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https://api.github.com/repos/huggingface/transformers/issues/3313 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3313/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3313/comments | https://api.github.com/repos/huggingface/transformers/issues/3313/events | https://github.com/huggingface/transformers/issues/3313 | 583,159,176 | MDU6SXNzdWU1ODMxNTkxNzY= | 3,313 | KeyError in GLUE data tokenization with RoBERTA | {
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"I also have this issue when i run run_multiple_choice.py in RACE data with RoBERTA.",
"I get the same error when I try to fine-tune Squad",
"Tagging @LysandreJik ",
"> \r\n> \r\n> I also have this issue when i run run_multiple_choice.py in RACE data with RoBERTA.\r\n\r\nSame here. Any solution?",
"@nieling... | 1,584 | 1,585 | 1,585 | CONTRIBUTOR | null | # 🐛 Bug
I'm getting a KeyError [here](https://github.com/huggingface/transformers/blob/master/src/transformers/data/processors/glue.py#L94) when using RoBERTa in [examples/run_glue.py](https://github.com/huggingface/transformers/blob/master/examples/run_glue.py) and trying to access `'token_type_ids'` while preproc... | {
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https://api.github.com/repos/huggingface/transformers/issues/3312 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3312/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3312/comments | https://api.github.com/repos/huggingface/transformers/issues/3312/events | https://github.com/huggingface/transformers/issues/3312 | 583,143,521 | MDU6SXNzdWU1ODMxNDM1MjE= | 3,312 | GPT2Tokenizer doesn't include BOS or EOS token | {
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"Accidental double post -- closing this in favour of #3311 "
] | 1,584 | 1,584 | 1,584 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT-2
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
*... | {
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https://api.github.com/repos/huggingface/transformers/issues/3311 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3311/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3311/comments | https://api.github.com/repos/huggingface/transformers/issues/3311/events | https://github.com/huggingface/transformers/issues/3311 | 583,143,221 | MDU6SXNzdWU1ODMxNDMyMjE= | 3,311 | GPT2 -- build_inputs_with_special_tokens lacking BOS and EOS tokens. | {
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"Hi @moinnadeem, \r\n\r\nThanks for posting this! \r\nAs it is implemented in the moment, you are right, GPT2 Tokenizer does not add the BOS in the beginning nor the EOS token in the end. \r\nYou can see e.g. that the XLNet tokenizer has a method that adds special tokens to the encoded input string (see https://git... | 1,584 | 1,705 | 1,606 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT-2
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
*... | {
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https://api.github.com/repos/huggingface/transformers/issues/3310 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3310/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3310/comments | https://api.github.com/repos/huggingface/transformers/issues/3310/events | https://github.com/huggingface/transformers/issues/3310 | 583,087,221 | MDU6SXNzdWU1ODMwODcyMjE= | 3,310 | Add sample softmax possibility to TransfoXL model for TransfoXL training | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,584 | 1,590 | 1,590 | MEMBER | null | # 🚀 Feature request
TransfoXL samples the logits during training if required. At the moment TransfoXL can only be used whithout sampling from the logits during training. A partrly finished implementation can be found under the branch: `add_sampling_and_training_to_transfo_xl_models` .
## Motivation
To be able... | {
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https://api.github.com/repos/huggingface/transformers/issues/3309 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3309/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3309/comments | https://api.github.com/repos/huggingface/transformers/issues/3309/events | https://github.com/huggingface/transformers/pull/3309 | 583,048,379 | MDExOlB1bGxSZXF1ZXN0Mzg5ODY2MDY1 | 3,309 | Create model card for CodeBERTaPy | {
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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"
] | 1,584 | 1,590 | 1,590 | NONE | null | I am using ``AutoModel`` to load ``distilbert-base-uncased`` and save the fine-tuned model after training using ``model.save_pretrained('path_to_save')``. However, when I load the fine-tuned model using ``AutoModel.from_pretrained('path_to_the_saved_model')``, it extracts 12 layers instead of 6 layers. I also checked ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3307 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3307/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3307/comments | https://api.github.com/repos/huggingface/transformers/issues/3307/events | https://github.com/huggingface/transformers/pull/3307 | 582,897,039 | MDExOlB1bGxSZXF1ZXN0Mzg5NzM5Nzgz | 3,307 | Make sacremoses dependency optional due to GPL license. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3306?src=pr&el=h1) Report\n> Merging [#3306](https://codecov.io/gh/huggingface/transformers/pull/3306?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/68ef0a111f8740f06ca4e5a00374ec4e2adb0a6d&el=desc) will **decrease... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | {
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Maybe @srush can review this. | {
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"@anjubaoGDUT If you can provide the code in text (instead of image) that can copy and paste, it is easy to test. ",
"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"
] | 1,584 | 1,590 | 1,590 | NONE | null | 
Help~~
The above problems appear in loading the pre-trained Albert by transformers. | {
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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"
] | 1,584 | 1,590 | 1,590 | NONE | null | 
Help~
The above problems appear in loading the pre-trained Albert by transformers. Albert pre-trained model download address is https://drive.google.com/file/d/1byZQmWDgyhrLpj8oXtxBG6AA52c8IHE-/view | {
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https://api.github.com/repos/huggingface/transformers/issues/3302 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3302/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3302/comments | https://api.github.com/repos/huggingface/transformers/issues/3302/events | https://github.com/huggingface/transformers/pull/3302 | 582,694,463 | MDExOlB1bGxSZXF1ZXN0Mzg5NTc0Nzcy | 3,302 | [BART] Delete redundant unit test | {
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https://api.github.com/repos/huggingface/transformers/issues/3301 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3301/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3301/comments | https://api.github.com/repos/huggingface/transformers/issues/3301/events | https://github.com/huggingface/transformers/pull/3301 | 582,654,131 | MDExOlB1bGxSZXF1ZXN0Mzg5NTQxNTY4 | 3,301 | Add model card for Google AI's BERT Miniatures | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3301?src=pr&el=h1) Report\n> Merging [#3301](https://codecov.io/gh/huggingface/transformers/pull/3301?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/47591763137f17021928e686ef171f25c240f076&el=desc) will **decrease... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | This model card is intended to be shared among all models under google/bert_uncased_*
(We'll need some support from HuggingFace to get this card cross-linked from all models) | {
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https://api.github.com/repos/huggingface/transformers/issues/3300 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3300/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3300/comments | https://api.github.com/repos/huggingface/transformers/issues/3300/events | https://github.com/huggingface/transformers/issues/3300 | 582,552,153 | MDU6SXNzdWU1ODI1NTIxNTM= | 3,300 | ImportError: cannot import name 'BartForConditionalGeneration' | {
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"I saw that to use the examples, it has to be installed from source."
] | 1,584 | 1,584 | 1,584 | NONE | null |
## Information
Hi, I am trying to use the BART model to sumamrize a text snippet.
The problem arises when using:
* from transformers import BartTokenizer, BartConfig, BartForConditionalGeneration
## To reproduce
Steps to reproduce the behavior:
1. Installed Tensorflow 2.0 and Pytorch
2. pip install... | {
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https://api.github.com/repos/huggingface/transformers/issues/3299 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3299/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3299/comments | https://api.github.com/repos/huggingface/transformers/issues/3299/events | https://github.com/huggingface/transformers/pull/3299 | 582,522,705 | MDExOlB1bGxSZXF1ZXN0Mzg5NDMwNzA3 | 3,299 | add camembert for Question answering for examples | {
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"Wow that was quick :D "
] | 1,584 | 1,584 | 1,584 | MEMBER | null | This one might have been accidently deleted in PR #2700 I think. | {
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"Not 100% sure how this results in a \"Prettier API,\" but agree this isn't a big deal to fix downstream. (my current code explicitly sets `do_sample=True` just in case something like this happened.)\r\n\r\nIf you are creating any demo generation notebooks/tooling like Write With Transformer, I recommend explicitly... | 1,584 | 1,584 | 1,584 | MEMBER | null | This somewhat reverts the commit:
https://github.com/huggingface/transformers/commit/6c1b23554f8bb5b5e1f6c80969acab764c755678
and the decision taken in #2696
and sets the default sampling behavior of `generate()` to greedy - / beam search.
Pros:
- `False` is the more natural default value
- Prettier API (... | {
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"Yes, this will be quite hard and is not a feature that is implemented at the moment nor a feature that we plan on implementing soon. \r\n\r\nAn easy way to get what you want though, will be to clone the repo and adapt the code. You can easily add the layer outputs (e.g. `ffn_output`) you want to the `return` funct... | 1,584 | 1,589 | 1,584 | 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. -->
Is there a way to get output from any hidden layer of the model?
## Motivation
<!-- Please outline the motivation for the proposal. Is your feature ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3296 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3296/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3296/comments | https://api.github.com/repos/huggingface/transformers/issues/3296/events | https://github.com/huggingface/transformers/issues/3296 | 582,158,024 | MDU6SXNzdWU1ODIxNTgwMjQ= | 3,296 | Installation error: can not find Rust compiler | {
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"Can you please open an issue on https://github.com/huggingface/tokenizers?\r\n\r\nThanks!\r\ncc @n1t0 @mfuntowicz "
] | 1,584 | 1,584 | 1,584 | NONE | null | I used pip to install transformers like this:
pip install transformers
in the end, I got the error:
Can not find Rust compiler
while, I have installed rust on my apple computer, please tell me how to deal with the problem, thank you!
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https://api.github.com/repos/huggingface/transformers/issues/3295 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3295/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3295/comments | https://api.github.com/repos/huggingface/transformers/issues/3295/events | https://github.com/huggingface/transformers/pull/3295 | 582,128,023 | MDExOlB1bGxSZXF1ZXN0Mzg5MDkzMTUw | 3,295 | Create CodeBERTaJS model card | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3295?src=pr&el=h1) Report\n> Merging [#3295](https://codecov.io/gh/huggingface/transformers/pull/3295?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/af471ce5e8ca7c19183e70bb998561170addc276?src=pr&el=desc) will **i... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3294 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3294/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3294/comments | https://api.github.com/repos/huggingface/transformers/issues/3294/events | https://github.com/huggingface/transformers/issues/3294 | 582,088,134 | MDU6SXNzdWU1ODIwODgxMzQ= | 3,294 | BertForPreTraining should compute only <MASKED> prediction_scores | {
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"I had little modification on the source code and solve the problem. (But I may changed the behavior and the return format of class BertForPretraining)\r\n\r\n```python\r\ndef gather_indexes_auto(sequence_tensor, masked_lm_labels):\r\n \"\"\"Gathers the vectors according to masked_lm_labels over a minibatch.\r\n... | 1,584 | 1,590 | 1,590 | NONE | null | # 🚀 Feature request
In class transformers.BertForPreTraining, the forward compute all prediction_scores. In fact, we may only calculate the prediction_scores on the <MASKED> tokens to save some computational cost.
## Motivation
In source code of class BertForPreTraining:
```python
outputs = self.bert(input_ids,... | {
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https://api.github.com/repos/huggingface/transformers/issues/3292 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3292/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3292/comments | https://api.github.com/repos/huggingface/transformers/issues/3292/events | https://github.com/huggingface/transformers/issues/3292 | 581,958,138 | MDU6SXNzdWU1ODE5NTgxMzg= | 3,292 | NER Pipeline returns null | {
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"By \"it returns null\" you mean it returns an empty array? That's because it didn't identify any named entity in your sequence."
] | 1,584 | 1,585 | 1,585 | NONE | null | # 🐛 Bug
## Information
Model I am using (NER Pipeline):
Language I am using the model on (English):
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQUaD ta... | {
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"@patrickvonplaten my OS is mac OS 10.14.6, Python 3.6.10, tensorflow 2.0, transformers version is the resoruce code in github",
"Hi @policeme, which example did you use? ",
"\r\nlike this",
"@patrick... | 1,584 | 1,585 | 1,585 | NONE | null | I used example in doc, but a lot of example can't run successful, what's wrong? | {
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https://api.github.com/repos/huggingface/transformers/issues/3290 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3290/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3290/comments | https://api.github.com/repos/huggingface/transformers/issues/3290/events | https://github.com/huggingface/transformers/pull/3290 | 581,892,856 | MDExOlB1bGxSZXF1ZXN0Mzg4ODkxNTcz | 3,290 | [WIP] Lightning glue example | {
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"@srush Can you please take a look?",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3290?src=pr&el=h1) Report\n> Merging [#3290](https://codecov.io/gh/huggingface/transformers/pull/3290?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8320feec09309a94f673e1e7c... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | This PR adds an example of using Pytorch Lightning to run the GLUE benchmark. Additionally, I altered the `transformer_base.py` to use auto models and moved it to the example directory so it could be copied in by any script that wishes to use it.
Preferably, the base transformer would have subclasses for the differe... | {
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https://api.github.com/repos/huggingface/transformers/issues/3289 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3289/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3289/comments | https://api.github.com/repos/huggingface/transformers/issues/3289/events | https://github.com/huggingface/transformers/issues/3289 | 581,775,502 | MDU6SXNzdWU1ODE3NzU1MDI= | 3,289 | GPT-2 attention_mask reshaping uses input_ids first dimension | {
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"Hey @lazarevskiVsg, thanks a lot for pointing this out!\r\nIt should be fixed now :-) "
] | 1,584 | 1,584 | 1,584 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT-2
## To reproduce
Use attention_mask in **GPT2LMHead**, while feeding **inputs_embeds** instead of **input_ids**
The code fails because line 427 of modeling_gpt2.py uses input_ids first dimension to reshape the mask
```
if attention_ma... | {
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https://api.github.com/repos/huggingface/transformers/issues/3288 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3288/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3288/comments | https://api.github.com/repos/huggingface/transformers/issues/3288/events | https://github.com/huggingface/transformers/issues/3288 | 581,701,674 | MDU6SXNzdWU1ODE3MDE2NzQ= | 3,288 | Dockerhub images huggingface/transformers_cpu for version 2.5.1 has version 2.5.0 installed | {
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"Should be fixed, I'll push updated images for all the others Dockerfile in the next hours. \r\n\r\nThanks for reporting @edwardcqian ",
"I'm closing, feel free to reopen if I missed something 👍 "
] | 1,584 | 1,584 | 1,584 | NONE | null | # 🐛 Bug
## Information
Model I am using any model introduced in 2.5.1
The problem arises when using:
pulling `huggingface/transformers_cpu:2.5.1` from dockerhub
## To reproduce
Steps to reproduce the behavior:
1. pull docker image from dockerhub
2. run docker container
3. run `pip freeze` to see `... | {
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"The tokenizer adds special tokens (here, specific to BERT) at the beginning and end of the sentence. \r\n\r\nYou can check that with:\r\n```python\r\ntokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')\r\nlen(tokenizer.encode(TEXT)) == 18\r\n```",
"@julien-c is there any way to avoid the special token... | 1,584 | 1,584 | 1,584 | NONE | null | Hi everyone,
I'm not sure if it is a bug or if I simply overlooking something so I did not want to submit a bug report yet. I have the following example code:
```
from transformers import pipeline, AutoTokenizer
import numpy as np
tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased',
add_special_to... | {
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https://api.github.com/repos/huggingface/transformers/issues/3286 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3286/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3286/comments | https://api.github.com/repos/huggingface/transformers/issues/3286/events | https://github.com/huggingface/transformers/pull/3286 | 581,650,752 | MDExOlB1bGxSZXF1ZXN0Mzg4Njg1MzEw | 3,286 | Adding LM Head to Transfo-XL and first step to fixing problem with Adaptive Embeddings in TransfoXL | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3286?src=pr&el=h1) Report\n> Merging [#3286](https://codecov.io/gh/huggingface/transformers/pull/3286?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/68ef0a111f8740f06ca4e5a00374ec4e2adb0a6d&el=desc) will **increase... | 1,584 | 1,584 | 1,584 | MEMBER | null | This PR adds LM generation capabilitiies to the TF transfo-xl model. The integration tests for language generation pass, so generation from a pretrained model works now in TF as well.
What does definitely not work yet is running the both PT and TF models with `self.sample_softmax > 0`:
- Transfo-XL uses adaptive ... | {
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"A common way of evaluating LMs is to measure their Perplexity. \r\nSay you want to finetune GPT2 on your dataset D.\r\nDefine train, val and test datasets (maybe something around 75%, 10%, 15%.\r\nMeasure the [perplexity](https://towardsdatascience.com/perplexity-intuition-and-derivation-105dd481c8f3) on train an... | 1,584 | 1,650 | 1,584 | NONE | null | # ❓ Questions & Help
I'm trying to evaluate GPT-2 model during fine tuning process, and I'm able to calculate the loss at each epoch, but do not know how accuracy can be calculated or how to give a score to the model. Would like to get some suggestions as help.
## Details
<!-- Description of your issue -->
<!-... | {
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"Oh, I guess a workaround is to pass in `ignore_labels=[]` when creating the pipeline. This makes the nlp call return all tokens, including the ones that are not part of NER. Then I can just chunk two tokens together if their label is the same and they are nearby. Does this make sense, or am I missing something fun... | 1,584 | 1,590 | 1,590 | NONE | null | # 🚀 Feature request
I would like to suggest that NerPipeline should return the span in the original text where the matched entity exists.
Instead of:
```python
[
{"word": "New", "score": 0.9995751976966858, "entity": "LOC"},
{"word": "York", "score": 0.9996403455734253, "entity": "LOC"}
]
```
... | {
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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"
] | 1,584 | 1,591 | 1,591 | CONTRIBUTOR | null | We use pretrained self-supervised learning (SSL) models for NLP as feature extractors for downstream tasks like sentiment analysis. In most of such cases, we add a simple new classification layer and **fine-tune the whole model**. With the SSL models getting bigger and the amount of unsupervised training data is huge ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3282 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3282/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3282/comments | https://api.github.com/repos/huggingface/transformers/issues/3282/events | https://github.com/huggingface/transformers/issues/3282 | 581,578,692 | MDU6SXNzdWU1ODE1Nzg2OTI= | 3,282 | Install error , Win10,anaconda3,python3.5,pytorch | {
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"seems to be a sentencepiece issue, please open an issue at https://github.com/google/sentencepiece"
] | 1,584 | 1,584 | 1,584 | NONE | null |
When I pip install the transformers,its not successfull,my environment is Win10,anaconda3,python3.5,the error is as follows,what is wrong with it,thank you!.
## Details
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "<string>", line 1, in <module>
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3281 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3281/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3281/comments | https://api.github.com/repos/huggingface/transformers/issues/3281/events | https://github.com/huggingface/transformers/issues/3281 | 581,532,887 | MDU6SXNzdWU1ODE1MzI4ODc= | 3,281 | how to use TFBertModel to load a Bert, which the path is from own computer. | {
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"and how to use AutoTokenizer to load a local vocab file, instead of download a vocab file from server"
] | 1,584 | 1,585 | 1,585 | NONE | null | my model's path is on my computer, so, I want to load it, but when I use TFBertModel to load it, it appeared this error.
`model = TFBertModel.from_pretrained('/Users/maxiong/Workpace/Code/transformers/pre_model',config=config)`
error:
![image](https://user-images.githubusercontent.com/30991932/76696213-dcf63400-66... | {
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https://api.github.com/repos/huggingface/transformers/issues/3280 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3280/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3280/comments | https://api.github.com/repos/huggingface/transformers/issues/3280/events | https://github.com/huggingface/transformers/issues/3280 | 581,527,835 | MDU6SXNzdWU1ODE1Mjc4MzU= | 3,280 | how to finetune with PreTrainedEncoderDecoder | {
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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"
] | 1,584 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3279?src=pr&el=h1) Report\n> Merging [#3279](https://codecov.io/gh/huggingface/transformers/pull/3279?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3814e167d99c4b2e135b250d73deaa3f63ebef0c&el=desc) will **decrease... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | This doesn't change anything,
- k_dim and v_dim kwargs are there for other models in fairseq but we don't need them.
- attention weights are returned by the AttentionModule (and ignored later) no matter what | {
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https://api.github.com/repos/huggingface/transformers/issues/3278 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3278/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3278/comments | https://api.github.com/repos/huggingface/transformers/issues/3278/events | https://github.com/huggingface/transformers/pull/3278 | 581,397,782 | MDExOlB1bGxSZXF1ZXN0Mzg4NDYyNzAz | 3,278 | [BART] generation_mode as a kwarg not a class attribute | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3278?src=pr&el=h1) Report\n> Merging [#3278](https://codecov.io/gh/huggingface/transformers/pull/3278?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3814e167d99c4b2e135b250d73deaa3f63ebef0c?src=pr&el=desc) will **d... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | Currently, we set it to `BartModel.decoder.generation_mode = True` and then never unset it, which is confusing in the the rare case where you try to finetune or extract features after generating.
We can encapsulate bart specific logic to modeling_bart.py by just using a kwarg.
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https://api.github.com/repos/huggingface/transformers/issues/3277 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3277/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3277/comments | https://api.github.com/repos/huggingface/transformers/issues/3277/events | https://github.com/huggingface/transformers/pull/3277 | 581,297,842 | MDExOlB1bGxSZXF1ZXN0Mzg4Mzc2MDc3 | 3,277 | Add missing token classification for XLM | {
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now `XLMForTokenClassification` can be called via:
```python
from tr... | {
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"I don't follow your workflow. Why do you want to run forward after you generate using the generated_ids as decoder_input_ids?\r\n\r\nIt would be easier to follow if you:\r\n- checked whether the behavior you expect is achieved by the authors' implementation in fairseq\r\n- made the example smaller\r\n\r\nThanks fo... | 1,584 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): BART
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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"I have the same issue and I get (sometimes wildly) different results from run to run. Here's my code:\r\n\r\nhttps://github.com/dmitriydligach/Thyme/blob/master/RelKeras/et.py\r\n\r\nDoes anybody have a solution yet?",
"This issue has been automatically marked as stale because it has not had recent activity. It ... | 1,584 | 1,593 | 1,593 | NONE | null | I've been experimenting with the roberta-large model with both PyTorch and TensorFlow for a sentiment analysis task. With the PyTorch model, I am able to achieve 100% reproducability, however, this is not the case with the Tensorflow model.
I have set all the necessary seeds as follows:
```
seed_val = 3
os.envi... | {
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"Did you find an answer to what the cause is?",
"Well, I guess that you need infiniband between the nodes to train a model as large as bert. The ethernet interface seems to be a bottleneck during the gradient synchronization process.\r\n\r\nTo test this out, I tried out a much smaller bert model on the existing s... | 1,584 | 1,605 | 1,584 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Finetuning a bert-base model on language modeling for a particular domain
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modifie... | {
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https://api.github.com/repos/huggingface/transformers/issues/3273 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3273/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3273/comments | https://api.github.com/repos/huggingface/transformers/issues/3273/events | https://github.com/huggingface/transformers/pull/3273 | 581,241,930 | MDExOlB1bGxSZXF1ZXN0Mzg4MzMwNzU5 | 3,273 | add XLMForTokenClassification | {
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Turned out I found not TokenClassification class for XLM yet. | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"Any answer on this? "
] | 1,584 | 1,649 | 1,589 | NONE | null | # ❓ Questions & Help
how can i distill xlm-roberta model , maybe i can distill it ,just like distill roberta model , any suggestion ? thanks a lot | {
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https://api.github.com/repos/huggingface/transformers/issues/3271 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3271/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3271/comments | https://api.github.com/repos/huggingface/transformers/issues/3271/events | https://github.com/huggingface/transformers/issues/3271 | 581,171,540 | MDU6SXNzdWU1ODExNzE1NDA= | 3,271 | Finetuning before feature extraction | {
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"The script has been renamed [`run_language_modeling.py`](https://github.com/huggingface/transformers/blob/master/examples/run_language_modeling.py) to better reflect the fact that it can also be used to train a new model from scratch.\r\n\r\nLet us know if it works.",
"Hi @julien-c thanks for the quick reply!\r... | 1,584 | 1,588 | 1,588 | NONE | null | Hi,
Currently I am using the pipeline feature extraction to extract features with my own dataset as input. I was wondering if it is possible to finetune different models using my own dataset before using the pipeline for feature extraction and if so what will be the easiest way to do so?
In the past there used to... | {
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https://api.github.com/repos/huggingface/transformers/issues/3270 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3270/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3270/comments | https://api.github.com/repos/huggingface/transformers/issues/3270/events | https://github.com/huggingface/transformers/issues/3270 | 581,133,096 | MDU6SXNzdWU1ODExMzMwOTY= | 3,270 | train model from scratch with big data | {
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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"
] | 1,584 | 1,589 | 1,589 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
I would like to train a new model from scratch with some big data sets and the tutorial suggests to load and tokenize examples on the fly. It ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3269 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3269/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3269/comments | https://api.github.com/repos/huggingface/transformers/issues/3269/events | https://github.com/huggingface/transformers/issues/3269 | 581,023,842 | MDU6SXNzdWU1ODEwMjM4NDI= | 3,269 | when I install transformers, it appeared this error | {
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"You should add more information about your environment like OS, Python Version etc?\r\nI just installed it on Windows 10, WSL etc Python 3.6.9 :: Anaconda, Inc.; It worked..",
"I installed it on Mac, Python 3.6.10 Anaconda"
] | 1,584 | 1,585 | 1,585 | NONE | null | ERROR: Could not build wheels for tokenizers which use PEP 517 and cannot be installed directly | {
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https://api.github.com/repos/huggingface/transformers/issues/3268 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3268/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3268/comments | https://api.github.com/repos/huggingface/transformers/issues/3268/events | https://github.com/huggingface/transformers/pull/3268 | 580,820,138 | MDExOlB1bGxSZXF1ZXN0Mzg3OTU5NzU1 | 3,268 | add gpt2-xl for tf | {
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"Good to merge for me. Tested whether model can generate text and everything seems fine.\r\n@julien-c ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3268?src=pr&el=h1) Report\n> Merging [#3268](https://codecov.io/gh/huggingface/transformers/pull/3268?src=pr&el=desc) into [master](https://code... | 1,584 | 1,584 | 1,584 | MEMBER | null | TF GPT2-XL is now added to AWS and can be loaded via:
```
from transformers import TFGPT2LMHeadModel
model = TFGPT2LMHeadModel.from_pretrained('gpt2-xl')
```
Thanks @bkkaggle for pointing this out! | {
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https://api.github.com/repos/huggingface/transformers/issues/3267 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3267/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3267/comments | https://api.github.com/repos/huggingface/transformers/issues/3267/events | https://github.com/huggingface/transformers/pull/3267 | 580,768,852 | MDExOlB1bGxSZXF1ZXN0Mzg3OTE2MzEw | 3,267 | removing torch.cuda.empty_cache() from TF function | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3267?src=pr&el=h1) Report\n> Merging [#3267](https://codecov.io/gh/huggingface/transformers/pull/3267?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cc4c37952a961f2d13e83f3d5ba6dab811d0bbfd&el=desc) will **not chan... | 1,584 | 1,585 | 1,584 | CONTRIBUTOR | null | torch.cuda.empty_cache() was being called from a TF function (even when torch is unavailable)
not sure any replacement is needed if TF OOMs
simply running the benchmarks on a GPU with lower HBM will reproduce this error | {
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https://api.github.com/repos/huggingface/transformers/issues/3266 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3266/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3266/comments | https://api.github.com/repos/huggingface/transformers/issues/3266/events | https://github.com/huggingface/transformers/pull/3266 | 580,720,844 | MDExOlB1bGxSZXF1ZXN0Mzg3ODc2MzY2 | 3,266 | [BART] FP16 testing fixes | {
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"I have a suspicion that this will also fix the GPU test runner. "
] | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | closes #3249: fp16 forward pass failing when no `decoder_attention_mask` provided. Adds test coverage.
closes #3265: test_generate_fp16 was failing since #3140 (by sending proper kwargs to `BartForConditionalGenerate.generate`)
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"Interesting - will investigate. Probably something with the `device` of `unfinished_sents` then!\r\n\r\n@julien-c ",
"Caused by previously unexposed kwargs changing behavior:\r\npassing\r\n```\r\ndo_sample=False, early_stopping=True\r\n```\r\nin the unit test fixes them.",
"I'm getting this error @sshleifer ",... | 1,584 | 1,592 | 1,584 | CONTRIBUTOR | null | passes after `git checkout d6de6423` (commit preceding #3140)
Traceback:
```
unfinished_sents.mul_((~eos_in_sents).long())
# stop when there is a </s> in each sentence, or if we exceed the maximul length
> if unfinished_sents.max() == 0:
E RuntimeError: cuda runt... | {
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https://api.github.com/repos/huggingface/transformers/issues/3264 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3264/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3264/comments | https://api.github.com/repos/huggingface/transformers/issues/3264/events | https://github.com/huggingface/transformers/pull/3264 | 580,636,961 | MDExOlB1bGxSZXF1ZXN0Mzg3ODA2ODkx | 3,264 | Clean special token init in modeling_....py | {
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"Is good to merge for me if you guys are fine with it. Can open a new PR for a test proposal for this one and then also adapt the dutch bert model config on AWS. ",
"Isn't this breaking other hosted configs than the ones you're listing?\r\n\r\nLike https://huggingface.co/microsoft/DialoGPT-large for instance? (mo... | 1,584 | 1,584 | 1,584 | MEMBER | null | #### INTRO:
This PR is a follow-up from PR #3011.
After discussion with @thomwolf today, we decided that the variable `eos_token_ids` in all models causes more confusion and ugly code than it helps.
#### BACKGROUND:
All models now have `pad_token_id`, `bos_token_id` and `eos_token_id` as default values. The ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3263?src=pr&el=h1) Report\n> Merging [#3263](https://codecov.io/gh/huggingface/transformers/pull/3263?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/afea70c01c7d2a844662a4d66b9f9d933cc6449c?src=pr&el=desc) will **i... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | First version of our model_card for the original uploaded CamemBERT.
@louismartin @pjox | {
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"This seems like a valid point, what do you think @LysandreJik?"
] | 1,584 | 1,584 | 1,584 | NONE | null | Unlike the TFBertMainLayer class which can be imported from transformers, TFAlbertMainLayer cannot be imported.
Locally I made the changes to init.py:
Import TFAlbertMainLayer from modeling_tf_albert
Similar to tensorflow version, pytorch version should also be implemented. | {
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https://api.github.com/repos/huggingface/transformers/issues/3261 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3261/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3261/comments | https://api.github.com/repos/huggingface/transformers/issues/3261/events | https://github.com/huggingface/transformers/pull/3261 | 580,479,370 | MDExOlB1bGxSZXF1ZXN0Mzg3Njc4ODUx | 3,261 | Update examples/ner/run_ner.py | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3261?src=pr&el=h1) Report\n> Merging [#3261](https://codecov.io/gh/huggingface/transformers/pull/3261?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/afea70c01c7d2a844662a4d66b9f9d933cc6449c&el=desc) will **increase... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | Update the example file by changing the name of AlbertForTokenClassification to AlbertForSequenceClassification. | {
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https://api.github.com/repos/huggingface/transformers/issues/3260 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3260/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3260/comments | https://api.github.com/repos/huggingface/transformers/issues/3260/events | https://github.com/huggingface/transformers/issues/3260 | 580,454,121 | MDU6SXNzdWU1ODA0NTQxMjE= | 3,260 | Model name 'distilbert-base-german-cased' was not found in model name list. | {
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"Hi @woiza,\r\n\r\ntry to use: `DistilBertForSequenceClassification` instead of `BertForSequenceClassification` :)\r\n\r\n",
"@stefan-it \r\n\r\nthat worked, thank you!"
] | 1,584 | 1,584 | 1,584 | NONE | null | This code is ok:
`from transformers import AutoModel, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("distilbert-base-german-cased")
model = AutoModel.from_pretrained("distilbert-base-german-cased")
`
But the following fails:
`from transformers import BertForSequenceClassification, AdamW, BertCon... | {
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https://api.github.com/repos/huggingface/transformers/issues/3259 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3259/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3259/comments | https://api.github.com/repos/huggingface/transformers/issues/3259/events | https://github.com/huggingface/transformers/issues/3259 | 580,329,711 | MDU6SXNzdWU1ODAzMjk3MTE= | 3,259 | Great job advice | {
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"@DenceChen thanks for sharing :-) Feel free trying to add a model if you need it!"
] | 1,584 | 1,584 | 1,584 | NONE | null | First of all this is a very perfect job，I shared it with multiple colleagues，also please provide an implementation of the ElMo model and more tensorflow examples.
thank you very much~ | {
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https://api.github.com/repos/huggingface/transformers/issues/3258 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3258/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3258/comments | https://api.github.com/repos/huggingface/transformers/issues/3258/events | https://github.com/huggingface/transformers/issues/3258 | 580,317,715 | MDU6SXNzdWU1ODAzMTc3MTU= | 3,258 | very slow performance on transformer 2.5.0 versus 2.3.0 | {
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"I met the same issue when running the run_squad.py using the 2.5.0 version. ",
"Which PyTorch version are you using for your benchmarks? Is it the same for both, or is it different?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further acti... | 1,584 | 1,591 | 1,591 | NONE | null | Hi
I am running the run_glue version with last version of transformer 2.5.0 python=3.5 and this is at least 10 times slower than running the same code with transformer 2.3.0 with python 3.6.9. I use the BERT model. The difference between speed of these versions is extremely high, could you have a look and check why th... | {
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https://api.github.com/repos/huggingface/transformers/issues/3257 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3257/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3257/comments | https://api.github.com/repos/huggingface/transformers/issues/3257/events | https://github.com/huggingface/transformers/pull/3257 | 580,266,986 | MDExOlB1bGxSZXF1ZXN0Mzg3NTEwMzU5 | 3,257 | ELECTRA | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3257?src=pr&el=h1) Report\n> Merging [#3257](https://codecov.io/gh/huggingface/transformers/pull/3257?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/012d775b14d1ab673aab7eae151823a74a8525a6&el=desc) will **not chan... | 1,584 | 1,586 | 1,585 | MEMBER | null | Adds ELECTRA to the library.
The script I'm using to compare the different models is this [Github gist](https://gist.github.com/LysandreJik/db4c948f6b4483960de5cbac598ad4ed), coupled to [a modified version of the ELECTRA repository](https://github.com/LysandreJik/electra).
- [x] add model/configuration/tokenizati... | {
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https://api.github.com/repos/huggingface/transformers/issues/3256 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3256/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3256/comments | https://api.github.com/repos/huggingface/transformers/issues/3256/events | https://github.com/huggingface/transformers/issues/3256 | 580,235,096 | MDU6SXNzdWU1ODAyMzUwOTY= | 3,256 | Implement Electra | {
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"We are currently working on it :-) \r\nCheck out PR: #3257"
] | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
https://github.com/google-research/electra
## Motivation
<!-- Please outline the motivation for the proposal. Is your feature request
related to ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3255 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3255/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3255/comments | https://api.github.com/repos/huggingface/transformers/issues/3255/events | https://github.com/huggingface/transformers/pull/3255 | 580,140,231 | MDExOlB1bGxSZXF1ZXN0Mzg3NDA4MjY5 | 3,255 | add BART to README | {
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https://api.github.com/repos/huggingface/transformers/issues/3254 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3254/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3254/comments | https://api.github.com/repos/huggingface/transformers/issues/3254/events | https://github.com/huggingface/transformers/pull/3254 | 580,130,186 | MDExOlB1bGxSZXF1ZXN0Mzg3Mzk5NTMx | 3,254 | Bump psutil from 5.6.3 to 5.6.6 in /examples/distillation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3254?src=pr&el=h1) Report\n> Merging [#3254](https://codecov.io/gh/huggingface/transformers/pull/3254?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2e81b9d8d76a4d41a13f74eb5e0f4a65d8143cab?src=pr&el=desc) will **d... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | Bumps [psutil](https://github.com/giampaolo/psutil) from 5.6.3 to 5.6.6.
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a href="https://github.com/giampaolo/psutil/blob/master/HISTORY.rst">psutil's changelog</a>.</em></p>
<blockquote>
<h1>5.6.6</h1>
<p>2019-11-25</p>
<p><strong>Bug fixes</strong></p>
<ul>
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3253 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3253/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3253/comments | https://api.github.com/repos/huggingface/transformers/issues/3253/events | https://github.com/huggingface/transformers/issues/3253 | 580,057,898 | MDU6SXNzdWU1ODAwNTc4OTg= | 3,253 | bug in run_glue | {
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"If you could include your environment and steps to replicate the issue, that would help. Its working for me on version 2.5.1 (from master branch).",
"Hi. Sorry then I must have used the old version of transformer, I will close the issue and reopen if needed. thanks. ",
"This issue has been automatically marked... | 1,584 | 1,589 | 1,584 | NONE | null | Hi I got this error when running the run_glue.py
from transformers import glue_compute_metrics as compute_metrics
ImportError: cannot import name 'glue_compute_metrics' | {
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https://api.github.com/repos/huggingface/transformers/issues/3252 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3252/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3252/comments | https://api.github.com/repos/huggingface/transformers/issues/3252/events | https://github.com/huggingface/transformers/issues/3252 | 580,052,979 | MDU6SXNzdWU1ODAwNTI5Nzk= | 3,252 | batch_encode_plus cannot work properly | {
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"This is quite a weird way to encode your data with `ds[0][0:3]`. There are two cases:\r\n\r\n1) You have a single string you want to encode:\r\n```\r\ninput_str = 'hello, what time is it?'\r\ninput_ids_dict = tokenizer.encode_plus(input_str)\r\n```\r\n\r\n2) You have a batch of input string data that you want to e... | 1,584 | 1,584 | 1,584 | NONE | null | I have data like below:
```
>>> ds[0][0:3]
["John was writing lyrics for his new album.He started experiencing writer 's block.He tried to force himself to write but it would n't do anythingHe tried to force himself to write but it would n't do anything.He took a walk , hung out with some friends , and looked at nat... | {
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https://api.github.com/repos/huggingface/transformers/issues/3251 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3251/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3251/comments | https://api.github.com/repos/huggingface/transformers/issues/3251/events | https://github.com/huggingface/transformers/issues/3251 | 580,049,804 | MDU6SXNzdWU1ODAwNDk4MDQ= | 3,251 | Why is the seq_len dimension hard coded to be the first dimension of BERT's input? | {
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"My wild guess is maybe there is no specific reason for this. It's just an implementation issue. If I really want do feed a tensor of different number of dimensions I can just do reshape twice (i.e., one before forward one after)."
] | 1,584 | 1,586 | 1,586 | NONE | null | According to your [code](https://github.com/huggingface/transformers/blob/2e81b9d8d76a4d41a13f74eb5e0f4a65d8143cab/src/transformers/modeling_bert.py#L164), the `seq_len` dimension always corresponds to the first dimension of the input tensor. I found this problem when I tried to feed a tensor of shape `(batch_size, num... | {
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https://api.github.com/repos/huggingface/transformers/issues/3250 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3250/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3250/comments | https://api.github.com/repos/huggingface/transformers/issues/3250/events | https://github.com/huggingface/transformers/issues/3250 | 580,029,285 | MDU6SXNzdWU1ODAwMjkyODU= | 3,250 | UnicodeDecodeError when loading BART from fairseq checkpoint | {
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"Unfortunately, I don't think the conversion you are describing is currently supported. \r\nIf I were to attempt this on my own, I would try to modify https://github.com/huggingface/transformers/blob/master/src/transformers/convert_bart_original_pytorch_checkpoint_to_pytorch.py to take in a path to a checkpoint, ra... | 1,584 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
When trying to load a checpoint from the fariseq library I'm getting an UnicodeError
## Information
Model I am using (Bert, XLNet ...): BART
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
... | {
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"@sshleifer May I ask could you reproduce the error in your machine? I ran the same code on a Linux machine with master-branch of transformers, but still got the same error. I'm planning to use BartModel these days so please notify me at your earliest convenience if there're any updates. Many thanks!",
"Yes, will... | 1,584 | 1,608 | 1,584 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): BART
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3247 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3247/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3247/comments | https://api.github.com/repos/huggingface/transformers/issues/3247/events | https://github.com/huggingface/transformers/pull/3247 | 579,923,877 | MDExOlB1bGxSZXF1ZXN0Mzg3MjMwNzg1 | 3,247 | Improved Error message when loading config/model with .from_pretrained() | {
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"Thanks to @mariamabarham for pointing this out :-) ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3247?src=pr&el=h1) Report\n> Merging [#3247](https://codecov.io/gh/huggingface/transformers/pull/3247?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/dc848c29... | 1,584 | 1,584 | 1,584 | MEMBER | null | Given the previous error message, it can be quite time-consuming to find out that the only problem was that the /path/to/model/dir was incorrect :D | {
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"Did you try out to just use this `save_...` function: https://github.com/huggingface/transformers/blob/2e81b9d8d76a4d41a13f74eb5e0f4a65d8143cab/src/transformers/modeling_tf_utils.py#L232 ? \r\n\r\n-> \r\n```\r\ntf_model = TFGPT2LMHeadModel.from_pretrained(\"tmp/\", from_pt=True)\r\ntf_model.save_pretrained(\"./tf_... | 1,584 | 1,674 | 1,588 | 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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"This will greatly effect the output of BERT model,I do not quite know whether this is the problem of the code or the problem of the package.\r\nd[0] and d[1] are lists of sentences,which is used to train the model.",
"When I was trying to decode the input_ids, the result shows that the text_pair is not encoded p... | 1,584 | 1,590 | 1,590 | NONE | null | As the document writes,the value that bert do not attend should have attention value of 0.However, I was using the BertTokenizer,the result is different.
This is my code:
```
input_wsrq1ids=tokenizer.batch_encode_plus(d[0],text_pair=d[1],add_special_tokens=True,return_tensors='pt')
>>> input_wsrq1ids['input_ids'][0... | {
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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 don't think you should delete the issue since it's kinda useful to have and not having it may be embarassing. But do as you want !",
... | 1,583 | 1,595 | 1,595 | NONE | null | # 🚀 Feature request
When using some of tokenization models (e.g. : CamemBERT) you can find the char used to separate words after some investigation ([start](https://github.com/huggingface/transformers/blob/a4c75f149269099a98613f51b76cd0b579a109ee/src/transformers/tokenization_camembert.py#L274), [first jump](https://... | {
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"All of our TensorFlow models are TF2+ only."
] | 1,583 | 1,584 | 1,584 | NONE | null | for TFPreTrainedModel
model.load_weights(resolved_archive_file, by_name=True)
seems by_name is always true.while i see in "tensorflow_core/python/keras/engine/network.py"
if save_format == 'tf':
status = self._trackable_saver.restore(filepath)
if by_name:
raise NotImplementedError(
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"Squashed into #3248 ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3241?src=pr&el=h1) Report\n> Merging [#3241](https://codecov.io/gh/huggingface/transformers/pull/3241?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a4c75f149269099a98613f51b76cd0b579a109e... | 1,583 | 1,584 | 1,584 | CONTRIBUTOR | null | Indeed this is much simpler now! Pipelines look great :) | {
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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"
] | 1,583 | 1,594 | 1,594 | NONE | null | I need key-value of the present state like GPT class for BERT as well (I'm testing PPLM like architecture but with masked LM), and here I've added the option `output_past` to BERT to enable returning those statistics. | {
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"`batch_encode_plus` is the correct method :-) \r\n\r\n```\r\nfrom transformers import BertTokenizer\r\nbatch_input_str = ((\"Mary spends $20 on pizza\"), (\"She likes eating it\"), (\"The pizza was great\"))\r\ntok = BertTokenizer.from_pretrained('bert-base-uncased')\r\nprint(tok.batch_encode_plus(batch_input_str,... | 1,583 | 1,584 | 1,584 | NONE | null | Hi,I am trying to learn this transformers package.
I prepared the data as following format:
`(("Mary spends $20 on pizza"),("She likes eating it),("The pizza was great"))`
I saw methods like `tokenizer.encode`,`tokenizer.encode_plus`t and `tokenizer.batch_encode_plus`.However, the `tokenizer.encode` seems to only en... | {
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https://api.github.com/repos/huggingface/transformers/issues/3236 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3236/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3236/comments | https://api.github.com/repos/huggingface/transformers/issues/3236/events | https://github.com/huggingface/transformers/pull/3236 | 579,630,038 | MDExOlB1bGxSZXF1ZXN0Mzg2OTg5Nzg1 | 3,236 | [WIP] Add BART for summarization training with CNN/DM using pytorch-lightning | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3236?src=pr&el=h1) Report\n> Merging [#3236](https://codecov.io/gh/huggingface/transformers/pull/3236?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9d4a01905fad4f5eed2e6c1037dea9877711427a&el=desc) will **not chan... | 1,583 | 1,585 | 1,585 | CONTRIBUTOR | null | This pull request adds to the example for BART for summarization. I used the [example for NER](https://github.com/huggingface/transformers/tree/master/examples/ner) using pytorch-lightning as guidance. This example will train on CNN/DM and evaluate, and get decent results, though I haven't trained it on the full datase... | {
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"Do you mind making sure the code quality test runs before we merge? You can see how to do that in the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed i... | 1,583 | 1,594 | 1,594 | NONE | null | _rotate_checkpoints deletes some checkpoint directory which causes "directories not found" error | {
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https://api.github.com/repos/huggingface/transformers/issues/3234 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3234/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3234/comments | https://api.github.com/repos/huggingface/transformers/issues/3234/events | https://github.com/huggingface/transformers/pull/3234 | 579,568,049 | MDExOlB1bGxSZXF1ZXN0Mzg2OTM5MTIy | 3,234 | [model_cards] 🇹🇷 Add new (cased) DistilBERTurk model | {
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"Also cc @VictorSanh for the model distillation script.\r\n\r\nThanks @stefan-it this is awesome",
"I'm supposed to use the same line-breaking options as GitHub for markdown formatting (using marked.js), however this still seems to not render like on GitHub: https://huggingface.co/dbmdz/distilbert-base-turkish-ca... | 1,583 | 1,583 | 1,583 | COLLABORATOR | null | Hi,
this PR adds a new distilled BERT model for Turkish: DistilBERTurk 🤗
It was trained with the official Hugging Face [implementation](https://github.com/huggingface/transformers/tree/master/examples/distillation) for model distillation. It uses 7GB of the original training data of BERTurk, and uses the cased B... | {
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"Had to temporarily pause the self-hosted CI runner while I debug while it's been failing, @sshleifer "
] | 1,583 | 1,584 | 1,584 | CONTRIBUTOR | null | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"Any plan to fix this?",
"I missed that issue, but this was fixed a couple of weeks ago, and it's even covered by CI now: https://gith... | 1,583 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
When I try loading a model/tokenizer from the [pytorch hub](https://pytorch.org/hub/huggingface_pytorch-transformers/) page, the hub loading code is not working anymore. Pre transformers 2.0.0, the same loading code is working.
On a quick look, I believe it's related to the repo's fold layout since 2.0 w... | {
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"You can write or add your own version easily..",
"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"
] | 1,583 | 1,589 | 1,589 | NONE | null | Does `run_multiple_choice.py` work on train dev test splits?
I need to run BERT on 3 labeled datasets. Train it on my training set, validate it on my validation set (tune hyperparameters and calculate loss), and evaluate it on my test set (report performance). I finally want to do prediction on a forth unlabeled datas... | {
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the `T5WithLMHeadModel.forward()` has a special API due to its encoder-decoder nature.
This is why we need to add a `prepare_inputs_for_generation()` in `t5_modeling_utils.py` to
correctly prepare t5's inputs for generation.
Some easy t... | {
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https://api.github.com/repos/huggingface/transformers/issues/3227 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3227/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3227/comments | https://api.github.com/repos/huggingface/transformers/issues/3227/events | https://github.com/huggingface/transformers/issues/3227 | 579,302,501 | MDU6SXNzdWU1NzkzMDI1MDE= | 3,227 | An Error report about pipeline | {
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"I have this same issue, but have no problems running:\r\n\r\nnlp = pipeline(\"question-answering\")\r\n\r\n\r\nNote: To install the library, I had to install tokenizers version 0.6.0 separately, git clone the transformers repo and edit the setup.py file before installing as per @dafraile's answer for issue: https:... | 1,583 | 1,585 | 1,585 | NONE | null | # 🐛 Bug
## Information
This may be an easy question, but it has been bothering me all day.
When I run the code:
nlp = pipeline("question-answering")
It always tells me:
Couldn't reach server at 'https://s3.amazonaws.com/models.huggingface.co/bert/distilbert-base-cased-distilled-squad-modelcard.json' to... | {
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"No, this is expected behavior. If it was returning `['inv', 'ol', 've']`, then the model would identify each token as being a beginning of word token, whereas the last two are actually part of words following a beginning of a word.",
"Thanks for your response. But since both 'involve' and `['inv', 'ol', 've']` a... | 1,583 | 1,584 | 1,584 | NONE | null | When a word is in origin Bert vocabulary, it would not be split. But after adding several its subtokens, it would be split into pieces, which seems to inconsistent with the longest match first algorithm.
To reproduce:
```
import transformers
tokenizer = transformers.BertTokenizer.from_pretrained('bert-base-uncased... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3225?src=pr&el=h1) Report\n> Merging [#3225](https://codecov.io/gh/huggingface/transformers/pull/3225?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2e81b9d8d76a4d41a13f74eb5e0f4a65d8143cab?src=pr&el=desc) will **i... | 1,583 | 1,584 | 1,584 | MEMBER | null | This is a follow-up PR to finalize #3140 .
There was still no conclusion on how to handle the fairseq tricks for generation. To summarize:
I think we have three options:
1. Remove all faiseq tricks. Here the ROUGE score is: **20.285**
2. Implement the fairseq tricks EXCEPT leaving the starting decoding_input... | {
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"I am running into the same issue. Any progress on getting this into a release?",
"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"
] | 1,583 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert, bert-large-uncased-whole-word-masking-finetuned-squad
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 work... | {
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<!-- Description of your issue -->
**singularity :** ```singularity build pytorch20.02.simg docker://nvcr.io/nvidia/pytorch:20.02-py3```
I use Slurm and singularity to run run_glue.py but have NCCL error on torch.distributed.barrier()
### test.sh
```
#!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntas... | {
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"They should definitely be cached locally.\r\n\r\nDo you have a sample code showing the behaviour of re-downloading every time?",
"Yes, here is a example (not happen every time but after system restart):\r\n```\r\nimport torch\r\nfrom transformers import AlbertTokenizer\r\nalbert_tokenizer = AlbertTokenizer.from_... | 1,583 | 1,689 | 1,585 | NONE | null | I often use pre-trained models, but when I want to import it (after restart).
But each time, I have to download again. So is there a function that can automatically save the model you downloaded in a directory? In Gluon-NLP, it will save the model you used in `.mxnet` in your home directory. | {
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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"
] | 1,583 | 1,590 | 1,590 | NONE | null | I am studying machine reading comprehension on xlmroberta.
My data is korquad.
I need to tokenize all word to character.
e.g. by english
This is a dog
-> _T h i s _i s _a _d o g
please let me know. | {
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