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https://api.github.com/repos/huggingface/transformers/issues/4312 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4312/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4312/comments | https://api.github.com/repos/huggingface/transformers/issues/4312/events | https://github.com/huggingface/transformers/issues/4312 | 616,613,657 | MDU6SXNzdWU2MTY2MTM2NTc= | 4,312 | how can I make BERT word embedding faster? | {
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"It seems you're not actually putting anything on GPU. You need to call `bertModel.to(device)` and `input_ids.to(device)`.\r\n\r\nThe BERT model is much larger than GloVe, however, so you'll never get the same speed.",
"Thank you @LysandreJik. It actually increases speed but not that much.\r\nIs there any model w... | 1,589 | 1,595 | 1,595 | NONE | null | Hello guys,
I have a code in which words get embedded with **Glove Embedding** for the number of iterations.
model.word_emb= utils.load_word_emb(args.glove_embed_path)
a =time.time()
w = "Transformer"
X = model.word_emb.get(w, model.word_emb['unk'])
b =time.time()
print(b-a)
and for each word glove embedd... | {
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"Pull request welcome!"
] | 1,589 | 1,589 | 1,589 | NONE | null | There is no ready to use RobertaForQuestionAnsweringModel Class in transformers.
Please add it as you have done for other models. | {
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https://api.github.com/repos/huggingface/transformers/issues/4310 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4310/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4310/comments | https://api.github.com/repos/huggingface/transformers/issues/4310/events | https://github.com/huggingface/transformers/issues/4310 | 616,556,297 | MDU6SXNzdWU2MTY1NTYyOTc= | 4,310 | MobileBert form google-research added | {
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"Will close this to track this at more general #4185",
"Please the \" checkpoint\" file to reset the path to \"mobilebert_variables.ckpt\" \r\nThis can solved my issue.\r\n"
] | 1,589 | 1,610 | 1,589 | CONTRIBUTOR | null | # 🌟 New model addition
## Model description
[MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices](https://arxiv.org/abs/2004.02984)
Repo [link](https://github.com/google-research/google-research/tree/master/mobilebert)
## Open source status
* [x] Uploaded to HF model hub
[bert_config.... | {
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https://api.github.com/repos/huggingface/transformers/issues/4309 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4309/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4309/comments | https://api.github.com/repos/huggingface/transformers/issues/4309/events | https://github.com/huggingface/transformers/issues/4309 | 616,536,041 | MDU6SXNzdWU2MTY1MzYwNDE= | 4,309 | Finetuning error: RuntimeError: Error(s) in loading state_dict for GPT2LMHeadModel: Missing key(s) in state_dict: “transformer.h.0.attn.masked_bias”, “transformer.h.1.attn.masked_bias” | {
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"I think we're missing some info here, can you add your complete code snippet to the issue's title? \r\n\r\n### 🤣🤣 \r\n\r\nYou can even add some binary data in there for good measure.\r\n\r\nHehe I'm just kidding :trollface: ",
"Managed: I just didn’t account for the May 7 transformers release! \n\nSent from my... | 1,589 | 1,590 | 1,589 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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https://api.github.com/repos/huggingface/transformers/issues/4308 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4308/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4308/comments | https://api.github.com/repos/huggingface/transformers/issues/4308/events | https://github.com/huggingface/transformers/issues/4308 | 616,517,287 | MDU6SXNzdWU2MTY1MTcyODc= | 4,308 | MPNet: Masked and Permuted Pre-training for Language Understanding | {
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"Hi huggingface/transformers,\r\n\r\nI am Xu Tan from Microsoft Research. Thanks for that you mentioned MPNet in huggingface/transformers repo.\r\n\r\nMPNet is an advanced pre-trained models for language understanding, which inherits the advantages of BERT and XLNet, while well address their problems. We have MPNe... | 1,589 | 1,611 | 1,611 | NONE | null | # 🌟 New model addition
## Model description
[MPNet: Masked and Permuted Pre-training for Language Understanding](https://arxiv.org/pdf/2004.09297.pdf)
use both Masked Language Model and Permuted Language Model
## Open source status
* [MPNet ] the model implementation is available: (https://github.com/micr... | {
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https://api.github.com/repos/huggingface/transformers/issues/4307 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4307/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4307/comments | https://api.github.com/repos/huggingface/transformers/issues/4307/events | https://github.com/huggingface/transformers/issues/4307 | 616,488,022 | MDU6SXNzdWU2MTY0ODgwMjI= | 4,307 | why Building wheel for tokenizers (PEP 517) ... error? | {
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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 have this problem too , how did you resolve it?can you share your ideas?"
] | 1,589 | 1,619 | 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
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https://api.github.com/repos/huggingface/transformers/issues/4306 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4306/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4306/comments | https://api.github.com/repos/huggingface/transformers/issues/4306/events | https://github.com/huggingface/transformers/issues/4306 | 616,426,900 | MDU6SXNzdWU2MTY0MjY5MDA= | 4,306 | Multiple token prediction with MLM | {
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"An error message would be great, want to submit a PR?\r\n\r\nFor multiple masked token support, I'm not entirely sure. The sampling might be very use case-specific.",
"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 ... | 1,589 | 1,620 | 1,595 | CONTRIBUTOR | null | # 🚀 Feature request
It would be great if the `fill_mask` interface would be able to predict multiple tokens at a time.
## Motivation
I didn't find any related issue. Using transformer for chemical data, queries like `fill_mask('CCCO<mask>C')` work fine. But writing `fill_mask('CC<mask>CO<mask>C')` I obtain:
`... | {
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https://api.github.com/repos/huggingface/transformers/issues/4305 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4305/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4305/comments | https://api.github.com/repos/huggingface/transformers/issues/4305/events | https://github.com/huggingface/transformers/pull/4305 | 616,423,200 | MDExOlB1bGxSZXF1ZXN0NDE2NTM2NTAx | 4,305 | fixed missing torch module import | {
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https://api.github.com/repos/huggingface/transformers/issues/4304 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4304/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4304/comments | https://api.github.com/repos/huggingface/transformers/issues/4304/events | https://github.com/huggingface/transformers/issues/4304 | 616,403,075 | MDU6SXNzdWU2MTY0MDMwNzU= | 4,304 | Latest Version Of HuggingFace is Not Using GPUs | {
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"If you don't tell us what code you use, we cannot help you. Be detailed and use code block. Don't post screenshots. ",
"I agree. I apologize, was kinda annoyed that version diff can cause this. Will share a minimal example. (In the mean time, re-verifying via setting up different env's)",
"Did you manage to s... | 1,589 | 1,594 | 1,589 | CONTRIBUTOR | null | I switched from v2.8 to v2.9 today morning keeping all my experiments, enviornment same etc but the same code which used v2.8 has an epoch time of 5 mins, where as in v2.9 it's more than 2 hours.
Code was custom which was working till yesterday with v2.8.
Please verify the same. | {
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https://api.github.com/repos/huggingface/transformers/issues/4303 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4303/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4303/comments | https://api.github.com/repos/huggingface/transformers/issues/4303/events | https://github.com/huggingface/transformers/issues/4303 | 616,394,243 | MDU6SXNzdWU2MTYzOTQyNDM= | 4,303 | How to perform Agglomerative clustering on Albert model last hidden state output, it gives tuple of tensors for each sequence in a sentence. I am processing multiple sentences from a document, How to achieve this ? | {
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] | 1,589 | 1,595 | 1,595 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
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we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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] | 1,589 | 1,594 | 1,594 | NONE | null | Edit args.tf_dump_path in convert_all_pt_checkpoints_to_tf | {
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https://api.github.com/repos/huggingface/transformers/issues/4301 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4301/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4301/comments | https://api.github.com/repos/huggingface/transformers/issues/4301/events | https://github.com/huggingface/transformers/issues/4301 | 616,306,298 | MDU6SXNzdWU2MTYzMDYyOTg= | 4,301 | why squad.py did not reproduce squad1.1 report result? | {
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"I have just solved this problem.\r\nYou have to set an additional flag: --do_lower_case.\r\nI wonder why the run_squad.py behaves differently than run_glue.py, etc. Is there is a code improve on the way?",
"You shouldn't have to set `--do_lower_case` as it should be lowercased by default for that model.",
"> Y... | 1,589 | 1,590 | 1,590 | NONE | null | # 📚 Migration
## Information
<!-- Important information -->
Model I am using (Bert, XLNet ...):
Language I am using the model on (English...):
The problem arises when using:
* [x] the official example scripts: (give details below)
examples/question-answering/run_squad.py
* [x] my own modified scripts... | {
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https://api.github.com/repos/huggingface/transformers/issues/4300 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4300/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4300/comments | https://api.github.com/repos/huggingface/transformers/issues/4300/events | https://github.com/huggingface/transformers/pull/4300 | 616,290,388 | MDExOlB1bGxSZXF1ZXN0NDE2NDMxNjQy | 4,300 | Fix nn.DataParallel compatibility in PyTorch 1.5 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4300?src=pr&el=h1) Report\n> Merging [#4300](https://codecov.io/gh/huggingface/transformers/pull/4300?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7cb203fae4e7964e9e99400b375d660ebce765ee&el=desc) will **decrease... | 1,589 | 1,600 | 1,589 | MEMBER | null | As reported in #3936
PyTorch 1.5 changes the handling of nn.Parameters in `DataParallel` replicas. (https://github.com/pytorch/pytorch/pull/33907). The replicas now don't have parameters() anymore.
This PR updates our `self.device` and `self.dtype` helpers to mimic `nn.Module`'s `parameters()` helper but for att... | {
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https://api.github.com/repos/huggingface/transformers/issues/4299 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4299/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4299/comments | https://api.github.com/repos/huggingface/transformers/issues/4299/events | https://github.com/huggingface/transformers/issues/4299 | 616,257,011 | MDU6SXNzdWU2MTYyNTcwMTE= | 4,299 | Issue with XLNet using xlnet-base-cased | {
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"I also have the same problem @alexandrenriq ",
"I think there's a mistake in the code which sets the `AutoModelForQuestionAnswering` as `XLNetForQuestionAnsweringSimple`. You can run the code by substituting `AutoModelForQuestionAnswering` into `XLNetForQuestionAnswering` (or by removing `cls_index` and `p_mask`... | 1,589 | 1,602 | 1,602 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): XLNet
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
*... | {
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https://api.github.com/repos/huggingface/transformers/issues/4298 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4298/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4298/comments | https://api.github.com/repos/huggingface/transformers/issues/4298/events | https://github.com/huggingface/transformers/pull/4298 | 616,255,513 | MDExOlB1bGxSZXF1ZXN0NDE2NDAzNDk1 | 4,298 | Fix BART tests on GPU | {
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https://api.github.com/repos/huggingface/transformers/issues/4297 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4297/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4297/comments | https://api.github.com/repos/huggingface/transformers/issues/4297/events | https://github.com/huggingface/transformers/pull/4297 | 616,240,186 | MDExOlB1bGxSZXF1ZXN0NDE2MzkwODE1 | 4,297 | pin TF to 2.1 | {
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https://api.github.com/repos/huggingface/transformers/issues/4296 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4296/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4296/comments | https://api.github.com/repos/huggingface/transformers/issues/4296/events | https://github.com/huggingface/transformers/issues/4296 | 616,237,745 | MDU6SXNzdWU2MTYyMzc3NDU= | 4,296 | Error Training T5 Transformer Translation Model | {
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"Which library are you using? Could you maybe post a complete code example (with all relevant imports) to reproduce the error? ",
"https://github.com/jameschartouni/arabic_translation/blob/google-t5/Model_1.ipynb\r\n\r\nLet me know if you have difficulty viewing the code! We are using colab and use a fresh instal... | 1,589 | 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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https://api.github.com/repos/huggingface/transformers/issues/4295 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4295/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4295/comments | https://api.github.com/repos/huggingface/transformers/issues/4295/events | https://github.com/huggingface/transformers/pull/4295 | 616,180,071 | MDExOlB1bGxSZXF1ZXN0NDE2MzQyMjA0 | 4,295 | [Docs, Notebook] Include generation pipeline | {
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- adds the generation pipeline to the notebook
- Also, I updated the config of all models that can be used with generation with model specific params: GPT2, OpenAI-GPT, XLNet, TransfoXL, Reformer, so that they now include a `text-generation` speci... | {
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"A simple fix could be:\r\n\r\n1. Adding in file [modeling_encoder_decoder.py](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_encoder_decoder.py) @ line 140:\r\n\r\n```\r\nkwargs_decoder[\"is_decoder\"]=True\r\n```\r\n\r\n2. Adding in file [modeling_auto.py](https://github.com/hug... | 1,589 | 1,590 | 1,590 | 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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closes #4259 | {
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"The slow bart summarization tests all pass with this? ",
"yes!",
"LGTM",
"Correct, @LysandreJik not a breaking change.\r\n",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4290?src=pr&el=h1) Report\n> Merging [#4290](https://codecov.io/gh/huggingface/transformers/pull/4290?src=pr&el=desc)... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | (this should probably be 3 PRs, sorry).
TLDR: This gets us to equal or better BLEU for 99+% of the converted models.
### Issue 1: non-breaking Generation Issue
`pad_token_id` is predicted with score 0, but we never want to generate it.
Previously, we set its score to inf after softmax, so probabilities summed ... | {
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closes https://github.com/huggingface/transformers/issues/4153
closes #4163
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"Duplicated of [https://github.com/huggingface/transformers/issues/4166](url)"
] | 1,589 | 1,589 | 1,589 | NONE | null | # 🌟 TAPAS (Weakly Supervised Table Parsing via Pre-Training)
## Model description
**TAPAS** [ArXiV Paper](https://arxiv.org/pdf/2004.02349.pdf) [Google AI Blog](https://ai.googleblog.com/2020/04/using-neural-networks-to-find-answers.html?utm_campaign=Learning%20Posts&utm_content=128690771&utm_medium=social&utm_s... | {
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"Thanks for the detailed error description @binshengliu! I linked a PR that should fix it :-) ",
"Hi, there's still some chance we get `nan` values during training. It does not always happen but is still pretty easy to reproduce. My current version is `2.11.0`.\r\n\r\n```\r\nimport torch\r\nfrom transformers impo... | 1,589 | 1,625 | 1,589 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): T5
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] 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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"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 have the exact same issue. When I share GPT2 model trained with AlbertTokenizer on huggingface.co the default code snippet doesn't wo... | 1,589 | 1,608 | 1,595 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT2 with AlbertTokenizer
Language I am using the model on (English, Chinese ...): Ukrainian
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
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"Good to be merged for me :) We should update the `setup.py` in same time to do not limit anymore to TF 2.1. Should it be done in this PR? /cc @julien-c @LysandreJik ",
"I think you can cc @LysandreJik @julien-c ",
"Yes can you do it in the same PR? and it'll be ready to merge.",
"Nice! Unfortunately there ar... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | This PR updates the TF gradient accumulator optimization to make it compliant with the new TF 2.2. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4281?src=pr&el=h1) Report\n> Merging [#4281](https://codecov.io/gh/huggingface/transformers/pull/4281?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b290c32e1617fa74f44ccd8b83365fe764437be9&el=desc) will **decrease... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | First model card for bert-turkish-question-answering question-answering model | {
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https://api.github.com/repos/huggingface/transformers/issues/4280 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4280/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4280/comments | https://api.github.com/repos/huggingface/transformers/issues/4280/events | https://github.com/huggingface/transformers/pull/4280 | 615,842,026 | MDExOlB1bGxSZXF1ZXN0NDE2MDY5NzY4 | 4,280 | Update model-card | {
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- Fix the XTREME link.
- add the number of evaluation documents for each language.
- fix the usage piece of code to specify which framework to use. | {
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https://api.github.com/repos/huggingface/transformers/issues/4279 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4279/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4279/comments | https://api.github.com/repos/huggingface/transformers/issues/4279/events | https://github.com/huggingface/transformers/pull/4279 | 615,749,989 | MDExOlB1bGxSZXF1ZXN0NDE1OTkzNTYx | 4,279 | Documentation: fix links to NER examples | {
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"👍 \r\n"
] | 1,589 | 1,589 | 1,589 | COLLABORATOR | null | Hi,
this PR just fixes some links related to the NER examples :) | {
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https://api.github.com/repos/huggingface/transformers/issues/4278 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4278/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4278/comments | https://api.github.com/repos/huggingface/transformers/issues/4278/events | https://github.com/huggingface/transformers/issues/4278 | 615,663,406 | MDU6SXNzdWU2MTU2NjM0MDY= | 4,278 | Could you help with a huggingface/transformers pretrained models download link? | {
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"Hi, you can find the model identifiers in this JSON: https://huggingface.co/api/models\r\n\r\nThen you can get all files URLs by removing `bert/` from the objects' keys and prefixing with URL endpoint \"https://cdn.huggingface.co/\"",
"This issue has been automatically marked as stale because it has not had rece... | 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/4277 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4277/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4277/comments | https://api.github.com/repos/huggingface/transformers/issues/4277/events | https://github.com/huggingface/transformers/issues/4277 | 615,647,775 | MDU6SXNzdWU2MTU2NDc3NzU= | 4,277 | Use BART for longer documents | {
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"@thomwolf @sshleifer ",
"Yeah, here is working code for the copy approach, starting with bart-large-cnn weights.\r\n\r\n```python\r\nfrom copy import deepcopy\r\nfrom transformers import BartForConditionalGeneration\r\n\r\n# Get original model\r\nmodel = BartForConditionalGeneration.from_pretrained('bart-large-... | 1,589 | 1,648 | 1,589 | NONE | null | # ❓ Questions & Help
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new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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https://api.github.com/repos/huggingface/transformers/issues/4275 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4275/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4275/comments | https://api.github.com/repos/huggingface/transformers/issues/4275/events | https://github.com/huggingface/transformers/issues/4275 | 615,579,698 | MDU6SXNzdWU2MTU1Nzk2OTg= | 4,275 | training script for any tensorflow based pre-trained model for question-answer | {
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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 | 1,594 | 1,594 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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"Yes, this is https://github.com/huggingface/transformers/issues/1784 come again, the issue is in the doc, not in the code",
"Indeed, thanks for raising this issue."
] | 1,589 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Roberta
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x ] my own modified scripts: (give details below)
I use transformers tokenizer, a... | {
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"LGTM"
] | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | "Migrating from pytorch-transformers to transformers" is missing in the main document. It is available in the main `readme` thought. Just move it to the document. | {
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https://api.github.com/repos/huggingface/transformers/issues/4272 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4272/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4272/comments | https://api.github.com/repos/huggingface/transformers/issues/4272/events | https://github.com/huggingface/transformers/issues/4272 | 615,511,571 | MDU6SXNzdWU2MTU1MTE1NzE= | 4,272 | FileNotFoundError when running distributed Trainer | {
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"Yes, I think you're right. Relaunching training from a checkpoint would however require the user to copy the weights to other machines, right?",
"> Yes, I think you're right. Relaunching training from a checkpoint would however require the user to copy the weights to other machines, right?\r\n\r\nYes, loading fr... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | # 🐛 Bug
## Information
I'm running the language modeling example in distributed mode and am getting FileNotFoundError in the Trainer.
The error :
```
Traceback (most recent call last):
File "run_language_modeling.py", line 292, in <module>
main()
File "run_language_modeling.py", line 257, in main... | {
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"Yes: you need to use the path to the saved model as the `--model_name_or_path` argument.\r\n\r\n`--model_name_or_path` is the argument that conditions which model is loaded.\r\n\r\nWill close this for now."
] | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | # ❓ Questions & Help
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new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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"Hey! \r\n\r\nThanks a lot for your contribution on the trainer :+1:\r\n\r\nYour PR looks great! Just have a small comment, see above. Don't hesitate if you have questions!",
"#4252 \r\n\r\n```\r\n05/11/2020 19:59:05 - INFO - oauth2client.transport - Attempting refresh to obtain initial access_token\r\nINFO:ten... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | Working on getting the TF trainer running on TPUs for multiple choice. I'm quite the newb so input is needed.
- [x] Add 1 GPU strategy
- [x] Args for TPU Name
- [x] Add MPC example for TFTrainer
- [x] Fix docstrings
Examples:
GPU on Swag
https://colab.research.google.com/drive/1X9d1TY1I7r8d3rCJ9vWiy0UgvJ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4268 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4268/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4268/comments | https://api.github.com/repos/huggingface/transformers/issues/4268/events | https://github.com/huggingface/transformers/issues/4268 | 615,460,537 | MDU6SXNzdWU2MTU0NjA1Mzc= | 4,268 | KlDivBackward | {
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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 | 1,594 | 1,594 | NONE | null | Hi,
I fine-tune bert and using KLDivLoss instead of CrossEntropyLoss in binary classification. when I call
loss.backward()
I got this error !?
Thank you in advance | {
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https://api.github.com/repos/huggingface/transformers/issues/4267 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4267/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4267/comments | https://api.github.com/repos/huggingface/transformers/issues/4267/events | https://github.com/huggingface/transformers/pull/4267 | 615,443,765 | MDExOlB1bGxSZXF1ZXN0NDE1NzU3NTgx | 4,267 | useless chg | {
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https://api.github.com/repos/huggingface/transformers/issues/4266 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4266/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4266/comments | https://api.github.com/repos/huggingface/transformers/issues/4266/events | https://github.com/huggingface/transformers/pull/4266 | 615,443,223 | MDExOlB1bGxSZXF1ZXN0NDE1NzU3MTk1 | 4,266 | [CI] remove run_tests_torch_and_tf | {
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"(fixed git history locally for future PRs)",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4266?src=pr&el=h1) Report\n> Merging [#4266](https://codecov.io/gh/huggingface/transformers/pull/4266?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3487be75ef8f0d51c... | 1,589 | 1,597 | 1,597 | CONTRIBUTOR | null | Problem:
This job is rerunning all tests, after `run_tests_torch` and `run_tests_tf` with both packages installed. Meaning that it ~doubles the runtime of CI and doesn't find very many bugs.
Solution: This changes `run_tests_torch_and_tf` to only run the tests that require both TF and torch | {
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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 | Documentation of https://huggingface.co/transformers/model_doc/bert.html#transformers.BertModel.forward currently doesn't mention the usage of `tokenizers.BertWordPieceTokenizer` for instance when I am using BertModel.
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https://api.github.com/repos/huggingface/transformers/issues/4264 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4264/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4264/comments | https://api.github.com/repos/huggingface/transformers/issues/4264/events | https://github.com/huggingface/transformers/pull/4264 | 615,437,018 | MDExOlB1bGxSZXF1ZXN0NDE1NzUyNjQ4 | 4,264 | Align sentiment-analysis' tokenizer (currently cased) to the model (uncased) | {
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"LGTM, or even better we could duplicate those tokenizer files into `distilbert-base-uncased-finetuned-sst-2-english` as now we kind of assume that a model == model + tokenizer.",
"Merging this for now and can update to @julien-c's proposal in a future PR",
"Yeah, just wanted to ping @mfuntowicz on this model/t... | 1,589 | 1,589 | 1,589 | MEMBER | null | `sentiment-analysis` pipeline has a tokenizer using a cased vocab while the model is uncased.
This PR makes the tokenizer uncased to match the actual model's vocab. | {
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https://api.github.com/repos/huggingface/transformers/issues/4263 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4263/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4263/comments | https://api.github.com/repos/huggingface/transformers/issues/4263/events | https://github.com/huggingface/transformers/issues/4263 | 615,365,353 | MDU6SXNzdWU2MTUzNjUzNTM= | 4,263 | Sentiment Analysis Pipeline is predicting incorrect sentiment in 2.9 | {
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"This PR should fix the problem:\r\nhttps://github.com/huggingface/transformers/pull/4264\r\n\r\nA mismatched tokenizer is hooked up with the pipeline.",
"yes, you are right. \r\n\r\nI also tested all sentences both positive and negative. But it is showing NEGATIVE all the time.",
"> This PR should fix the prob... | 1,589 | 1,606 | 1,595 | NONE | null | # 🐛 Bug
Sentiment Analysis Pipeline is predicting incorrect sentiment. Everything seems to be NEGATIVE.
## To reproduce
Steps to reproduce the behavior:
Left a Colab Notebook here for reproducing: https://colab.research.google.com/drive/1hIwyBOGFpcLMUNmaKf5UYb0wPeYb4yKS?usp=sharing
`pip install -qU transfo... | {
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https://api.github.com/repos/huggingface/transformers/issues/4262 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4262/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4262/comments | https://api.github.com/repos/huggingface/transformers/issues/4262/events | https://github.com/huggingface/transformers/issues/4262 | 615,343,457 | MDU6SXNzdWU2MTUzNDM0NTc= | 4,262 | NER Models not using BIO tagging scheme | {
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"Hi @guillaume-be , only the CoNLL-2003 models are using this IOB1 tagging scheme, because it is used in the original dataset. You could convert it (+ needs proper testing) but this requires a modification of the original dataset.\r\n\r\nI could train models e.g. on the WikiANN corpus (see [here](https://www.aclweb... | 1,589 | 1,589 | 1,589 | CONTRIBUTOR | null | Hello,
I have noticed that most (all?) pre-trained models uploaded seem not to use the BIO tagging scheme, instead returning `I-xxx` and `O` for all categories (`B-xxx` is not used). I believe this is just caused by the way these models have been trained. This makes using these models in actual pipelines difficult a... | {
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https://api.github.com/repos/huggingface/transformers/issues/4261 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4261/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4261/comments | https://api.github.com/repos/huggingface/transformers/issues/4261/events | https://github.com/huggingface/transformers/issues/4261 | 615,341,240 | MDU6SXNzdWU2MTUzNDEyNDA= | 4,261 | I am training a bert model for question classification task, now it is a binary classifier. 0 for Descriptive question and 1 for not descriptive. While testing I am getting the following error :- | {
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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",
"use torch.unsqueeze(0) on b_input_ids,b_input_masks so that they become of shape (batch_size(=1),dim)",
"This issue has been automati... | 1,589 | 1,600 | 1,600 | NONE | null | I have generated my model with the help of around 1700 questions
But when I am testing it for one question at a time and running
outputs = model(b_input_ids, token_type_ids=None, attention_mask=b_input_masks)
It is giving me the following error
ValueError: Wrong shape for input_ids (shape torch.Size([1]))... | {
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https://api.github.com/repos/huggingface/transformers/issues/4260 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4260/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4260/comments | https://api.github.com/repos/huggingface/transformers/issues/4260/events | https://github.com/huggingface/transformers/issues/4260 | 615,322,870 | MDU6SXNzdWU2MTUzMjI4NzA= | 4,260 | Strange Behaviour using Transformer pipline with FLASK | {
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"Hi @nimahm2020, \r\n\r\nThanks for reporting. \r\nIt seems the tokenizer used for the default Sentiment Analysis pipeline was not aligned with the actual model. More precisely, the model is using an **uncased** vocab while the tokenizer is **cased**.\r\n\r\nI've opened a PR(#4264) to solve the issue, if you can/wa... | 1,589 | 1,594 | 1,594 | NONE | null | # ❓ Questions & Help
I am building a web-frame with Flask to run Transformer pipeline ( sentiment - analysis ) over Excel columns text.
However , In first try running Flask app , gives following error as :
ModuleNotFoundError: No module named 'tensorflow_core._api'
after few days, without any success,... | {
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"It seems this example was not updated after #3734. This is not the correct way to do it, as it now requires the user to specify the entire context all the time. Will open a PR now.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activit... | 1,589 | 1,594 | 1,594 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4258 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4258/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4258/comments | https://api.github.com/repos/huggingface/transformers/issues/4258/events | https://github.com/huggingface/transformers/issues/4258 | 615,260,837 | MDU6SXNzdWU2MTUyNjA4Mzc= | 4,258 | Model call with `inputs_embeds` does not match that with `input_ids` | {
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"I was incorrectly treating the output of the first layer as the actual embedding lookup when it is in fact the embedding lookup *plus* positional and token type embeddings. See [here](https://stackoverflow.com/a/61704348/424306) for more details."
] | 1,589 | 1,589 | 1,589 | 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: my own modified scripts: (details below)
## To reproduce
Steps to reproduce the behavior:
```
import tensorflow as tf
from transformers ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4257 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4257/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4257/comments | https://api.github.com/repos/huggingface/transformers/issues/4257/events | https://github.com/huggingface/transformers/pull/4257 | 615,245,432 | MDExOlB1bGxSZXF1ZXN0NDE1NjIwMzE4 | 4,257 | added functionality for electra classification head | {
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"This is great, thanks @liuzzi!\r\n\r\nWe would need to add the corresponding tests. Can you do it, or would you like me to do it? If so, may I push directly on your fork?",
"@LysandreJik sure! i just invited you to collaborate. I haven't been inside the transformers testing code so it'd probably be much faster ... | 1,589 | 1,590 | 1,590 | CONTRIBUTOR | null | Added functionality for an electra classification head following the google repo.
Tested and trains fine with the run_glue script. I was testing on my own repurposed classification problems so i didnt evaluate the actual GLUE accuracies, but can confirm that it is getting competitive results on my own problems.
Sa... | {
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https://api.github.com/repos/huggingface/transformers/issues/4256 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4256/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4256/comments | https://api.github.com/repos/huggingface/transformers/issues/4256/events | https://github.com/huggingface/transformers/issues/4256 | 615,238,397 | MDU6SXNzdWU2MTUyMzgzOTc= | 4,256 | Vaswani's Transformer (Encoder-Decoder) decoding methods | {
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"Hello @manzar96 \r\nThe `.generate` method can be used with any HF model with a LM head on top.",
"Ok thank you.\r\nSo it can be used only with those models https://pytorch.org/hub/huggingface_pytorch-transformers/ (having a LM head on top) ",
"This issue has been automatically marked as stale because it has n... | 1,589 | 1,594 | 1,594 | NONE | null | Hi,
I recently studied this blog https://huggingface.co/blog/how-to-generate for using different decoding methods with PreTrained Models.
I would like to ask if it is possible to use those methods with the simple Encoder-Decoder Transformer model (as mentioned in Vaswani's paper) (as it is available in pytorch l... | {
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https://api.github.com/repos/huggingface/transformers/issues/4255 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4255/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4255/comments | https://api.github.com/repos/huggingface/transformers/issues/4255/events | https://github.com/huggingface/transformers/pull/4255 | 615,204,838 | MDExOlB1bGxSZXF1ZXN0NDE1NTkzNjgy | 4,255 | bert uncased models needs lower casing option turned on in the example code. | {
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"Those models should contain config that initializes their tokenizer with the correct `do_lower_case=True` option. Is this not the case?\r\n\r\ni.e. we are moving the tokenizer configuration out of those example scripts (see updated scripts for `Trainer` at https://github.com/huggingface/transformers/tree/master/ex... | 1,589 | 1,590 | 1,590 | NONE | null | The command to replicate bert-base-uncased model and bert-large-uncased-whole-word-masking model results on Squad requires --do_lower_case to be used. If not, the result is low. | {
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"I don't think you can load .tars directly. Simply use the name as described in [the model page](https://huggingface.co/allenai/scibert_scivocab_uncased), and it should work.\r\n\r\n```python\r\ntokenizer = AutoTokenizer.from_pretrained(\"allenai/scibert_scivocab_uncased\")\r\n```",
"Thank You @BramVanroy .\r\nIt... | 1,589 | 1,589 | 1,589 | NONE | null | os : google colab
from transformers import *
tokenizer = AutoTokenizer.from_pretrained('https://s3-us-west-2.amazonaws.com/ai2-s2-research/scibert/huggingface_pytorch/scibert_scivocab_uncased.tar')
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https://api.github.com/repos/huggingface/transformers/issues/4253 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4253/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4253/comments | https://api.github.com/repos/huggingface/transformers/issues/4253/events | https://github.com/huggingface/transformers/pull/4253 | 615,177,257 | MDExOlB1bGxSZXF1ZXN0NDE1NTc2MTE2 | 4,253 | Conversion script to export transformers models to ONNX IR. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4253?src=pr&el=h1) Report\n> Merging [#4253](https://codecov.io/gh/huggingface/transformers/pull/4253?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c558761ad11beba5e70dd505e1c97bdc4eb6ee9c&el=desc) will **not chan... | 1,589 | 1,589 | 1,589 | MEMBER | null | This PR adds conversion script to export our models to ONNX IR.
Plan is to support both PyTorch and TensorFlow:
- [x] PyTorch
- [x] TensorFlow
TensorFlow currently blocked because of an issue in the conversion script provided by ONNX (seems fixed on master : https://github.com/onnx/tensorflow-onnx/issues/87... | {
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https://api.github.com/repos/huggingface/transformers/issues/4252 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4252/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4252/comments | https://api.github.com/repos/huggingface/transformers/issues/4252/events | https://github.com/huggingface/transformers/issues/4252 | 615,175,259 | MDU6SXNzdWU2MTUxNzUyNTk= | 4,252 | How to specify a TPU IP for run_tf_glue.py? | {
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"TPUs can be autodiscovered if you use them through AI-platform by running the trainer with `gcloud ai-platform jobs submit training ...` This is the advised usage of TPUs I put in the trainer.\r\n\r\nNevertheless if your want to use it through its name, this is done in the following PR #4270 thanks to @ViktorAlm",... | 1,589 | 1,595 | 1,595 | CONTRIBUTOR | null | Hi team!
I have a VM on Google Cloud and a TPU. When running your example script `run_tf_glue.py` there is no option for specifying a TPU IP. It seems like the TPU cannot be auto-discovered and then training falls back to training on CPU 🐢 | {
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## Information
Model I am using (Bert, XLNet ...): Roberta as encoder and Bert as decoder
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 datas... | {
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https://api.github.com/repos/huggingface/transformers/issues/4250 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4250/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4250/comments | https://api.github.com/repos/huggingface/transformers/issues/4250/events | https://github.com/huggingface/transformers/issues/4250 | 615,152,099 | MDU6SXNzdWU2MTUxNTIwOTk= | 4,250 | [Request] NER Scripts on CoNLL 2003 dataset | {
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"Hi @gyuwankim the problem with English CoNLL dataset is, that it is not freely available (because it requires access to Reuters corpora in order to create it from scratch with the provided scripts).\r\n\r\nYou can find the dataset somehow on GitHub, but legally this is very dubious (and you have no guarantee that ... | 1,589 | 1,595 | 1,595 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
Current NER scripts (data preparation, train, and evaluation) is for the GermEval 2014 dataset.
It is very nice. However, according to the or... | {
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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 | 1,594 | 1,594 | NONE | null | It'd be helpful to provide an option for sentiment analysis pipeline output the original ratings rather than the positive/negative tags.
Also the documentation doesn't really explain what the output scores mean.. | {
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https://api.github.com/repos/huggingface/transformers/issues/4247 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4247/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4247/comments | https://api.github.com/repos/huggingface/transformers/issues/4247/events | https://github.com/huggingface/transformers/pull/4247 | 615,111,074 | MDExOlB1bGxSZXF1ZXN0NDE1NTMwMjA2 | 4,247 | removed variable api from pplm example | {
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"By the way, did this approach work for you? I tried a similar one and I couldn't stop getting an error about incompatible output shapes when calculating sparse categorical accuracy.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activi... | 1,588 | 1,636 | 1,599 | NONE | null | I'm looking to fine tune a GPT-2 model with several songs from the same artist. However, I'm not exactly sure how I should be feeding nearly 300 songs into the model to learn from.
Currently, I'm breaking the lyrics into blocks of 100 and feeding them into my model:
```
lyrics = open('/JayZ_lyrics.txt', "r", enc... | {
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https://api.github.com/repos/huggingface/transformers/issues/4245 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4245/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4245/comments | https://api.github.com/repos/huggingface/transformers/issues/4245/events | https://github.com/huggingface/transformers/pull/4245 | 615,073,186 | MDExOlB1bGxSZXF1ZXN0NDE1NTAxODQz | 4,245 | Add back option --do_lower_case in SQuAD for uncased models | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4245?src=pr&el=h1) Report\n> Merging [#4245](https://codecov.io/gh/huggingface/transformers/pull/4245?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7b75aa9fa55bee577e2c7403301ed31103125a35&el=desc) will **increase... | 1,588 | 1,590 | 1,590 | CONTRIBUTOR | null | The option `--do_lower_case` is currently needed by the uncased models (i.e., bert-base-uncased, bert-large-uncased). The results w/ and w/o this option are shown below.
The option was deleted in the current v2.9.0 version so this PR tries to add it back. This would not affect the cased models (i.e., RoBERTa, XLNet... | {
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https://api.github.com/repos/huggingface/transformers/issues/4244 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4244/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4244/comments | https://api.github.com/repos/huggingface/transformers/issues/4244/events | https://github.com/huggingface/transformers/pull/4244 | 615,053,367 | MDExOlB1bGxSZXF1ZXN0NDE1NDg3MDYz | 4,244 | Allow gpt2 to be exported to valid ONNX | {
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"@LysandreJik failing unittest seems unrelated to the change-set introduced in this PR",
"Indeed @mfuntowicz "
] | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | Problem: gpt2 model and other models using gelu_new or gelu_fast cannot be exported to valid ONNX model.
Causes:
PyTorch will export some constants like 1 or 2 as int64, while ONNX operators like [Add](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Add) and [Pow](https://github.com/onnx/onnx/blob/master... | {
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https://api.github.com/repos/huggingface/transformers/issues/4243 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4243/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4243/comments | https://api.github.com/repos/huggingface/transformers/issues/4243/events | https://github.com/huggingface/transformers/pull/4243 | 615,048,944 | MDExOlB1bGxSZXF1ZXN0NDE1NDgzNjM3 | 4,243 | Distributed eval: SequentialDistributedSampler + gather all results | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4243?src=pr&el=h1) Report\n> Merging [#4243](https://codecov.io/gh/huggingface/transformers/pull/4243?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2d05480174c736399c212b3d60b8774fbbf2b6c2&el=desc) will **decrease... | 1,588 | 1,589 | 1,589 | MEMBER | null | As discussed in #3944
In our [**`Trainer`**](https://github.com/huggingface/transformers/blob/master/src/transformers/trainer.py), in torch.distributed mode, eval/predict are currently running on a single node. This PR attempts to fix this.
This relies on:
- a custom `DistributedSampler` named SequentialDistribu... | {
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https://api.github.com/repos/huggingface/transformers/issues/4242 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4242/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4242/comments | https://api.github.com/repos/huggingface/transformers/issues/4242/events | https://github.com/huggingface/transformers/pull/4242 | 614,926,172 | MDExOlB1bGxSZXF1ZXN0NDE1MzgzNDIz | 4,242 | Reformer self attention mask value not converted in apex half precision | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4242?src=pr&el=h1) Report\n> Merging [#4242](https://codecov.io/gh/huggingface/transformers/pull/4242?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7b75aa9fa55bee577e2c7403301ed31103125a35&el=desc) will **increase... | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using Reformer:
Language I am using the model on 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 below)
## To reproduce
Steps to reproduce the... | {
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"I have submitted a pull request in #4242 ",
"Awesome I will take a look - thanks for the PR :-) "
] | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using Reformer:
Language I am using the model on 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 below)
## To reproduce
Steps to reproduce the... | {
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"Try initialize the model in the trainer script from transformers with self.model = model.cuda()",
"I am getting the same error. Is there work around ? \r\nWhat @tebandesade mentioned didnt work out for.",
"I faced the same problem with RoBERTa pretraining, however inserting line model = model.cuda() before tr... | 1,588 | 1,590 | 1,589 | NONE | null | I am traing a roberta model and running the script examples/run_language_modeling.py
The following error occurs when i am trying to resume training.
Traceback (most recent call last):
File "examples/run_language_modeling.py", line 284, in <module>
main()
File "examples/run_language_modeling.py", line 254, ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4239 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4239/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4239/comments | https://api.github.com/repos/huggingface/transformers/issues/4239/events | https://github.com/huggingface/transformers/issues/4239 | 614,909,295 | MDU6SXNzdWU2MTQ5MDkyOTU= | 4,239 | distilbert-base-uncased | {
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"hi! did you find a solution? I got the same problem!",
"I have the same problem with a freshly installed version. Any ideas?",
"This can happen if there is a network or firewall issue that prevents the `transformers` library from downloading the required files. To replicate on a laptop, you can delete the ca... | 1,588 | 1,608 | 1,603 | NONE | null | # 🐛 Bug/Question
## Information
am trying to execute :
**import ktrain
from ktrain import text
MODEL_NAME='distilbert-base-uncased'
t=text.Transformer(MODEL_NAME, maxlen=500, classes=np.unique(y_train))**
I get the following error:
OSError: Model name 'distilbert-base-uncased' was not found in t... | {
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https://api.github.com/repos/huggingface/transformers/issues/4238 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4238/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4238/comments | https://api.github.com/repos/huggingface/transformers/issues/4238/events | https://github.com/huggingface/transformers/pull/4238 | 614,824,863 | MDExOlB1bGxSZXF1ZXN0NDE1MzAwNzcz | 4,238 | [tests] make pipelines tests faster with smaller models | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4238?src=pr&el=h1) Report\n> Merging [#4238](https://codecov.io/gh/huggingface/transformers/pull/4238?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/274d850d340c0004ee63627c88c433d0e55f5876&el=desc) will **increase... | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | - speedup: 8mins -> 90s on 1 CPU
- besides `test_fill_mask` the removed coverage was not meaningful, only shapes were being checked.
- Would be happy to continue for TF or get help.
- could use these in some examples tests also.
| {
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https://api.github.com/repos/huggingface/transformers/issues/4237 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4237/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4237/comments | https://api.github.com/repos/huggingface/transformers/issues/4237/events | https://github.com/huggingface/transformers/issues/4237 | 614,788,550 | MDU6SXNzdWU2MTQ3ODg1NTA= | 4,237 | Only self-attention returned when output_attentions = True for BERT | {
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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"
] | 1,588 | 1,594 | 1,594 | NONE | null | # 🐛 Bug
```
if self.output_attentions:
all_attentions = all_attentions + (layer_outputs[1],)
```
should be
```
if self.output_attentions:
all_attentions = all_attentions + (layer_outputs[1:],)
```
## Information
Line 412 [here](https://github.com/huggingface/transformers/blob... | {
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https://api.github.com/repos/huggingface/transformers/issues/4236 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4236/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4236/comments | https://api.github.com/repos/huggingface/transformers/issues/4236/events | https://github.com/huggingface/transformers/pull/4236 | 614,778,455 | MDExOlB1bGxSZXF1ZXN0NDE1MjYzNjE1 | 4,236 | Pipelines: use tokenizer.max_len | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4236?src=pr&el=h1) Report\n> Merging [#4236](https://codecov.io/gh/huggingface/transformers/pull/4236?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cf08830c2868c5335b1657f95779f370862e3a28&el=desc) will **decrease... | 1,588 | 1,592 | 1,592 | CONTRIBUTOR | null | fix #4224 by passing tokenizer.max_len to `tokenizer.batch_encode_plus`
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https://api.github.com/repos/huggingface/transformers/issues/4235 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4235/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4235/comments | https://api.github.com/repos/huggingface/transformers/issues/4235/events | https://github.com/huggingface/transformers/issues/4235 | 614,768,404 | MDU6SXNzdWU2MTQ3Njg0MDQ= | 4,235 | Error importing Reformer model | {
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"I think you only need to update the library.\r\nVersion 2.9, released esterday, contains the reformer model",
"Thanks, \r\nInstalling Version 2.9.0 solved the issue"
] | 1,588 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
I am trying to import the Reformer model as in here:
https://huggingface.co/transformers/model_doc/reformer.html
'''
from transformers import ReformerModel, ReformerConfig
'''
However, I am getting the following error:
ImportError: cannot import name 'ReformerModel' from 'transformer... | {
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https://api.github.com/repos/huggingface/transformers/issues/4234 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4234/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4234/comments | https://api.github.com/repos/huggingface/transformers/issues/4234/events | https://github.com/huggingface/transformers/issues/4234 | 614,767,184 | MDU6SXNzdWU2MTQ3NjcxODQ= | 4,234 | [infra] make a tiny "distilroberta-base" to speed up test_pipelines.py and test_examples.py | {
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doing the same for distilbert-base would probably also help. | {
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https://api.github.com/repos/huggingface/transformers/issues/4233 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4233/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4233/comments | https://api.github.com/repos/huggingface/transformers/issues/4233/events | https://github.com/huggingface/transformers/issues/4233 | 614,762,177 | MDU6SXNzdWU2MTQ3NjIxNzc= | 4,233 | How can I mute the info from BertTokenizerFast.encode_plus | {
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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"
] | 1,588 | 1,594 | 1,594 | NONE | null | # 🐛 Bug
## Information
Model I am using:
Bert
Language I am using the model on (English, Chinese ...):
Chinese
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
```python
tokenizer.encode_plus(...)
```
Every ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4232 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4232/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4232/comments | https://api.github.com/repos/huggingface/transformers/issues/4232/events | https://github.com/huggingface/transformers/issues/4232 | 614,733,144 | MDU6SXNzdWU2MTQ3MzMxNDQ= | 4,232 | MarianMTModel: Runtime Errors | {
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"Fixed on S3.\r\n"
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | 11/1010 models cannot me loaded because of state_dict mismatches (not tokenizer).
```python
failing = ['sv-tpi',
'fi-en',
'sv-ty',
'sv-toi',
'en-st',
'en-tl',
'sv-ts',
'sv-tvl',
'en-fi',
'en-ml',
'fi-sv']
for mname in failing:
slug = f'opus-mt-{mname}'
MarianMTModel.from_pretrained(slug)
`... | {
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https://api.github.com/repos/huggingface/transformers/issues/4231 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4231/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4231/comments | https://api.github.com/repos/huggingface/transformers/issues/4231/events | https://github.com/huggingface/transformers/issues/4231 | 614,704,731 | MDU6SXNzdWU2MTQ3MDQ3MzE= | 4,231 | Strange difference between NER results in 2.8.0 and previous versions | {
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"FYI, ran in 2.9.0 as well and got the same results.",
"Hi @pvcastro , so the CoNLL results are looking good 🤔 Because there's an improviment with 2.8.\r\n\r\nRegarding to HAREM: Could you verify that there's a `tokenizer_config.json` located in the `/home/models/albert/base_pt_brwac_en/albert_ckp_1176k` folder?... | 1,588 | 1,596 | 1,596 | NONE | null | # 🐛 Bug
## Information
Model I am using: Albert
Language I am using the model on: English and Portuguese
The problem arises when using:
* [ ] the official example scripts: (give details below)
The tasks I am working on is:
* [ ] my own task or dataset: (give details below)
## To reproduce
Not su... | {
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https://api.github.com/repos/huggingface/transformers/issues/4230 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4230/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4230/comments | https://api.github.com/repos/huggingface/transformers/issues/4230/events | https://github.com/huggingface/transformers/pull/4230 | 614,683,612 | MDExOlB1bGxSZXF1ZXN0NDE1MTg3Mzgw | 4,230 | example updated to use generation pipeline | {
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"That's great, thanks! cc @patrickvonplaten for the text-generation pipeline"
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4229 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4229/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4229/comments | https://api.github.com/repos/huggingface/transformers/issues/4229/events | https://github.com/huggingface/transformers/issues/4229 | 614,660,602 | MDU6SXNzdWU2MTQ2NjA2MDI= | 4,229 | Problem with BertTokenizer using additional_special_tokens | {
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"I've also confronted this issue. \r\nIn my case, with `transformers v2.8.0` it correctly splits special token. \r\nBut from `v2.9.0`, it splits the special tokens like `'[', 'e', '##11', ']'`. It's quite weird...",
"This issue has been automatically marked as stale because it has not had recent activity. It will... | 1,588 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
Model I am using: Bert (bert-base-uncased)
Language I am using the model on: English
The problem arises when using:
* [ ] the official example scripts: (give details below)
The tasks I am working on is:
* [ ] my own task or dataset: (give details below)
## To reproduce
Ste... | {
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`TextDataset` throws out of index error.
## Information
```
model_args = ModelArguments(model_name_or_path = 'Reformer',
config_name = 'ReformerConfig',
tokenizer_name = 'ReformerTokenizer')
training_args = TrainingArguments(output_dir = '/tmp', do... | {
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"Can you provide a smaller reproduction case?",
"```\r\n# Downloading pre-trained model\r\n!wget https://github.com/sdadas/polish-roberta/releases/download/models/roberta_base_transformers.zip\r\n!unzip roberta_base_transformers.zip -d roberta_base_transformers\r\n!pip install transformers -q\r\n\r\nfrom tokenize... | 1,588 | 1,604 | 1,598 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): **Roberta with RobertaForSequenceClassification head**
Language I am using the model on (English, Chinese ...): **Polish**
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (giv... | {
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https://api.github.com/repos/huggingface/transformers/issues/4226 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4226/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4226/comments | https://api.github.com/repos/huggingface/transformers/issues/4226/events | https://github.com/huggingface/transformers/pull/4226 | 614,585,645 | MDExOlB1bGxSZXF1ZXN0NDE1MTA5Nzk0 | 4,226 | Simplify cache vars and allow for TRANSFORMERS_CACHE env | {
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This PR:
- ad... | {
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https://api.github.com/repos/huggingface/transformers/issues/4225 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4225/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4225/comments | https://api.github.com/repos/huggingface/transformers/issues/4225/events | https://github.com/huggingface/transformers/issues/4225 | 614,514,275 | MDU6SXNzdWU2MTQ1MTQyNzU= | 4,225 | [Reformer/Longformer] Add cross-attention layers for Encoder-Decoder setting | {
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"It's a good question. I originally thought it will be quite easy to add - but it's not going to be that trivial.\r\n\r\nFor the encoder-decoder setting, we need a lsh cross attention layer that receives different embeddings for query and keys so that the usual LSH hashing method does not work. \r\n\r\nIt will prob... | 1,588 | 1,602 | 1,602 | MEMBER | null | # ❓ Questions & Help
## Details
It seems that Reformer model has been added in Transformers. But it's a standard auto-regressive language model. How can we use Reformer in Encoder-Decoder settings ?
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https://api.github.com/repos/huggingface/transformers/issues/4224 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4224/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4224/comments | https://api.github.com/repos/huggingface/transformers/issues/4224/events | https://github.com/huggingface/transformers/issues/4224 | 614,493,428 | MDU6SXNzdWU2MTQ0OTM0Mjg= | 4,224 | Bart now enforces maximum sequence length in Summarization Pipeline | {
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"#3857 might also be a culprit",
"@pwschaedler This is a change in pipelines that we may or may not undo. Previously, the tokenizer truncated your long documents to their beginnings\r\nIn the meantime, you can use this code on the latest transformers:\r\n\r\n```python\r\nfrom transformers import BartForConditiona... | 1,588 | 1,673 | 1,607 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bart (bart-large-cnn)
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)
Based on example... | {
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https://api.github.com/repos/huggingface/transformers/issues/4223 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4223/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4223/comments | https://api.github.com/repos/huggingface/transformers/issues/4223/events | https://github.com/huggingface/transformers/pull/4223 | 614,433,866 | MDExOlB1bGxSZXF1ZXN0NDE0OTkyMTA3 | 4,223 | [TPU] Doc, fix xla_spawn.py, only preprocess dataset once | {
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"Ok, merging this!"
] | 1,588 | 1,588 | 1,588 | MEMBER | null | - Fixed the `xla_spawn.py` launcher script which I broke earlier today when moving files around. It should be reasonably more robust now.
- Started to add a little documentation
- Changed the dataset logic so that multiple workers don't concurrently preprocess the dataset.
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https://api.github.com/repos/huggingface/transformers/issues/4222 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4222/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4222/comments | https://api.github.com/repos/huggingface/transformers/issues/4222/events | https://github.com/huggingface/transformers/issues/4222 | 614,417,240 | MDU6SXNzdWU2MTQ0MTcyNDA= | 4,222 | TPU Trainer's PerDeviceLoader has no len() | {
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"@jysohn23 (and @dlibenzi) might want to chime in on this but I think this works in xla's nightly from https://github.com/pytorch/xla/pull/1991\r\n\r\n(We might still want to improve things but if this is blocking you, please try using the nightly build of xla)",
"Yeah it's recently been added, so if you could se... | 1,588 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
The new TPU Trainer fails when running on a single TPU core in a colab notebook since the XLA ParallelLoader's PerDeviceLoader does not implement a length method.
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem... | {
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https://api.github.com/repos/huggingface/transformers/issues/4221 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4221/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4221/comments | https://api.github.com/repos/huggingface/transformers/issues/4221/events | https://github.com/huggingface/transformers/pull/4221 | 614,408,495 | MDExOlB1bGxSZXF1ZXN0NDE0OTcxNzg3 | 4,221 | feat(trainer): log epoch and final metrics | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4221?src=pr&el=h1) Report\n> Merging [#4221](https://codecov.io/gh/huggingface/transformers/pull/4221?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c99fe0386be118bceaab1c85cdb8309eb8cb8208&el=desc) will **increase... | 1,588 | 1,591 | 1,591 | CONTRIBUTOR | null | This PR adds new logging capabilities to `Trainer`:
* logs epoch -> this let us compare runs with different batch sizes, using "epoch" as the x-axis instead of "global_step"
* logs final metrics -> metrics are also logged by `Trainer.evaluate` at the end of the script (or at the start if we just use `--do_eval` and... | {
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https://api.github.com/repos/huggingface/transformers/issues/4220 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4220/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4220/comments | https://api.github.com/repos/huggingface/transformers/issues/4220/events | https://github.com/huggingface/transformers/pull/4220 | 614,404,557 | MDExOlB1bGxSZXF1ZXN0NDE0OTY4NTY3 | 4,220 | Improvements to the wandb integration | {
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"Hey guys, any updates on this?",
"@vanpelt Can't push to your fork so will tweak things in #4324 and combine with @borisdayma's #4221 "
] | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | Hey guys,
I'm one of the founders of W&B and have been working with @borisdayma on the wandb integration. I made a few changes to address a few cases we thought through:
1. If wandb is installed but the user hasn't logged in we now print a warning instead of prompting for an api_key
2. Made messaging more clear ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4219 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4219/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4219/comments | https://api.github.com/repos/huggingface/transformers/issues/4219/events | https://github.com/huggingface/transformers/issues/4219 | 614,402,367 | MDU6SXNzdWU2MTQ0MDIzNjc= | 4,219 | Need correction in GPT-2 perplexity equation based on computation | {
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"Off-topic, but it's high time that Github supports KaTeX =)",
"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"
] | 1,588 | 1,594 | 1,594 | NONE | null | # ❓ Questions & Help
I would like to formulate GPT-2 perplexity [calculation ](https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_language_modeling.py#L266)in terms of equation as under:
![image](https://user-images.githubusercontent.com/64096105/81352017-2d8b7b80-90ce-11ea-8c... | {
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https://api.github.com/repos/huggingface/transformers/issues/4218 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4218/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4218/comments | https://api.github.com/repos/huggingface/transformers/issues/4218/events | https://github.com/huggingface/transformers/pull/4218 | 614,387,362 | MDExOlB1bGxSZXF1ZXN0NDE0OTU0NjU0 | 4,218 | feat(Trainer): log epoch and final metrics | {
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"^^ I borked your PR unfortunately (💩). Sorry about that. Care to open a new one?\r\n\r\n(same for #4211)",
"Sure, no worry!"
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | This PR adds new logging capabilities to `Trainer`:
* logs epoch -> this let us compare runs with different batch sizes, using "epoch" as the x-axis instead of "global_step"
* logs final metrics -> metrics are also logged by `Trainer.evaluate` at the end of the script (or at the start if we just use `--do_eval` and... | {
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https://api.github.com/repos/huggingface/transformers/issues/4217 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4217/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4217/comments | https://api.github.com/repos/huggingface/transformers/issues/4217/events | https://github.com/huggingface/transformers/pull/4217 | 614,372,160 | MDExOlB1bGxSZXF1ZXN0NDE0OTQyMzA5 | 4,217 | [Pipeline, Generation] tf generation pipeline bug | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4217?src=pr&el=h1) Report\n> Merging [#4217](https://codecov.io/gh/huggingface/transformers/pull/4217?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8bf7312654d40cea1a399e86f9fe8e39e1ea3a1e&el=desc) will **increase... | 1,588 | 1,589 | 1,588 | MEMBER | null | Generation can currently not be used for TF due to a small bug. This PR fixes it and adds tests.
I will update the usage docs and pipeline notebook tomorrow. | {
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https://api.github.com/repos/huggingface/transformers/issues/4216 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4216/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4216/comments | https://api.github.com/repos/huggingface/transformers/issues/4216/events | https://github.com/huggingface/transformers/pull/4216 | 614,353,774 | MDExOlB1bGxSZXF1ZXN0NDE0OTI3NjIx | 4,216 | [examples/summarization] run_train_tiny.sh: remove unused kwarg | {
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"I borked your PR unfortunately (💩). Sorry about that. Care to open a new one?"
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4214 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4214/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4214/comments | https://api.github.com/repos/huggingface/transformers/issues/4214/events | https://github.com/huggingface/transformers/issues/4214 | 614,252,770 | MDU6SXNzdWU2MTQyNTI3NzA= | 4,214 | [examples] text_classification/run_pl.sh error | {
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"I encountered this bug",
"Removing the `test_end` method in `BaseTransformer` (file: https://github.com/huggingface/transformers/blob/master/examples/lightning_base.py) solved the issue for me.\r\n\r\nFrom my understanding, what is happening here is that at the end of testing, `test_end` is being called which is... | 1,588 | 1,595 | 1,595 | CONTRIBUTOR | null | ```bash
cd examples/text-classification
./run_pl.sh
```
trains for 1 epoch, tests 12/13 steps, then fails with the following traceback
```python
/home/shleifer/.conda/envs/nb/lib/python3.7/site-packages/pytorch_lightning/utilities/warnings.py:18: UserWarning: The dataloader, test dataloader 0, does not have man... | {
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https://api.github.com/repos/huggingface/transformers/issues/4213 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4213/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4213/comments | https://api.github.com/repos/huggingface/transformers/issues/4213/events | https://github.com/huggingface/transformers/pull/4213 | 614,225,845 | MDExOlB1bGxSZXF1ZXN0NDE0ODI0MDI0 | 4,213 | BIG Reorganize examples | {
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"Really cool!"
] | 1,588 | 1,588 | 1,588 | MEMBER | null | {
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