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https://api.github.com/repos/huggingface/transformers/issues/2712 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2712/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2712/comments | https://api.github.com/repos/huggingface/transformers/issues/2712/events | https://github.com/huggingface/transformers/issues/2712 | 558,705,269 | MDU6SXNzdWU1NTg3MDUyNjk= | 2,712 | a problem occur when I train Chinese distilgpt2 model | {
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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"
] | 1,580 | 1,586 | 1,586 | CONTRIBUTOR | null | ### When I was training a new model from zero to one, the following questions appeared, please help me answer them, thank you very much!
![image](https://user-images.githubusercontent.com/36957508/73609850... | {
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https://api.github.com/repos/huggingface/transformers/issues/2711 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2711/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2711/comments | https://api.github.com/repos/huggingface/transformers/issues/2711/events | https://github.com/huggingface/transformers/issues/2711 | 558,698,789 | MDU6SXNzdWU1NTg2OTg3ODk= | 2,711 | TypeError: apply_gradients() missing 1 required positional argument: 'clip_norm' | {
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"Hi, indeed this optimizer `AdamWeightDecay` requires an additional argument for truncating the gradient norm.\r\n\r\nIt essentially feeds the `clip_norm` argument (which is the second required argument in `apply_gradients`) to [tf.clip_by_global_norm](https://www.tensorflow.org/api_docs/python/tf/clip_by_global_no... | 1,580 | 1,588 | 1,581 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (TFBertModel):
Language I am using the model on (English):
Also I'm using `tensorflow==2.1.0` and `transformers==2.3.0`
The problem arises when using:
* [x] the official example scripts: (give details below)
I'm trying to use the `optimization_tf.create_optimize... | {
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https://api.github.com/repos/huggingface/transformers/issues/2710 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2710/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2710/comments | https://api.github.com/repos/huggingface/transformers/issues/2710/events | https://github.com/huggingface/transformers/pull/2710 | 558,667,128 | MDExOlB1bGxSZXF1ZXN0MzY5OTg5ODQ3 | 2,710 | Removed unused fields in DistilBert TransformerBlock | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2710?src=pr&el=h1) Report\n> Merging [#2710](https://codecov.io/gh/huggingface/transformers/pull/2710?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2ba147ecffa28e5a4f96eebd09dcd642117dedae?src=pr&el=desc) will **d... | 1,580 | 1,582 | 1,582 | CONTRIBUTOR | null | A few fields in the TransformerBlock are unused - this small PR cleans it up.
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https://api.github.com/repos/huggingface/transformers/issues/2709 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2709/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2709/comments | https://api.github.com/repos/huggingface/transformers/issues/2709/events | https://github.com/huggingface/transformers/issues/2709 | 558,655,284 | MDU6SXNzdWU1NTg2NTUyODQ= | 2,709 | DistributedDataParallel for multi-gpu single-node runs in run_lm_finetuning.py | {
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"As far as I can see, the script fully supports DDP:\r\n\r\nhttps://github.com/huggingface/transformers/blob/2ba147ecffa28e5a4f96eebd09dcd642117dedae/examples/run_lm_finetuning.py#L282-L286\r\n\r\nI haven't run the script myself, but looking at the source this should work with the [torch launch](https://pytorch.org... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
Modify `run_lm_finetuning.py` with DDP for multi-gpu single-node jobs.
## Motivation
<!-- Please outline the motivation for the proposal. Is your featu... | {
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https://api.github.com/repos/huggingface/transformers/issues/2708 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2708/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2708/comments | https://api.github.com/repos/huggingface/transformers/issues/2708/events | https://github.com/huggingface/transformers/issues/2708 | 558,610,431 | MDU6SXNzdWU1NTg2MTA0MzE= | 2,708 | Can't pickle local object using the finetuning example. | {
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"Do you mind specifying which versions of everything you're using, as detailed in the [bug report issue template](https://github.com/huggingface/transformers/issues/new/choose)?",
"Hi @Normand-1024 \r\n\r\nwere you able to fix this error?\r\nas i am getting the same error while trying to run glue task (QQP) but w... | 1,580 | 1,647 | 1,587 | NONE | null | I was testing out the finetuning example from the repo:
`python run_lm_finetuning.py --train_data_file="finetune-output/KantText.txt" --output_dir="finetune-output/hugkant" --model_type=gpt2 --model_name_or_path=gpt2 --do_train --block_size=128`
While saving the checkpoint, it gives the following error:
```
... | {
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https://api.github.com/repos/huggingface/transformers/issues/2707 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2707/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2707/comments | https://api.github.com/repos/huggingface/transformers/issues/2707/events | https://github.com/huggingface/transformers/pull/2707 | 558,559,779 | MDExOlB1bGxSZXF1ZXN0MzY5OTEyMjM4 | 2,707 | Fix typo in examples/utils_ner.py | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2707?src=pr&el=h1) Report\n> Merging [#2707](https://codecov.io/gh/huggingface/transformers/pull/2707?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ddb6f9476b58ed9bf4433622ca9aa49932929bc0?src=pr&el=desc) will **n... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | `"%s-%d".format()` -> `"{}-{}".format()` | {
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https://api.github.com/repos/huggingface/transformers/issues/2706 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2706/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2706/comments | https://api.github.com/repos/huggingface/transformers/issues/2706/events | https://github.com/huggingface/transformers/issues/2706 | 558,555,100 | MDU6SXNzdWU1NTg1NTUxMDA= | 2,706 | Load from tf2.0 checkpoint fail | {
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"Hi, in order to convert an official checkpoint to a checkpoint readable by `transformers`, you need to use the script `convert_bert_original_tf_checkpoint_to_pytorch`. You can then load it in a `BertModel` (PyTorch) or a `TFBertModel` (TensorFlow), by specifying the argument `from_pt=True` in your `from_pretrained... | 1,580 | 1,586 | 1,586 | 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/2705 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2705/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2705/comments | https://api.github.com/repos/huggingface/transformers/issues/2705/events | https://github.com/huggingface/transformers/issues/2705 | 558,519,030 | MDU6SXNzdWU1NTg1MTkwMzA= | 2,705 | What is the input for TFBertForSequenceClassification? | {
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"Have a look at an example, for instance [`run_tf_glue.py`](https://github.com/huggingface/transformers/blob/master/examples/run_tf_glue.py). To better understand all the arguments, I advise you to read the [documentation](https://huggingface.co/transformers/model_doc/bert.html#bertmodel). You'll find that token_ty... | 1,580 | 1,584 | 1,580 | NONE | null | # ❓ Questions & Help
What is the input for TFBertForSequenceClassification?
## Details
I have a simple multiclass text data on which I want to train the BERT model.
From docs I have found the input format of data:
```a list of varying length with one or several input Tensors IN THE ORDER given in the docstring: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2704 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2704/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2704/comments | https://api.github.com/repos/huggingface/transformers/issues/2704/events | https://github.com/huggingface/transformers/issues/2704 | 558,474,768 | MDU6SXNzdWU1NTg0NzQ3Njg= | 2,704 | How to make transformers examples use GPU? | {
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"GPU should be used by default and can be disabled with the `no_cuda` flag. If your GPU is not being used, that means that PyTorch can't access your CUDA installation. \r\n\r\nWhat is the output of running this in your Python interpreter?\r\n\r\n```python\r\nimport torch\r\ntorch.cuda.is_available()\r\n```",
"Tha... | 1,580 | 1,659 | 1,580 | NONE | null | # ❓ Questions & Help
I'm training the run_lm_finetuning.py with wiki-raw dataset. The training seems to work fine, but it is not using my GPU. Is there any flag which I should set to enable GPU usage?
## Details
I'm training the run_lm_finetuning.py with wiki-raw dataset. The training seems to work fine, but it ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2703 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2703/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2703/comments | https://api.github.com/repos/huggingface/transformers/issues/2703/events | https://github.com/huggingface/transformers/issues/2703 | 558,468,127 | MDU6SXNzdWU1NTg0NjgxMjc= | 2,703 | run_lm_finetuning.py on bert-base-uncased with wikitext-2-raw does not work | {
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"Hi, did you manage to fix your issue?",
"Hi,\r\nYes, I took the latest build, and it worked without any changes. "
] | 1,580 | 1,580 | 1,580 | NONE | null | # 🐛 Bug
## Running run_lm_finetuning.py on bert-base-uncased with wikitext-2-raw does not work.
Model I am using (Bert, XLNet ...): Bert - bert-base-uncased
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [*] the official example scripts: (give details be... | {
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"RoBERTa accepts token typen ids because RoBERTa is basically the same architecture as BERT. (The \"innovation\" lies in how it's pretrained, not architectural changes.) It's literally nothing more than this:\r\n\r\nhttps://github.com/huggingface/transformers/blob/ddb6f9476b58ed9bf4433622ca9aa49932929bc0/src/transf... | 1,580 | 1,673 | 1,587 | CONTRIBUTOR | null | ```Python
>>> tokenizer = transformers.AutoTokenizer.from_pretrained("distilbert-base-uncased-distilled-squad")
>>> tokenized = tokenizer.encode_plus("I ate a clock yesterday.", "It was very time consuming.")
>>> tokenized
{'input_ids': [101, 1045, 8823, 1037, 5119, 7483, 1012, 102, 2009, 2001, 2200, 2051, 15077, 1... | {
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https://api.github.com/repos/huggingface/transformers/issues/2701 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2701/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2701/comments | https://api.github.com/repos/huggingface/transformers/issues/2701/events | https://github.com/huggingface/transformers/pull/2701 | 558,400,986 | MDExOlB1bGxSZXF1ZXN0MzY5NzkzMDE3 | 2,701 | Store Model cards in the repo | {
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"Thanks for importing the readme files :heart: ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2701?src=pr&el=h1) Report\n> Merging [#2701](https://codecov.io/gh/huggingface/transformers/pull/2701?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d426b58b9e32a... | 1,580 | 1,580 | 1,580 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2700 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2700/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2700/comments | https://api.github.com/repos/huggingface/transformers/issues/2700/events | https://github.com/huggingface/transformers/pull/2700 | 558,248,770 | MDExOlB1bGxSZXF1ZXN0MzY5Njc0ODY5 | 2,700 | Add TF2 version of FlauBERT | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2700?src=pr&el=h1) Report\n> :exclamation: No coverage uploaded for pull request base (`master@bae644c`). [Click here to learn what that means](https://docs.codecov.io/docs/error-reference#section-missing-base-commit).\n> The diff coverage is `75%`.\n... | 1,580 | 1,589 | 1,584 | CONTRIBUTOR | null | Hello,
I worked today to add the new FlauBERT model in TF2 version. Translated models are available in:
```
jplu/tf-flaubert-base-cased
jplu/tf-flaubert-large-cased
jplu/tf-flaubert-small-cased
jplu/tf-flaubert-base-uncased
``` | {
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https://api.github.com/repos/huggingface/transformers/issues/2699 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2699/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2699/comments | https://api.github.com/repos/huggingface/transformers/issues/2699/events | https://github.com/huggingface/transformers/pull/2699 | 558,243,948 | MDExOlB1bGxSZXF1ZXN0MzY5NjcxMDU2 | 2,699 | CLI script to gather environment info | {
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"This is really cool!",
"> This is really cool!\r\n\r\nProps to spaCy, since I basically stole [the idea](https://github.com/explosion/spaCy/blob/master/spacy/cli/info.py) from them. ",
"LGTM but I've also pinged @mfuntowicz as he will have good insight",
"Is there a way to see which tests are run in `check_c... | 1,580 | 1,580 | 1,580 | COLLABORATOR | null | I noticed that all too often people leave the "Environment" section in their issue empty. However, things such as the version number of PT/TF and `transformers` itself are very useful to know when trying to debug things.
This PR adds a small script to the existing CLI workflow. Running `python transformers-cli info`... | {
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https://api.github.com/repos/huggingface/transformers/issues/2698 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2698/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2698/comments | https://api.github.com/repos/huggingface/transformers/issues/2698/events | https://github.com/huggingface/transformers/pull/2698 | 558,205,362 | MDExOlB1bGxSZXF1ZXN0MzY5NjQwNjI2 | 2,698 | Typo on markdown link in README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2698?src=pr&el=h1) Report\n> Merging [#2698](https://codecov.io/gh/huggingface/transformers/pull/2698?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0aa40e9569a71306036de3a217eed55521699604?src=pr&el=desc) will **n... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2697 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2697/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2697/comments | https://api.github.com/repos/huggingface/transformers/issues/2697/events | https://github.com/huggingface/transformers/issues/2697 | 558,183,121 | MDU6SXNzdWU1NTgxODMxMjE= | 2,697 | Albert language model fine tuning not running run_lm_finetuning.py | {
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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 am facing the same problem with BERT fine tuning for a masked language modeling fine tuning task. Can someone please help? I am exact... | 1,580 | 1,593 | 1,586 | NONE | null | # 🐛 Bug
## Information
Model I am using (Albert(all types)):
Language I am using the model on (English):
The problem arises when using:
* [ ] the official example scripts: (give details below)
the code returns memory allocation problems when run with any version from albert. i tried to reduce the sequenc... | {
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https://api.github.com/repos/huggingface/transformers/issues/2696 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2696/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2696/comments | https://api.github.com/repos/huggingface/transformers/issues/2696/events | https://github.com/huggingface/transformers/issues/2696 | 558,178,924 | MDU6SXNzdWU1NTgxNzg5MjQ= | 2,696 | Missing `do_sample` argument for run_generation example | {
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"You're absolutely correct, I pushed a fix with 7365f01!",
"Ran into this issue myself by accident.\r\n\r\nIMO, `do_sample=True` should be the default behavior for `generate()` since that's more in line with user expectations.",
"I agree with you, the default should be set to `True`. I've changed the default in... | 1,580 | 1,584 | 1,581 | NONE | null | # ❓ Questions & Help
It seems the arguments `k`, `p`, `temperature` are disabled because `do_sample` is set to False by default. Thus, [run_generation.py](https://github.com/huggingface/transformers/blob/master/examples/run_generation.py) will always use greedy decoding no matter how the `k`, `p`, `temperature` are... | {
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https://api.github.com/repos/huggingface/transformers/issues/2695 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2695/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2695/comments | https://api.github.com/repos/huggingface/transformers/issues/2695/events | https://github.com/huggingface/transformers/issues/2695 | 558,170,031 | MDU6SXNzdWU1NTgxNzAwMzE= | 2,695 | get_linear_schedule_with_warmup method can't be found in optimization.py | {
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"There clearly is:\r\n\r\nhttps://github.com/huggingface/transformers/blob/0aa40e9569a71306036de3a217eed55521699604/src/transformers/optimization.py#L47-L59\r\n\r\nPlease fill out the complete template - it's there for a reason. If you had shown us which version you're working with, we could probably tell you that ... | 1,580 | 1,580 | 1,580 | 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)
* [ ] my own modified scripts: (give details below)
My transformer was downloaded fro... | {
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https://api.github.com/repos/huggingface/transformers/issues/2694 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2694/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2694/comments | https://api.github.com/repos/huggingface/transformers/issues/2694/events | https://github.com/huggingface/transformers/issues/2694 | 558,137,584 | MDU6SXNzdWU1NTgxMzc1ODQ= | 2,694 | AutoModel fails to load FlauBERT with `output_hidden_states` | {
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"Hi! the `output_hidden_states` should be specified in the configuration when loading from `AutoModel` classes. Doing the following is necessary to instantiate a class with hidden states:\r\n\r\n```py\r\nimport transformers\r\n\r\nconfig = transformers.AutoConfig.from_pretrained(\"flaubert-base-cased\", output_hidd... | 1,580 | 1,587 | 1,586 | NONE | null | MWE:
```python
import transformers
model = transformers.AutoModel.from_pretrained("flaubert-base-cased", output_hidden_states=True)
```
Tested on rev 5a6b138 fails with
```console
Traceback (most recent call last):
File "mwe.py", line 3, in <module>
model = transformers.AutoModel.from_pretrained(... | {
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https://api.github.com/repos/huggingface/transformers/issues/2693 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2693/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2693/comments | https://api.github.com/repos/huggingface/transformers/issues/2693/events | https://github.com/huggingface/transformers/issues/2693 | 558,052,909 | MDU6SXNzdWU1NTgwNTI5MDk= | 2,693 | Input file format for examples/run_lm_finetuning.py | {
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"Hi, two datasets are available in `run_lm_finetuning.py`:\r\n\r\n- `TextDataset`, which just splits your data into chunks with no attention whatsoever to the line returns or separators\r\n- `LineByLineTextDataset`, which splits your data into chunks, being careful not to overstep line returns as each line is inter... | 1,580 | 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
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https://api.github.com/repos/huggingface/transformers/issues/2692 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2692/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2692/comments | https://api.github.com/repos/huggingface/transformers/issues/2692/events | https://github.com/huggingface/transformers/issues/2692 | 558,027,005 | MDU6SXNzdWU1NTgwMjcwMDU= | 2,692 | Regarding distlbert uncased model's size | {
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"please reply",
"You're comparing two formats that are different, so the comparison doesn't really make sense. The BERT model weighs 410MB when saved as a HDF5 file, whereas DistilBERT weighs 810MB when saved as a SavedModel, which also contains the graph and variables.\r\n\r\nSaving both files in HDF5:\r\n\r\n``... | 1,580 | 1,586 | 1,586 | NONE | null | I finetuned the distlbert uncased model, and I had a thought that since it is a lower layer model, it should have less weight. But, to my surprise, I find that the model generated after finetuning, I saved it as :
tf.saved_model.save(model, "./tempdir/distilbert/2/")
and the tf model got saved.
this model has ... | {
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"You can add new words to the tokenizer with [add_tokens](https://huggingface.co/transformers/main_classes/tokenizer.html?highlight=add_tokens#transformers.PreTrainedTokenizer.add_tokens):\r\n`tokenizer.add_tokens(['newWord', 'newWord2'])`\r\nAfter that you need to resize the dictionary size of the embedding layer ... | 1,580 | 1,692 | 1,587 | NONE | null | Is it possible to fine tune BertTokenizer so that the new vocab.txt file which it uses gets updated on my custom dataset? or do i need to retrain the bert model from scratch for the same? | {
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https://api.github.com/repos/huggingface/transformers/issues/2690 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2690/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2690/comments | https://api.github.com/repos/huggingface/transformers/issues/2690/events | https://github.com/huggingface/transformers/issues/2690 | 557,782,618 | MDU6SXNzdWU1NTc3ODI2MTg= | 2,690 | Hardware requirements for BERT QA inference | {
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"@LysandreJik wrote an article about benchmarking transformers (focusing on inference) that might be of interest to you.\r\n\r\nhttps://medium.com/huggingface/benchmarking-transformers-pytorch-and-tensorflow-e2917fb891c2",
"Thanks for the reply!\r\nI checked the benchmarks, there you tested with 16GB GPU and bert... | 1,580 | 1,580 | 1,580 | NONE | null | Hi,
I am using **bert-large-uncased-whole-word-masking-finetuned-squad** model for QA inference.
I used my laptop's CPU to build the pipeline and try it out.
Now I want to deploy it, and so I would like to know what is the minimum hardware requirement?(If I use the same settings as in your usage example scrip... | {
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https://api.github.com/repos/huggingface/transformers/issues/2689 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2689/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2689/comments | https://api.github.com/repos/huggingface/transformers/issues/2689/events | https://github.com/huggingface/transformers/pull/2689 | 557,779,358 | MDExOlB1bGxSZXF1ZXN0MzY5MzA4NjYw | 2,689 | Correct PyTorch distributed training command in examples/README.md | {
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"That's cool, thanks @jarednielsen !"
] | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | Running the command currently detailed in the documentation yields
`58.4/70.3 EM/F1` with Ubuntu 18.04 and torch 1.4.0, not `86.9/93.1` as promised. It also looks wrong because we're using a cased model with `--do_lower_case`.
Switching it to match the PyTorch distributed training example given in the main README... | {
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https://api.github.com/repos/huggingface/transformers/issues/2688 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2688/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2688/comments | https://api.github.com/repos/huggingface/transformers/issues/2688/events | https://github.com/huggingface/transformers/pull/2688 | 557,775,795 | MDExOlB1bGxSZXF1ZXN0MzY5MzA1NzEz | 2,688 | Config: reference array of architectures | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2688?src=pr&el=h1) Report\n> Merging [#2688](https://codecov.io/gh/huggingface/transformers/pull/2688?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b43cb09aaa6d81f4e1f4a2537764e37aa823b30b?src=pr&el=desc) will **d... | 1,580 | 1,580 | 1,580 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2687 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2687/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2687/comments | https://api.github.com/repos/huggingface/transformers/issues/2687/events | https://github.com/huggingface/transformers/issues/2687 | 557,634,614 | MDU6SXNzdWU1NTc2MzQ2MTQ= | 2,687 | Issue about pipeline of sentiment-analysis | {
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"I can't reproduce this. It works fine for me. Can you try deleting the cache directory and trying again?",
"@BramVanroy \r\nYes, I tried deleting the cached file under the `.cached` directory, but it still doesn't work for me.",
"Works for me too. Are you sure you deleted the right file?\r\n\r\n",
"@julien-c... | 1,580 | 1,619 | 1,580 | NONE | null | Hi,
I tried the `pipeline` code on the README:
```
from transformers import pipeline
nlp = pipeline('sentiment-analysis')
print(nlp('We are very happy to include pipeline into the transformers repository.'))
```
However, it shows the following error:
```
I0131 01:02:23.627610 4420611520 file_utils.py:35] P... | {
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https://api.github.com/repos/huggingface/transformers/issues/2686 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2686/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2686/comments | https://api.github.com/repos/huggingface/transformers/issues/2686/events | https://github.com/huggingface/transformers/pull/2686 | 557,592,714 | MDExOlB1bGxSZXF1ZXN0MzY5MTU2MjY5 | 2,686 | Add layerdrop to Flaubert | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2686?src=pr&el=h1) Report\n> Merging [#2686](https://codecov.io/gh/huggingface/transformers/pull/2686?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/df27648bd942d59481a13842904f8cb500136e31?src=pr&el=desc) will **d... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | This PR adds `layerdrop` to Flaubert. | {
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https://api.github.com/repos/huggingface/transformers/issues/2685 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2685/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2685/comments | https://api.github.com/repos/huggingface/transformers/issues/2685/events | https://github.com/huggingface/transformers/issues/2685 | 557,530,160 | MDU6SXNzdWU1NTc1MzAxNjA= | 2,685 | German Bert tokenizer does not recognize (some) special characters (!,?,...) | {
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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",
"Sounds like this was fixed by @Timoeller in #3618, @andrey999333 ",
"Thanks for referencing. This bug should be fixed with the change... | 1,580 | 1,586 | 1,586 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
**Bert**
Language I am using the model on (English, Chinese ...):
**German**
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ X] my own modified scripts: (give details below)
The tasks I am work... | {
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https://api.github.com/repos/huggingface/transformers/issues/2684 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2684/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2684/comments | https://api.github.com/repos/huggingface/transformers/issues/2684/events | https://github.com/huggingface/transformers/issues/2684 | 557,525,848 | MDU6SXNzdWU1NTc1MjU4NDg= | 2,684 | distilbert_multilingual_cased model for multiple language | {
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"Could you try to install a newer version of the library? The `distilbert-base-multilingual-cased` checkpoint is available in recent transformers versions, as you can see in the [source code](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_distilbert.py#L42).",
"thanks a lot",
... | 1,580 | 1,580 | 1,580 | NONE | null | By when distilbert_multilingual_cased model is going to be released.because I tried to finetune the
distilbert_multilingual_cased model , but it said "OSError: file distilbert-base-multilingual-cased not found", which means the above-mentioned model is not included in the list. Or let me know if I am doing any wrong ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2683 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2683/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2683/comments | https://api.github.com/repos/huggingface/transformers/issues/2683/events | https://github.com/huggingface/transformers/issues/2683 | 557,496,356 | MDU6SXNzdWU1NTc0OTYzNTY= | 2,683 | TFCamembertModel | {
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"Hi, the CamemBERT model for tensorflow was merged yesterday, and is therefore available from the master branch right now. You can install it with \r\n\r\n```py\r\npip install git+https://github.com/huggingface/transformers\r\n```\r\n\r\nIt will be in the next transformers release (2.4.0 or 2.3.1), which should be ... | 1,580 | 1,586 | 1,586 | NONE | null | Hi,
I wanted to use the tensorflow version of Camembert : TFCamembertModel, but the implememtation is not available with the v2.3.0 version : https://huggingface.co/transformers/v2.3.0/model_doc/camembert.html.
But TFCamembertModel seems to be available with another version of transformers : https://huggingfac... | {
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"Should be fixed.",
"Nice! Thanks :)",
"By the way, you should also add a README.md to the same `pretrained_model` folders so that it's displayed on the model pages (see [this one](https://huggingface.co/dbmdz/bert-base-german-cased) for instance)\r\n\r\nI'll document this feature better today.\r\n\r\n",
"Sho... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | Hello,
The URL of my [profile](https://huggingface.co/jplu) on the upload/share models webpage looks like if there was a model called `jplu`. Any idea why?
Thanks. | {
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https://api.github.com/repos/huggingface/transformers/issues/2681 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2681/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2681/comments | https://api.github.com/repos/huggingface/transformers/issues/2681/events | https://github.com/huggingface/transformers/issues/2681 | 557,376,935 | MDU6SXNzdWU1NTczNzY5MzU= | 2,681 | How to add a fc classification head to BertForQA to make a MTL-BertForQA model? | {
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"I am currently trying to figure out how to add an additional classification head to the BertForQA model. I am not sure which is the best / most efficient way to do that. Should I rewrite the source code for BertForQA and inherit from BertPretrainedModel, or should I rather inherit from BertForQA and change the for... | 1,580 | 1,586 | 1,586 | 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/2680 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2680/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2680/comments | https://api.github.com/repos/huggingface/transformers/issues/2680/events | https://github.com/huggingface/transformers/issues/2680 | 557,370,163 | MDU6SXNzdWU1NTczNzAxNjM= | 2,680 | Does loss function in the run_tf_ner.py takes logits or probabilities? | {
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"I think you are right, I also find this bug, see [🐛Bugs in run_tf_ner.py](https://github.com/huggingface/transformers/issues/3389)",
"Hey @andrey999333! I answered to the question just here https://github.com/huggingface/transformers/issues/3389",
"Hey @jplu Thanks a lot, i have not noticed that line for some... | 1,580 | 1,585 | 1,585 | NONE | null | The model used for ner model is TFBertForTokenClassification in case of Tensorflow. According to documentation this model produces logits for every token. But the loss function that is used in `run_tf_ner.py` is `tf.losses.SparseCategoricalCrossentropy(reduction=tf.keras.losses.Reduction.NONE)` which has default argume... | {
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https://api.github.com/repos/huggingface/transformers/issues/2679 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2679/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2679/comments | https://api.github.com/repos/huggingface/transformers/issues/2679/events | https://github.com/huggingface/transformers/pull/2679 | 557,334,954 | MDExOlB1bGxSZXF1ZXN0MzY4OTQyMjU1 | 2,679 | Add classifier dropout in ALBERT | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2679?src=pr&el=h1) Report\n> Merging [#2679](https://codecov.io/gh/huggingface/transformers/pull/2679?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/83446a88d902661fab12bf8c37a1aa2845cdca5f?src=pr&el=desc) will **i... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | As mentioned in the original [paper](https://arxiv.org/pdf/1909.11942.pdf), they separated the dropout rates of the transformer cells and the classifier, moreover, in V2 the dropouts are 0 (expect for the classifier, again).
Current implementation does not supports this and models are not training well (can't reprod... | {
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https://api.github.com/repos/huggingface/transformers/issues/2678 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2678/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2678/comments | https://api.github.com/repos/huggingface/transformers/issues/2678/events | https://github.com/huggingface/transformers/issues/2678 | 557,084,278 | MDU6SXNzdWU1NTcwODQyNzg= | 2,678 | Bug in consecutive creation of tokenizers with different parameters | {
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"Just to be clear: I understand that specifying `do_lower_case=True` for a cased model is wrong. The point is in overwriting or somewhat caching the parameter for future calls of the class constructor.",
"Here is the full output with logger.\r\n```\r\nI0129 23:25:47.064881 140331667420992 file_utils.py:38] PyTorc... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | # 🐛 Bug
Creating a tokenizer with do_lower_case set to True overwrites it for the consecutive creation.
## Information
Model I am using: bert-base-cased
Language I am using the model on (English, Chinese ...):
English
## To reproduce
```python
from transformers import AutoTokenizer
text = "Hello t... | {
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https://api.github.com/repos/huggingface/transformers/issues/2677 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2677/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2677/comments | https://api.github.com/repos/huggingface/transformers/issues/2677/events | https://github.com/huggingface/transformers/pull/2677 | 557,066,887 | MDExOlB1bGxSZXF1ZXN0MzY4NzI1NjYz | 2,677 | Flaubert | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2677?src=pr&el=h1) Report\n> Merging [#2677](https://codecov.io/gh/huggingface/transformers/pull/2677?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/adb8c93134f02fd0eac2b52189364af21977004c?src=pr&el=desc) will **d... | 1,580 | 1,580 | 1,580 | MEMBER | null | From PR #2632 by [formiel](https://github.com/formiel).
This PR adds [FlauBERT](https://github.com/getalp/Flaubert). Most of the code is derived from XLM (there are some new features in FlauBERT such as pre_norm and layerdrop).
The failing tests were fixed. | {
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https://api.github.com/repos/huggingface/transformers/issues/2676 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2676/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2676/comments | https://api.github.com/repos/huggingface/transformers/issues/2676/events | https://github.com/huggingface/transformers/issues/2676 | 557,006,163 | MDU6SXNzdWU1NTcwMDYxNjM= | 2,676 | Trouble fine tuning Huggingface GPT-2 on Colab — Assertion error | {
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"The error raised means that it cannot find the files you gave it. Do you manage to load the files using the \r\n`with open` syntax without using the script?",
"> Do you manage to load the files using the `with open` syntax without using the script?\r\n\r\nThanks for the reply. I guess the answer is 'no', as I'm... | 1,580 | 1,580 | 1,580 | NONE | null | [Cross posted from SO]
I wish to fine tune Huggingface's GPT-2 transformer model on my own text data. I want to do this on a Google Colab notebook. However, it doesn't seem to work.
I install the various bits and pieces via the Colab:
```
!git clone https://github.com/huggingface/transformers
%cd transformer... | {
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https://api.github.com/repos/huggingface/transformers/issues/2675 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2675/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2675/comments | https://api.github.com/repos/huggingface/transformers/issues/2675/events | https://github.com/huggingface/transformers/issues/2675 | 556,992,566 | MDU6SXNzdWU1NTY5OTI1NjY= | 2,675 | Best weights/models after fine-tuning gpt2 | {
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"Hi! Indeed saving checkpoints after every 50 iterations is quite a lot, therefore we've upped this value to 500 yesterday in 335dd5e. Concerning your questions:\r\n\r\n1. You can use the `--evaluate_during_training` flag to evaluate the model every `--logging_step`, or you can use the `--evaluate_all_checkpoints` ... | 1,580 | 1,580 | 1,580 | 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/2674 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2674/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2674/comments | https://api.github.com/repos/huggingface/transformers/issues/2674/events | https://github.com/huggingface/transformers/pull/2674 | 556,976,156 | MDExOlB1bGxSZXF1ZXN0MzY4NjUxNTg2 | 2,674 | Integrate fast tokenizers library inside transformers | {
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"only took a superficial look, but looks very clean 👍 \r\n\r\nExcited to use fast tokenizers by default!",
"Current CI issues are real and \"normal\" we need to release the next version of tokenizers lib which will bring all the dependencies.",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2... | 1,580 | 1,582 | 1,582 | MEMBER | null | Integrate the BPE-based tokenizers inside transformers.
- [x] Bert (100% match)
- [x] DistilBert (100% match)
- [x] OpenAI GPT (100% match)
- [x] GPT2 (100% match if no trailing \n)
- [x] Roberta (100% match if no trailing \n)
- [x] TransformerXL
- [x] CTRL (No binding will be provided).
Added priority for ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2673 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2673/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2673/comments | https://api.github.com/repos/huggingface/transformers/issues/2673/events | https://github.com/huggingface/transformers/issues/2673 | 556,950,222 | MDU6SXNzdWU1NTY5NTAyMjI= | 2,673 | Fine tuning XLMRoberta for Question Answering | {
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"Hi, we don't currently have an implementation of XLM RoBERTa in tensorflow.",
"I guess this one can now be closed since TensorFlow XLM-RoBERTa was released with 2.4.0. Thanks @LysandreJik @jplu . Quick question though: I guess you are not retraining the LM but convert the pytorch weighs. Is there any script in h... | 1,580 | 1,580 | 1,580 | 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/2672 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2672/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2672/comments | https://api.github.com/repos/huggingface/transformers/issues/2672/events | https://github.com/huggingface/transformers/issues/2672 | 556,930,415 | MDU6SXNzdWU1NTY5MzA0MTU= | 2,672 | bert-base-uncased have weird result on Squad 2.0 | {
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"Hi, running the exact same command but specifying you're using the version 2 with `--version_2_with_negative` gives me the following results:\r\n\r\n```\r\n01/29/2020 13:20:35 - INFO - __main__ - Results: {'exact': 73.29234397372188, 'f1': 76.50792180947842, 'total': 11873, 'HasAns_exact': 71.94669365721997, 'Ha... | 1,580 | 1,602 | 1,580 | NONE | null | I followed the example to fine-tuning BERT on SQuAD2.0:
https://huggingface.co/transformers/examples.html#fine-tuning-bert-on-squad1-0
I run the code as follow:
```
python /content/drive/My\ Drive/squad2/run_squad.py \
--model_type bert \
--model_name_or_path bert-base-uncased \
--do_train \
--do_eval... | {
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https://api.github.com/repos/huggingface/transformers/issues/2671 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2671/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2671/comments | https://api.github.com/repos/huggingface/transformers/issues/2671/events | https://github.com/huggingface/transformers/issues/2671 | 556,649,762 | MDU6SXNzdWU1NTY2NDk3NjI= | 2,671 | is SOP(sentence order prediction) implemented? | {
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"Hi, the layer that was used for SOP is the pooler layer, which is available in the base `AlbertModel`. When doing a forward pass, the model returns the `pooled_output` as a second value in the returned tuple. You can use this for doing a SOP task.",
"Oh I see! Thank you so much :)",
"Sorry for reopening this i... | 1,580 | 1,645 | 1,580 | NONE | null | # ❓ Questions & Help
I am reviewing huggingface's version of Albert.
However, I cannot find any code or comment about SOP.
I can find NSP(Next Sentence Prediction) implementation from modeling_from src/transformers/modeling_bert.py.
Is SOP inherited from here with SOP-style labeling? or Is there anything I am... | {
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https://api.github.com/repos/huggingface/transformers/issues/2670 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2670/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2670/comments | https://api.github.com/repos/huggingface/transformers/issues/2670/events | https://github.com/huggingface/transformers/pull/2670 | 556,585,774 | MDExOlB1bGxSZXF1ZXN0MzY4MzI5NDY3 | 2,670 | Remove unnecessary `del` in run_tf_glue.py example | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2670?src=pr&el=h1) Report\n> Merging [#2670](https://codecov.io/gh/huggingface/transformers/pull/2670?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9d87eafd118739a4c121d69d7cff425264f01e1c?src=pr&el=desc) will **n... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | Platform: Ubuntu 18.04 (Linux-4.15.0-1054-aws-x86_64-with-Ubuntu-18.04-bionic)
Python: 3.6.9
PyTorch: 1.4.0
TensorFlow: 2.0.0
Running `./examples/run_tf_glue.py` gives `KeyError: 'special_tokens_mask'`.
Diving into the code, it looks like there's an optional keyword argument in [`encode_plus()`](https://github... | {
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https://api.github.com/repos/huggingface/transformers/issues/2669 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2669/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2669/comments | https://api.github.com/repos/huggingface/transformers/issues/2669/events | https://github.com/huggingface/transformers/issues/2669 | 556,551,029 | MDU6SXNzdWU1NTY1NTEwMjk= | 2,669 | models and tokenizers trained with pytorch_pretrained_bert are not compatible with transformers | {
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"Can you share your vocabulary so we can have a look at the differences?",
"@thomwolf I took the `vocab.json` located inside `runs/mymodel` and the `openai-gpt-vocab.json` hosted in the Hugging Face [S3](https://s3.amazonaws.com/models.huggingface.co/bert/openai-gpt-vocab.json) bucket and compared the two as foll... | 1,580 | 1,581 | 1,581 | NONE | null | # 📚 Migration
## Information
The models and tokenizers in transformers 2.3.0 are backward incompatible with pytorch_pretrained_bert 0.6.2.
## Details
```
>>> import transformers
>>> transformers.__version__
'2.3.0'
>>> import pytorch_pretrained_bert
>>> pytorch_pretrained_bert.__version__
'0.6.2'
>>... | {
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https://api.github.com/repos/huggingface/transformers/issues/2668 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2668/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2668/comments | https://api.github.com/repos/huggingface/transformers/issues/2668/events | https://github.com/huggingface/transformers/issues/2668 | 556,473,673 | MDU6SXNzdWU1NTY0NzM2NzM= | 2,668 | How to get .ckpt files for tensorflow DistilBERT model | {
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"Hello JKP0,\r\n\r\nWhat do you need the .ckpt files for?",
"@Poaz Dear,\r\nWe are working on NLG models for coreference resolution. We started our project with BERT, so our implementations are dependent with the pre-trained [ BERT-model](https://storage.googleapis.com/bert_models/2018_10_18/cased_L-12_H-768_A-... | 1,580 | 1,643 | 1,586 | NONE | null | `model.save_pretrained('dir')` tf_model.h5 how to get .ckpt files for it | {
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https://api.github.com/repos/huggingface/transformers/issues/2667 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2667/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2667/comments | https://api.github.com/repos/huggingface/transformers/issues/2667/events | https://github.com/huggingface/transformers/issues/2667 | 556,286,583 | MDU6SXNzdWU1NTYyODY1ODM= | 2,667 | Calling AlbertTokenizer.from_pretrained() with the path to a single file or url is deprecated | {
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"You're trying to load a checkpoint in a tokenizer. Use `AlbertModel` to load the model, not `AlbertTokenizer`.",
"Okay. Thanks.\r\nThese two work okay\r\nmodel = TFAlbertModel.from_pretrained('albert-base-v2')\r\nmodel = TFAlbertForSequenceClassification.from_pretrained('albert-base-v2')\r\n\r\nbecause they are ... | 1,580 | 1,586 | 1,586 | NONE | null | <!-- A clear and concise description of the question. -->
I recently downloaded the [ALBERT_base_v2](https://storage.googleapis.com/albert_models/albert_base_v2.tar.gz) TF pretrained model and converted it to a pytorch with the following code:
`(base) enoch@enoch-pc:~/dl_repos/transformers/src/transformers$ python ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2666 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2666/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2666/comments | https://api.github.com/repos/huggingface/transformers/issues/2666/events | https://github.com/huggingface/transformers/issues/2666 | 556,241,636 | MDU6SXNzdWU1NTYyNDE2MzY= | 2,666 | Multiple token IDs for same token | {
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"Okay, I found that the symbol is not `<space>` but this `Ġ`\r\nSo there exist two words in the vocab - `can` and `Ġcan`\r\nWhy is this so?",
"Hi! This is indeed an intended property of the tokenizer. The GPT-2 tokenizer is a byte-level BPE that has a sufficient vocabulary size to make the distinction between tok... | 1,580 | 1,586 | 1,586 | NONE | null | ## ❓ Questions & Help
I am using GPT2Tokenizer. I observed that some tokens are duplicated in the vocabulary with a space appended to them in the beginning. For example, there exist two separate tokens - `can` and `<space>can`. Both of them are mapped to different token IDs - `5171` and `460` respectively.
Althou... | {
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https://api.github.com/repos/huggingface/transformers/issues/2665 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2665/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2665/comments | https://api.github.com/repos/huggingface/transformers/issues/2665/events | https://github.com/huggingface/transformers/pull/2665 | 556,189,262 | MDExOlB1bGxSZXF1ZXN0MzY3OTk2NjU5 | 2,665 | standardize CTRL BPE files - upload models to S3 | {
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"Also cc @keskarnitish!"
] | 1,580 | 1,651 | 1,582 | MEMBER | null | This PR:
- update CTRL BPE files (`vocab.json` and `merges.txt`) to use a single format for sub-word splitting (selected to use `</w>` at the end of words)
- upload CTRL updated vocabulary files and pytorch model (not updated) to AWS.
cc @mfuntowicz | {
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https://api.github.com/repos/huggingface/transformers/issues/2664 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2664/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2664/comments | https://api.github.com/repos/huggingface/transformers/issues/2664/events | https://github.com/huggingface/transformers/pull/2664 | 556,173,228 | MDExOlB1bGxSZXF1ZXN0MzY3OTgzMjcy | 2,664 | Updates to the templates | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2664?src=pr&el=h1) Report\n> Merging [#2664](https://codecov.io/gh/huggingface/transformers/pull/2664?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ea2600bd5f1d36f2fb61958be21db5b901e33884?src=pr&el=desc) will **n... | 1,580 | 1,582 | 1,580 | COLLABORATOR | null | This PR updates the existing GitHub templates. Main changes are:
- motivate users to post general question on Stack Overflow, tagged [huggingface-transformers](https://stackoverflow.com/questions/tagged/huggingface-transformers)
- removing the 'additional context' section as it might not add much and just bloats th... | {
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https://api.github.com/repos/huggingface/transformers/issues/2663 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2663/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2663/comments | https://api.github.com/repos/huggingface/transformers/issues/2663/events | https://github.com/huggingface/transformers/pull/2663 | 556,125,120 | MDExOlB1bGxSZXF1ZXN0MzY3OTQzMTQw | 2,663 | Add check to verify existence of pad_token_id | {
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"Tests failed on loading the Bert Whole Word Masking model:\r\n\r\n\r\n> OSError: Couldn't reach server at 'https://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-whole-word-masking-config.json' to download pretrained model configuration file.\r\n\r\nFetching that file from the browser does work, thou... | 1,580 | 1,580 | 1,580 | COLLABORATOR | null | In batch_encode_plus we have to ensure that the tokenizer has a pad_token_id so that, when padding, no None values are added as padding. That would happen with gpt2, openai, transfoxl.
closes https://github.com/huggingface/transformers/issues/2640 | {
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https://api.github.com/repos/huggingface/transformers/issues/2662 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2662/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2662/comments | https://api.github.com/repos/huggingface/transformers/issues/2662/events | https://github.com/huggingface/transformers/issues/2662 | 556,068,065 | MDU6SXNzdWU1NTYwNjgwNjU= | 2,662 | 'Embedding' object has no attribute 'shape' | {
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"You can't import a .ckpt file directly in a PyTorch model. You first need to convert your obtained BERT model to our format, using the script [convert_bert_original_tf_checkpoint_to_pytorch](https://github.com/huggingface/transformers/blob/master/src/transformers/convert_bert_original_tf_checkpoint_to_pytorch.py).... | 1,580 | 1,629 | 1,581 | CONTRIBUTOR | null | ## ❓ Questions & Help
**version**
tensorflow : 2.0.0
tensorflow-gpu : 2.0.0
torch : 1.3.1
transformers : 2.3.0
Also I'm using **google Colab**
I want to convert tf pretrained-model(for Korean) to pytorch model.
I just tried below code
**config = BertConfig.from_json_file(BERT_PATH+'/config.json')
mode... | {
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https://api.github.com/repos/huggingface/transformers/issues/2661 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2661/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2661/comments | https://api.github.com/repos/huggingface/transformers/issues/2661/events | https://github.com/huggingface/transformers/pull/2661 | 555,886,364 | MDExOlB1bGxSZXF1ZXN0MzY3NzQ3ODg4 | 2,661 | [Umberto] model shortcuts | {
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"Failing test is Heisenbug",
"@julien-c thank you we are looking at it right now.",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2661?src=pr&el=h1) Report\n> Merging [#2661](https://codecov.io/gh/huggingface/transformers/pull/2661?src=pr&el=desc) into [master](https://codecov.io/gh/huggingfa... | 1,580 | 1,580 | 1,580 | MEMBER | null | cc @loretoparisi @simonefrancia
see #2485 | {
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https://api.github.com/repos/huggingface/transformers/issues/2660 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2660/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2660/comments | https://api.github.com/repos/huggingface/transformers/issues/2660/events | https://github.com/huggingface/transformers/issues/2660 | 555,867,597 | MDU6SXNzdWU1NTU4Njc1OTc= | 2,660 | PPLM with Tensorflow | {
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"I think this is a mistake on our part. cc @LysandreJik @w4nderlust ",
"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",
"Yes, the code I / we contributed is only for PyTorch. I think ... | 1,580 | 1,585 | 1,585 | CONTRIBUTOR | null | ## ❓ Questions & Help
Hello,
I am still quite new to the library, so I do apologize if the answer is straightforward.
The latest release (https://github.com/huggingface/transformers/releases/tag/v2.3.0) mentions the inclusion of PPLM as a new architecture, both as Pytorch and TF.
I can't however seem to f... | {
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https://api.github.com/repos/huggingface/transformers/issues/2659 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2659/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2659/comments | https://api.github.com/repos/huggingface/transformers/issues/2659/events | https://github.com/huggingface/transformers/pull/2659 | 555,828,667 | MDExOlB1bGxSZXF1ZXN0MzY3Njk5OTk5 | 2,659 | [FIX] #2658 Inconsistent values returned by batch_encode_plus and enc… | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2659?src=pr&el=h1) Report\n> Merging [#2659](https://codecov.io/gh/huggingface/transformers/pull/2659?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e0849a66accda8aa435a3db164c373175115a5b0?src=pr&el=desc) will **i... | 1,580 | 1,587 | 1,587 | NONE | null | As ticket describe, when using batch_encode_plus, instead of encode_plus, tokens type and mask are different. They should be the same using batch processing or not. Proposed fix here solve the issue | {
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https://api.github.com/repos/huggingface/transformers/issues/2658 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2658/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2658/comments | https://api.github.com/repos/huggingface/transformers/issues/2658/events | https://github.com/huggingface/transformers/issues/2658 | 555,793,096 | MDU6SXNzdWU1NTU3OTMwOTY= | 2,658 | Inconsistent values returned by batch_encode_plus and encode_plus | {
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"I've been experimenting with `batch_encode_plus` with my current project and I have found few more inconsistencies and code affected:\r\n\r\n* `batch_encode_plus` is not introduced in any tests, so it is hard to tell what was desired behavior of this method\r\n* `batch_encode_plus` is not extending `encode_plus` i... | 1,580 | 1,582 | 1,582 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Bert
Language I am using the model on (English, Chinese....): bert-base-uncased
The problem arise when using:
* batch_encode_plus and encode_plus with pad_to_max_length & max_length
## To Reproduce
Minimal exemple :
I com... | {
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https://api.github.com/repos/huggingface/transformers/issues/2657 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2657/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2657/comments | https://api.github.com/repos/huggingface/transformers/issues/2657/events | https://github.com/huggingface/transformers/pull/2657 | 555,713,855 | MDExOlB1bGxSZXF1ZXN0MzY3NjA2MDkz | 2,657 | Add `return_special_tokens_mask` to `batch_encode_plus()` | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2657?src=pr&el=h1) Report\n> Merging [#2657](https://codecov.io/gh/huggingface/transformers/pull/2657?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/875c4ae48f97af9792ab0b87b49a426ca7e7586b?src=pr&el=desc) will **d... | 1,580 | 1,586 | 1,586 | NONE | null | Proposal to add the keyword argument `return_special_tokens_mask` to the method `batch_encode_plus()` to match the functionality of `encode_plus()`. The implementation simply adds the argument in the `encode_plus()` call, so it inherits its implementation and should be compatible with other changes to the `batch_encode... | {
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https://api.github.com/repos/huggingface/transformers/issues/2656 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2656/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2656/comments | https://api.github.com/repos/huggingface/transformers/issues/2656/events | https://github.com/huggingface/transformers/issues/2656 | 555,683,613 | MDU6SXNzdWU1NTU2ODM2MTM= | 2,656 | Using Transformers for a Sequence with Multiple Variables at Each Step | {
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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"
] | 1,580 | 1,585 | 1,585 | NONE | null | ## ❓ Questions & Help
I have sequence data which I want to classify and predict future sequence. However, I know that there are a few additional features which aso affect the subsequent values, each to a different extent. So I have multiple features for each step of input sequence. However, the output sequence can... | {
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https://api.github.com/repos/huggingface/transformers/issues/2655 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2655/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2655/comments | https://api.github.com/repos/huggingface/transformers/issues/2655/events | https://github.com/huggingface/transformers/pull/2655 | 555,683,391 | MDExOlB1bGxSZXF1ZXN0MzY3NTgxMDA4 | 2,655 | Fix AutoModelForQuestionAnswering for Roberta | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2655?src=pr&el=h1) Report\n> Merging [#2655](https://codecov.io/gh/huggingface/transformers/pull/2655?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/babd41e7fa07bdd764f8fe91c33469046ab7dbd1?src=pr&el=desc) will **n... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | When using `AutoModelForQuestionAnswering()` to load a Roberta model, we are currently instantiating a `BertForQuestionAnswering` class. This is happening because `RobertaConfig` is an instance of `BertConfig` (due to inheritance) and there's no other mapping for Roberta in here:
https://github.com/huggingface/trans... | {
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https://api.github.com/repos/huggingface/transformers/issues/2654 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2654/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2654/comments | https://api.github.com/repos/huggingface/transformers/issues/2654/events | https://github.com/huggingface/transformers/issues/2654 | 555,680,863 | MDU6SXNzdWU1NTU2ODA4NjM= | 2,654 | Add keyword arguments to batch_encode_plus() to match encode_plus() | {
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"This should require adding a simple `**kwargs` at the end of \r\n\r\nhttps://github.com/huggingface/transformers/blob/f1e8a51f08eeecacf0cde33d40702d70c737003b/src/transformers/tokenization_utils.py#L977"
] | 1,580 | 1,582 | 1,582 | NONE | null | ## 🚀Consistent Keyword arguments for batch_encode_plus() to match encode_plus()
Currently, features such as `return_special_tokens_mask` that are available for the `encode_plus()` method are not available for `batch_encode_plus()`. It would be nice if all keyword arguments worked in a similar fashion.
## Motivati... | {
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https://api.github.com/repos/huggingface/transformers/issues/2653 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2653/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2653/comments | https://api.github.com/repos/huggingface/transformers/issues/2653/events | https://github.com/huggingface/transformers/pull/2653 | 555,635,103 | MDExOlB1bGxSZXF1ZXN0MzY3NTQxMjQ1 | 2,653 | Fix token_type_ids for XLM-R | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2653?src=pr&el=h1) Report\n> Merging [#2653](https://codecov.io/gh/huggingface/transformers/pull/2653?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/babd41e7fa07bdd764f8fe91c33469046ab7dbd1?src=pr&el=desc) will **n... | 1,580 | 1,580 | 1,580 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2652 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2652/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2652/comments | https://api.github.com/repos/huggingface/transformers/issues/2652/events | https://github.com/huggingface/transformers/pull/2652 | 555,625,668 | MDExOlB1bGxSZXF1ZXN0MzY3NTMzNDUy | 2,652 | Fix importing unofficial TF models with extra optimizer weights | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2652?src=pr&el=h1) Report\n> Merging [#2652](https://codecov.io/gh/huggingface/transformers/pull/2652?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/babd41e7fa07bdd764f8fe91c33469046ab7dbd1?src=pr&el=desc) will **n... | 1,580 | 1,581 | 1,581 | CONTRIBUTOR | null | Hi:)
I was trying to convert the BERT `tf model` to `torch model`, and tf model has *extra optimizer weights* ([This file](https://drive.google.com/file/d/1mNDA-SNCsnu60wzKVe_Y3k-dq3LoDHB2/view) is the one I've tried to convert).
But it encounters the error, and I've printed the parameters' name in tf model.
<... | {
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https://api.github.com/repos/huggingface/transformers/issues/2651 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2651/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2651/comments | https://api.github.com/repos/huggingface/transformers/issues/2651/events | https://github.com/huggingface/transformers/issues/2651 | 555,285,818 | MDU6SXNzdWU1NTUyODU4MTg= | 2,651 | XLNET SQuAD2.0 Fine-Tuning - What May Have Changed? | {
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"I have been facing the same problem with RoBERTa finetuning for multiple choice QA datasets. I have even tried going back to the older version of transformers (version 2.1.0 from Oct 2019) and re-running my experiments but I am not able to replicate results from before anymore. The loss just varies within a range ... | 1,580 | 1,633 | 1,588 | CONTRIBUTOR | null | ## ❓ Questions & Help
I fine-tuned XLNet_large_cased on SQuAD 2.0 last November 2019 with Transformers V2.1.1 yielding satisfactory results:
```
xlnet_large_squad2_512_bs48
{
"exact": 82.07698138633876,
"f1": 85.898874470488,
"total": 11873,
"HasAns_exact": 79.60526315789474,
"HasAns_f1": 87.260009... | {
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https://api.github.com/repos/huggingface/transformers/issues/2650 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2650/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2650/comments | https://api.github.com/repos/huggingface/transformers/issues/2650/events | https://github.com/huggingface/transformers/issues/2650 | 555,262,879 | MDU6SXNzdWU1NTUyNjI4Nzk= | 2,650 | loss function error when running run_lm_finetuning.py file | {
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"I got the exact same error while trying to finetune BERT with mlm on ENRON emails dataset. This problem doesn't occur in older versions of this repo (before Jan 5th). So perhaps you can try that while they fix this issue?",
"I had your same error. Trying with different block size and batch size, with a certain c... | 1,580 | 1,585 | 1,585 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): BERT
Language I am using the model on (English, Chinese....): Multilingual model (trying to finetune with Bengali)
The problem arise when using:
* [run_lm_finetuning.py] the official example scripts: I wanted to fine tune the mult... | {
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https://api.github.com/repos/huggingface/transformers/issues/2649 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2649/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2649/comments | https://api.github.com/repos/huggingface/transformers/issues/2649/events | https://github.com/huggingface/transformers/issues/2649 | 555,257,914 | MDU6SXNzdWU1NTUyNTc5MTQ= | 2,649 | Using a Model without any pretrained data | {
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"Just don't use the [from_pretrained](https://huggingface.co/transformers/main_classes/model.html#transformers.PreTrainedModel.from_pretrained) method and initialize the class with a config.\r\n```\r\nfrom transformers import BertModel, BertConfig\r\n\r\n#model with pretrained weights\r\nmodel_with_Pretrained = Ber... | 1,580 | 1,682 | 1,580 | NONE | null | ## ❓ Questions & Help
<!-- Sorry for a very basic question. Can I use your library without any pertained data? For example, I want to use a BERT transformer model, but using only my corpus of data. In the docs, I only see examples using pretrained models. Thanks. -->
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https://api.github.com/repos/huggingface/transformers/issues/2648 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2648/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2648/comments | https://api.github.com/repos/huggingface/transformers/issues/2648/events | https://github.com/huggingface/transformers/issues/2648 | 555,243,376 | MDU6SXNzdWU1NTUyNDMzNzY= | 2,648 | run_lm_finetuning.py for GPT2 throw error "Using pad_token, but it is not set yet." | {
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"I am having same error as well. Did you manage to fix it or any other updates?",
"Can you let me know if 6b4c3ee234db010ae2fb0554c0099fbf1f7f1f51 fixes your issue?",
"I encountered this issue and sure enough it is fixed with `6b4c3ee`.\r\n\r\nThanks @julien-c. It's mind blowing that I found the error 15 mins a... | 1,580 | 1,699 | 1,580 | NONE | null | I used the official setting.
```bash
python transformers/examples/run_lm_finetuning.py \
--output_dir=gpt2_q_model \
--model_type=gpt2 \
--model_name_or_path=gpt2 \
--do_train \
--train_data_file=txt/{q_files[0]} \
```
But it says the padding id was not set.
```python
ERROR - transfor... | {
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https://api.github.com/repos/huggingface/transformers/issues/2647 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2647/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2647/comments | https://api.github.com/repos/huggingface/transformers/issues/2647/events | https://github.com/huggingface/transformers/issues/2647 | 555,222,017 | MDU6SXNzdWU1NTUyMjIwMTc= | 2,647 | Question Answering with Japanese | {
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"Hi @Mukei,\r\n\r\nAs far as I know, there is no Transformer-based model fine-tuned for Japanese question answering tasks.\r\nIt is partly due to the scarcity of Japanese QA datasets (like SQuAD) to train the models on.\r\n\r\n(Of course, we do wish to release models for QA, and it is left for our future work.)",
... | 1,580 | 1,586 | 1,586 | NONE | null | ## ❓ Questions & Help
Hi @singletongue,
I am trying to use Question-Answering for Japanese, however I could not find any model trained for that.
I tried with the available models but the results were way off (as expected...).
Any suggestions on available models, or other library that already handle QnA with Japa... | {
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https://api.github.com/repos/huggingface/transformers/issues/2646 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2646/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2646/comments | https://api.github.com/repos/huggingface/transformers/issues/2646/events | https://github.com/huggingface/transformers/issues/2646 | 555,212,360 | MDU6SXNzdWU1NTUyMTIzNjA= | 2,646 | glue.py: AttributeError: 'numpy.str_' object has no attribute 'text_a' | {
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"I think the problem was due to the dataset not being set to (index,example) structure",
"@pacebrian0 Could you post what changes did you make?",
"I decided to use simpletransformers python package, which allows you to train custom datasets.\r\nThe above problem can only be solved by using tensorflow-datasets ... | 1,580 | 1,580 | 1,580 | NONE | null | when I am executing the glue data conversion i.e.
`sequences = glue_convert_examples_to_features(X_train, tokenizer, max_length=MAX_SEQUENCE_LENGTH, task='mrpc')
`
I'm getting this error:
> I0126 11:57:07.862119 16252 glue.py:70] Using label list ['0', '1'] for task mrpc
> I0126 11:57:07.863118 16252 glue.py:7... | {
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https://api.github.com/repos/huggingface/transformers/issues/2645 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2645/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2645/comments | https://api.github.com/repos/huggingface/transformers/issues/2645/events | https://github.com/huggingface/transformers/issues/2645 | 555,187,701 | MDU6SXNzdWU1NTUxODc3MDE= | 2,645 | How to load locally saved tensorflow DistillBERT model | {
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"Please format your code correctly using code tags and not quote tags, and don't use screenshots but post your actual code so that we can copy-paste it and reproduce your errors. https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks",
"Thanks to your response, now it will be c... | 1,580 | 1,580 | 1,580 | NONE | null | I have got tf model for DistillBERT by the following python line
> `import tensorflow as tf
from transformers import DistilBertTokenizer, TFDistilBertModel
tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
model = TFDistilBertModel.from_pretrained('distilbert-base-uncased')
input_ids = ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2644 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2644/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2644/comments | https://api.github.com/repos/huggingface/transformers/issues/2644/events | https://github.com/huggingface/transformers/issues/2644 | 555,164,973 | MDU6SXNzdWU1NTUxNjQ5NzM= | 2,644 | XLNet run_squad.py IndexError: tuple index out of range | {
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"Hi, are you sure you're running on commit babd41e, and that you didn't take the script from this version without updating the library itself? I believe this was patched in 073219b.\r\n\r\nCould you try to install from source `pip install git+https://github.com/huggingface/transformers` and let me know if it fixes ... | 1,580 | 1,580 | 1,580 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): XLNet
Language I am using the model on (English, Chinese....): English (xlnet-base-cased)
The problem arise when using:
* [x] the official example scripts: run_squad.py
* [ ] my own modified scripts: (give details)
The tasks I... | {
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https://api.github.com/repos/huggingface/transformers/issues/2643 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2643/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2643/comments | https://api.github.com/repos/huggingface/transformers/issues/2643/events | https://github.com/huggingface/transformers/issues/2643 | 555,148,887 | MDU6SXNzdWU1NTUxNDg4ODc= | 2,643 | BERT LOSS FUNCTION | {
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"Sure you can do that. Create a class which inherits from [BertForSequenceClassification](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_bert.py#L1122) and overwrite the [forward](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_bert.py#L1134) meth... | 1,579 | 1,614 | 1,594 | NONE | null | My question is that can I use KLDivLoss instead of CrossEntropyLoss when I fine-tune BERT for classification? the reason for that is that I want to pass the weight of each class(e.g for binary classification, instead of 1 or 0 I will pass the probability distribution )
Thank you in advance | {
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https://api.github.com/repos/huggingface/transformers/issues/2642 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2642/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2642/comments | https://api.github.com/repos/huggingface/transformers/issues/2642/events | https://github.com/huggingface/transformers/issues/2642 | 555,131,572 | MDU6SXNzdWU1NTUxMzE1NzI= | 2,642 | Scrambled dimensions on output of forward pass | {
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"Hi! There was a mistake with the re-arrangement of the input embeddings inside the forward method of XLNet. I've fixed it with f09f42d.\r\n\r\nConcerning the issue with `d_model=25` and `n_heads=5`, this is due to the model dimension being an odd number which doesn't fare well with [`torch.arange` leveraging the ... | 1,579 | 1,596 | 1,596 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): XLNet
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [ ] the official example scripts: (give details)
* [X] my own modified scripts: see attached minimum working example.
The t... | {
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https://api.github.com/repos/huggingface/transformers/issues/2641 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2641/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2641/comments | https://api.github.com/repos/huggingface/transformers/issues/2641/events | https://github.com/huggingface/transformers/issues/2641 | 555,081,290 | MDU6SXNzdWU1NTUwODEyOTA= | 2,641 | ImportError: cannot import name 'TFDistilBertModel' | {
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"Does the following import work?\r\n`from transformers.modeling_tf_distilbert import TFDistilBertModel`\r\nand what is the output of:\r\n```\r\nfrom transformers.file_utils import is_tf_available\r\nis_tf_available()\r\n```",
"Thank you for response. Thanks! \r\n\r\n> Does the following import work?\r\n> `from tr... | 1,579 | 1,599 | 1,580 | NONE | null | ```
import tensorflow as tf
from transformers import DistilBertTokenizer, TFDistilBertModel
tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
model = TFDistilBertModel.from_pretrained('distilbert-base-uncased')
input_ids = tf.constant(tokenizer.encode("Hello, my dog is cute"))[None, :] ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2640 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2640/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2640/comments | https://api.github.com/repos/huggingface/transformers/issues/2640/events | https://github.com/huggingface/transformers/issues/2640 | 555,071,161 | MDU6SXNzdWU1NTUwNzExNjE= | 2,640 | batch_encode_plus not working for GPT2, OpenAI, TransfoXL when returning PyTorch tensors | {
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"The problem lies here\r\n\r\nhttps://github.com/huggingface/transformers/blob/babd41e7fa07bdd764f8fe91c33469046ab7dbd1/src/transformers/tokenization_utils.py#L1003-L1006\r\n\r\nsince for these tokenizers `self.pad_token_id` is None.",
"Still having this issue running the above script :-(\r\nAny ideas?\r\n\r\nEnv... | 1,579 | 1,619 | 1,580 | COLLABORATOR | null | ## 🐛 Bug
`batch_encode_plus` does not work on GPT2, OpenAI, and TransfoXL when returning PyTorch tensors. Note that the code does work when leaving out the `return_tensors` argument. In that case, the output of `encoded` looks normal.
## To Reproduce
```python
from transformers import *
TOKENIZERS = {
... | {
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https://api.github.com/repos/huggingface/transformers/issues/2639 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2639/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2639/comments | https://api.github.com/repos/huggingface/transformers/issues/2639/events | https://github.com/huggingface/transformers/issues/2639 | 555,069,654 | MDU6SXNzdWU1NTUwNjk2NTQ= | 2,639 | AttributeError: 'Tensor' object has no attribute 'transpose' | {
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"It seems you're passing TensorFlow variables to a PyTorch model. The TensorFlow equivalent of `XLNetModel` is `TFXLNetModel`.",
"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"
] | 1,579 | 1,585 | 1,585 | NONE | null | ## ❓ Questions & Help
<!-- error comes from modeling_xlnet.py file -->
i get this error :
---------------------------------------------------------------------------
```
AttributeError Traceback (most recent call last)
<ipython-input-80-01c16e13fe9a> in <module>()
----> 1 get_ip... | {
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https://api.github.com/repos/huggingface/transformers/issues/2638 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2638/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2638/comments | https://api.github.com/repos/huggingface/transformers/issues/2638/events | https://github.com/huggingface/transformers/issues/2638 | 555,030,516 | MDU6SXNzdWU1NTUwMzA1MTY= | 2,638 | Get Warning Message: Unable to convert output to tensors format pt | {
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"It seems that you are loading a tensorflow model, which you incorrectly call pytorch_model. The reason that the function doesn't work, though, is probably because you don't have pytorch installed and only tensorflow. Convert to tensorflow tenors instead ",
"This issue has been automatically marked as stale becau... | 1,579 | 1,585 | 1,585 | NONE | null | I am running the following code:
```
from transformers.modeling_tf_bert import TFBertForSequenceClassification
pytorch_model = TFBertForSequenceClassification.from_pretrained('./save/')
# Quickly test a few predictions - MRPC is a paraphrasing task, let's see if our model learned the task
sentence_0 = "This r... | {
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https://api.github.com/repos/huggingface/transformers/issues/2637 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2637/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2637/comments | https://api.github.com/repos/huggingface/transformers/issues/2637/events | https://github.com/huggingface/transformers/pull/2637 | 554,992,078 | MDExOlB1bGxSZXF1ZXN0MzY3MDQ2OTU4 | 2,637 | Add AutoModelForPreTraining | {
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This class can be used for instance to convert between an original PyTorch and a TF2.0 models while being sure that all the pretrained weig... | {
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https://api.github.com/repos/huggingface/transformers/issues/2636 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2636/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2636/comments | https://api.github.com/repos/huggingface/transformers/issues/2636/events | https://github.com/huggingface/transformers/issues/2636 | 554,989,462 | MDU6SXNzdWU1NTQ5ODk0NjI= | 2,636 | Gradient checkpointing with GPT2DoubleHeadsModel | {
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"I think I figured this out, it looks like I'll have to change the outputs returned by `Block` to be tuples instead of lists:\r\n\r\nhttps://github.com/huggingface/transformers/blob/babd41e7fa07bdd764f8fe91c33469046ab7dbd1/src/transformers/modeling_gpt2.py#L238\r\n\r\ni.e., change the above to `return tuple(outputs... | 1,579 | 1,593 | 1,590 | NONE | null | ## ❓ Questions & Help
I've been trying to fine-tune `GPT2DoubleHeadsModel` using `gpt2-large` and `gpt2-xl` on the [Topical-Chat](https://github.com/alexa/alexa-prize-topical-chat-dataset) dataset.
I'm finding that loading even a single example into memory is difficult with the larger versions of GPT-2. I found [... | {
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https://api.github.com/repos/huggingface/transformers/issues/2635 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2635/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2635/comments | https://api.github.com/repos/huggingface/transformers/issues/2635/events | https://github.com/huggingface/transformers/pull/2635 | 554,984,937 | MDExOlB1bGxSZXF1ZXN0MzY3MDQxMTIy | 2,635 | Improving generation | {
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"It would be great if this PR could handle the padding index for the models that do not have one. For example, GPT-2 doesn't have a padding index and therefore can't use the `generate` method, nor can it use the `batch_encode_plus` method.",
"PR #2885 added the proposed changes."
] | 1,579 | 1,651 | 1,582 | MEMBER | null | Fix #2554
TODO:
- add tests on generation
TODO potential:
- this PR could be used to fix #2415 and fix #2482 as well
- add TF 2.0 support for generation | {
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https://api.github.com/repos/huggingface/transformers/issues/2634 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2634/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2634/comments | https://api.github.com/repos/huggingface/transformers/issues/2634/events | https://github.com/huggingface/transformers/pull/2634 | 554,965,890 | MDExOlB1bGxSZXF1ZXN0MzY3MDI1NzE0 | 2,634 | AutoModels Documentation | {
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https://api.github.com/repos/huggingface/transformers/issues/2633 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2633/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2633/comments | https://api.github.com/repos/huggingface/transformers/issues/2633/events | https://github.com/huggingface/transformers/issues/2633 | 554,898,766 | MDU6SXNzdWU1NTQ4OTg3NjY= | 2,633 | Details on T5's current integration status | {
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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"
] | 1,579 | 1,585 | 1,585 | MEMBER | null | Hi all,
Regarding Google's T5 model, here is a quick summary of the status:
* the core model is in the library and some people have started to use it, but:
- while the operations are identical or very similar (einsum vs. matmul), there is quite a significantly higher relative error between this model's PT hidden... | {
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https://api.github.com/repos/huggingface/transformers/issues/2632 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2632/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2632/comments | https://api.github.com/repos/huggingface/transformers/issues/2632/events | https://github.com/huggingface/transformers/pull/2632 | 554,783,628 | MDExOlB1bGxSZXF1ZXN0MzY2ODc1ODEy | 2,632 | Add FlauBERT: Unsupervised Language Model Pre-training for French | {
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"Hi, I don't really know how it happened but I was denied push access on your repository while patching the failing FlauBERT bug. Instead I pushed to a new branch `flaubert` on this remote (huggingface/transformers), and I'm opening a pull request with your changes.\r\n\r\nYou're still the author of the commit.",
... | 1,579 | 1,580 | 1,580 | CONTRIBUTOR | null | This PR adds [FlauBERT](https://github.com/getalp/Flaubert). Most of the code is derived from XLM (there are some new features in FlauBERT such as `pre_norm` and `layerdrop`).
`make test` had 1 failure related to BERT and not to FlauBERT:
> [gw0] FAILED tests/test_configuration_auto.py::AutoConfigTest::test_patte... | {
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https://api.github.com/repos/huggingface/transformers/issues/2631 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2631/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2631/comments | https://api.github.com/repos/huggingface/transformers/issues/2631/events | https://github.com/huggingface/transformers/issues/2631 | 554,753,717 | MDU6SXNzdWU1NTQ3NTM3MTc= | 2,631 | CamembertTokenizer cannot be pickled | {
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"Did you look into just calling `save_pretrained()` on your CamembertTokenizer (and not include it inside your `MyModelCamembert`)?",
"No I did not try that because my model class is quite a big class that extends `nn.Module` and not `PreTrainedModel`. \r\nI'm just surprised that saving the model it works for Ber... | 1,579 | 1,579 | 1,579 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Camembert
Language I am using the model on (English, Chinese....): French
The problem arise when using my own modified scripts:
I have a nn.Module and, within this module, I store the tokenizers
I can normally save these to... | {
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https://api.github.com/repos/huggingface/transformers/issues/2630 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2630/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2630/comments | https://api.github.com/repos/huggingface/transformers/issues/2630/events | https://github.com/huggingface/transformers/issues/2630 | 554,735,095 | MDU6SXNzdWU1NTQ3MzUwOTU= | 2,630 | Pad token for GPT2 and OpenAIGPT models | {
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"Padding tokens were not used during the pre-training of GPT and GPT-2, therefore they have none. It shouldn't matter as when doing padding, you should specify an [attention mask](https://huggingface.co/transformers/glossary.html#attention-mask) to your model so that it doesn't attend to padded indices, therefore i... | 1,579 | 1,705 | 1,583 | NONE | null | ## ❓ Questions & Help
I noticed that out of all the models `pad_token` is not set for only `OpenAIGPTModel` and `GPT-2Model`.
I get a warning: `Using pad_token, but it is not set yet.` and `pad_token_id` is `None`
Is there any specific reason why is that so?
If not, what is the appropriate padding token to b... | {
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https://api.github.com/repos/huggingface/transformers/issues/2629 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2629/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2629/comments | https://api.github.com/repos/huggingface/transformers/issues/2629/events | https://github.com/huggingface/transformers/issues/2629 | 554,688,657 | MDU6SXNzdWU1NTQ2ODg2NTc= | 2,629 | Question about Architecture of BERT for QA | {
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"Please don't post screenshots. Use code tags instead and preferably post reproducible code.\r\n\r\nhttps://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further... | 1,579 | 1,585 | 1,585 | NONE | null | ## ❓ Questions & Help
I have a question about the architecture of Bert for QA.
In Bert forward function
``` python
class BertForQuestionAnswering(BertPreTrainedModel):
def __init__(self, config):
super(BertForQuestionAnswering, self).__init__(config)
self.num_labels = config.num_labels
... | {
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https://api.github.com/repos/huggingface/transformers/issues/2628 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2628/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2628/comments | https://api.github.com/repos/huggingface/transformers/issues/2628/events | https://github.com/huggingface/transformers/issues/2628 | 554,675,763 | MDU6SXNzdWU1NTQ2NzU3NjM= | 2,628 | Albert on QQP inference | {
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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"
] | 1,579 | 1,585 | 1,585 | NONE | null | While using Albert model trained on QQP data, i am using following code for inference.
How to manage two sentences and two labels (0,1) like QQP?
ffrom transformers import AlbertTokenizer, AlbertForSequenceClassification
import torch
tokenizer = AlbertTokenizer.from_pretrained('albert-base-v2')
model = Alber... | {
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https://api.github.com/repos/huggingface/transformers/issues/2627 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2627/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2627/comments | https://api.github.com/repos/huggingface/transformers/issues/2627/events | https://github.com/huggingface/transformers/issues/2627 | 554,470,324 | MDU6SXNzdWU1NTQ0NzAzMjQ= | 2,627 | Why does the hidden state of the same input token change every time I call the same GPT2 model? | {
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"Hello,\r\n\r\nThe hidden state vectors doesn't seem to change with fixed input and token when I use the Hugging Face pre-trained GPT2 model, but in my case, I made and trained my own GPT2 model by doing the following:\r\n```python\r\n\r\nbptt = 1024\r\nbatch_size = 1\r\nlog_int = 50\r\nnlayer = 6\r\n\r\n# Define d... | 1,579 | 1,579 | 1,579 | NONE | null | Hello,
Say I fixed my input to the GPT2 model:
```python
input_ids = test_i[:,0]
input_ids = torch.tensor(input_ids.tolist()).unsqueeze(0)
```
Then I try to retrieve the hidden state vector of the last token:
```python
tst_hidden_states = best_model(input_ids)[3][1][0, (test_i.size()[0] - 1), :].detach()
... | {
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https://api.github.com/repos/huggingface/transformers/issues/2626 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2626/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2626/comments | https://api.github.com/repos/huggingface/transformers/issues/2626/events | https://github.com/huggingface/transformers/issues/2626 | 554,437,093 | MDU6SXNzdWU1NTQ0MzcwOTM= | 2,626 | BertModel output the same embedding during Evaluation | {
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"Wherees the `forward()` function of your `BertTextEncoderFactory(nn.Module)`?",
"It problem is caused by the data.",
"@nimning hi, i got stuck on the same issue exactly the same as you mentioned, cloud you please tell me how did you solve this problem"
] | 1,579 | 1,594 | 1,581 | NONE | null | ## ❓ Questions & Help
During evaluation, my text model outputs the same embedding regardless of the token id. The following is my model.
```
class BertTextEncoderFactory(nn.Module):
def __init__(self, embedding_dim = 256, model_name_or_path = None, backbone ='bert'):
super(BertTextEncoderFactory, s... | {
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"Please format your post correctly by using code blocks. https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks",
"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 contri... | 1,579 | 1,586 | 1,586 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Bert
Language I am using the model on (English, Chinese....):
English
The problem arise when using:
* [ ] the official example scripts: (give details)
* [x] my own modified scripts: (give details)
```python
import sys
from trans... | {
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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",
"Wait, is this just the end? Am also interested in doing this",
"This [comment](https://github.com/huggingface/transformers/issues/473... | 1,579 | 1,593 | 1,585 | NONE | null | ## ❓ Questions & Help
In TensorFlow 2, what is the recommended way to merge `TFDistilBertForSequenceClassification` (or any other Transformer model) with another `tf.keras` model?
In other words, I'd like to do something like this:
```
merged_out = keras.layers.concatenate([other_model.output, distilbert_mode... | {
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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"
] | 1,579 | 1,586 | 1,586 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Bert large uncased SQUAD /finetuned on SQUAD2.0 and my dataset
Language I am using the model on (English, Chinese....):
English
The problem arise when using:
* [x ] the official example scripts: (give details)
```python
from tran... | {
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"I believe this was fixed recently. Could you please try installing from source `pip install git+https://github.com/huggingface/transformers` and let me know if it fixes the bug?",
"I executed the above command and it worked.\r\nThanks",
"Glad it worked.",
"I found a similar bug even with the latest version b... | 1,579 | 1,636 | 1,579 | NONE | null | ## 🐛 Bug
<!-- Important information -->
I tried to add new tokens in vocabulary using tokenizer.add_tokens() and then called model() according to the code given in `BertForMaskedLM` class definition. The code is given below:
```
from transformers import BertForMaskedLM, BertTokenizer
import torch
tokenize... | {
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https://api.github.com/repos/huggingface/transformers/issues/2621 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2621/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2621/comments | https://api.github.com/repos/huggingface/transformers/issues/2621/events | https://github.com/huggingface/transformers/issues/2621 | 554,187,568 | MDU6SXNzdWU1NTQxODc1Njg= | 2,621 | Documentation markup for model descriptions | {
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"Hi! Indeed there were quite a few issues with the documentation. #2532 was merged this morning, and hopefully fixes all these issues!\r\n\r\nWould love your feedback on the new documentation (be sure to refresh your cache to see the new doc on https://huggingface.co/transformers). ",
"Ah, sorry, didn't check the... | 1,579 | 1,585 | 1,585 | COLLABORATOR | null | ## 🐛 Bug
Looking at [the documentation](https://huggingface.co/transformers/model_doc/bert.html#bertforsequenceclassification), it seems something went wrong in markup land. In some models (but not all, e.g. BertModel, BertForMaskedLM, BertForNextSentencePrediction), the model description (i.e. the first paragraph)... | {
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https://api.github.com/repos/huggingface/transformers/issues/2620 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2620/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2620/comments | https://api.github.com/repos/huggingface/transformers/issues/2620/events | https://github.com/huggingface/transformers/issues/2620 | 554,184,245 | MDU6SXNzdWU1NTQxODQyNDU= | 2,620 | Document which heads are pretrained and which aren't | {
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"I'm certain the random initialisation occurs when we instantiate the class (See `BertPreTrainedModel.init_weights()`)",
"> I'm certain the random initialisation occurs when we instantiate the class (See `BertPreTrainedModel.init_weights()`)\r\n\r\nYou're right. It gets a bit complicated to track down though.\r\n... | 1,579 | 1,585 | 1,585 | COLLABORATOR | null | ## 🚀 Feature
I was going through the documentation and I realised I never thought about the different heads in much detail (I always start from the base model and built on top of that). Now that I did, I wonder whether users (mistakenly?) assume that models such as `BertForQuestionAnswering` have a pretrained head.... | {
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https://api.github.com/repos/huggingface/transformers/issues/2619 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2619/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2619/comments | https://api.github.com/repos/huggingface/transformers/issues/2619/events | https://github.com/huggingface/transformers/issues/2619 | 554,140,805 | MDU6SXNzdWU1NTQxNDA4MDU= | 2,619 | Adding scibert in the list of pre-trained models? | {
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"It would be nice if AllenAI uploaded their models to [the user hub](https://huggingface.co/models). That would allow you to simply load the models like `.from_pretrained('allenai/scibert-scivocab-uncased')`. Perhaps you can open an issue on their repository and ask whether that is possible. It might be too much wo... | 1,579 | 1,579 | 1,579 | NONE | null | # 🌟New model addition
## Model description
Would it be possible/is it in the pipeline to add SCIBERT as one of the pre-trained models for Bert? Could be as simple as adding it to the `BERT_PRETRAINED_MODEL_ARCHIVE_MAP`.
## Open Source status
Scibert is available on its own repository (https://github.com/al... | {
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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"
] | 1,579 | 1,585 | 1,585 | NONE | null | Hi
I greatly appreciate to add also possibilities to train the summarization codes from scratch. I see only evaluation part in the codes. Does this also work for training?
thanks a lot for your response.
Kind regards
Rabeeh | {
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"`model.eval()` is a PyTorch directive. It will disable dropout/norm, as you point out. On top of that, though, you'd also set the `no_grad` parameter so that weights are not updated.\r\n\r\nTypically, your code'd look like this for inference/evaluation/testing.\r\n\r\n```python\r\nmodel.eval()\r\nwith torch.no_gra... | 1,579 | 1,610 | 1,590 | NONE | null | ## 🐛 Bug
Using any of the TF models I am unable to set the **.eval()** or **.train()** properties. In addition, when loading from a pre-trained path (which the documentation seems to imply would mean that the models will be set to eval mode) I see non deterministic outputs given the same input indicating the models... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"Any clue about how to integrate that into a BERT model?"
] | 1,579 | 1,588 | 1,585 | NONE | null | # 🌟New model addition
## Model description
<!-- Important information -->
## Open Source status
* [x] the model implementation is available: https://github.com/facebookresearch/adaptive-span
* [x] the model weights are available: get_pretrained.sh
* [x] who are the authors: Facebook Research
## Additi... | {
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https://api.github.com/repos/huggingface/transformers/issues/2615 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2615/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2615/comments | https://api.github.com/repos/huggingface/transformers/issues/2615/events | https://github.com/huggingface/transformers/issues/2615 | 553,823,698 | MDU6SXNzdWU1NTM4MjM2OTg= | 2,615 | Question answering pipeline fails with long context | {
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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 also have this issue",
"This seems to be fixed when limiting the batch size."
] | 1,579 | 1,594 | 1,585 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Question Answering Pipeline / Distilbert
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [x] the official example scripts: (give details): Based on the sample pipeline code form here: https... | {
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https://api.github.com/repos/huggingface/transformers/issues/2614 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2614/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2614/comments | https://api.github.com/repos/huggingface/transformers/issues/2614/events | https://github.com/huggingface/transformers/issues/2614 | 553,677,077 | MDU6SXNzdWU1NTM2NzcwNzc= | 2,614 | Missing module "startlette" when calling transformers-cli | {
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"Hi @tailaiw, thanks for reporting the issue.\r\n\r\nCan you try to update to the latest version of transformers ? it should have been fixed in 5004d5af42c61c91d5df07aa139d37599ceb6215.\r\n\r\nFeel free to reopen if its not the case !"
] | 1,579 | 1,581 | 1,581 | NONE | null | Calling `transformers-cli` in terminal returns error ``ModuleNotFoundError: No module named 'starlette'``.
I assume starlette should be added into dependencies in setup.py and it will be a quick fix. | {
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https://api.github.com/repos/huggingface/transformers/issues/2613 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2613/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2613/comments | https://api.github.com/repos/huggingface/transformers/issues/2613/events | https://github.com/huggingface/transformers/issues/2613 | 553,676,558 | MDU6SXNzdWU1NTM2NzY1NTg= | 2,613 | XLnet memory usage for long sequences | {
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] | 1,579 | 1,585 | 1,585 | NONE | null | ## ❓ Questions & Help
Hello,
I have some questions regarding how the XLnet memory and output work in this implementation.
1. As it's been mentioned before, by default, XLnet doesn't use memory. So, how is this possible that it accepts long sequences as input (in other words, why there isn't any limit on the numb... | {
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