 105, in <module>
trainer.train()
File "c:\programdata\anaconda3\lib\site-packages\transformers\trainer.py", line 359, in train
self.tb_writer.add_hparams(self.args.to_sanitized_dict(), metric_dict={... | {
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https://api.github.com/repos/huggingface/transformers/issues/4510 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4510/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4510/comments | https://api.github.com/repos/huggingface/transformers/issues/4510/events | https://github.com/huggingface/transformers/pull/4510 | 622,866,382 | MDExOlB1bGxSZXF1ZXN0NDIxNjUwMTYz | 4,510 | [HUGE] Refactoring tokenizers backend - padding - truncation - pre-tokenized pipeline - fast tokenizers - tests | {
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Edit @thomwolf: I morphed this in a large refactoring of the tokenizer code and test to make it more flexible and have a better API. Here is a summary of the changes.
## Breaking change
There is no breaking change in the user-facing methods (`encode`, `encode_plus`, `batch_encode_plus`, `tokenize`, `c... | {
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```bash
ModuleNotFoundError: No module named 'packaging'
Thu May 21 21:59:44 2020<stderr>:Traceback (most recent call last):
Thu May 21 21:59:44 2020<stderr>: File "/.../", line 37, ... | {
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"Hello! Pipelines are not tested on TPUs yet, unfortunately, and we have not made any effort to support them on that device. We may down the road, once TPU CI is more easily available."
] | 1,590 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
I am following the tutorial in https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb#scrollTo=QDNgPls7_l13 and running on Google Colab using the TPU. The Pipeline object creation works fine, but when I try to run it on the example sentence, t... | {
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"Hi, thanks for the well-formulated question! Are you using the latest examples? When I look at the current branch, there is no force_downloading (any more) - it has been commented out:\r\n\r\nhttps://github.com/huggingface/transformers/blob/a08652772791fdaeed6f263b1a99926ca64be5dc/examples/question-answering/run_s... | 1,590 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
Using a community-registered model (albert, squad2) I noticed that there's no real caching going on during predict/evaluate. In an application that invokes run_squad dozens to hundreds of times, this adds significantly to processing time.
This is due to at least one of the two force_downl... | {
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"Is this issue fixed in version 2.10.0?",
"@julien-c I still get the same error when doing\r\n\r\n```\r\nsummarizer = pipeline('summarization')\r\n```\r\n\r\nand using it to summarize.\r\n\r\nHowever the following explicitely works for me:\r\n\r\n```\r\nsummarizer = pipeline('summarization', model='bart-large-cnn... | 1,590 | 1,592 | 1,590 | MEMBER | null | ```python
summarize = pipeline("summarization")
summarize("Sam Shleifer writes the best docstring examples in the whole world.")
```
➡️
```
/usr/local/lib/python3.6/dist-packages/transformers/pipelines.py in _parse_and_tokenize(self, pad_to_max_length, *args, **kwargs)
461 # Parse arguments
462 ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4503 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4503/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4503/comments | https://api.github.com/repos/huggingface/transformers/issues/4503/events | https://github.com/huggingface/transformers/pull/4503 | 622,648,390 | MDExOlB1bGxSZXF1ZXN0NDIxNDcyNTg2 | 4,503 | Fix convert_token_type_ids_from_sequences for fast tokenizers | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4503?src=pr&el=h1) Report\n> Merging [#4503](https://codecov.io/gh/huggingface/transformers/pull/4503?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a08652772791fdaeed6f263b1a99926ca64be5dc&el=desc) will **increase... | 1,590 | 1,590 | 1,590 | MEMBER | null | Before this fix, the generic version of `convert_token_type_ids_from_sequences` from `tokenizer_utils` gets called when called on a `PreTrainedTokenizerFast`. The `type_ids` for the special token are thus not included.
There is no way at the moment to get this information from the rust tokenizers, so we just use the i... | {
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https://api.github.com/repos/huggingface/transformers/issues/4502 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4502/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4502/comments | https://api.github.com/repos/huggingface/transformers/issues/4502/events | https://github.com/huggingface/transformers/issues/4502 | 622,596,101 | MDU6SXNzdWU2MjI1OTYxMDE= | 4,502 | How to finetune ELECTRA on glue? | {
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"I have a pull request here\r\nhttps://github.com/huggingface/transformers/pull/4257",
"I just cloned your repo an tried to test with my model and it keeps saying the same: \r\n\r\n\r\nCould you tell me h... | 1,590 | 1,594 | 1,590 | CONTRIBUTOR | null | After pretraining my own electra model, I wanted to test it out in Glue using run_glue.py.
However I got this:
```
ValueError: Unrecognized configuration class <class 'transformers.configuration_electra.ElectraConfig'> for this kind of AutoModel: AutoModelForSequenceClassification.
Model type should be one of Dist... | {
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https://api.github.com/repos/huggingface/transformers/issues/4501 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4501/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4501/comments | https://api.github.com/repos/huggingface/transformers/issues/4501/events | https://github.com/huggingface/transformers/issues/4501 | 622,556,769 | MDU6SXNzdWU2MjI1NTY3Njk= | 4,501 | Pipelines do not control input sequences longer than those accepted by the model | {
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"Thanks for the well-structured question! It helps a lot in helping you.\r\n\r\n`pipeline` actually already accepts what you request: you can pass in a tuple for the tokenizer so that the first item is the tokenizer name and the second part is its kwargs.\r\n\r\nhttps://github.com/huggingface/transformers/blob/a086... | 1,590 | 1,679 | 1,598 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): DistilBERT
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on i... | {
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https://api.github.com/repos/huggingface/transformers/issues/4500 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4500/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4500/comments | https://api.github.com/repos/huggingface/transformers/issues/4500/events | https://github.com/huggingface/transformers/pull/4500 | 622,541,164 | MDExOlB1bGxSZXF1ZXN0NDIxMzg2NDM1 | 4,500 | Longformer for question answering | {
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"Could you add it to the automodel class too ?",
"@ibeltagy - could you also take a look here",
"Thank you @patil-suraj, this looks good. One thing I would suggest is to automatically configure the `attention_mask` with global attention on all the question tokens so that the user doesn't need to worry about it.... | 1,590 | 1,590 | 1,590 | MEMBER | null | This PR adds `LongformerForQuestionAnswering` following `RobertaForQuestionAnswering`.
The code is almost identical to `RobertaForQuestionAnswering`, just had to remove `head_mask` parameter from forward method of `RobertaForQuestionAnswering`.
Also trained the model to verify this. You can check inference [here]... | {
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https://api.github.com/repos/huggingface/transformers/issues/4499 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4499/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4499/comments | https://api.github.com/repos/huggingface/transformers/issues/4499/events | https://github.com/huggingface/transformers/pull/4499 | 622,536,853 | MDExOlB1bGxSZXF1ZXN0NDIxMzgyOTY5 | 4,499 | [T5] Fix Cross Attention position bias | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4499?src=pr&el=h1) Report\n> Merging [#4499](https://codecov.io/gh/huggingface/transformers/pull/4499?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a08652772791fdaeed6f263b1a99926ca64be5dc&el=desc) will **decrease... | 1,590 | 1,590 | 1,590 | CONTRIBUTOR | null | This PR fixes the Cross Attention position bias assignment in Class T5Stack. | {
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https://api.github.com/repos/huggingface/transformers/issues/4498 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4498/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4498/comments | https://api.github.com/repos/huggingface/transformers/issues/4498/events | https://github.com/huggingface/transformers/issues/4498 | 622,531,704 | MDU6SXNzdWU2MjI1MzE3MDQ= | 4,498 | Pre-trained electra-large model doesn't converge when fine-tuned on SST-2 | {
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"This is a general question and does not sound like a bug. With these large models it is sometimes hard to find a good set of hyperparameters to get the model to converge well. The same is true, and reported, for ALBERT. I don't think this is a bug.",
"@shanybarhom A good start would be to use the hyper-parameter... | 1,590 | 1,637 | 1,596 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): ELECTRA
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: SST-2
## To repr... | {
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"Your use case seems specific, so maybe you should try a custom Tokenizer via the `tokenizers` library. I believe the results you're getting are the intended behavior.\r\n\r\nFor example, any generic sentence where someone forgets to put a space after the period would end up tokenized incorrectly otherwise:\r\n\r\n... | 1,590 | 1,590 | 1,590 | NONE | null | 🐛 Bug
Information
Model I am using (Bert, XLNet ...): XLNet
Language I am using the model on (English, Chinese ...): Chinese
The problem arises when using: Tokenizer
the official example scripts: (give details below) N/A
my own modified scripts: (give details below) N/A
The tasks I am working on is: Any
... | {
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https://api.github.com/repos/huggingface/transformers/issues/4496 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4496/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4496/comments | https://api.github.com/repos/huggingface/transformers/issues/4496/events | https://github.com/huggingface/transformers/issues/4496 | 622,355,210 | MDU6SXNzdWU2MjIzNTUyMTA= | 4,496 | python run_glue.py with the AttributeError: 'NoneType' object has no attribute 'seek' | {
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"You really need to put more effort in how you ask questions. Just throwing in some error trace and leaving it up to us to figure out what you want or where things go wrong is not the way to go. Use [**code blocks**](https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks) and when... | 1,590 | 1,686 | 1,596 | NONE | null | # 🐛 Bug
Traceback (most recent call last):
File "/gpfs/home/bsub/anaconda3/envs/abc/lib/python3.6/site-packages/torch/serialization.py", line 191, in _check_seekable
f.seek(f.tell())
AttributeError: 'NoneType' object has no attribute 'seek'
During handling of the above exception, another exception occur... | {
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https://api.github.com/repos/huggingface/transformers/issues/4495 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4495/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4495/comments | https://api.github.com/repos/huggingface/transformers/issues/4495/events | https://github.com/huggingface/transformers/issues/4495 | 622,312,127 | MDU6SXNzdWU2MjIzMTIxMjc= | 4,495 | ❓ [BART] Why Decoder Layer Normalization is applied only at the last layer ? | {
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"That `layer_norm` should be None in `bart-large*`.\r\nSee [this comment](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_bart.py#L266)\r\n\r\nNo final `layer_norm` was applied before `mbart` was added, afaict."
] | 1,590 | 1,590 | 1,590 | CONTRIBUTOR | null | # ❓ Questions & Help
It seems this line :
https://github.com/huggingface/transformers/blob/efbc1c5a9d96048ab11f8d746fe51107cb91646f/src/transformers/modeling_bart.py#L524
was modified when MBART was added.
---
Before, Layer Normalization was applied after **all** layers of the decoder (_similar to the enc... | {
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https://api.github.com/repos/huggingface/transformers/issues/4494 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4494/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4494/comments | https://api.github.com/repos/huggingface/transformers/issues/4494/events | https://github.com/huggingface/transformers/issues/4494 | 622,222,502 | MDU6SXNzdWU2MjIyMjI1MDI= | 4,494 | Incorporate HuggingFace 'nlp' library in examples | {
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"Love this idea. @thomwolf @julien-c what do you guys think about adding `nlp` as a dependency in `examples/requirements.txt`",
"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"
] | 1,590 | 1,596 | 1,596 | CONTRIBUTOR | null | # 🚀 Feature request
I propose we replace the custom data downloading/preprocessing logic found within the examples directory with the new [**HuggingFace `nlp` Library**](https://github.com/huggingface/nlp) where applicable.
## Motivation
The examples directory is filled with custom shell scripts that download... | {
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https://api.github.com/repos/huggingface/transformers/issues/4493 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4493/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4493/comments | https://api.github.com/repos/huggingface/transformers/issues/4493/events | https://github.com/huggingface/transformers/pull/4493 | 622,216,265 | MDExOlB1bGxSZXF1ZXN0NDIxMTI0OTg4 | 4,493 | Use args.per_gpu_train_batch_size instead of args.train_batch_size in… | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4493?src=pr&el=h1) Report\n> Merging [#4493](https://codecov.io/gh/huggingface/transformers/pull/4493?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/865d4d595eefc8cc9cee58fec9179bd182be0e2e&el=desc) will **increase... | 1,590 | 1,590 | 1,590 | CONTRIBUTOR | null | … Trainer.
It appears that this is preferred, per https://github.com/huggingface/transformers/blob/master/src/transformers/training_args.py. This also matches the calculation which is printed referring to batch size at https://github.com/huggingface/transformers/blob/master/src/transformers/trainer.py#L432.
As a ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4492 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4492/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4492/comments | https://api.github.com/repos/huggingface/transformers/issues/4492/events | https://github.com/huggingface/transformers/issues/4492 | 622,141,936 | MDU6SXNzdWU2MjIxNDE5MzY= | 4,492 | Cannot load reformer-enwik8 tokenizer | {
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"Hi. This is not a bug but is expected: since the model works on the character level, a tokenizer is not \"required\". You can read more in [the model card](https://huggingface.co/google/reformer-enwik8#reformer-language-model-on-character-level-and-trained-on-enwik8) on how you can encode/decode your data.",
"@e... | 1,590 | 1,615 | 1,590 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Reformer tokenizer
## To reproduce
Steps to reproduce the behavior:
1. Try to load the pretrained reformer-enwik8 tokenizer with `AutoTokenizer.from_pretrained("google/reformer-enwik8")`
This is the error I got:
```
OSError ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4491 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4491/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4491/comments | https://api.github.com/repos/huggingface/transformers/issues/4491/events | https://github.com/huggingface/transformers/issues/4491 | 622,130,895 | MDU6SXNzdWU2MjIxMzA4OTU= | 4,491 | Windows: Can't find vocabulary file for MarianTokenizer | {
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"I cannot reproduce this. This works for me (same environment except Python 3.8 which should not make a difference). Can you try again but force_overwrite potentially corrupt files?\r\n\r\n```python\r\ntok = MarianTokenizer.from_pretrained(mname, force_download=True)\r\n```",
"Hi, \n\nI rebased the transformers p... | 1,590 | 1,593 | 1,592 | NONE | null | # 🐛 Bug MarianTokenizer.from_pretrained() fails in Python 3.6.4 in Windows 10
## Information
Occurs with using the example here: [https://huggingface.co/transformers/model_doc/marian.html?highlight=marianmtmodel#transformers.MarianMTModel](huggingface.co/transformers/model_doc/marian.html?highlight=marianmtmodel#t... | {
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https://api.github.com/repos/huggingface/transformers/issues/4490 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4490/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4490/comments | https://api.github.com/repos/huggingface/transformers/issues/4490/events | https://github.com/huggingface/transformers/issues/4490 | 622,130,080 | MDU6SXNzdWU2MjIxMzAwODA= | 4,490 | How to load a pruned Albert model with from_pretrained()? | {
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"Now I'm using head_mask instead of prune_heads. So, I didn't actually prune heads."
] | 1,590 | 1,590 | 1,590 | NONE | null | # ❓ Questions & Help
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4489?src=pr&el=h1) Report\n> Merging [#4489](https://codecov.io/gh/huggingface/transformers/pull/4489?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/14cb5b35faeda7881341656aacf89d12a8a7e07b&el=desc) will **decrease... | 1,589 | 1,590 | 1,590 | CONTRIBUTOR | null | I think I found a small bug in the `load_graph_from_args` function in `convert_graph_to_onnx.py` as it accepts a tokenizer as input but doesn't pass it on to the pipeline inside the function.
Love the library 🤗 | {
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https://api.github.com/repos/huggingface/transformers/issues/4488 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4488/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4488/comments | https://api.github.com/repos/huggingface/transformers/issues/4488/events | https://github.com/huggingface/transformers/pull/4488 | 621,879,693 | MDExOlB1bGxSZXF1ZXN0NDIwODQ2MzE0 | 4,488 | Make changes to german-bert vocab file more prominent | {
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- So we wanted to make the changes to the vocab more prominent in the model card
- and also support a solution where people can easily use the old version through https:/... | {
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"This is the expected behaviour: `len(tokenizer)` shows you the actual size (including the added tokens), whereas `.vocab_size` tells you the original size.\r\n\r\nhttps://github.com/huggingface/transformers/blob/a08652772791fdaeed6f263b1a99926ca64be5dc/src/transformers/tokenization_utils.py#L2285-L2290\r\n\r\nPS: ... | 1,589 | 1,628 | 1,596 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
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"Closing in favour of the better formulated question here: https://github.com/huggingface/transformers/issues/4491",
"Can anyone help with this issue: #5040 ?"
] | 1,589 | 1,592 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using MarianMT:
The problem arises when using the tokenizer with from_pretrained
## To reproduce
from transformers import MarianTokenizer, MarianMTModel
src = 'fr' # source language
trg = 'en' # target language
sample_text = "où est l'arrêt de bus ?"
mname = f'Hel... | {
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"Hi, could you please post a code sample and a textual error, rather than an image? Thanks.",
"@LysandreJik yes, its very simple my code I just trying to run a transformers example.\r\n\r\n if __name__ == '__main__':\r\n import ipywidgets as widgets\r\n from transformers.pipelines import pip... | 1,589 | 1,618 | 1,596 | NONE | null | # 🐛 Bug
Hello, I cant use any roberta model with pipeline('question-answering'), someone can help me in how to fix this issue?
OBS=This error appears just when I use Roberta models.
ERROR:
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"@dimi1357 out of curiosity, what does training this look like?",
"> @dimi1357 out of curiosity, what does training this look like?\r\n\r\nThis is my training loop:\r\n```python\r\nx, encoder_attention_mask, y, decoder_attention_mask, _ = batch\r\nx = x.to(self.device)\r\ny = y.to(self.device)\r\nencoder_attentio... | 1,589 | 1,707 | null | NONE | null | # 🚀 Feature request
Hi,
I am trying to add the option of using GPT2 as the decoder in the EncoderDecoder model, which only support
## Motivation
For a generation problem, it usually better to use GPT2 as the decoder, over BERT.
## Your contribution
I've made the following changes in `modeling_gpt2.py... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4482?src=pr&el=h1) Report\n> Merging [#4482](https://codecov.io/gh/huggingface/transformers/pull/4482?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/efbc1c5a9d96048ab11f8d746fe51107cb91646f&el=desc) will **not chan... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | {
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```
2020-05-19T17:01:17.3352437Z [gw0] linux -- Python 3.7.6 /home/hf/actions-r
2020-05-19T17:01:17.3354221Z @slow
2020-05-19T17:01:17.3354825Z def test_sequence_builders(self):
2020-05-19T17:01:17.3356512Z > tokenizer = self.tokenizer_class.from_pretrained("bert-base-j... | {
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"@patrickvonplaten Thank you your awesome work. I´m super excited about a char-lm. \r\nI´m trying to can train the \"reformer\" model, using the \"google/reformer-enwik8\".\r\n\r\nBut using this script or the run_language_modeling.py I get the error about the lack of tokenizer ( that is expected to a char only LM)... | 1,589 | 1,593 | 1,593 | MEMBER | null | Trainer currently expects every model to have a tokenizer. The reformer: `google/reformer-enwik8` is a char lm which does not require a tokenizer. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4479?src=pr&el=h1) Report\n> :exclamation: No coverage uploaded for pull request base (`master@18d233d`). [Click here to learn what that means](https://docs.codecov.io/docs/error-reference#section-missing-base-commit).\n> The diff coverage is `n/a`.\n... | 1,589 | 1,590 | 1,590 | CONTRIBUTOR | null | the `new_head_mask` index assignment operation makes it become a non-leaf node in the following gradient computation, resulting in grad is None bug as mentioned in #3895
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"I have the same problem, but I'm not sure if it's really a problem. I thought the extreme speed before the fix was because it wasn't training properly, and that the slower speed now is supposed to be this way, but that's just my guess.",
"Hi, you're right @LeonieWeissweiler. Previous to that fix, the optimizer w... | 1,589 | 1,596 | 1,596 | CONTRIBUTOR | null | # ❓ Questions & Help
On master, after applying the fix of #4450, the training on 8 TPU cores is much slower.
* Before the fix : **20 min / epoch (8 iterations / s)**
* After the fix : **1h30 / epoch (2~3 iterations / s)**
Of course the training before the fix was not working (loss was not decreasing).
But ... | {
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Fix #4451 | {
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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",
"@misrasaurabh1 What solution do you use now for this encoding dialog data problem?",
"I use something like\r\n`self.tokenizer.encode(... | 1,589 | 1,686 | 1,604 | CONTRIBUTOR | null | # 🚀 Feature request
Current tokenizer encode variants ( encode, batch_encode, batch_encode_plus) handle longer sequences than max_length by overflowing tokens from the right hand side and thus restricting the length to max_length. This feature request is to allow an option for the tokenizer encode methods to overfl... | {
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"Hi @rjsaito we are actually moving to serving all our files from the cloudfront powered cdn.huggingface.co",
"Awesome! Do you have a current ETA when this change would be in place?",
"It's already in place for model weights.",
"This issue has been automatically marked as stale because it has not had recent a... | 1,589 | 1,596 | 1,596 | NONE | null | Is there any plans for the s3 buckets currently hosting the model files to migrate from the current "Path-Style Request" format to a "Virtual Hosted-Style Request" format?
Path-Style URLs follow the following format (s3.amazonaws.com/* OR s3.Region.amazonaws.com/*). For example, today the model config file for 'bert... | {
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"Signature is of `addcdiv_` is different between Pytorch 1.4 and 1.5\r\n\r\nhttps://pytorch.org/docs/1.4.0/tensors.html?highlight=addcdiv#torch.Tensor.addcdiv\r\nhttps://pytorch.org/docs/stable/tensors.html?highlight=addcdiv_#torch.Tensor.addcdiv\r\n\r\nI guess as long as Pytorch 1.4 is supported by `transformers` ... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | Remove warning of deprecated overload of `addcdiv_`
Fix #4451 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4473?src=pr&el=h1) Report\n> Merging [#4473](https://codecov.io/gh/huggingface/transformers/pull/4473?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/48c3a70b4eaedab1dd9ad49990cfaa4d6cb8f6a0&el=desc) will **decrease... | 1,589 | 1,590 | 1,590 | CONTRIBUTOR | null | Here is a tutorial notebook I created for fine-tuning the DialoGPT on a Spanish conversation dataset. It shows how to prepare a dataset that conforms to the necessary style of the original DialoGPT dataset and how to train it using a GPU provided by Google Colab. Sadly it is not using the newer Trainer that Huggingface... | {
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"This is not a bug but expected behaviour. The length of the tokenized input is only calculated after padding.\r\n\r\nhttps://github.com/huggingface/transformers/blob/a08652772791fdaeed6f263b1a99926ca64be5dc/src/transformers/tokenization_utils.py#L1981-L1982\r\n\r\nPerhaps you are right, though, and it would be mor... | 1,589 | 1,596 | 1,596 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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"by the way, could you add a \r\n\r\n```\r\n---\r\nlanguage: ukrainian\r\n---\r\n```\r\n\r\nmetadata block on top, for the model to be surfaced in search etc.?",
"Sure, I’ll add it\n\nOn Wed, 20 May 2020 at 18:05, Julien Chaumond <notifications@github.com>\nwrote:\n\n> by the way, could you add a\n>\n> ---\n> lan... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | Create model card for "Tereveni-AI/gpt2-124M-uk-fiction" model | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4467?src=pr&el=h1) Report\n> Merging [#4467](https://codecov.io/gh/huggingface/transformers/pull/4467?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/07dd7c2fd8996fec2979555437dfeff0d38cbf28&el=desc) will **decrease... | 1,589 | 1,590 | 1,590 | MEMBER | null | Similarly to when saving a model state dict, the optimizer and scheduler should be saved using `xm.save` and behind an `xm.rendezvous`.
Additional fix: `pl.ParallelLoader` is not a `torch.utils.data.DataLoader`, and, therefore, must be reinitialized at each epoch. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4464?src=pr&el=h1) Report\n> Merging [#4464](https://codecov.io/gh/huggingface/transformers/pull/4464?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8f1d0471489352ec01556ae61f8e8246002bbc58&el=desc) will **increase... | 1,589 | 1,589 | 1,589 | MEMBER | null | This PR:
- adds a documentation page for Longformer. @ibeltagy - it's best to read it using this link I think: https://github.com/huggingface/transformers/pull/4464/files?short_path=3909947#diff-3909947f36862a1731195bf05c85c64c.
- fixes a typo to correctly render the pretrained models doc page
- changes the A... | {
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"Looks good!\r\n\r\nI just improved consistency with other scripts we have (in particular, `run_ner.py`) by:\r\n- using an enum instead of two boolean flags\r\n- I also always append the actual label name in the predictions file, which removes the need for a new arg\r\n\r\nLet me know if that works for you and I'll... | 1,589 | 1,590 | 1,590 | CONTRIBUTOR | null | By simply fine-tune robterta-large with 3k steps on several tasks, achieved:
Task | Metrics | Score
-- | -- | --
Microsoft Research Paraphrase Corpus | F1 / Accuracy | 91.5/88.6
Semantic Textual Similarity Benchmark | Pearson-Spearman Corr | 90.7/90.2
Quora Question Pairs | F1 / Accuracy | 69.5/87.3
Recognizi... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4462?src=pr&el=h1) Report\n> Merging [#4462](https://codecov.io/gh/huggingface/transformers/pull/4462?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8f1d0471489352ec01556ae61f8e8246002bbc58&el=desc) will **increase... | 1,589 | 1,589 | 1,589 | MEMBER | null | @patrickvonplaten
This is the second notebook which shows how to fine-tune T5 for multiple tasks with text-to-text approach (IMDB, emotion classification, SWAG) that we discussed in issue #4426 . I didn't find emotion and SWAG dataset in the `nlp` library so I decided to keep my original dataset code to keep everythi... | {
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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"
] | 1,589 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Transformer-XL
Language I am using the model on (English, Chinese ...): WikiText-103 (English)
The problem arises when using:
* [x] the official example scripts: `run_transfo_xl.py` (give details below)
* [ ] my own modified scripts: (give detail... | {
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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"
] | 1,589 | 1,651 | 1,595 | MEMBER | null | - Use functional as much as possible instead of creating a class instance everytime
- Precompute and store the attention scaling factor to avoid `1/sqrt(...)` every forward
- Refactor Self-Attention to group QKV weights and and increase hardware density | {
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] | 1,589 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Transformer-XL (`transfo-xl-wt103`)
Language I am using the model on (English, Chinese ...): WikiText-103 (English)
The problem arises when using:
* [x] the official example scripts: `run_transfo_xl.py` (give details below)
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`AttributeError: 'BertForQuestionAnswering' object has no attribute 'classifier'`
As pointed out in the thread it should be "qa_outputs" and not "classifier" for this functionality to... | {
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"Thanks for the extensive bug report! I can confirm that you are correct and that the issue does not occur when using the slow option.\r\n\r\nPinging @n1t0 "
] | 1,589 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): BERT FastTokenizer
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [X] my own modified scripts: (give details below)
The tasks I am working on is:
* [X] my own task or dataset: (give details bel... | {
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"cc @jplu, might be of interest :)",
"Hello!\r\n\r\nLike this there is not enough details to see what is the issue. Can you provide the piece of code you are trying to run? plz :)\r\n\r\nAlso if you are looking for how to properly use the trainer I suggest you to look at the already existing examples:\r\n\r\n- [Q... | 1,589 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
### Model I am using Bert.
### The problem arises when using:
I'm using the run_language_modling.py to fine-tuning with (Tf2.0.0/Tf2.2.0). Of course i modify the script.
I use TFAutoModelWithLMHead,TFTrainer in this repo to build my script.
When i'm traning,here is the problem.
`ValueError: Trying to... | {
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https://api.github.com/repos/huggingface/transformers/issues/4455 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4455/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4455/comments | https://api.github.com/repos/huggingface/transformers/issues/4455/events | https://github.com/huggingface/transformers/issues/4455 | 620,892,040 | MDU6SXNzdWU2MjA4OTIwNDA= | 4,455 | get output from a particular layer of pre-trained transformer (xlnet) | {
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"Sure, these are called hidden states! Here's the [documentation of the XLNet model](https://huggingface.co/transformers/model_doc/xlnet.html?highlight=output_hidden_states#transformers.XLNetModel).\r\n\r\nPlease note the third return:\r\n\r\n> **hidden_states (tuple(torch.FloatTensor), optional, returned when conf... | 1,589 | 1,590 | 1,590 | NONE | null | As the title, how can I do this in PyTorch version of pre-trained transformer? | {
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"Can you check the Dmoz[Dmoz] \r\nthe database in sql he cost 1000$ to change it (https://idmoz.org) ",
"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"
] | 1,589 | 1,595 | 1,595 | NONE | null | Hi,
Hope you are all well !
Still quite a newbie with transformers, I wanted to know how could it be possible to build a web page classifier with the DMOZ dump and to classify them into categories in several languages.
Thanks in advance for any insights or inputs on that question.
Cheers,
X | {
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"Hello!\r\n\r\nIf you want to train over SQuAD I suggest you to use the [run_tf_squad.py](https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_tf_squad.py) example that uses the TF Trainer or to check the following [Colab](https://colab.research.google.com/github/huggingface/nlp/b... | 1,589 | 1,592 | 1,590 | NONE | null | # 🐛 Bug
## Information
I'm using TFBertForSequenceClassification on SQUaD data v1 data.
The problem arises when using:
* [ ] Both official example scripts and my own modified scripts
The tasks I am working on is:
* [ ] an official SQUaD v1 data and my own SQUaD v1 data.
## To reproduce
### Try 1 - w... | {
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"Not expected, but shouldn't be an issue. Feel free to open a PR swapping args in https://github.com/huggingface/transformers/blob/31eedff5a0fc47d60609089627af6698c21da88d/src/transformers/optimization.py#L165"
] | 1,589 | 1,590 | 1,590 | CONTRIBUTOR | null | # ❓ Questions & Help
When running the [official Colab example of GLUE](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/trainer/01_text_classification.ipynb), during training I receive a `UserWarning` :
```
/pytorch/torch/csrc/utils/python_arg_parser.cpp:756: UserWarning: This over... | {
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Thanks @shaoyent for diagnosing the issue | {
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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"
] | 1,589 | 1,595 | 1,595 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"Hello!\r\n\r\nThanks for the fix! Just one suggestion above :)",
"Thanks for the feedback! Sounds like a good idea, added that. Are the failing ci tests an issue? Everything passes on my machine. ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4448?src=pr&el=h1) Report\n> Merging [#4448](ht... | 1,589 | 1,590 | 1,590 | CONTRIBUTOR | null | Fixes #4360
Layer Norm is formated in the wrong way for TensorFlow. This causes it not to be excluded from weight decay in the [run_tf_glue.py](https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_tf_glue.py) script.
This pr simply formats the string to fit the TensorFlow nam... | {
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## Information
Model I am using (Bert, XLNet ...): ALL TF generate models
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
* [ ] all genera... | {
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@julien-c | {
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https://api.github.com/repos/huggingface/transformers/issues/4445 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4445/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4445/comments | https://api.github.com/repos/huggingface/transformers/issues/4445/events | https://github.com/huggingface/transformers/issues/4445 | 620,435,716 | MDU6SXNzdWU2MjA0MzU3MTY= | 4,445 | Generation with EncoderDecoder Model | {
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"Do we have any updates on this issue?",
"I will take a look at this at the end of next week - will get to you! ",
"> I will take a look at this at the end of next week - will get to you!\r\n\r\nThanks a lot!",
"Hi @manzar96,\r\nMultiple bugs were fixed in #4680 . Can you please take a look whether this error... | 1,589 | 1,596 | 1,596 | NONE | null | # ❓ Questions & Help
Hi,
I am using the EncoderDecoder Model and I would like to use the generate method for sequence generation. As I have read in docs, the generate method can be used with any Pretrained HF model with LM head on top.
So wrapping a pretrained LM model (e.g. GPT2LMHeadModel, BertForMaskedLM) (an... | {
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https://api.github.com/repos/huggingface/transformers/issues/4444 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4444/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4444/comments | https://api.github.com/repos/huggingface/transformers/issues/4444/events | https://github.com/huggingface/transformers/issues/4444 | 620,400,246 | MDU6SXNzdWU2MjA0MDAyNDY= | 4,444 | model.save() does not save keras model that includes DIstillBert layer | {
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"Same issue",
"Hi, we don't fully support saving/loading these models using keras' save/load methods (yet). In the meantime, please use `model.from_pretrained` or `model.save_pretrained`, which also saves the configuration file.",
"Hello @LysandreJik , \r\nThank you for the information. \r\n\r\nCould you point ... | 1,589 | 1,638 | 1,636 | NONE | null | # 🐛 Bug
## Information
I am trying to build a Keras Sequential model, where, I use DistillBERT as a non-trainable embedding layer. The model complies and fits well, even predict method works. But when I want to save it using model.save(model.h5), It fails and shows the following error:
```
> -----------------... | {
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"Update -- after hours working with this code, I somehow only now realized that the PR I linked had updates to modeling_encoder_decoder.py that fixed the issues I'm describing in part 2 of my issue, which is why the example works there.\r\n\r\nI am still confused about part 1 (and 3) however, since it does not look... | 1,589 | 1,606 | 1,606 | NONE | null | # ❓ Questions & Help
I have been attempting with various models to try to build an encoder-decoder, sequence to sequence transformer model. For the most part, I have been using BERT (bert-base-cased), but have encountered issues with various models.
The model is intended for an English to English sequence to seq... | {
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https://api.github.com/repos/huggingface/transformers/issues/4442 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4442/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4442/comments | https://api.github.com/repos/huggingface/transformers/issues/4442/events | https://github.com/huggingface/transformers/pull/4442 | 620,316,295 | MDExOlB1bGxSZXF1ZXN0NDE5NTg3NDI1 | 4,442 | [Communtiy notebooks] Fine-tuning / Training | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4442?src=pr&el=h1) Report\n> Merging [#4442](https://codecov.io/gh/huggingface/transformers/pull/4442?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d9ece8233d584cdc2eeae5165dd3329328fae328&el=desc) will **increase... | 1,589 | 1,589 | 1,589 | MEMBER | null | Proposal of how notebooks for training could be added. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4441?src=pr&el=h1) Report\n> Merging [#4441](https://codecov.io/gh/huggingface/transformers/pull/4441?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/590adb130be8e99eb638bb22136dda537b2da71d&el=desc) will **increase... | 1,589 | 1,589 | 1,589 | MEMBER | null | A proposal how we could link community notebooks.
I'm using the awesome notebook of @patil-suraj (`nlp` + `Trainer` + `transformers` :-)) as an example of how community models can be added.
@patil-suraj - could you maybe review the PR and see whether it's ok for you? | {
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https://api.github.com/repos/huggingface/transformers/issues/4440 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4440/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4440/comments | https://api.github.com/repos/huggingface/transformers/issues/4440/events | https://github.com/huggingface/transformers/issues/4440 | 620,292,238 | MDU6SXNzdWU2MjAyOTIyMzg= | 4,440 | Reformer training error | {
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"Reformer does not support `mlm` training at the moment. Please make sure you use `lm` training :-) ",
"@patrickvonplaten thanks! Is there a plan to support mlm in the near future? \r\n\r\nI assume I can just remove the mlm flag to do lm training, right? How can I tell the script to pad the input sequences to a c... | 1,589 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
When training a Reformer model from scratch, I got the following error:
**TypeError: forward() got an unexpected keyword argument 'masked_lm_labels'**
## Information
I am trying to train a Reformer model from scratch on English documents. My data is one document per line:
The problem arises when... | {
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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"
] | 1,589 | 1,595 | 1,595 | NONE | null | Checkpoint path will be deleted when using --save_total_limit. torch.save() would not be able to store and abort. | {
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https://api.github.com/repos/huggingface/transformers/issues/4438 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4438/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4438/comments | https://api.github.com/repos/huggingface/transformers/issues/4438/events | https://github.com/huggingface/transformers/issues/4438 | 620,270,635 | MDU6SXNzdWU2MjAyNzA2MzU= | 4,438 | BERT Fine-tuning problems | {
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"Is your dataset following the SQuAD dataset format? It seems that what's making it crash is that there's no `title` entry.\r\n\r\nYou can take a look at how SQuAD is setup [here](https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json).",
"This issue has been automatically marked as stale because it h... | 1,589 | 1,595 | 1,595 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/4437 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4437/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4437/comments | https://api.github.com/repos/huggingface/transformers/issues/4437/events | https://github.com/huggingface/transformers/pull/4437 | 620,227,207 | MDExOlB1bGxSZXF1ZXN0NDE5NTE2MjMx | 4,437 | Added model cards for Romanian BERT models | {
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"Awesome, thanks for sharing\r\n\r\nhttps://huggingface.co/dumitrescustefan/bert-base-romanian-cased-v1\r\n\r\nI've added a filter for 🇷🇴 here: https://huggingface.co/models?filter=romanian"
] | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | Added model card for ``dumitrescustefan/bert-base-romanian-cased-v1`` and ``dumitrescustefan/bert-base-romanian-uncased-v1`` | {
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"> Bart doesn't use this method yet, but LGTM!\r\n\r\nYeah, I noticed that as well - it's Bert that is using it."
] | 1,589 | 1,589 | 1,589 | MEMBER | null | This PR fixes the issue: #4287.
- A test for T5 is added.
- The function self.invert_attention_mask included a if statement now so that no errors will occur when using the function in `fp16` mode. | {
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https://api.github.com/repos/huggingface/transformers/issues/4435 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4435/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4435/comments | https://api.github.com/repos/huggingface/transformers/issues/4435/events | https://github.com/huggingface/transformers/pull/4435 | 620,202,426 | MDExOlB1bGxSZXF1ZXN0NDE5NDk1NzAy | 4,435 | added model card for german-sentiment-bert | {
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"Awesome model card. Link: https://huggingface.co/oliverguhr/german-sentiment-bert",
"Thanks a lot :+1: "
] | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | I added a description for my german sentiment model. If you have any feedback or questions please let me know. | {
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https://api.github.com/repos/huggingface/transformers/issues/4434 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4434/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4434/comments | https://api.github.com/repos/huggingface/transformers/issues/4434/events | https://github.com/huggingface/transformers/issues/4434 | 620,149,232 | MDU6SXNzdWU2MjAxNDkyMzI= | 4,434 | albertModel object has no attribute bias | {
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"Hi! What is the `xxx` model? Is it one of our pre-trained checkpoints, is it an original TF checkpoint? Did this error happen in previous versions? Would you mind giving a bit of context?",
"Hi, I tried this model https://storage.googleapis.com/albert_models/albert_base_zh.tar.gz , which is new model release by ... | 1,589 | 1,593 | 1,593 | NONE | null | transformers version:2.9.0
model = AlbertModel.from_pretrained("xxx", from_tf=True)
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'key', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel
Initialize PyTorch we... | {
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https://api.github.com/repos/huggingface/transformers/issues/4433 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4433/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4433/comments | https://api.github.com/repos/huggingface/transformers/issues/4433/events | https://github.com/huggingface/transformers/pull/4433 | 620,053,168 | MDExOlB1bGxSZXF1ZXN0NDE5MzczNTA1 | 4,433 | Create README.md | {
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"Also it could be interesting to convert and also upload PyTorch weights",
"I've tried - but the script unfortunately only works for TF 1.4 - would be glad share though! "
] | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4432 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4432/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4432/comments | https://api.github.com/repos/huggingface/transformers/issues/4432/events | https://github.com/huggingface/transformers/pull/4432 | 620,028,633 | MDExOlB1bGxSZXF1ZXN0NDE5MzUzNDkz | 4,432 | Tag onnx export tests as slow | {
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This PR marks both PyTorch & TensorFlow as slow, and keeps all the others (fast) as non-slow. | {
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https://api.github.com/repos/huggingface/transformers/issues/4431 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4431/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4431/comments | https://api.github.com/repos/huggingface/transformers/issues/4431/events | https://github.com/huggingface/transformers/pull/4431 | 620,022,817 | MDExOlB1bGxSZXF1ZXN0NDE5MzQ4NzYz | 4,431 | Adding optimizations block from ONNXRuntime. | {
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"cc @tianleiwu ",
"use_external_data_format has some side-effect we'd like to mitigate here, I set to False by default and let the possibility for the user to override through CLI args."
] | 1,589 | 1,589 | 1,589 | MEMBER | null | cc @EmmaNingMS | {
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https://api.github.com/repos/huggingface/transformers/issues/4430 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4430/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4430/comments | https://api.github.com/repos/huggingface/transformers/issues/4430/events | https://github.com/huggingface/transformers/issues/4430 | 620,009,014 | MDU6SXNzdWU2MjAwMDkwMTQ= | 4,430 | 🐛 Weird learning rate with TPU Trainer | {
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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"
] | 1,589 | 1,595 | 1,595 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): **ELECTRA**
Language I am using the model on (English, Chinese ...): **English**
The problem arises when using:
* [ ] the official example scripts:
* [x] my own modified scripts:
The tasks I am working on is:
* [ ] an official GLUE/SQUaD ta... | {
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https://api.github.com/repos/huggingface/transformers/issues/4429 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4429/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4429/comments | https://api.github.com/repos/huggingface/transformers/issues/4429/events | https://github.com/huggingface/transformers/issues/4429 | 619,974,661 | MDU6SXNzdWU2MTk5NzQ2NjE= | 4,429 | mbart config.json missing | {
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"fairseq doesn't use config.json.\r\n\r\n`BartConfig.from_pretrained('mbart-large-en-ro').to_json_file('config.json')` gets the config.json for English-Romanian, which is the only mbart checkpoint that's usable in this repository."
] | 1,589 | 1,589 | 1,589 | NONE | null | I downloaded mbart from fairseq, there are dict.txt, model.pt, sentence.bpe.model in it but no config.json, where can we get it (and other necessary missing files)?
I use mbart as pretrained model.
Is bart-large trained on multilingual data?
Anyone has compared bart with t5? | {
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https://api.github.com/repos/huggingface/transformers/issues/4428 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4428/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4428/comments | https://api.github.com/repos/huggingface/transformers/issues/4428/events | https://github.com/huggingface/transformers/issues/4428 | 619,930,847 | MDU6SXNzdWU2MTk5MzA4NDc= | 4,428 | How to extract the best candidate after token classification? | {
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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"
] | 1,589 | 1,595 | 1,595 | NONE | null | Let's assume the model predicts the following for an input sequence.
```
The O
creation. O
date O
is O
27 B-DATE
Aug I-DATE
2020 I-DATE
and O
update. O
date. O
is O
01-09-2020 B-DATE
```
How do you pick the best candidate for **creation date** from logist values? | {
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https://api.github.com/repos/huggingface/transformers/issues/4427 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4427/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4427/comments | https://api.github.com/repos/huggingface/transformers/issues/4427/events | https://github.com/huggingface/transformers/pull/4427 | 619,904,711 | MDExOlB1bGxSZXF1ZXN0NDE5MjU0NzAx | 4,427 | Refactored the README.md file | {
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"Ok for you @savasy?",
"Ya for sure @julien-c \r\nthanks a lot",
"Thanks @girishponkiya!",
"Thanks @girishponkiya !"
] | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4426 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4426/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4426/comments | https://api.github.com/repos/huggingface/transformers/issues/4426/events | https://github.com/huggingface/transformers/issues/4426 | 619,879,741 | MDU6SXNzdWU2MTk4Nzk3NDE= | 4,426 | Lack of funetune examples for T5 model | {
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"I've setup T5 fine-tuning using lightning and also HF's new Trainer. I can submit a PR for that. Would like to hear from @patrickvonplaten ",
"It would be awesome if you could open a PR for this! ",
"Great! I'll organize my examples and submit PR as soon as I finish it.\r\n\r\n ",
"@Chenyzsjtu @patrickvonpl... | 1,589 | 1,603 | 1,591 | NONE | null | # 🚀 Feature request
It seems like examples under transformers/examples doesn't support T5 except for translation.
## Motivation
We need more examples! It should be easy for some simple benchmarks.
## Your contribution
None currently.. But I am working on it!
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"https://huggingface.co/blog/how-to-train",
"Thank you for your swift reply :)\r\nHow about Electra model? Is it possible to pretrain from scratch as well?",
"Did you read the article? Section 3",
"Yup, I've read Section 3. :)\r\nAs long as I know Electra uses replaced token detection with discriminator and g... | 1,589 | 1,628 | 1,601 | NONE | null | Hi,
I've been finetuning lots of tasks using this repo. Thanks :)
But I couldn't find any pretraining from scratch examples.
Please let me know if you guys have any advices on that.
It would be very helpful for me to do my research.
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"Yes, looks good now"
] | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | - add a citation.
- modify the table of the BLUE benchmark.
The table of the first version was not displayed correctly on https://huggingface.co/seiya/oubiobert-base-uncased.
Could you please confirm that this fix will allow you to display it correctly? | {
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https://api.github.com/repos/huggingface/transformers/issues/4423 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4423/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4423/comments | https://api.github.com/repos/huggingface/transformers/issues/4423/events | https://github.com/huggingface/transformers/issues/4423 | 619,822,455 | MDU6SXNzdWU2MTk4MjI0NTU= | 4,423 | How to change transformers model embedding layer weights | {
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] | 1,589 | 1,595 | 1,595 | NONE | null | I trained my own tokenizer and added new words. Now I need to change the embedding size from the pretrained model. What I do is like this:
```
import transformers as tfm
import tensorflow as tf
backbone = tfm.TFRobertaModel.from_pretrained(PRETRAINED_PATH, output_hidden_states=True)
add_emb = tf.random.uniform... | {
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This PR renames the arguments in the docstring and adds an explanation that those arguments can also be accessed via their properties.
To not break backward compatibility, rena... | {
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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"
] | 1,589 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): BERT
Language I am using the model on (English, Chinese ...): English
The problem arises when using: Tokenizer
* [ ] the official example scripts: (give details below) N/A
* [ ] my own modified scripts: (give details below) N/A
The tasks I am ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4419 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4419/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4419/comments | https://api.github.com/repos/huggingface/transformers/issues/4419/events | https://github.com/huggingface/transformers/pull/4419 | 619,803,944 | MDExOlB1bGxSZXF1ZXN0NDE5MTc4ODc3 | 4,419 | [TF generate] Fix issue for batch output generation of different output length. | {
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A wrong variable was used in TF generate to determine the sentence length in the case when multiple outputs have different sentence lengths and the max sentence lengths is < the user defined `max_length`.
Also, both PT and TF generate are refactored a bit so that the `cur_length` ... | {
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"You can pretty easily \"freeze\" parameters you don't want to backpropagate against, in PyTorch: \r\n\r\n```python\r\nfor param in parameters:\r\n param.requires_grad = False\r\n```",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further act... | 1,589 | 1,595 | 1,595 | CONTRIBUTOR | null | If I have a system, where I want to train many text classifiers for many users, how could I go about it with the transformers library in a scalable way?
Right now I would have to run let's say a 10min training per user on a RTX 2080 ti for Albert for the dataset I have. That doesn't scale if I have thousands of users.... | {
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"This was fixed on master on Friday, can you try pulling from master again?"
] | 1,589 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
I was trying to reproduce the GLUE fine-tuning example (https://huggingface.co/transformers/examples.html#fine-tuning-example) when I ran into this error:
```
File "~/anaconda3/lib/python3.7/site-packages/transformers/optimization.py", line 155, in step
exp_avg.mul_(beta1).add_(... | {
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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"
] | 1,589 | 1,595 | 1,595 | NONE | null | As I understand GPT2 uses TextDataset as a loader and it produces the example list in block sizes. So say we have a sentence "**we are in a climate crisis**" and have block size 3. So this will produce the example list as
`ex = [["we","are","in"],["a","climate","crisis"]]`
So in such a scenario when calculating ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4414 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4414/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4414/comments | https://api.github.com/repos/huggingface/transformers/issues/4414/events | https://github.com/huggingface/transformers/issues/4414 | 619,733,445 | MDU6SXNzdWU2MTk3MzM0NDU= | 4,414 | Get BERT sentence encoding | {
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"I believe you can't do like that, you have to run the model just as is with all the necessary inputs(pertaining to the sentence) as mentioned in the docs : https://huggingface.co/transformers/model_doc/bert.html#transformers.BertModel\r\nand then add the configuration : `config.output_hidden_states=True` for getti... | 1,589 | 1,595 | 1,595 | NONE | null | I am trying to access to encoding of sentences in the vaious layers in pre-trained BERT model.
So it should be something like this:
```
sentence = 'We bought a new car'
bert_encoder = load_encoder('bert-base-uncased')
enc = bert_encoder.encode(sentence)
enc.get_layer[0] #this is the first layer
enc.get_layer[-... | {
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