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https://api.github.com/repos/huggingface/transformers/issues/4720 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4720/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4720/comments | https://api.github.com/repos/huggingface/transformers/issues/4720/events | https://github.com/huggingface/transformers/pull/4720 | 629,111,523 | MDExOlB1bGxSZXF1ZXN0NDI2NTEyNjU3 | 4,720 | [Reformer] Improved memory if input is shorter than chunk length | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4720?src=pr&el=h1) Report\n> Merging [#4720](https://codecov.io/gh/huggingface/transformers/pull/4720?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/47a551d17b6ed2eaf03301f049006d559fca5cf3&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | MEMBER | null | This PR improves memory and speed of Reformer for language generatinon.
Reformer is based on chunked self attention. This means that for an input length which is not a multiple of the chunk length, the input has to be padded to be a multiple of the chunk length. This is not the case though when the input length is ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4719 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4719/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4719/comments | https://api.github.com/repos/huggingface/transformers/issues/4719/events | https://github.com/huggingface/transformers/issues/4719 | 629,103,653 | MDU6SXNzdWU2MjkxMDM2NTM= | 4,719 | About `do_basic_tokenize` behavior in BertTokenizer | {
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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",
"there is a `BasicTokenizer` in previous `pytorch_transformers` package:\r\n it just says that it performs a basic tokenization before the word piecer. But what is actually a "basic tokenization"? I would really appreciate a little more of information on th... | {
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https://api.github.com/repos/huggingface/transformers/issues/4718 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4718/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4718/comments | https://api.github.com/repos/huggingface/transformers/issues/4718/events | https://github.com/huggingface/transformers/pull/4718 | 629,021,810 | MDExOlB1bGxSZXF1ZXN0NDI2NDQyNTMw | 4,718 | Replace pad_token with -100 for LM loss calculation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4718?src=pr&el=h1) Report\n> Merging [#4718](https://codecov.io/gh/huggingface/transformers/pull/4718?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e80d6c689bd62f805a5c8d77ec0cc3b09f240d14&el=desc) will **decrease... | 1,591 | 1,593 | 1,593 | CONTRIBUTOR | null | The docs for both GPT and [GPT2](https://huggingface.co/transformers/model_doc/gpt2.html#gpt2lmheadmodel) specify that labels that are not -100 will be used for the calculation of the loss. So, the padding for the labels should be `-100`, not `tokenizer.pad_token_id`. | {
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https://api.github.com/repos/huggingface/transformers/issues/4717 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4717/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4717/comments | https://api.github.com/repos/huggingface/transformers/issues/4717/events | https://github.com/huggingface/transformers/pull/4717 | 629,010,238 | MDExOlB1bGxSZXF1ZXN0NDI2NDMzODgz | 4,717 | Override get_vocab for fast tokenizer. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4717?src=pr&el=h1) Report\n> Merging [#4717](https://codecov.io/gh/huggingface/transformers/pull/4717?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/76779363160a598f130433209a77f8a747351b61&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4716 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4716/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4716/comments | https://api.github.com/repos/huggingface/transformers/issues/4716/events | https://github.com/huggingface/transformers/issues/4716 | 628,994,410 | MDU6SXNzdWU2Mjg5OTQ0MTA= | 4,716 | Can I save a word embedding from BERT and used again later for computational purpose(as BERT takes much more time). Just like in Glove. If yes then How? and is this good idea to do so? | {
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"As per my understanding, you can! \r\n\r\nIf you read the BERT paper by Devlin et.al., you can see that two suggested ways to extract said word embeddings would be to concatenate the last four hidden layers (9 to 12), generating a 4*768=3072 sized embedding for each token. Alternatively you can also sum or average... | 1,591 | 1,597 | 1,597 | 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/4715 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4715/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4715/comments | https://api.github.com/repos/huggingface/transformers/issues/4715/events | https://github.com/huggingface/transformers/issues/4715 | 628,935,530 | MDU6SXNzdWU2Mjg5MzU1MzA= | 4,715 | how to make a multi-task deep neural network baseline using huggingface 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"
] | 1,591 | 1,596 | 1,596 | NONE | null | I was trying to build a [multi-task deep neural network][1] using [xlm roberta large model][2] for a multilingual classification problem. my training dataset contains 4 columns :
1. ID
2. comment_text (according to id number,each users english comment is stored in this column. example comment : "you are a loser"... | {
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https://api.github.com/repos/huggingface/transformers/issues/4714 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4714/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4714/comments | https://api.github.com/repos/huggingface/transformers/issues/4714/events | https://github.com/huggingface/transformers/issues/4714 | 628,881,518 | MDU6SXNzdWU2Mjg4ODE1MTg= | 4,714 | ImportError: cannot import name 'MODEL_WITH_LM_HEAD_MAPPING' | {
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"This might help: #3444",
"`MODEL_WITH_LM_HEAD_MAPPING` is a mapping containing all the *Pytorch* models that have an LM head. Since you don't have PyTorch installed, you can't import them.\r\n\r\nWith TensorFlow you're probably looking for `TF_MODEL_WITH_LM_HEAD_MAPPING`.\r\n\r\nPlease note that the `run_languag... | 1,591 | 1,591 | 1,591 | NONE | null | ImportError: cannot import name 'MODEL_WITH_LM_HEAD_MAPPING' from 'transformers' (C:\Users\<username>\anaconda3\envs\tensorflow\lib\site-packages\transformers\__init__.py)
Model I am using (Bert, XLNet ...): GPT2
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
[... | {
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https://api.github.com/repos/huggingface/transformers/issues/4713 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4713/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4713/comments | https://api.github.com/repos/huggingface/transformers/issues/4713/events | https://github.com/huggingface/transformers/issues/4713 | 628,796,389 | MDU6SXNzdWU2Mjg3OTYzODk= | 4,713 | Is there any need to fine-tune the already pre-trained GPT-2 models? | {
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"\"Finetuning\" a GPT-2 model is generally used for generation, to make it output text more similar to a given dataset.\r\n\r\nIf you are using it for other tasks (e.g. binary predictions), you may not have to finetune it.",
"Hello,\r\n\r\nThank you for your reply.\r\nSo say if I am trying to solve multiple choic... | 1,591 | 1,596 | 1,596 | NONE | null | Hello,
If I am using the pre-trained GPT-2 for my research, should I still fine-tune the already pre-trained models with my dataset? I am a bit confused by the term "pre-trained".
Thank you, | {
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https://api.github.com/repos/huggingface/transformers/issues/4712 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4712/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4712/comments | https://api.github.com/repos/huggingface/transformers/issues/4712/events | https://github.com/huggingface/transformers/issues/4712 | 628,775,192 | MDU6SXNzdWU2Mjg3NzUxOTI= | 4,712 | Converting model to pytorch | {
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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"
] | 1,591 | 1,596 | 1,596 | NONE | null | # 🐛 Bug
Folks, I am trying to convert the Biobert model to Pytorch. Here are the things that I did so far:
**1. For the vocab:** I am trying to convert the vocab using solution from #69 :
```tokenizer = BartTokenizer.from_pretrained('/content/biobert_v1.1_pubmed/vocab.txt')```
I get :
`OSError: Model name '... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4711?src=pr&el=h1) Report\n> Merging [#4711](https://codecov.io/gh/huggingface/transformers/pull/4711?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6449c494d0f40f0b70442f3da9e61f042ff807a8&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | When replying to #4698, I realized some language model docstrings are using arguments that are not present in the function signature. This PR addresses that (for all the ones I found at least).
The alternative would be to change the argument names in the function signatures (if it makes the various model APIs more c... | {
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https://api.github.com/repos/huggingface/transformers/issues/4710 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4710/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4710/comments | https://api.github.com/repos/huggingface/transformers/issues/4710/events | https://github.com/huggingface/transformers/pull/4710 | 628,651,719 | MDExOlB1bGxSZXF1ZXN0NDI2MTU0MDA2 | 4,710 | Specify PyTorch versions | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4710?src=pr&el=h1) Report\n> Merging [#4710](https://codecov.io/gh/huggingface/transformers/pull/4710?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6449c494d0f40f0b70442f3da9e61f042ff807a8&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | MEMBER | null | Specify that the examples require a different PyTorch version than the base library. | {
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https://api.github.com/repos/huggingface/transformers/issues/4709 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4709/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4709/comments | https://api.github.com/repos/huggingface/transformers/issues/4709/events | https://github.com/huggingface/transformers/issues/4709 | 628,647,110 | MDU6SXNzdWU2Mjg2NDcxMTA= | 4,709 | Wrong argument passed during TFRobertaClassificationHead initialization | {
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"Hello,\r\n\r\nThe way the TF models behave has been recently updated. Can you please retry with the `master` version?",
"Hi Julien,\r\n\r\nThanks. It's the same issue in the `master` currently:\r\n\r\nhttps://github.com/huggingface/transformers/blob/9f5d5a531d769d07403f59661884e254f8420afe/src/transformers/model... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🐛 Bug
## Information
There is an issue preventing a RoBERTa classification model from being serialized. It is related to a problem in passing `config` as the first argument to `tf.keras.layers.Layer`. However, the [expected positional argument](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Layer) ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4708 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4708/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4708/comments | https://api.github.com/repos/huggingface/transformers/issues/4708/events | https://github.com/huggingface/transformers/issues/4708 | 628,638,631 | MDU6SXNzdWU2Mjg2Mzg2MzE= | 4,708 | Is the separation token absolutely necessary if I use GPT2DoubleHeadsModel with token_type_ids? | {
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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"
] | 1,591 | 1,596 | 1,596 | NONE | null | Hello,
I am trying to use the GPT2DoubleHeadsModel to process the multiple choice questions.
For the pre-processing of the multiple choice questions, I didn't add any special separating token between the multiple choice question and the multiple choice option. Instead, I generated the token_type_ids, which denote 0... | {
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https://api.github.com/repos/huggingface/transformers/issues/4707 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4707/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4707/comments | https://api.github.com/repos/huggingface/transformers/issues/4707/events | https://github.com/huggingface/transformers/issues/4707 | 628,638,123 | MDU6SXNzdWU2Mjg2MzgxMjM= | 4,707 | How tokenizers work | {
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"pinging @n1t0, lead on [huggingface/tokenizers](https://github.com/huggingface/tokenizers) :)",
"Thank you! Closing it here, moved link: [https://github.com/huggingface/tokenizers/issues/290](url)"
] | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | Good afternoon.
If possible, I would ask a few questions which I cannot solve for several days running.
1) What does the file _merge.txt_ mean which is used in `ByteLevelBPETokenizer`? Does it store the config for the tokenizer? I deepened into it, however, did not manage to understand its purpose.
2) Is it possi... | {
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https://api.github.com/repos/huggingface/transformers/issues/4706 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4706/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4706/comments | https://api.github.com/repos/huggingface/transformers/issues/4706/events | https://github.com/huggingface/transformers/issues/4706 | 628,620,903 | MDU6SXNzdWU2Mjg2MjA5MDM= | 4,706 | When using the Hugging Face Transformer, if I set my pad_token to be a different token then the default, do I need to train my model on that new pad_token as well? | {
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"Hi @h56cho, if you add new tokens then yes, you'll need to train the model. If you just want `eos` and `pad` token then its a good idea to use the model defaults. `eos` and `pad` tokens are already available in GPT2 model ",
"Hi,\r\n\r\nThank you for your reply.\r\nSo what I am getting is that if I add any ne... | 1,591 | 1,591 | 1,591 | NONE | null | Hello,
For using the GPT2DoubleHeadsModel, I used ``<eos>`` as the last token of my text sequence, which my model will use to make predictions for multiple-choice questions.
I also set ``<pad>`` as the padding token in my tokenizer, which is different than the default.
When using the Hugging Face pre-trained GPT... | {
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https://api.github.com/repos/huggingface/transformers/issues/4705 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4705/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4705/comments | https://api.github.com/repos/huggingface/transformers/issues/4705/events | https://github.com/huggingface/transformers/issues/4705 | 628,602,225 | MDU6SXNzdWU2Mjg2MDIyMjU= | 4,705 | Is transformers 2.11.0 compatible with tokenizers 0.8.0(-dev*)? | {
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https://api.github.com/repos/huggingface/transformers/issues/4704 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4704/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4704/comments | https://api.github.com/repos/huggingface/transformers/issues/4704/events | https://github.com/huggingface/transformers/issues/4704 | 628,538,364 | MDU6SXNzdWU2Mjg1MzgzNjQ= | 4,704 | Tensorflow XLMRoberta Multi-Class Problem | {
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"Hello! If you're using 8 labels, you'll need to tell the model that it needs to do 8-way classification. You can do so by specifying the `num_labels` argument during instantiation:\r\n\r\n```py\r\nmodel = TFXLMRobertaForSequenceClassification.from_pretrained(\r\n \"jplu/tf-xlm-roberta-base\", \r\n num_labels... | 1,591 | 1,591 | 1,591 | NONE | null | ## Details
I am attempting to fine tune an XLMRoberta sequence classification model. I have an array of text snippets from physicians labelled 1-8 with various diagnostic indications. I've created a tensorflow dataset object with the
```
convert_raw_to_xlmroberta_tfdataset()
```
function seen here (https://sta... | {
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"Hi! What's your model? Do you have the configuration file?\r\n\r\nWhat is the `run_pretraining.py`? This doesn't seem to be one of our scripts.",
"Hi, extremely sorry for not providing adequate information.\r\n\r\nI used google-research/bert for creating the model. The bert repo contains the run_pretraining.py, ... | 1,591 | 1,591 | 1,591 | NONE | null | Hi,
I have created a model on kaggle tpu using run_pretraining.py and it gives me tf_checkpoint file. First of all the model is 12gb in size due to which it is throwing memory error while loading weights into it on kaggle and colab.
Is there a way to reduce the size?
Secondly, I tried performing the operation ove... | {
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https://api.github.com/repos/huggingface/transformers/issues/4702 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4702/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4702/comments | https://api.github.com/repos/huggingface/transformers/issues/4702/events | https://github.com/huggingface/transformers/issues/4702 | 628,228,585 | MDU6SXNzdWU2MjgyMjg1ODU= | 4,702 | Why DataCollatorForLanguageModeling do not make attention_mask feature? | {
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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",
"@makailove123 Have you figured out why?"
] | 1,590 | 1,622 | 1,596 | 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/4701 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4701/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4701/comments | https://api.github.com/repos/huggingface/transformers/issues/4701/events | https://github.com/huggingface/transformers/issues/4701 | 628,110,456 | MDU6SXNzdWU2MjgxMTA0NTY= | 4,701 | Why we need the init_weight function in BERT pretrained model | {
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"Have a look at the code for [`.from_pretrained()`](https://github.com/huggingface/transformers/blob/a9aa7456ac824c9027385b149f405e4f5649273f/src/transformers/modeling_utils.py#L490). What actually happens is something like this:\r\n\r\n- find the correct base model class to initialise\r\n- initialise that class wi... | 1,590 | 1,637 | 1,591 | CONTRIBUTOR | null | # ❓ Questions & Help
I have already tried asking the question is SO, which you can find the link [here](https://stackoverflow.com/questions/62040309/why-we-need-the-init-weight-function-in-bert-pretrained-model-in-huggingface-tra/62053791#62053791).
## Details
In the code by Hugginface transformers, there are m... | {
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https://api.github.com/repos/huggingface/transformers/issues/4700 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4700/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4700/comments | https://api.github.com/repos/huggingface/transformers/issues/4700/events | https://github.com/huggingface/transformers/pull/4700 | 628,098,124 | MDExOlB1bGxSZXF1ZXN0NDI1NzA5ODg4 | 4,700 | Add community notebook for T5 sentiment span extraction | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4700?src=pr&el=h1) Report\n> Merging [#4700](https://codecov.io/gh/huggingface/transformers/pull/4700?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0866669e751bef636fa693b704a28c1fea9a17f3&el=desc) will **decrease... | 1,590 | 1,591 | 1,591 | CONTRIBUTOR | null | This is an example notebook that aims to increase the coverage of T5 fine-tuning examples to address #4426 .
This notebook presents a high level overview of T5, its significance for the future of NLP in practice, and a thoroughly commented tutorial on how to fine-tune T5 for sentiment span extraction with an extract... | {
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https://api.github.com/repos/huggingface/transformers/issues/4699 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4699/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4699/comments | https://api.github.com/repos/huggingface/transformers/issues/4699/events | https://github.com/huggingface/transformers/issues/4699 | 628,058,488 | MDU6SXNzdWU2MjgwNTg0ODg= | 4,699 | NER example doesn’t work with tensorflow | {
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"Also, the example was missing this parameter in the python3 run_tf_ner.py command to work. Would be good to update the doc:\r\n\r\n`--logging_dir ./my-model/`",
"@chuckabees I got the same issue, did you solve this problem?",
"@YuqiShen Unfortunately no. I even wrote to the code's author but no response :(",
... | 1,590 | 1,598 | 1,598 | NONE | null | I’m working through the Pytorch text tokenization example here using the tensorflow version run_tf_ner.py: https://github.com/huggingface/transformers/tree/master/examples/token-classification
The PyTorch version using run_ner.py works. I believe the difference is in https://github.com/huggingface/transformers/blob/... | {
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https://api.github.com/repos/huggingface/transformers/issues/4698 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4698/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4698/comments | https://api.github.com/repos/huggingface/transformers/issues/4698/events | https://github.com/huggingface/transformers/issues/4698 | 628,015,442 | MDU6SXNzdWU2MjgwMTU0NDI= | 4,698 | Transformer-XL: Input and labels for Language Modeling | {
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"Hi there!\r\n\r\n> I currently pass this data into the model like this:\r\n> \r\n> ```\r\n> output = model(input_ids=data, labels=target, mems=mems)\r\n> ```\r\n> \r\n> Is this correct?\r\n\r\nNo, this is not correct, because the labels are shifted inside the model (as the documentation suggests). This happens [he... | 1,590 | 1,593 | 1,591 | CONTRIBUTOR | 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,
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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"
] | 1,590 | 1,596 | 1,596 | NONE | null | I tried to use this implementation - https://huggingface.co/SpanBERT/spanbert-base-cased, but as a prediction I always get the same exect outoput no matter where I put [MASK] in a sentence. Here is the code. Am I doing something wrong?
import torch
from transformers import AutoTokenizer,AutoModel
toke... | {
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"Hello! The `d_head` is actually computed in the configuration: `self.d_head = d_model // n_head`. \r\n\r\nIt would probably be better to handle `d_head` directly, but currently the `d_model` and `d_head` are linked to each other. \r\n\r\nThis would crash in your case as `d_model // n_head != d_head`",
"@Lysandr... | 1,590 | 1,591 | 1,591 | NONE | null | Hi guys.
I have released a new (XLNet based) transformer model for low-resource language Tigrinya
[(TigXLNet)](https://github.com/abryeemessi/Transferring-Monolingual-Model-to-Low-Resource-Language) and found a bug when loading a pre-trained config file:
My config file looks like:
https://s3.amazonaws.com/m... | {
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"This would be good indeed (cc @julien-c). In the meantime I think you can specify \r\n```\r\n--tokenizer_name=$TOKENIZER_NAME_OR_PATH\r\n```\r\n so that it always loads the initial tokenizer (which does not change during training).",
"> This would be good indeed (cc @julien-c). In the meantime I think you can sp... | 1,590 | 1,663 | 1,619 | NONE | null | # 🚀 Feature request
Please add the feature to save the tokenizer model during training to the checkpoint folders.
## Motivation
When I tried out the script for [fine-tuning with language modeling](transformers/examples/language_modeling/run_language_modeling.py), I realized that the generated checkpoints during... | {
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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",
"Hey all, any chance anyone else is working around this? I think a neutral label or a standard sentiment score would be great for such a... | 1,590 | 1,600 | 1,596 | NONE | null | # 🚀 Feature request
After performing some experimentation and comparison to VADER, we come to consensus that "pretrained BERT-based Hugging Face transfomer" is performing way beyond the other lexicons, but VADER is also good at social media context + it provides "neutral" label which turns out to be useful in some ... | {
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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"
] | 1,590 | 1,596 | 1,596 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an offici... | {
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"\r\nI get this message every 2000 steps. \r\n\"Gradient overflow. Skipping step, loss scaler 0 reducing loss scale to 262144.0\"\r\n\r\nThe train run on rtx 2070 and seems to... | 1,590 | 1,596 | 1,596 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4691?src=pr&el=h1) Report\n> Merging [#4691](https://codecov.io/gh/huggingface/transformers/pull/4691?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0866669e751bef636fa693b704a28c1fea9a17f3&el=desc) will **increase... | 1,590 | 1,596 | 1,596 | NONE | null | * Add crossattention input
* Add EncoderDecoder tests for RoBERTa
Since RoBERTa is a subclass of BERT, it inherits all the crossattention mechanics in the model itself. This change allows RobertaForMaskedLM to take in encoder hidden states and language model labels to work with the EncoderDecoder framework. | {
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"@tchainzzz Can you tell how you resolved the particular issue?\r\n"
] | 1,590 | 1,635 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): BertTokenizer
Language I am using the model on (English, Chinese ...): English (`bert-base-uncased`)
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X ] my own modified scripts: (give details below)
T... | {
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"Can you post a minimal dataset that we can test this with? So for instance two sentences that give the same result for you.",
"```\r\n[\r\n [\"Nah I don't think he goes to usf, he lives around here though\", 2],\r\n [\"URGENT! You have won a 1 week FREE membership in our $100,000 Prize Jackpot!\", 1]\r\n]\r\n`... | 1,590 | 1,631 | 1,596 | NONE | null | # ❓ Questions & Help
## Details
I use BartForSequenceClassification pre-trained model from the HuggingFace Transformers library. During training phase logits from classification head gets different values, but during validation phase all logits values are equal even for different input texts.
I use BartTokenizer.b... | {
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https://api.github.com/repos/huggingface/transformers/issues/4688 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4688/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4688/comments | https://api.github.com/repos/huggingface/transformers/issues/4688/events | https://github.com/huggingface/transformers/issues/4688 | 627,729,310 | MDU6SXNzdWU2Mjc3MjkzMTA= | 4,688 | Compressive Transformer | {
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"Interested in model weights too but currently not available. Author does mention releasing tf code here:\r\n\r\nhttps://news.ycombinator.com/item?id=22290227\r\n\r\nRequires tf 1.15+ and deepmind/sonnet ver 1.36. Link to python script here:\r\n\r\nhttps://github.com/deepmind/sonnet/blob/cd5b5fa48e15e4d020f744968f5... | 1,590 | 1,598 | 1,598 | NONE | null | # 🌟 New model addition
## Model description
<table>
<tr><th>Title</th><td>Compressive Transformers for Long-Range Sequence Modelling (ICLR '20)</td></tr>
<tr><th>arXiv</th><td><a href="https://arxiv.org/pdf/1911.05507.pdf">1911.05507</a></td></tr>
<tr><th>Blog</th><td><a href="https://deepmind.com... | {
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https://api.github.com/repos/huggingface/transformers/issues/4687 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4687/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4687/comments | https://api.github.com/repos/huggingface/transformers/issues/4687/events | https://github.com/huggingface/transformers/pull/4687 | 627,719,545 | MDExOlB1bGxSZXF1ZXN0NDI1NDU4MjY0 | 4,687 | Update HooshvareLab/bert-base-parsbert-uncased | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4687?src=pr&el=h1) Report\n> Merging [#4687](https://codecov.io/gh/huggingface/transformers/pull/4687?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0866669e751bef636fa693b704a28c1fea9a17f3&el=desc) will **decrease... | 1,590 | 1,591 | 1,591 | CONTRIBUTOR | null | mBERT results added regarding NER datasets! | {
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https://api.github.com/repos/huggingface/transformers/issues/4686 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4686/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4686/comments | https://api.github.com/repos/huggingface/transformers/issues/4686/events | https://github.com/huggingface/transformers/pull/4686 | 627,703,213 | MDExOlB1bGxSZXF1ZXN0NDI1NDQ4OTg4 | 4,686 | [pipeline] Tokenizer should not add special tokens for text generation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4686?src=pr&el=h1) Report\n> Merging [#4686](https://codecov.io/gh/huggingface/transformers/pull/4686?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9c17256447b91cf8483c856cb15e95ed30ace538&el=desc) will **increase... | 1,590 | 1,591 | 1,591 | MEMBER | null | This PR fixes generation in pipelines for all models whose tokenizer adds special tokens to the input, *e.g.* XLNet.
I think this is good for now, but I think the `_parse_and_tokenize()` function needs a larger refactoring to allow more flexibility in the future, also see Issue: #4501 | {
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https://api.github.com/repos/huggingface/transformers/issues/4685 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4685/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4685/comments | https://api.github.com/repos/huggingface/transformers/issues/4685/events | https://github.com/huggingface/transformers/issues/4685 | 627,683,780 | MDU6SXNzdWU2Mjc2ODM3ODA= | 4,685 | AutoModel.from_config loads random parameter values. | {
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"This is expected behaviour, but I understand your confusion.\r\n\r\n```python\r\nmodel_from_pretrained = AutoModel.from_pretrained(pretrained)\r\n```\r\n\r\nThis actually loads the pretrained weights. It looks up the mapping and locations of the config file and the weights, and loads both.\r\n\r\n```python\r\nmode... | 1,590 | 1,591 | 1,591 | 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)
Model parameters are (apparently) r... | {
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https://api.github.com/repos/huggingface/transformers/issues/4684 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4684/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4684/comments | https://api.github.com/repos/huggingface/transformers/issues/4684/events | https://github.com/huggingface/transformers/pull/4684 | 627,681,291 | MDExOlB1bGxSZXF1ZXN0NDI1NDM1ODM2 | 4,684 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4684?src=pr&el=h1) Report\n> Merging [#4684](https://codecov.io/gh/huggingface/transformers/pull/4684?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0866669e751bef636fa693b704a28c1fea9a17f3&el=desc) will **increase... | 1,590 | 1,591 | 1,591 | CONTRIBUTOR | null | {
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"I can reproduce this. cc @n1t0 @mfuntowicz Special \"unused\" tokens are not tokenised correctly. This happens in the fast tokenizers as well as the slow ones. See test case below.\r\n\r\n```python\r\nfrom transformers import BertTokenizer\r\nUSE_FAST = True\r\n\r\ntokenizer = BertTokenizer.from_pretrained(\"bert-... | 1,590 | 1,679 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using: tokenizer.encode('[unused1]')
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The... | {
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https://api.github.com/repos/huggingface/transformers/issues/4682 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4682/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4682/comments | https://api.github.com/repos/huggingface/transformers/issues/4682/events | https://github.com/huggingface/transformers/issues/4682 | 627,671,646 | MDU6SXNzdWU2Mjc2NzE2NDY= | 4,682 | XLNet Generation appears to reference padding text in run_generation script | {
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"Hi @thesamuel, \r\n\r\nIdeally, the padding text should not influence the outcome, but this is more a hack to make XLNet work with short prompts, than actual science.\r\n\r\nAlso note that it is recommended now to use the TextGeneration Pipeline instead of the `run_generation` script: \r\n\r\n```\r\nfrom transform... | 1,590 | 1,591 | 1,591 | NONE | null | When generating with XLNet in the `run_generation.py` script, the outputs seem to reference the context from the padding text. For instance, given the prompt "We propose a", XLNet generates "We propose a boy Go Ya Ya, a young Iriel Farg, to be named Rasputin."
This seems to reference the padding text:
https://githu... | {
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https://api.github.com/repos/huggingface/transformers/issues/4681 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4681/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4681/comments | https://api.github.com/repos/huggingface/transformers/issues/4681/events | https://github.com/huggingface/transformers/pull/4681 | 627,602,575 | MDExOlB1bGxSZXF1ZXN0NDI1Mzc5NzAz | 4,681 | NER: Add new WNUT’17 example | {
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"Looks great!",
"(I've relaunched the failing CI test that's unrelated)",
"@julien-c do you think rebasing onto latest master would fix that problem?"
] | 1,590 | 1,591 | 1,591 | COLLABORATOR | null | Hi,
this PR extends the NER example section, and adds an extra section for fine-tuning a NER model on the (difficult) WNUT’17 shared task:
> The WNUT’17 shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions.
> Named entities form the basis of many modern ap... | {
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https://api.github.com/repos/huggingface/transformers/issues/4680 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4680/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4680/comments | https://api.github.com/repos/huggingface/transformers/issues/4680/events | https://github.com/huggingface/transformers/pull/4680 | 627,585,410 | MDExOlB1bGxSZXF1ZXN0NDI1MzY1ODUy | 4,680 | [EncoderDecoder] Fix initialization and save/load bug | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4680?src=pr&el=h1) Report\n> Merging [#4680](https://codecov.io/gh/huggingface/transformers/pull/4680?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a801c7fd74f56a651ba43bfc93eba93c63e84766&el=desc) will **decrease... | 1,590 | 1,600 | 1,590 | MEMBER | null | This PR fixes two bugs:
- Cross attention layers were not initialized when initiating the `EncoderDecoderModel` via `from_encoder_decoder_pretrained()`. Thanks goes to https://github.com/huggingface/transformers/issues/4293 for finding this bug! A slow test is including in this PR to prevent future bugs of this kin... | {
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https://api.github.com/repos/huggingface/transformers/issues/4679 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4679/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4679/comments | https://api.github.com/repos/huggingface/transformers/issues/4679/events | https://github.com/huggingface/transformers/issues/4679 | 627,495,658 | MDU6SXNzdWU2Mjc0OTU2NTg= | 4,679 | GPT-3 | {
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"Thanks, looks like a duplicate of #4658 ",
"Ups, haven't seen this on mobile.\r\nMy apologies"
] | 1,590 | 1,590 | 1,590 | CONTRIBUTOR | null | Paper: https://arxiv.org/pdf/2005.14165
GitHub: https://github.com/openai/gpt-3
Author: @8enmann | {
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https://api.github.com/repos/huggingface/transformers/issues/4677 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4677/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4677/comments | https://api.github.com/repos/huggingface/transformers/issues/4677/events | https://github.com/huggingface/transformers/issues/4677 | 627,439,718 | MDU6SXNzdWU2Mjc0Mzk3MTg= | 4,677 | Documentation for non-nlp experts | {
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"Since no one else answers this:\r\nCheck out the simpletransformers library, it's and wrapper of this one and there are some blog posts linked to examples.\r\nhttps://github.com/ThilinaRajapakse/simpletransformers\r\nThe author is very open to every idea and the work with him is pretty good.\r\nMaybe it will help ... | 1,590 | 1,602 | 1,602 | 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
I want to use these models as an end-user, without having to read academic papers describing them.
I have been following deep learning in ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4675 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4675/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4675/comments | https://api.github.com/repos/huggingface/transformers/issues/4675/events | https://github.com/huggingface/transformers/issues/4675 | 627,420,440 | MDU6SXNzdWU2Mjc0MjA0NDA= | 4,675 | Gpt2 generation of text larger than 1024 | {
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"After looking over `modeling_utils.generate` (the function used for generation by `run_generation.py`), I believe that the sliding window approach is not yet implemented.\r\n\r\nThis method was implemented for CTRL generation in their repo, so you may be able to adapt some of their code for your use case: https://... | 1,590 | 1,615 | 1,596 | 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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"I can't reproduce on master. Do you mind specifying the context/question?",
"Because you couldn't reproduce, I tried with the latest version (from git : 2.11.0) and the problem seems gone (tested with random articles from wikipedia). \r\n\r\nMaybe my first text had bad format or non utf-8 characters (but I reme... | 1,590 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
`Camembert ("illuin/camembert-large-fquad")`
Language I am using the model on (English, Chinese ...):
`French`
The problem arises when using:
* [X] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details belo... | {
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"Hi! If you're new to the library, I heavily recommend taking a look at the [glossary (position IDs in this case)](https://huggingface.co/transformers/glossary.html#position-ids), which explains how to use such inputs.\r\n\r\nIf you ignore the `position_ids`, then they're always automatically generated to be the sa... | 1,590 | 1,598 | 1,590 | NONE | null | Hello HuggingFace team,
I am familiarizing myself with the HuggingFace tutorials and understand the functionality of the various methods. However, I have a general question for example when using models like BERT.
Considering that I am doing sentiment classification and I want to fine-tune the whole BERT based on... | {
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https://api.github.com/repos/huggingface/transformers/issues/4672 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4672/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4672/comments | https://api.github.com/repos/huggingface/transformers/issues/4672/events | https://github.com/huggingface/transformers/pull/4672 | 627,268,550 | MDExOlB1bGxSZXF1ZXN0NDI1MTAzMjI3 | 4,672 | [Longformer] Better handling of global attention mask vs local attention mask | {
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"Regarding the Multiple Choice `global_attention_mask`. Discussion taken from PR: https://github.com/huggingface/transformers/pull/4645#issuecomment-635429380\r\n\r\n> @patil-suraj, we can leave it to the user, or we can just do as you suggested earlier, put global attention on the question and all choices, which s... | 1,590 | 1,590 | 1,590 | MEMBER | null | This PR extends Longformer's API to also take a `global_attention_mask` besides the usual `attention_mask` as an input as discussed with @thomwolf @ibeltagy.
Docs are updated. | {
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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",
"Ran into this today, this is a major issue behind corporate proxy/CA self signed certs. @SinghB maybe you can reopen this, I'm not sur... | 1,590 | 1,614 | 1,605 | NONE | null | # 🐛 Bug
No information from the package on SSL error encountered, making it difficult to troubleshoot or figure out a workaround
## Information
When trying to do:
`TFAutoModelWithLMHead.from_pretrained("t5-small")`
Get an error:
`TypeError: stat: path should be string, bytes, os.PathLike or integer, not None... | {
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"GPT-2 and BERT have very different tokenization mechanism. What do you mean by \"convert between the tokenizers\"? What do you want to do?",
"I want to use Bert as encoder and GPT2 as decoder. Then I want to evaluate the generated text with another Bert as discriminator (like the technique [here](https://arxiv.o... | 1,590 | 1,590 | 1,590 | NONE | null | I want to convert GPT2 tokens to BERT tokens. Is there any API that can directly convert between the Tokenizers? | {
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https://api.github.com/repos/huggingface/transformers/issues/4669 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4669/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4669/comments | https://api.github.com/repos/huggingface/transformers/issues/4669/events | https://github.com/huggingface/transformers/issues/4669 | 627,225,434 | MDU6SXNzdWU2MjcyMjU0MzQ= | 4,669 | Cannot load labels from old models | {
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"I think I see where that could be a problem, indeed. Do you mind sharing your model configuration file so that I may take a closer look?",
"Here it is:\r\n\r\n```\r\n{\r\n \"architectures\": [\r\n \"BertForTokenClassification\"\r\n ],\r\n \"attention_probs_dropout_prob\": 0.3,\r\n \"bos_token_id\": 0,\r\n... | 1,590 | 1,591 | 1,591 | CONTRIBUTOR | null | # ❓ Questions & Help
If I load a model from 2.8 or older in 2.9 o newer, the labels from my model are changed automatically so all the tests in my code start to fail because instead of predicting `I-PER` it predicts `LABEL_2`.
After reading the source code I think I found what happens but I'm not quite sure. I t... | {
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"Hi! This is indeed a memory error. At which point does it crash?",
"A similar problem like this has been reported when using the Lazy version of LinebyLineTextDataset. Colab deals badly with situation where you are using 90+% of memory - it'll kick you out or throw OOM errors - which you would not get on local m... | 1,590 | 1,625 | 1,598 | NONE | null | I am pretraining a RoBERTa model on the Newsroom dataset on colab. I have trained a custom tokenizer on the text data. I am using the Text Dataset LinebyLineTextDataset as I have a single file and each line is the text of a news article. The colab crashes when I run this code
_%%time
from transformers import LineByL... | {
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https://api.github.com/repos/huggingface/transformers/issues/4666 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4666/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4666/comments | https://api.github.com/repos/huggingface/transformers/issues/4666/events | https://github.com/huggingface/transformers/pull/4666 | 627,135,859 | MDExOlB1bGxSZXF1ZXN0NDI0OTk1NjIx | 4,666 | HooshvareLab readme parsbert-armananer | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4665?src=pr&el=h1) Report\n> Merging [#4665](https://codecov.io/gh/huggingface/transformers/pull/4665?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b5015a2a0f4ea63035a877f5626cb0c3ce97e25d&el=desc) will **increase... | 1,590 | 1,591 | 1,591 | CONTRIBUTOR | null | Readme for HooshvareLab/bert-base-parsbert-ner-uncased | {
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"Hello,\r\n\r\nThis is because you have to specify `--logging_dir /path/to/logs` as parameter. There will be a default location for the next release of the TF Trainer.",
"Right. I later passed a parameter in run_tf_ner.py and it worked. I felt somewhere in the Trainer or run_tf_ner.py, it needs to be indicated. \... | 1,590 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): bert
Language I am using the model on (English, Chinese ...): bert-base-multilingual-cased
The problem arises when using:
* [x] the official example scripts: (give details below)
run_tf_ner.py
* [ ] my own modified scripts: (give details belo... | {
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"I might be wrong, but I think the focus of this library is on NLP which at most is multimodal. Also including object detection transformers may fall out of the scope of this project."
] | 1,590 | 1,591 | 1,590 | CONTRIBUTOR | null | # 🚀 Feature request
A modular Transformer Encoder-Decoder block that can be attached to ConvNets for many tasks.
## Motivation
As shown in the recent paper [End-to-end Object Detection with Transformers](https://ai.facebook.com/research/publications/end-to-end-object-detection-with-transformers) which used Tran... | {
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"Delete. It may be a hardware issue. When I changed it to Colab, this problem disappeared"
] | 1,590 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...):bert-base-multilingual-cased
The problem arises when using:
* [ ] the official example scripts: (give details below)
original code in _run_tf_ner.py_
original data from _germaeval2014e... | {
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"I cannot reproduce your problem. Can you try again?",
"I tried again. \r\n\r\nConsole on dev tools shows:\r\n\r\n```\r\nDevTools failed to load SourceMap: Could not load content for chrome-extension://ibnejdfjmmkpcnlpebklmnkoeoihofec/dist/contentScript.js.map: HTTP error: status code 404, net::ERR_UNKNOWN_URL_SC... | 1,590 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
Triggering autocomplete results in endless spinning.
iOS safari But also desktop Safari, Firefox and Chrome.
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In the function `apply_chunking_to_forward`, an assertion checking the input tensor shape is trying to print the contents of the tensor itself instead of its shape:
https://github.com/huggingface/transformers/blob/b5015a2a0f4ea63035a877f5626cb0c3ce97e25d/src/transformers/modeling_utils.py#L2195
I'm pr... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4659?src=pr&el=h1) Report\n> Merging [#4659](https://codecov.io/gh/huggingface/transformers/pull/4659?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f4e1f022100834bd00d4f877a883b5946c4cac37&el=desc) will **decrease... | 1,590 | 1,592 | 1,592 | CONTRIBUTOR | null | This PR adds support for gradient checkpointing in `modeling_bert.py` to save memory at training time at the expense of a slower backward pass. This is particularly useful if we want to pretrain a version of BERT for sequences longer than 512. It is also useful for long-document models like Longformer.
Stats:
```
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"My god, the paper hasn't even been up for a day...\r\n\r\nSaid being, +1",
"So who can run 175B parameters and what do I have to do for a favor?",
"The full model will be at least 350 GB (16-bit parameters). You'd need to partition it across more than (350 GB) / (16 GB) ~ **22 GPUs** just to run it! Not to men... | 1,590 | 1,685 | 1,666 | COLLABORATOR | null | # 🌟 New model addition
## Model description
The GPT-3 paper just landed on ArXiv: https://arxiv.org/abs/2005.14165.
Would be great to integrate it into Transformers, whenever models are available.
> Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes... | {
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"I've tried `transformers 2.10.0` under `CUDA 10.2` with `PyTorch 1.5.0` and apex compiled for that environment, as well as under `CUDA 10.1` with both PyTorch 1.5.0 and 1.4.1, as well as apex compiled for both of those. However, I get pretty much the same issue. Should I down convert to a different version of tran... | 1,590 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
`roberta-large`
Language I am using the model on (English, Chinese ...):
`English`
The problem arises when using:
* the official example scripts
The tasks I am working on is:
* Finetuning a LM with `run_language_modeling.py` and the SST-2 task... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4656?src=pr&el=h1) Report\n> Merging [#4656](https://codecov.io/gh/huggingface/transformers/pull/4656?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/76779363160a598f130433209a77f8a747351b61&el=desc) will **decrease... | 1,590 | 1,651 | 1,619 | MEMBER | null | # Electra Trainer
_**Still in testing process. Feedback welcome!**_
This PR introduces:
## New features
- A new language modeling script based on the [ELECTRA pre-training method](https://github.com/google-research/electra).
### Combined model
- Combines `ElectraForMaskedLM` and `ElectraForPreTraining` ... | {
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"If you are using `pytorch-lightning` then you won't need to transfer data on GPU or TPU manually. `lightning` takes care of that for you",
"I have copied the method, which transfer data from pytorch-lightning, so you can reproduce the error.",
"Okay, sorry I misunderstood the question.",
"It is my bad Engli... | 1,590 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert with pytorch-lightning
Language I am using the model on (English, Chinese ...): English
The problem arises when using
* my own modified scripts: Pytorch Dataset with tokenizer inside
The tasks I am working on is:
* my own task or dataset... | {
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"@LysandreJik this should work (assuming tf >=2.2.0) let me know if I can do anything to help.",
"Hello !\r\n\r\nThanks a lot for this PR!! Can you rebase on master plz? It will be easier to review :)",
"@jplu (I think/hope) I just did it. Let me know if everything is ok. Great work by the way, congrats to all ... | 1,590 | 1,596 | 1,596 | NONE | null | This pull request add functionality for sequence classification with Electra. The only missing bit is that I have put the activation function as "tanh" instead of "gelu" (in the orig. implementation) | {
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@ibeltagy @patrickvonplaten Please provide feedback if you think this notebook can be further improved.
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"I trained a bert model from pretrained models. and the output embedding are all the same regardless of the input and attention mask during prediction. But when set model.train(), the model will give different embeddings for different input. I'm quite confused to be honest. I suppose that's the same problem?",
"H... | 1,590 | 1,603 | 1,601 | NONE | null | # ❓ Questions & Help
Hi, everyone. I need help with the encoding-decoding model. I'm trying to train the model to create a title for a small text.
I'm creating a basic Encode-Decode model with Bert
```
from transformers import EncoderDecoderModel, BertTokenizer
import torch
tokenizer = BertTokenizer.from_... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4646?src=pr&el=h1) Report\n> Merging [#4646](https://codecov.io/gh/huggingface/transformers/pull/4646?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e444648a302dc8520beec96356a4bf500944355c&el=desc) will **decrease... | 1,590 | 1,590 | 1,590 | CONTRIBUTOR | null | {
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"As mentioned in the paper, they used global attention on all answer candidates for WikiHop, so maybe we can use global attention on all choice tokens ?",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4645?src=pr&el=h1) Report\n> Merging [#4645](https://codecov.io/gh/huggingface/transformers/p... | 1,590 | 1,590 | 1,590 | MEMBER | null | ## Description:
- This PR adds Multiple Choice for Longformer as in: #4644 (Sorry for not telling you earlier @patil-suraj). @ibeltagy
- The documentation is updated for all models using MultipleChoice since their `input_ids` have 3 dimensions. It is done by use of `{}.format()` for `INPUTS_DOCSTRING`. @Lysandre... | {
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"Haha, I shouldn't have touched this - I kinda already assumed you are working on it :D See PR here: #4645",
"Yes 😀 , I was just waiting for `LongformerForTokenClassifiction` to be merged",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4644?src=pr&el=h1) Report\n> Merging [#4644](https://cod... | 1,590 | 1,590 | 1,590 | MEMBER | null | This PR adds `LongformerForMultipleChoice` following `RobertaForMultipleChoice`
@patrickvonplaten , @ibeltagy
Same question as before, do we need any automatic global attention here ? | {
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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"
] | 1,590 | 1,596 | 1,596 | CONTRIBUTOR | null | Regarding
https://github.com/huggingface/transformers/blob/96f57c9ccb6363623005fb3f05166dfd7acb3f53/src/transformers/pipelines.py#L1739
it will cause a reproducible bug:
```python
from transformers import pipeline
nlp_qa = pipeline('question-answering', model='distilbert-base-cased-distilled-squad', tokenizer=... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4642?src=pr&el=h1) Report\n> Merging [#4642](https://codecov.io/gh/huggingface/transformers/pull/4642?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5e737018e1fcb22c8b76052058279552a8d6c806&el=desc) will **not chan... | 1,590 | 1,590 | 1,590 | CONTRIBUTOR | null | This PR adds a community notebook that demonstrates how we pretrained Longformer starting from the RoBERTa checkpoint. The same procedure can be followed to convert other existing pretrained models into their Long version.
@patrickvonplaten, @patil-suraj, it would be great if you also check the notebook. Any comment... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4641?src=pr&el=h1) Report\n> Merging [#4641](https://codecov.io/gh/huggingface/transformers/pull/4641?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/14cb5b35faeda7881341656aacf89d12a8a7e07b&el=desc) will **decrease... | 1,590 | 1,591 | 1,591 | CONTRIBUTOR | null | This PR makes it possible to export custom bert models to onnx.
It resolves the issue addressed [here](https://github.com/huggingface/transformers/issues/4523#issuecomment-634920569).
TODO:
- [x] update ensure_valid_input function
- [x] update test ensure_valid_input_function
- [x] update convert_pytorch
- [... | {
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"Hi @Xunzhuo,\r\nMultiple bugs were fixed in #4680 . Can you please take a look whether this error persists?",
"okay tks!"
] | 1,590 | 1,590 | 1,590 | NONE | null | # 🐛 Bug Report
When loading the config the in configuration_auto.py the model_type is expected on the form encoder-decoder
but in configuration_encoder_decoder.py
model_type is on the form encoder_decoder which raises a KeyError. | {
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https://api.github.com/repos/huggingface/transformers/issues/4639 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4639/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4639/comments | https://api.github.com/repos/huggingface/transformers/issues/4639/events | https://github.com/huggingface/transformers/issues/4639 | 626,253,663 | MDU6SXNzdWU2MjYyNTM2NjM= | 4,639 | How to generate prediction/answer from a custom model fined-tuned/trained for self-defined questions? | {
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"Considering you saved the model(the files you mentioned above) in 'model_dir' here's how you can do it.\r\n\r\n```python\r\nfrom transformers import AutoTokenizer, AutoModelForQuestionAnswering\r\nimport torch\r\n\r\ntokenizer = AutoTokenizer.from_pretrained(\"model_dir\")\r\nmodel = AutoModelForQuestionAnswering.... | 1,590 | 1,596 | 1,596 | NONE | null | I used run_squad.py to fine-tuned a pre-trained DistilledBERT, and I wonder how exactly to implement my model to answer a list of self-defined questions. It seems to me that the pipeline only works with one of the "regular" models (BERT DistBert, XLM, XLNET, etc.), or a model that has already been uploaded to the commu... | {
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https://api.github.com/repos/huggingface/transformers/issues/4638 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4638/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4638/comments | https://api.github.com/repos/huggingface/transformers/issues/4638/events | https://github.com/huggingface/transformers/pull/4638 | 626,227,433 | MDExOlB1bGxSZXF1ZXN0NDI0MjU4MzA1 | 4,638 | LongformerForTokenClassification | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4638?src=pr&el=h1) Report\n> Merging [#4638](https://codecov.io/gh/huggingface/transformers/pull/4638?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/96f57c9ccb6363623005fb3f05166dfd7acb3f53&el=desc) will **increase... | 1,590 | 1,590 | 1,590 | MEMBER | null | This PR adds `LongformerForTokenClassification`
@patrickvonplaten @ibeltagy
do we need any automatic global attention here ? | {
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https://api.github.com/repos/huggingface/transformers/issues/4637 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4637/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4637/comments | https://api.github.com/repos/huggingface/transformers/issues/4637/events | https://github.com/huggingface/transformers/pull/4637 | 626,215,465 | MDExOlB1bGxSZXF1ZXN0NDI0MjQ4OTY1 | 4,637 | Movement pruning | {
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"Thanks for the valuable inputs on quantization @mfuntowicz! --> `Saving_PruneBERT.ipynb`",
"> This is great. Didn't you want to include the `MaskedBertXXX` directly in the library, as was done with `DistilBERT`?\r\n> \r\n> We can also do it at a later date, as we'll need to write the tests (kudos on the docs, lo... | 1,590 | 1,591 | 1,591 | MEMBER | null | This PR adds the code to reproduce the results of our recent work on Movement pruning.
Some supplemental treats:
- A notebook showcasing how to efficiently store an extremely sparse model
- Sharing a couple of fine-pruned checkpoints (PruneBERT)
- Details of all hyper-parameters and results
| {
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https://api.github.com/repos/huggingface/transformers/issues/4636 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4636/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4636/comments | https://api.github.com/repos/huggingface/transformers/issues/4636/events | https://github.com/huggingface/transformers/pull/4636 | 626,192,126 | MDExOlB1bGxSZXF1ZXN0NDI0MjMxNDMy | 4,636 | Kill model archive maps | {
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"Love this! is there a plan to allow aliases moving forward?\r\ntyping `'Helsinki-NLP/opus-mt-romance-en'` is not awful so I don't feel very strongly that we should, but interested in your thoughts.",
"Hmm no I don't see an obvious need for aliases personally.",
"Awesome!",
"# [Codecov](https://codecov.io/gh/... | 1,590 | 1,591 | 1,591 | MEMBER | null | Links to model weights inside the code are not useful anymore, on the contrary, defining those shortcuts to URLs in code tend to lead to discrepancies with the canonical naming scheme of models at huggingface.co
As an example, we cannot cleanly load [`facebook/bart-large-cnn`](https://huggingface.co/facebook/bart-la... | {
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https://api.github.com/repos/huggingface/transformers/issues/4635 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4635/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4635/comments | https://api.github.com/repos/huggingface/transformers/issues/4635/events | https://github.com/huggingface/transformers/issues/4635 | 626,191,613 | MDU6SXNzdWU2MjYxOTE2MTM= | 4,635 | 03-pipelines.ipynb on Colab: error on "Summarization" | {
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https://api.github.com/repos/huggingface/transformers/issues/4634 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4634/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4634/comments | https://api.github.com/repos/huggingface/transformers/issues/4634/events | https://github.com/huggingface/transformers/issues/4634 | 626,178,795 | MDU6SXNzdWU2MjYxNzg3OTU= | 4,634 | tensorflow2_gpt2 Slow speed | {
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"With tf. Varibable model for packaging\r\n```\r\n @tf.function(experimental_relax_shapes=True)\r\n def model_static(self, model_inputs):\r\n outputs = self(**model_inputs)\r\n return outputs\r\n\r\n```",
"Same problem here\r\n@only-yao Did you find a solution yet?",
"> @ only-yao这是同样的问题，您找到... | 1,590 | 1,596 | 1,596 | NONE | null | # ❓ The speed of pytorch_gpt2 based on transformers is 4-5 times faster than that of tensorflow_gpt2, which is unreasonable. Where is my problem
**pytorch_gpt2**
```
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
model = GPT2LMHeadModel.from_pretrained('gpt2')
model.to(dev)
raw_text_2 = "And if so be ye ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4633 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4633/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4633/comments | https://api.github.com/repos/huggingface/transformers/issues/4633/events | https://github.com/huggingface/transformers/pull/4633 | 626,130,139 | MDExOlB1bGxSZXF1ZXN0NDI0MTg0NzU5 | 4,633 | Merge pull request #1 from huggingface/master | {
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https://api.github.com/repos/huggingface/transformers/issues/4632 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4632/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4632/comments | https://api.github.com/repos/huggingface/transformers/issues/4632/events | https://github.com/huggingface/transformers/pull/4632 | 626,095,495 | MDExOlB1bGxSZXF1ZXN0NDI0MTU4NDEx | 4,632 | Pipelines: miscellanea of QoL improvements and small features... | {
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see individual commits for description | {
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https://api.github.com/repos/huggingface/transformers/issues/4631 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4631/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4631/comments | https://api.github.com/repos/huggingface/transformers/issues/4631/events | https://github.com/huggingface/transformers/issues/4631 | 626,087,281 | MDU6SXNzdWU2MjYwODcyODE= | 4,631 | Numpy format string issue in TFTrainer | {
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"same here ",
"How did you resolve it? Do we have to wait till TFTrainer developer change the code in trainer_tf.py?\r\nIs there a way around it?",
"Hello,\r\n\r\nCan you give a sample of data and a command line with which I can reproduce the issue? Thanks!",
"> Hello,\r\n> \r\n> Can you give a sample of data... | 1,590 | 1,596 | 1,596 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [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/4630 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4630/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4630/comments | https://api.github.com/repos/huggingface/transformers/issues/4630/events | https://github.com/huggingface/transformers/issues/4630 | 626,079,533 | MDU6SXNzdWU2MjYwNzk1MzM= | 4,630 | Model evaluated at each checkpoint, but results not in checkpoint file | {
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"What is the proper way to get an `eval.txt` file for each checkpoint?",
"No, this is not a built-in feature. I'd suggest you install from source and modify the code directly. \r\n\r\nThe code in this repo is meant to be optimized for \"hackability\", feel free to open a new issue if needed."
] | 1,590 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
I start `run_language_modeling.py` and `run_glue.py` with `--do_eval` and `--evaluate_during_training` arguments. While it checkpoints and evaluates the model at each saving step, the evaluation results are not output to the checkpoint folder but merely the terminal at each saving step, as well ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4629 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4629/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4629/comments | https://api.github.com/repos/huggingface/transformers/issues/4629/events | https://github.com/huggingface/transformers/pull/4629 | 626,015,473 | MDExOlB1bGxSZXF1ZXN0NDI0MTAyNzc4 | 4,629 | gpt2 typo | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4629?src=pr&el=h1) Report\n> Merging [#4629](https://codecov.io/gh/huggingface/transformers/pull/4629?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ec4cdfdd05d89b243d6d842fce019959291dd92a&el=desc) will **not chan... | 1,590 | 1,590 | 1,590 | CONTRIBUTOR | null | From #4572 | {
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https://api.github.com/repos/huggingface/transformers/issues/4628 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4628/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4628/comments | https://api.github.com/repos/huggingface/transformers/issues/4628/events | https://github.com/huggingface/transformers/pull/4628 | 625,992,602 | MDExOlB1bGxSZXF1ZXN0NDI0MDg1NzY0 | 4,628 | [Longformer] more models + model cards | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4628?src=pr&el=h1) Report\n> Merging [#4628](https://codecov.io/gh/huggingface/transformers/pull/4628?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a801c7fd74f56a651ba43bfc93eba93c63e84766&el=desc) will **decrease... | 1,590 | 1,590 | 1,590 | CONTRIBUTOR | null | This PR adds the following:
- Longformer models trained with frozen-roberta weights
- Model cards
- Model names start with `allenai/`
- Remove unnecessary type casting
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https://api.github.com/repos/huggingface/transformers/issues/4627 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4627/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4627/comments | https://api.github.com/repos/huggingface/transformers/issues/4627/events | https://github.com/huggingface/transformers/pull/4627 | 625,989,076 | MDExOlB1bGxSZXF1ZXN0NDI0MDgzMjA0 | 4,627 | [WIP] lightning glue example uses nlp package | {
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"@julien-c I'm not sure why my checks for isort aren't passing on run_pl_glue.py. Could it be because I imported `pyarrow` which is not listed in third party within `setup.cfg`?",
"lmk when you’re ready for me to give this a look over :)\r\n\r\none major feature we added is the option to not rely on hparams, they... | 1,590 | 1,592 | 1,592 | CONTRIBUTOR | null | Main goal here was to use `nlp` library to load datasets instead of custom scripts. I've made some changes to the GLUE example, and will reflect those changes elsewhere if the patterns used seem reasonable. Feedback would be greatly appreciated.
**So far, this PR:**
- Uses `nlp` library instead of manual processing... | {
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https://api.github.com/repos/huggingface/transformers/issues/4626 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4626/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4626/comments | https://api.github.com/repos/huggingface/transformers/issues/4626/events | https://github.com/huggingface/transformers/issues/4626 | 625,952,668 | MDU6SXNzdWU2MjU5NTI2Njg= | 4,626 | How to use run_glue.py with tensorboard? | {
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"What `--logging_dir` have you specified to the `run_glue.py` script?",
"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'm having this problem how do you fixed this?\r\nI put the d... | 1,590 | 1,659 | 1,596 | 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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https://api.github.com/repos/huggingface/transformers/issues/4625 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4625/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4625/comments | https://api.github.com/repos/huggingface/transformers/issues/4625/events | https://github.com/huggingface/transformers/pull/4625 | 625,854,895 | MDExOlB1bGxSZXF1ZXN0NDIzOTc5MjE3 | 4,625 | [Model Card] model card for longformer-base-4096-finetuned-squadv1 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4625?src=pr&el=h1) Report\n> Merging [#4625](https://codecov.io/gh/huggingface/transformers/pull/4625?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6a17688021268fe429e78c66ea0932cb55cd03b1&el=desc) will **decrease... | 1,590 | 1,590 | 1,590 | MEMBER | null | @patrickvonplaten | {
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https://api.github.com/repos/huggingface/transformers/issues/4624 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4624/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4624/comments | https://api.github.com/repos/huggingface/transformers/issues/4624/events | https://github.com/huggingface/transformers/issues/4624 | 625,851,238 | MDU6SXNzdWU2MjU4NTEyMzg= | 4,624 | Can't see logger output | {
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"Hi, have you tried setting the logging level to `INFO`? You can do so with the following lines:\r\n\r\n```py\r\nimport logging\r\n\r\nlogging.basicConfig(level=logging.INFO)\r\n```",
"It worked! Thanks",
"Hey, this doesn't log the training progress by trainer.train() into a log file. I want to keep appending t... | 1,590 | 1,636 | 1,590 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): RoBERTa
Language I am using the model on (English, Chinese ...): Sanskrit
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/4623 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4623/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4623/comments | https://api.github.com/repos/huggingface/transformers/issues/4623/events | https://github.com/huggingface/transformers/issues/4623 | 625,825,359 | MDU6SXNzdWU2MjU4MjUzNTk= | 4,623 | `train.jsonl` file missing in MM-IMDb task | {
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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",
"It seems like this is the method to get the jsonl files: https://github.com/facebookresearch/mmbt/blob/master/scripts/mmimdb.py"
] | 1,590 | 1,606 | 1,596 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [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/4622 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4622/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4622/comments | https://api.github.com/repos/huggingface/transformers/issues/4622/events | https://github.com/huggingface/transformers/issues/4622 | 625,806,171 | MDU6SXNzdWU2MjU4MDYxNzE= | 4,622 | GPU memory usage | {
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"How do you launch your training? Can you paste your command?",
"I am using the trainer.\r\n```\r\n\r\ntraining_args = TrainingArguments(\r\n output_dir=\"albert_model\",\r\n overwrite_output_dir=True,\r\n num_train_epochs=1,\r\n per_gpu_train_batch_size=85,\r\n learning_rate=5e-5,\r\n save_step... | 1,590 | 1,605 | 1,596 | 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/4621 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4621/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4621/comments | https://api.github.com/repos/huggingface/transformers/issues/4621/events | https://github.com/huggingface/transformers/pull/4621 | 625,805,256 | MDExOlB1bGxSZXF1ZXN0NDIzOTM5Njk4 | 4,621 | Cleanup glue | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4621?src=pr&el=h1) Report\n> Merging [#4621](https://codecov.io/gh/huggingface/transformers/pull/4621?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/003c4771290b00e6d14b871210c3a369edccaeed&el=desc) will **increase... | 1,590 | 1,591 | 1,591 | COLLABORATOR | null | * Make sure that MNLI acc metrics are named differently for match vs mismatch
* Allow writing to `cache_dir` from Glue dataset in case where datasets live in readOnly filesystem
* Flush TB writer at end to not miss any metrics | {
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https://api.github.com/repos/huggingface/transformers/issues/4620 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4620/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4620/comments | https://api.github.com/repos/huggingface/transformers/issues/4620/events | https://github.com/huggingface/transformers/issues/4620 | 625,796,457 | MDU6SXNzdWU2MjU3OTY0NTc= | 4,620 | The new abstractions in /master are counterproductive | {
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"Thanks for your feedback, it's interesting.\r\n\r\nWe've also heard good feedback on the refactoring you mention (because for instance opening an example script that was 700 lines of code long could be daunting) so it's good to hear a diversity of feedback.\r\n\r\nI think the crux of it is that it's not realistic ... | 1,590 | 1,596 | 1,596 | NONE | null | I understand the desire to use abstraction to make the library easier to use out-of-the-box, especially for newer users who just want to call run_model.py with some hyparameters.
However, as someone who considers himself a novice-intermediate and frequently needs to look at or modify the source code to achieve what ... | {
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