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https://api.github.com/repos/huggingface/transformers/issues/1911 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1911/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1911/comments | https://api.github.com/repos/huggingface/transformers/issues/1911/events | https://github.com/huggingface/transformers/pull/1911 | 526,957,579 | MDExOlB1bGxSZXF1ZXN0MzQ0MzI2NjIw | 1,911 | Fix GPT2 docstring from #1906 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1911?src=pr&el=h1) Report\n> Merging [#1911](https://codecov.io/gh/huggingface/transformers/pull/1911?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/26db31e0c09a8b5e1ca7a61c454b159eab9d86be?src=pr&el=desc) will **n... | 1,574 | 1,574 | 1,574 | CONTRIBUTOR | null | Fixes #1906
Changes the GPT2 Tokenizer's docstrings to correctly explain the reason for `add_prefix_space` parameter | {
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https://api.github.com/repos/huggingface/transformers/issues/1910 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1910/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1910/comments | https://api.github.com/repos/huggingface/transformers/issues/1910/events | https://github.com/huggingface/transformers/issues/1910 | 526,751,179 | MDU6SXNzdWU1MjY3NTExNzk= | 1,910 | Bart Tokenizer treat symbols in a word as a new word. | {
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"Hi, this is due to the original BERT's tokenization. You can try it using the [google-research's implementation](https://github.com/google-research/bert):\r\n\r\n```py\r\nraw_text = 'text with percentage%'\r\ntokenizer = tokenization.FullTokenizer(vocab_file=vocab_file, do_lower_case=True)\r\ntokens = tokenizer.to... | 1,574 | 1,575 | 1,575 | NONE | null | ## 🐛 Bug
<!-- Important information -->
The model I am using is Bart:
The problem arises when using:
* [ ] `tokenizer.encode`
* [ ] `tokenizer.decode`
The tasks I am working on is:
* [ ] Encode a string, then decode it back.
## To Reproduce
```
import torch
from transformers import BertTokenizer
... | {
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https://api.github.com/repos/huggingface/transformers/issues/1909 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1909/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1909/comments | https://api.github.com/repos/huggingface/transformers/issues/1909/events | https://github.com/huggingface/transformers/issues/1909 | 526,689,923 | MDU6SXNzdWU1MjY2ODk5MjM= | 1,909 | Passing inputs to TFGPT2LMHeadModel results in error: 'TensorSliceDataset' object has no attribute 'shape' | {
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"Hi! You can simply use `tf.constant` to build your input tensors, like this:\r\n\r\n```py\r\nraw_text = \"Here comes the sun\"\r\ntokens = tokenizer.encode(raw_text, add_special_tokens=False)\r\ninputs = {'input_ids': tf.constant(tokens)}\r\noutputs = model(inputs)\r\n```\r\n\r\nYou can use datasets when using bui... | 1,574 | 1,580 | 1,580 | NONE | null | ## 🐛 Bug
Model I am using (Bert, XLNet....): `TFGPT2LMHeadModel`
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)
```
import tensorflow as tf
from transformers... | {
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https://api.github.com/repos/huggingface/transformers/issues/1908 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1908/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1908/comments | https://api.github.com/repos/huggingface/transformers/issues/1908/events | https://github.com/huggingface/transformers/issues/1908 | 526,686,571 | MDU6SXNzdWU1MjY2ODY1NzE= | 1,908 | Training transformer XL from scratch with my own dataset | {
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"I think yes, \r\nJust load the model (class) and then start training. As it is mentioned [here](https://huggingface.co/transformers/model_doc/transformerxl.html#transformers.TransfoXLModel), model classes are just a PyTorch torch.nn.Module sub-class.\r\n\r\n> This model is a PyTorch torch.nn.Module sub-class. Use ... | 1,574 | 1,621 | 1,574 | NONE | null | ## ❓ Questions & Help
Is it possible to train a transformer XL model from scratch with my own dataset?
Just initialize the model with default params and compile & fit the model?
<!-- A clear and concise description of the question. -->
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https://api.github.com/repos/huggingface/transformers/issues/1907 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1907/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1907/comments | https://api.github.com/repos/huggingface/transformers/issues/1907/events | https://github.com/huggingface/transformers/issues/1907 | 526,617,266 | MDU6SXNzdWU1MjY2MTcyNjY= | 1,907 | lm_fine-tuning on small dataset of 3 documents | {
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"How do you know you have exact identical `pytorch_model.bin` files? Do you just compare file sizes? IF so, it is not a qualified method just because weights usually are just float numbers and they (almost) always occupy same size on the disk. You can compare the hashes of files to make sure.",
"Yes, I just thoug... | 1,574 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi,
I am trying to use [run_lm_finetuning.py](https://github.com/huggingface/transformers/blob/master/examples/run_lm_finetuning.py) on a sample dataset [here](https://github.com/dmlc/gluon-nlp/blob/master/scripts/bert/sample_text.tx... | {
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https://api.github.com/repos/huggingface/transformers/issues/1906 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1906/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1906/comments | https://api.github.com/repos/huggingface/transformers/issues/1906/events | https://github.com/huggingface/transformers/issues/1906 | 526,613,213 | MDU6SXNzdWU1MjY2MTMyMTM= | 1,906 | Documentation error in GPT2Tokenizer | {
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"According to the code (https://github.com/huggingface/transformers/blob/master/transformers/tokenization_gpt2.py#L183) the docstring is incomplete. \r\n\r\nThe `add_prefix_space` parameter should be passed to `tokenizer.tokenize()` as well as `tokenizer.encode()` or `tokenizer.decode()`.\r\n\r\nAs well, the docstr... | 1,574 | 1,574 | 1,574 | CONTRIBUTOR | null | Documentation page:
https://huggingface.co/transformers/model_doc/gpt2.html#transformers.GPT2Tokenizer
Code place:
https://github.com/huggingface/transformers/blob/d7d36181fdefdabadc53adf51bed4a2680f5880a/transformers/tokenization_gpt2.py#L112-L113
This phrase:
> Otherwise, this tokenizer encode and decode metho... | {
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https://api.github.com/repos/huggingface/transformers/issues/1905 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1905/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1905/comments | https://api.github.com/repos/huggingface/transformers/issues/1905/events | https://github.com/huggingface/transformers/issues/1905 | 526,599,866 | MDU6SXNzdWU1MjY1OTk4NjY= | 1,905 | run_summarization_finetuning.py | {
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"I think so. The script called `run_summarization_finetuning.py` has the goal of extracting text summary given as input a text document. This code shows how to fine-tune a text summarizer model (called **BertSum**) with two different datasets: CNN and Daily Mail.\r\n\r\n> ## Questions & Help\r\n> Hi\r\n> Does your... | 1,574 | 1,580 | 1,580 | CONTRIBUTOR | null | ## ❓ Questions & Help
Hi
Does your code run_summarization_finetuning.py implement the abstractive summarization approach described in "Text summarization with pretrained encoders." by Liu, Yang, and Mirella Lapata?
Thanks
<!-- A clear and concise description of the question. -->
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https://api.github.com/repos/huggingface/transformers/issues/1904 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1904/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1904/comments | https://api.github.com/repos/huggingface/transformers/issues/1904/events | https://github.com/huggingface/transformers/issues/1904 | 526,553,318 | MDU6SXNzdWU1MjY1NTMzMTg= | 1,904 | Typo in Documentation for GPT2LM Output "past" | {
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"Yes, feel free to open a PR to fix this Patrick ;-)"
] | 1,574 | 1,577 | 1,577 | MEMBER | null | I think the described output shape for "past" for GPT-2 is wrong.
In:
[https://github.com/huggingface/transformers/blob/0cdfcca24b5739e25b584c05b866baa19ea382ef/transformers/modeling_gpt2.py#L332](url)
it says the output shape of each key, value tensor in each self attention layer is
``(batch_size, num_heads, sequ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1903 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1903/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1903/comments | https://api.github.com/repos/huggingface/transformers/issues/1903/events | https://github.com/huggingface/transformers/pull/1903 | 526,487,351 | MDExOlB1bGxSZXF1ZXN0MzQzOTQyMjc3 | 1,903 | Valohai integration | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1903?src=pr&el=h1) Report\n> Merging [#1903](https://codecov.io/gh/huggingface/transformers/pull/1903?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0cdfcca24b5739e25b584c05b866baa19ea382ef?src=pr&el=desc) will **n... | 1,574 | 1,575 | 1,575 | CONTRIBUTOR | null | Huggingface / Transformers Valohai integration
Changes to existing Transformers code:
- Prints Valohai-styled logs (JSON)
Additional info:
- valohai.yaml has most (but not all) parameters used by run_glue.py
- Valohai execution downloads all glue datas by default (still pretty fast). Download script placed in ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1902 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1902/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1902/comments | https://api.github.com/repos/huggingface/transformers/issues/1902/events | https://github.com/huggingface/transformers/pull/1902 | 526,477,413 | MDExOlB1bGxSZXF1ZXN0MzQzOTM0Mjky | 1,902 | Add CamemBERT models to modeling_auto | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1902?src=pr&el=h1) Report\n> Merging [#1902](https://codecov.io/gh/huggingface/transformers/pull/1902?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e70cdf083ddb8bfe298d43e6d70d698a3a2f56d3?src=pr&el=desc) will **d... | 1,574 | 1,574 | 1,574 | CONTRIBUTOR | null | CamemBERT was in autoconfig but not in automodel, this PR aims to correct that. Also first PR here so please tell me if I missed some things :-)
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"Did you check if the methods are in `modeling_utils.py` in your local package?\r\nSee #1837 . As @julien-c said, the version of the lib you use may not be in sync with the scripts you run.\r\nTry to install the lib from `master`:\r\n`pip install git+https://github.com/huggingface/transformers`\r\n",
"The doc you... | 1,574 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
Hi, I'm trying to access the word embeddings layer of Bert multilingual, as I want to take out all tokens not belonging to spanish and add some tokens which are part of this language, with the objective of adapting BERT multilingual to spanish. The thing is, in your documentation you claim that t... | {
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"You don't need to do anything in order to make it predict the next word. That's what it is. But you may consider finetuning it with your own dataset.",
"Hello,\r\n\r\nThank you for your reply.\r\nso the **GPT2DoubleHeadsModel** (NOT GPT2LMHeadModel but the DoubleHeadsModel), without any adjustment on its head, c... | 1,574 | 1,644 | 1,574 | NONE | null | Hello,
According to the HuggingFace Transformer's website (https://huggingface.co/transformers/model_doc/gpt2.html#gpt2doubleheadsmodel), **GPT2DoubleHeadsModel** is the GPT2 Model transformer with a language modelling and a multiple-choice classification head on top e.g. for RocStories/SWAG tasks.
Does this mea... | {
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https://api.github.com/repos/huggingface/transformers/issues/1899 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1899/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1899/comments | https://api.github.com/repos/huggingface/transformers/issues/1899/events | https://github.com/huggingface/transformers/issues/1899 | 526,340,095 | MDU6SXNzdWU1MjYzNDAwOTU= | 1,899 | Classify entities - run_ner script | {
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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"
] | 1,574 | 1,580 | 1,580 | NONE | null | Hello all,
I am just wondering what extra input to the "BertForTokenClassification" if I want to classify the entities TO (PER, LOC ..) . Note that the entities are given in advance. I used run_ner script but it extracts the entities and classify them (the extraction is not needed). I did not get how the script(or t... | {
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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"
] | 1,574 | 1,580 | 1,580 | CONTRIBUTOR | null | https://github.com/huggingface/transformers/blame/master/README.md#L546
I think it's not here to do `scheduler.step` but in epoch loop. | {
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https://api.github.com/repos/huggingface/transformers/issues/1897 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1897/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1897/comments | https://api.github.com/repos/huggingface/transformers/issues/1897/events | https://github.com/huggingface/transformers/issues/1897 | 526,312,104 | MDU6SXNzdWU1MjYzMTIxMDQ= | 1,897 | Distilling GPT2 with gives OOM | {
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"Do you need pretrain distilgpt2 from scratch? You can consider just finetuning it.",
"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"
] | 1,574 | 1,580 | 1,580 | NONE | null | ## ❓ Questions & Help
Distilling GPT2 gives OOM what is the best way to fit both teacher student in single GPU and train?
Tried reducing batch size but that itself results into an error.
File "train.py", line 285, in main
distiller.train()
File "trabsformersexamples\distillation\distiller.py", line 340... | {
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https://api.github.com/repos/huggingface/transformers/issues/1896 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1896/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1896/comments | https://api.github.com/repos/huggingface/transformers/issues/1896/events | https://github.com/huggingface/transformers/issues/1896 | 526,304,569 | MDU6SXNzdWU1MjYzMDQ1Njk= | 1,896 | Tokenizing/Loading Data for GPT-2 (1 example per line) | {
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"Please check this out: https://github.com/huggingface/transformers/issues/1816#issuecomment-554759751\r\nThis finetuning script https://github.com/huggingface/transformers/blob/master/examples/run_lm_finetuning.py and the library do almost everything for you. Thus you don't need to split the text into fixed blocks... | 1,574 | 1,580 | 1,580 | NONE | null | I want to finetune GPT-2 on a dataset that has one example per line, and the examples all have different length. What is the best way to alter the TextDataset class to allow for this? I understand GPT-2 requires fixed length inputs but I'm not sure how to apply the attention mask to achieve this? Also do I need to add ... | {
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"Could you give at least some explanation in the title and the body of your post explaining what fixed or changed? Now it's very vague. ",
"> Could you give at least some explanation in the title and the body of your post explaining what fixed or changed? Now it's very vague.\r\n\r\nSorry about the vagueness, I'l... | 1,574 | 1,578 | 1,578 | CONTRIBUTOR | null | Update https://github.com/huggingface/transformers/blob/master/examples/run_squad.py
Implemented solution from
https://github.com/huggingface/transformers/issues/1837#issuecomment-554206349 | {
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"Indeed, thank you!"
] | 1,574 | 1,574 | 1,574 | CONTRIBUTOR | null | There is an unused argument in `run_lm_finetuning.py`
https://github.com/huggingface/transformers/blob/e70cdf083ddb8bfe298d43e6d70d698a3a2f56d3/examples/run_lm_finetuning.py#L418
Is it forgotten? | {
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https://api.github.com/repos/huggingface/transformers/issues/1893 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1893/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1893/comments | https://api.github.com/repos/huggingface/transformers/issues/1893/events | https://github.com/huggingface/transformers/pull/1893 | 526,261,028 | MDExOlB1bGxSZXF1ZXN0MzQzNzYwOTA5 | 1,893 | Cleanup TPU bits from `run_glue.py` | {
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"Great, thanks @jysohn23 !",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1893?src=pr&el=h1) Report\n> Merging [#1893](https://codecov.io/gh/huggingface/transformers/pull/1893?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/454455c695ff38df1ed3670a43677fdd1a... | 1,574 | 1,574 | 1,574 | COLLABORATOR | null | TPU runner is currently implemented in:
https://github.com/pytorch-tpu/transformers/blob/tpu/examples/run_glue_tpu.py.
We plan to upstream this directly into `huggingface/transformers`
(either `master` or `tpu`) branch once it's been more thoroughly tested. | {
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"We can't help you without more information.\r\nPlease fill in the issues templates required information.",
"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"
] | 1,574 | 1,581 | 1,581 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
The size of tensor a (384) must match the size of tensor b (12) at non-singleton dimension 1.
On passing values to fit function in modelling/bert.py facing above error.
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https://api.github.com/repos/huggingface/transformers/issues/1891 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1891/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1891/comments | https://api.github.com/repos/huggingface/transformers/issues/1891/events | https://github.com/huggingface/transformers/pull/1891 | 526,087,315 | MDExOlB1bGxSZXF1ZXN0MzQzNjAyOTQ5 | 1,891 | fixes issue with unrecognized arguments for AdamW | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1890?src=pr&el=h1) Report\n> Merging [#1890](https://codecov.io/gh/huggingface/transformers/pull/1890?src=pr&el=desc) into [xlnet](https://codecov.io/gh/huggingface/transformers/commit/1b35d05d4b3c121a9740544aa6f884f1039780b1?src=pr&el=desc) will **no... | 1,574 | 1,575 | 1,575 | NONE | null | This fixes the problem described and corrected in https://github.com/huggingface/transformers/issues/831 | {
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https://api.github.com/repos/huggingface/transformers/issues/1889 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1889/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1889/comments | https://api.github.com/repos/huggingface/transformers/issues/1889/events | https://github.com/huggingface/transformers/pull/1889 | 526,035,853 | MDExOlB1bGxSZXF1ZXN0MzQzNTUzOTI2 | 1,889 | explain how to successfully run examples in readme and doc | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1889?src=pr&el=h1) Report\n> Merging [#1889](https://codecov.io/gh/huggingface/transformers/pull/1889?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/454455c695ff38df1ed3670a43677fdd1abcedf3?src=pr&el=desc) will **i... | 1,574 | 1,574 | 1,574 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/1888 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1888/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1888/comments | https://api.github.com/repos/huggingface/transformers/issues/1888/events | https://github.com/huggingface/transformers/issues/1888 | 525,939,353 | MDU6SXNzdWU1MjU5MzkzNTM= | 1,888 | Is there a straightforward way to classify documents at the sentence level, while using surrounding sentences for context? | {
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"Maybe you should start with [XLNet](https://arxiv.org/abs/1906.08237).",
"@iedmrc Thanks, I'm sure that most of these models could do this. I'm looking for guidance on adjusting the architecture of these transformer models to look for context form surrounding sentences to classify the current sentence. XLNetForS... | 1,574 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
I'm curious how one would go about classifying documents at the sentence level using the Sequence Classification classes where the classification of a document's sentence would use other sentences in the document for context.
For example, if a document says, "I truly hate this product. Thank... | {
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https://api.github.com/repos/huggingface/transformers/issues/1887 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1887/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1887/comments | https://api.github.com/repos/huggingface/transformers/issues/1887/events | https://github.com/huggingface/transformers/issues/1887 | 525,927,375 | MDU6SXNzdWU1MjU5MjczNzU= | 1,887 | Using GPU for gpt2-xl | {
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"We have not released a new Pypi/conda version yet, but will do so in the next few days. You can install from source if you want to use GPT2-xl before that!",
"Via docker:\r\nhttps://github.com/huggingface/transformers/blob/master/docker/Dockerfile\r\n\r\nVia pip:\r\nhttps://github.com/huggingface/transformers/bl... | 1,574 | 1,575 | 1,575 | NONE | null | I want to use gpt2-xl using my PC's GPU (NVIDIA GeForce GTX 1070). The usual way to do this is via conda, but it appears that the latest version of gpt-2 is not available for conda. For example, the following installation commands don't work:
```
conda install transformers
conda install git+https://github.com/huggin... | {
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"This should be fixed in #1860 which should be merged shortly"
] | 1,574 | 1,575 | 1,575 | NONE | null | ## 🐛 Bug
This is probably something you already know, but `save_pretrained` for `CamembertTokenizer` seems not working at the moment.
Here is the error message I get:
```
---------------------------------------------------------------------------
OSError Traceback (most rec... | {
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"Hi, there have been a few fixes done on the tokenizers recently that haven't been released on Pypi yet. When I run your script with the library installed from source, I obtain: \r\n\r\n```py\r\n[SEP] 50258\r\n[PAD] 50257\r\nAll special tokens: ['[PAD]', '[SEP]', '<|endoftext|>']\r\nAll special ids: [50257, 50258, ... | 1,574 | 1,574 | 1,574 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): GPT2 Tokenizer
The problem arise when using:
my own modified script: The problem arises when I try to add special tokens to the GPT2 tokenizer, specifically a pad token and a sep token.
The tasks I am working on is:
* [ ] my own ... | {
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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"
] | 1,574 | 1,580 | 1,580 | CONTRIBUTOR | null | Hi,
`logging_steps` parameter defined as `"Log every X updates steps."` but it's been affected by `gradient_accumulation_steps` as follows:
https://github.com/huggingface/transformers/blob/f3386d938348628c91457fc7d8650c223317a053/examples/run_lm_finetuning.py#L243-L254
Therefore, if you, e.g., set logging_steps=... | {
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"I got the same situation. However, when I changed the learning rate to 1e-5, the problem was solved.",
"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"
] | 1,574 | 1,581 | 1,581 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I am trying to stack an LSTM on top of RoBERTa model for binary classification problem
I tried two moods , freezing BERT embedding and Fine-tuning
In case of freezing the embedding I get around 57% F-score compared to regular fine tu... | {
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https://api.github.com/repos/huggingface/transformers/issues/1882 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1882/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1882/comments | https://api.github.com/repos/huggingface/transformers/issues/1882/events | https://github.com/huggingface/transformers/issues/1882 | 525,709,764 | MDU6SXNzdWU1MjU3MDk3NjQ= | 1,882 | XLNetForSequenceClassification and CLS token | {
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"Ok, I found why : the padding is done before the sentence, and not after. "
] | 1,574 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi,
As we can see in the official XLNet code ([https://github.com/zihangdai/xlnet]()), the [SEP] and [CLS] tokens are added before the zero-padding. (in convert_single_sequence() in classifier_utils.py)
(example : "This is my sequenc... | {
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https://api.github.com/repos/huggingface/transformers/issues/1881 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1881/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1881/comments | https://api.github.com/repos/huggingface/transformers/issues/1881/events | https://github.com/huggingface/transformers/pull/1881 | 525,617,419 | MDExOlB1bGxSZXF1ZXN0MzQzMjA0NjU4 | 1,881 | convert list to set in tokenize().split_on_tokens() | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1881?src=pr&el=h1) Report\n> Merging [#1881](https://codecov.io/gh/huggingface/transformers/pull/1881?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f3386d938348628c91457fc7d8650c223317a053?src=pr&el=desc) will **i... | 1,574 | 1,582 | 1,575 | NONE | null | As [issue 1830](https://github.com/huggingface/transformers/issues/1830), I meet the same question
when i add some special_tokens in Tokenizer.
But I think it is property **self.all_special_tokens** that slow the code.
property self.all_special_tokens will **be called so many time** when we added some special toke... | {
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https://api.github.com/repos/huggingface/transformers/issues/1880 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1880/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1880/comments | https://api.github.com/repos/huggingface/transformers/issues/1880/events | https://github.com/huggingface/transformers/issues/1880 | 525,381,645 | MDU6SXNzdWU1MjUzODE2NDU= | 1,880 | question about 'add_prefix_space' of encode method | {
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"Actually, both 616 and 1820 are indices for `my`. The difference lies in the prefix space that was added: in the case that it was not added (1820), it is identified as being the beginning of the sentence or part of a word.\r\n\r\nIn the case that it was added (616), it is identified as being the beginning of a wor... | 1,574 | 1,590 | 1,574 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi, I have a question about the 'add_prefix_space' parameter of encode method. I'll use small gpt2 for example.
> tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
> print(tokenizer.encode("my",add_prefix_space=True)) #616
> prin... | {
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https://api.github.com/repos/huggingface/transformers/issues/1879 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1879/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1879/comments | https://api.github.com/repos/huggingface/transformers/issues/1879/events | https://github.com/huggingface/transformers/issues/1879 | 525,368,726 | MDU6SXNzdWU1MjUzNjg3MjY= | 1,879 | run_squad hangs for small max_seq_length | {
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"Great, thanks for letting us know!"
] | 1,574 | 1,574 | 1,574 | NONE | null | ## 🐛 Bug
I am experimenting with minimal examples to understand how sequences are generated, setting `max_seq_length` very low to trigger document chunking, and I hit this bug:
When `max_seq_length` is smaller than the query, `max_tokens_for_doc` becomes negative causing an infinite loop.
https://github.com/... | {
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https://api.github.com/repos/huggingface/transformers/issues/1878 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1878/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1878/comments | https://api.github.com/repos/huggingface/transformers/issues/1878/events | https://github.com/huggingface/transformers/issues/1878 | 525,346,481 | MDU6SXNzdWU1MjUzNDY0ODE= | 1,878 | Is this a bug? | {
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"duplicated \r\nhttps://github.com/huggingface/transformers/issues/1837#issue-523145270",
"I checked the other comment but did not work. Any idea ? \r\n```\r\n__init__() got an unexpected keyword argument 'num_warmup_steps'\r\n```\r\n",
"Hi, could you specify which versions of Python and Transformers is your en... | 1,574 | 1,576 | 1,574 | NONE | null | Hello,
I tried to import this:
`from transformers import AdamW, get_linear_schedule_with_warmup`
but got error : model not found
but when i did this, it worked:
```
from transformers import AdamW
from transformers import WarmupLinearSchedule as get_linear_schedule_with_warmup
```
however when I set the sc... | {
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https://api.github.com/repos/huggingface/transformers/issues/1877 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1877/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1877/comments | https://api.github.com/repos/huggingface/transformers/issues/1877/events | https://github.com/huggingface/transformers/issues/1877 | 525,330,957 | MDU6SXNzdWU1MjUzMzA5NTc= | 1,877 | Can the HuggingFace GPT2DoubleHeadsModel either for regular language modelling or solving multiple-choice questions? or is it only for solving multiple-choice questions? | {
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According to the HuggingFace Transformer's website (https://huggingface.co/transformers/model_doc/gpt2.html#gpt2doubleheadsmodel), GPT2DoubleHeadsModel is the GPT2 Model transformer with a language modelling and a multiple-choice classification head on top e.g. for RocStories/SWAG tasks.
Does this mean tha... | {
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https://api.github.com/repos/huggingface/transformers/issues/1876 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1876/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1876/comments | https://api.github.com/repos/huggingface/transformers/issues/1876/events | https://github.com/huggingface/transformers/pull/1876 | 525,323,366 | MDExOlB1bGxSZXF1ZXN0MzQyOTM3NzY0 | 1,876 | Mean does not exist in TF2 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1876?src=pr&el=h1) Report\n> Merging [#1876](https://codecov.io/gh/huggingface/transformers/pull/1876?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f3386d938348628c91457fc7d8650c223317a053?src=pr&el=desc) will **i... | 1,574 | 1,576 | 1,575 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/1875 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1875/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1875/comments | https://api.github.com/repos/huggingface/transformers/issues/1875/events | https://github.com/huggingface/transformers/issues/1875 | 525,316,325 | MDU6SXNzdWU1MjUzMTYzMjU= | 1,875 | Clarifications about the Quick-tour of the fine-tuning scripts? | {
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"Hi, what exactly is your task? Is it question answering, sequence classification, language modeling, other?",
"> Hi, what exactly is your task? Is it question answering, sequence classification, language modeling, other?\r\n\r\nHi LysandreJik\r\n\r\nI have two tasks: First one is sequence classification. Second ... | 1,574 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
The [quick tour](https://github.com/huggingface/transformers#quick-tour-of-the-fine-tuningusage-scripts) mentions an example of fine-tuning on different GLUE tasks.
My task/trained model has nothing to do with GLUE tasks, i.e.: I already have a pre-trained pytorch model file and the formatt... | {
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"We would need more information",
"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",
"Also cc @joeddav ",
"Ok, I've reproduced an issue here.\r\n\r\n```python\r\nsentence = ' My favor... | 1,574 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
When experimenting with the fill mask functionality on the fairseq repo I realized there is a disparity with the results I get from huggingface implementation. Wondering if there is a mismatch between the model released here and their latest release.
Thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/1873 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1873/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1873/comments | https://api.github.com/repos/huggingface/transformers/issues/1873/events | https://github.com/huggingface/transformers/pull/1873 | 525,203,965 | MDExOlB1bGxSZXF1ZXN0MzQyODM5Nzk3 | 1,873 | German DistilBERT | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1873?src=pr&el=h1) Report\n> Merging [#1873](https://codecov.io/gh/huggingface/transformers/pull/1873?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f3386d938348628c91457fc7d8650c223317a053?src=pr&el=desc) will **i... | 1,574 | 1,575 | 1,575 | COLLABORATOR | null | Hi,
this PR adds the German DistilBERT to the library 🤗
Thanks to the Hugging Face team (incl. hardware support) the German DistilBERT was trained on 1/2 of the data that was used for training the [German DBMDZ BERT](https://github.com/dbmdz/german-bert) model for ~4 days.
Evaluation on NER tasks (German CoNL... | {
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https://api.github.com/repos/huggingface/transformers/issues/1871 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1871/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1871/comments | https://api.github.com/repos/huggingface/transformers/issues/1871/events | https://github.com/huggingface/transformers/issues/1871 | 525,132,664 | MDU6SXNzdWU1MjUxMzI2NjQ= | 1,871 | Understanding feature creation | {
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"Just to clarify, I am asking this because I originally tried to create a custom vocab/merges files by giving a new path for tokenizer.from_pretrained for my new files. Failure to do so led me to notice that giving a new path for the original files downloaded from S3 also fail in the new path. If I put my custom fi... | 1,574 | 1,581 | 1,581 | NONE | null | ## ❓ Questions & Help
Hi,
I am trying to understand feature creation when using run_lm_finetuning.py. If I let the script download the tokenizer files, everything works fine. If I manually assign a folder for the tokenizer with vocab.json and merges.txt downloaded from Hugging Face, I get an empty dataframe dur... | {
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https://api.github.com/repos/huggingface/transformers/issues/1870 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1870/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1870/comments | https://api.github.com/repos/huggingface/transformers/issues/1870/events | https://github.com/huggingface/transformers/pull/1870 | 524,961,807 | MDExOlB1bGxSZXF1ZXN0MzQyNjQwMjA2 | 1,870 | XLNet for Token classification | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1870?src=pr&el=h1) Report\n> Merging [#1870](https://codecov.io/gh/huggingface/transformers/pull/1870?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f3386d938348628c91457fc7d8650c223317a053?src=pr&el=desc) will **i... | 1,574 | 1,575 | 1,575 | NONE | null | Hi,
this PR adds a XLNet based token classifier for PyTorch `XLNetForTokenClassification` and TensorFlow `TFXLNetForTokenClassification` with unit test that allows performing sequence labeling tasks like NER or PoS tagging.
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https://api.github.com/repos/huggingface/transformers/issues/1869 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1869/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1869/comments | https://api.github.com/repos/huggingface/transformers/issues/1869/events | https://github.com/huggingface/transformers/issues/1869 | 524,921,099 | MDU6SXNzdWU1MjQ5MjEwOTk= | 1,869 | Pre-training a smaller version of BERT on own data | {
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"Hi, you might be interested in freezing some layers rather than initializing a model with only 3 layers. Freezing some layers mean that they won't be affected by the backpropagation.\r\n\r\nIf that's what you're looking for, @BramVanroy's answer may be of help: https://github.com/huggingface/transformers/issues/14... | 1,574 | 1,575 | 1,575 | NONE | null | ## ❓ Questions & Help
Hello,
<!-- A clear and concise description of the question. -->
I want to load the first 3-4 layers of BERT, pre-train those on my own data and then fine-tune the model on the target task. Is this possible?
I took a look at the [run_lm_finetuning.py](https://github.com/huggingface/transfor... | {
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https://api.github.com/repos/huggingface/transformers/issues/1868 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1868/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1868/comments | https://api.github.com/repos/huggingface/transformers/issues/1868/events | https://github.com/huggingface/transformers/pull/1868 | 524,901,118 | MDExOlB1bGxSZXF1ZXN0MzQyNTg5ODk1 | 1,868 | XLNet for Token classification | {
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this PR adds a `TFXLNetForTokenClassification` implementation and unit test that allows to perform sequence labeling tasks like NER or PoS tagging.
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https://api.github.com/repos/huggingface/transformers/issues/1867 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1867/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1867/comments | https://api.github.com/repos/huggingface/transformers/issues/1867/events | https://github.com/huggingface/transformers/issues/1867 | 524,881,347 | MDU6SXNzdWU1MjQ4ODEzNDc= | 1,867 | How to fine-tune BERT on a large training dataset? | {
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"I think you should check out pytorch dataloaders https://pytorch.org/docs/stable/data.html\r\nAlso, gradient accumulation is helpful.",
"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"
... | 1,574 | 1,579 | 1,579 | NONE | null | ## ❓ Questions & Help
Hi,
I want to fine-tune BERT on a large training dataset. With around 1.5million training examples, this is currently consuming around 60GB of RAM. Is there any way to reduce the RAM usage or load the training examples in parts? Thanks!.
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https://api.github.com/repos/huggingface/transformers/issues/1866 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1866/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1866/comments | https://api.github.com/repos/huggingface/transformers/issues/1866/events | https://github.com/huggingface/transformers/issues/1866 | 524,878,431 | MDU6SXNzdWU1MjQ4Nzg0MzE= | 1,866 | BertForTokenClassification for NER . what is the conclusion of this output ? | {
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"Why not just use flair? Flair has integrated BERT.",
"BERT was performing sentence embedding better than Flair(tired all different type of stacked embedding ) but less when compared to USC . Flair had a functionality that gave NER tagging directly . i was expecting the same will would be available in BERT but ... | 1,574 | 1,580 | 1,580 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi ,
Im trying to perform NER using BertForTokenClassification .I saw this sample code in transformers GIT page.
from transformers import BertForTokenClassification
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
... | {
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https://api.github.com/repos/huggingface/transformers/issues/1865 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1865/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1865/comments | https://api.github.com/repos/huggingface/transformers/issues/1865/events | https://github.com/huggingface/transformers/issues/1865 | 524,824,317 | MDU6SXNzdWU1MjQ4MjQzMTc= | 1,865 | Run bert for multi-classification but loss never decrease | {
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"Your copy&pasta is broken. Perhaps Roberto can help you? [Text classification with RoBERTa](https://rsilveira79.github.io/fermenting_gradients/machine_learning/nlp/pytorch/text_classification_roberta/)",
"> Your copy&pasta is broken. Perhaps Roberto can help you? [Text classification with RoBERTa](https://rsilve... | 1,574 | 1,580 | 1,580 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I copy the code in example/run_glue.py for text classification task with bert model. All i change in this code is changed to a multi-classification task. I didn't change the main stream of this code. however, after 80 epoches running, i... | {
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https://api.github.com/repos/huggingface/transformers/issues/1864 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1864/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1864/comments | https://api.github.com/repos/huggingface/transformers/issues/1864/events | https://github.com/huggingface/transformers/issues/1864 | 524,771,067 | MDU6SXNzdWU1MjQ3NzEwNjc= | 1,864 | tensorflow2.0 does not has mean, but reduce mean | {
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"This bug has been reviewed and corrected in this PR #1876!\r\nClose this issue."
] | 1,574 | 1,575 | 1,575 | CONTRIBUTOR | null | ## 🐛 Bug
tensorflow2.0 does not has a mean function but only a reduce_mean().
```
output = tf.mean(hidden_states, axis=1)
```
should be:
```
output = tf.reduce_mean(hidden_states, axis=1)
```
<!-- Important information -->
Model I am using: TFXLMForSequenceClassification with summary_type == 'mean'
Lang... | {
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https://api.github.com/repos/huggingface/transformers/issues/1863 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1863/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1863/comments | https://api.github.com/repos/huggingface/transformers/issues/1863/events | https://github.com/huggingface/transformers/issues/1863 | 524,737,968 | MDU6SXNzdWU1MjQ3Mzc5Njg= | 1,863 | How do I train OpenAIGPTDoubleHeadsModel from scratch? | {
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"You can initialize a model by calling its constructor with a configuration:\r\n\r\n```py\r\nfrom transformers import OpenAIGPTDoubleHeadsModel, OpenAIGPTConfig\r\n\r\nconfig = OpenAIGPTConfig()\r\nmodel = OpenAIGPTDoubleHeadsModel(config)\r\n```",
"Cool, so if I instantiate the model with the default config, it ... | 1,574 | 1,575 | 1,575 | NONE | null | ## ❓ Questions & Help
It looks like I cannot train `OpenAIGPTDoubleHeadsModel` from scratch because it necessarily needs to be initialized using the `from_pretrained()` method. How should I initialize this model to be able to train it from scratch?
As a hack, perhaps I could initialize it using `from_pretrained()... | {
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https://api.github.com/repos/huggingface/transformers/issues/1862 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1862/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1862/comments | https://api.github.com/repos/huggingface/transformers/issues/1862/events | https://github.com/huggingface/transformers/issues/1862 | 524,692,708 | MDU6SXNzdWU1MjQ2OTI3MDg= | 1,862 | save all 12 layers outputs for each token | {
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"Hi, to retrieve all layers you can set the `output_hidden_states` flag to `True` in your model configuration:\r\n\r\n```py\r\nfrom transformers import BertConfig, BertModel\r\n\r\nconfig = BertConfig.from_pretrained(\"bert-base-uncased\")\r\nconfig.output_hidden_states = True\r\nmodel = BertModel.from_pretrained(\... | 1,574 | 1,575 | 1,575 | NONE | null | Hi,
I am following [this](https://mccormickml.com/2019/05/14/BERT-word-embeddings-tutorial/) post to create sentence vectors from the last 4 layers or sum all 12 layers and so on.
Considering a given document has 10,000 tokens and I am planning to use "bert_base_uncased", I was wondering how to save all 12 layer... | {
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https://api.github.com/repos/huggingface/transformers/issues/1861 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1861/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1861/comments | https://api.github.com/repos/huggingface/transformers/issues/1861/events | https://github.com/huggingface/transformers/pull/1861 | 524,468,313 | MDExOlB1bGxSZXF1ZXN0MzQyMjM3NTYz | 1,861 | Better TensorFlow 2 examples | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1861?src=pr&el=h1) Report\n> Merging [#1861](https://codecov.io/gh/huggingface/transformers/pull/1861?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a5a06a851e1da79138e53978aa079a093f243dde?src=pr&el=desc) will **n... | 1,574 | 1,651 | 1,586 | MEMBER | null | This PR aims to improve the TensorFlow examples of the library. It aims to use many tf-specific paradigms, including but not limited to Keras API, AMP, XLA, `tensorflow_datasets`, `tf.train.Features` and `tf.train.Examples`, model saving using Keras callbacks.
Two examples are specifically targeted:
- [x] `run_t... | {
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https://api.github.com/repos/huggingface/transformers/issues/1860 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1860/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1860/comments | https://api.github.com/repos/huggingface/transformers/issues/1860/events | https://github.com/huggingface/transformers/pull/1860 | 524,362,290 | MDExOlB1bGxSZXF1ZXN0MzQyMTUwNTcz | 1,860 | [WIP] Add support for CamembertForTokenClassification | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1860?src=pr&el=h1) Report\n> Merging [#1860](https://codecov.io/gh/huggingface/transformers/pull/1860?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3916b334a86484af8442d1cfdb2f15695feae581?src=pr&el=desc) will **d... | 1,574 | 1,574 | 1,574 | COLLABORATOR | null | Hi,
this PR adds a `CamembertForTokenClassification` implementation, so that fine-tuning of NER models is possible.
Tasks:
* [x] Implement `CamembertForTokenClassification`
* [x] Add `CamembertForTokenClassification` to module import list
* [x] Add support for CamemBERT model in `run_ner.py` example | {
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https://api.github.com/repos/huggingface/transformers/issues/1859 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1859/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1859/comments | https://api.github.com/repos/huggingface/transformers/issues/1859/events | https://github.com/huggingface/transformers/pull/1859 | 524,228,881 | MDExOlB1bGxSZXF1ZXN0MzQyMDQwNzE4 | 1,859 | Adds CamemBERT to Model architectures list | {
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https://api.github.com/repos/huggingface/transformers/issues/1858 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1858/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1858/comments | https://api.github.com/repos/huggingface/transformers/issues/1858/events | https://github.com/huggingface/transformers/issues/1858 | 524,065,422 | MDU6SXNzdWU1MjQwNjU0MjI= | 1,858 | Conversion of [Model]ForSequenceClassification logits to probabilities | {
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"Logits are the classification scores before softmax.\r\nI don't see why the results of your equation should add up to 1.\r\nYou may try to use the softmax function directly.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occur... | 1,574 | 1,579 | 1,579 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I noticed that whenever I would convert logits coming from the model to probabilities using the following equation:
probability = e^logit/(1 + e^logit)
The probabilities for my two classes do not add up to 1. Why is this?
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https://api.github.com/repos/huggingface/transformers/issues/1857 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1857/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1857/comments | https://api.github.com/repos/huggingface/transformers/issues/1857/events | https://github.com/huggingface/transformers/issues/1857 | 524,011,348 | MDU6SXNzdWU1MjQwMTEzNDg= | 1,857 | XLM Masked Word Prediction | {
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"Duplicate of #1842 "
] | 1,574 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
Does anyone knows how to mask a word in a sentence and then get predictions with probabilities from XLM models | {
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https://api.github.com/repos/huggingface/transformers/issues/1856 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1856/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1856/comments | https://api.github.com/repos/huggingface/transformers/issues/1856/events | https://github.com/huggingface/transformers/issues/1856 | 523,994,469 | MDU6SXNzdWU1MjM5OTQ0Njk= | 1,856 | multitask learning | {
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"from the documentation of the class,\r\nhttps://github.com/huggingface/transformers/blob/933841d903a032d93b5100220dc72db9d1283eca/pytorch_transformers/modeling_bert.py#L1100\r\n\r\nI understand that I could use the ```scores```, as input to an additional module that I could stack on top of BertForTokenClassificat... | 1,574 | 1,594 | 1,575 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi, I would like to apply multitask learning, using for example two tasks, and the one (and maybe both) of the two tasks is sequential labeling like NER. To my understanding, in order to apply the library on such a task, the way to go i... | {
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https://api.github.com/repos/huggingface/transformers/issues/1855 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1855/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1855/comments | https://api.github.com/repos/huggingface/transformers/issues/1855/events | https://github.com/huggingface/transformers/issues/1855 | 523,990,667 | MDU6SXNzdWU1MjM5OTA2Njc= | 1,855 | Some questions about the abstractive summarization code. | {
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"Hi!\r\n\r\nFirst, please check the `run_summarization.py` script in the `example-summarization` branch as it is more up-to-date. To answer your questions:\r\n\r\na) We are following this implementation: https://arxiv.org/pdf/1908.08345.pdf where they add an extra [CLS] token for each new sentence.\r\n\r\nb) I woul... | 1,573 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi, thanks for sharing the code, i was confused about some code and implements when i reading it.
a) In run_summarization_finetuning.py,
![image](https://user-images.githubusercontent.com/9161371/69008385-bf6ac500-0984-11ea-8f02-728... | {
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https://api.github.com/repos/huggingface/transformers/issues/1854 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1854/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1854/comments | https://api.github.com/repos/huggingface/transformers/issues/1854/events | https://github.com/huggingface/transformers/issues/1854 | 523,965,809 | MDU6SXNzdWU1MjM5NjU4MDk= | 1,854 | run glue problem | {
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"Could you please respect the issue template so that we can help you better? It's hard to help without seeing the versions or the full error."
] | 1,573 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
How to fix this problem
| {
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https://api.github.com/repos/huggingface/transformers/issues/1853 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1853/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1853/comments | https://api.github.com/repos/huggingface/transformers/issues/1853/events | https://github.com/huggingface/transformers/pull/1853 | 523,957,722 | MDExOlB1bGxSZXF1ZXN0MzQxODM0NDY5 | 1,853 | typo "deay" -> "decay" | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1853?src=pr&el=h1) Report\n> Merging [#1853](https://codecov.io/gh/huggingface/transformers/pull/1853?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0477b307c7501ea76e01b03cb387a2312db752b3?src=pr&el=desc) will **d... | 1,573 | 1,574 | 1,574 | CONTRIBUTOR | null | a typo has been fixed. | {
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https://api.github.com/repos/huggingface/transformers/issues/1852 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1852/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1852/comments | https://api.github.com/repos/huggingface/transformers/issues/1852/events | https://github.com/huggingface/transformers/issues/1852 | 523,890,600 | MDU6SXNzdWU1MjM4OTA2MDA= | 1,852 | XLNet model params for Question answering | {
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"What parameters should I exactly pass for XLNet QA model?",
"More details would be nice but please check #1849 #1848 and #1805 . Also set `CUDA_LAUNCH_BLOCKING=1` environment variable to have more details about the error, from the CUDA.",
"Thanks. It worked after changing the input sequence limit to 128.",
"... | 1,573 | 1,581 | 1,581 | NONE | null | Model: XLNet for QA
model(parameters ...)
RuntimeError: CUDA error: device-side assert triggered | {
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https://api.github.com/repos/huggingface/transformers/issues/1851 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1851/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1851/comments | https://api.github.com/repos/huggingface/transformers/issues/1851/events | https://github.com/huggingface/transformers/issues/1851 | 523,864,475 | MDU6SXNzdWU1MjM4NjQ0NzU= | 1,851 | The acc of RACE is always low by roberta model | {
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"Same.\r\nmodel =roberta-base\r\ntotal batch size=8\r\ntrain num epochs=5\r\nfp16 =False\r\nmax seq length =512\r\neval_acc = 0.29568242275424594\r\neval_loss = 1.3862943781258896\r\n@spolu ",
"This issue has been automatically marked as stale because it has not had recent activity. It will ... | 1,573 | 1,585 | 1,585 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
My scripts like follows:
python ./examples/run_multiple_choice.py \
--model_type roberta \
--task_name race \
--model_name_or_path roberta-base \
--do_train \
--do_eval \
--do_lower... | {
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https://api.github.com/repos/huggingface/transformers/issues/1850 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1850/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1850/comments | https://api.github.com/repos/huggingface/transformers/issues/1850/events | https://github.com/huggingface/transformers/issues/1850 | 523,862,513 | MDU6SXNzdWU1MjM4NjI1MTM= | 1,850 | Can't run convert_roberta_original_pytorch_checkpoint_to_pytorch.py | {
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"Hi! Do you succeed in loading your pre-trained model in Fairseq?",
"Yes, it work well in Fairseq~",
"My script:\r\npython ./transformers/convert_roberta_original_pytorch_checkpoint_to_pytorch.py --roberta_checkpoint_path ./checkpoint_best.pt --pytorch_dump_folder_path ./race_base/roberta-convert-checkpoint/",
... | 1,573 | 1,645 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
when i want to convert my model which prertrained in fairseq, the error like follows:
2019-11-16 23:53:48.119139: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not... | {
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https://api.github.com/repos/huggingface/transformers/issues/1849 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1849/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1849/comments | https://api.github.com/repos/huggingface/transformers/issues/1849/events | https://github.com/huggingface/transformers/pull/1849 | 523,853,950 | MDExOlB1bGxSZXF1ZXN0MzQxNzYyMjE3 | 1,849 | run_finetuning resize token embeddings | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1849?src=pr&el=h1) Report\n> Merging [#1849](https://codecov.io/gh/huggingface/transformers/pull/1849?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0477b307c7501ea76e01b03cb387a2312db752b3?src=pr&el=desc) will **n... | 1,573 | 1,574 | 1,574 | CONTRIBUTOR | null | Please see #1848 | {
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https://api.github.com/repos/huggingface/transformers/issues/1848 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1848/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1848/comments | https://api.github.com/repos/huggingface/transformers/issues/1848/events | https://github.com/huggingface/transformers/issues/1848 | 523,852,649 | MDU6SXNzdWU1MjM4NTI2NDk= | 1,848 | CUDA runtime error (59) : device-side assert triggered | {
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"Indeed, this seems to be a problem. Thanks for the PR!",
"fixed at #1849 "
] | 1,573 | 1,574 | 1,574 | CONTRIBUTOR | null | Hi,
When you run `run_lm_finetuning.py` with a custom tokenizer via `--tokenizer_name tokenizer` parameter, you need to resize model embedding according to the new tokenizer. Otherwise you are going to get `CUDA runtime error (59) : device-side assert triggered` or `Assertion 'srcIndex < srcSelectDimSize' failed`.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/1847 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1847/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1847/comments | https://api.github.com/repos/huggingface/transformers/issues/1847/events | https://github.com/huggingface/transformers/pull/1847 | 523,852,292 | MDExOlB1bGxSZXF1ZXN0MzQxNzYxMDgz | 1,847 | Update modeling_utils.py by adding "DUMMY_INPUTS" after "logger" variable. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1847?src=pr&el=h1) Report\n> Merging [#1847](https://codecov.io/gh/huggingface/transformers/pull/1847?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0477b307c7501ea76e01b03cb387a2312db752b3?src=pr&el=desc) will **i... | 1,573 | 1,575 | 1,575 | NONE | null | This Pull Request fixes a probable bug found using Transformers in Anaconda, using TFBertForSequenceClassification, Tensorflow 2.0.0b0, according to:
https://github.com/huggingface/transformers/issues/1810#issuecomment-554572471
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https://api.github.com/repos/huggingface/transformers/issues/1846 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1846/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1846/comments | https://api.github.com/repos/huggingface/transformers/issues/1846/events | https://github.com/huggingface/transformers/pull/1846 | 523,823,764 | MDExOlB1bGxSZXF1ZXN0MzQxNzQwOTM5 | 1,846 | fix summary_type value of SequenceSummary | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1846?src=pr&el=h1) Report\n> Merging [#1846](https://codecov.io/gh/huggingface/transformers/pull/1846?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0477b307c7501ea76e01b03cb387a2312db752b3?src=pr&el=desc) will **n... | 1,573 | 1,575 | 1,575 | CONTRIBUTOR | null | from #1845
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https://api.github.com/repos/huggingface/transformers/issues/1845 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1845/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1845/comments | https://api.github.com/repos/huggingface/transformers/issues/1845/events | https://github.com/huggingface/transformers/issues/1845 | 523,823,525 | MDU6SXNzdWU1MjM4MjM1MjU= | 1,845 | summary_type value of SequenceSummary is incorrect | {
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"Thanks!"
] | 1,573 | 1,575 | 1,575 | CONTRIBUTOR | null | https://github.com/huggingface/transformers/blob/0477b307c7501ea76e01b03cb387a2312db752b3/transformers/modeling_utils.py#L731
I think `if hasattr(config, 'summary_use_proj')` is incorrect, `if hasattr(config, 'summary_type')` is correct. | {
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https://api.github.com/repos/huggingface/transformers/issues/1844 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1844/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1844/comments | https://api.github.com/repos/huggingface/transformers/issues/1844/events | https://github.com/huggingface/transformers/pull/1844 | 523,793,866 | MDExOlB1bGxSZXF1ZXN0MzQxNzIzNjI4 | 1,844 | Rebase and merge Louismartin/camembert | {
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"Please, continue the comments [here](https://github.com/huggingface/transformers/pull/1822#issuecomment-558095282)\r\n\r\n> Great work!\r\n> \r\n> Could you show how to get the embedding vector of a sentence please?\r\n> \r\n> ```python\r\n> from transformers import CamembertTokenizer\r\n> import torch\r\n> \r\n> ... | 1,573 | 1,574 | 1,573 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/1843 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1843/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1843/comments | https://api.github.com/repos/huggingface/transformers/issues/1843/events | https://github.com/huggingface/transformers/issues/1843 | 523,663,376 | MDU6SXNzdWU1MjM2NjMzNzY= | 1,843 | "This tokenizer does not make use of special tokens." warning | {
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"Same here. Is there any way to suppress this warning? I use `run_lm_finetuning.py` to finetune distilgpt2 and it outputs thousands \"This tokenizer does not make use of special tokens.\". It's so annoying :(",
"Here's how to suppress the warnings until this is fixed:\r\n\r\n```py\r\nimport logging\r\nlogging.get... | 1,573 | 1,587 | 1,574 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I just updated to the latest version transformers. Now when I use tokenizer to encode word, it always show the warning "This tokenizer does not make use of special tokens."
Is there any way to hide that warning? Thank you. | {
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https://api.github.com/repos/huggingface/transformers/issues/1842 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1842/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1842/comments | https://api.github.com/repos/huggingface/transformers/issues/1842/events | https://github.com/huggingface/transformers/issues/1842 | 523,602,478 | MDU6SXNzdWU1MjM2MDI0Nzg= | 1,842 | xlm-mlm-17-1280 model masked word prediction | {
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"Would it be possible to use XML-R #1769 ? Its model has a simple description ( `Masked Language Models` in chapter 3) and is similar to BERT-Base besides tokenization, training configuration and language embeddings.",
"Hi\r\nThanks for the advice but idk if the model you mentioned has a pretrained one for Tur... | 1,573 | 1,574 | 1,574 | NONE | null | Hi
I would like some help with how to use pretrained xlm-mlm-17-1280 model to get predictions for masked word prediction. I have followed http://mayhewsw.github.io/2019/01/16/can-bert-generate-text/ for BERT mask prediction and it is working. Could you help me with how to use xlm-mlm-17-1280 model for word prediction.... | {
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https://api.github.com/repos/huggingface/transformers/issues/1841 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1841/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1841/comments | https://api.github.com/repos/huggingface/transformers/issues/1841/events | https://github.com/huggingface/transformers/issues/1841 | 523,567,401 | MDU6SXNzdWU1MjM1Njc0MDE= | 1,841 | BPE error when fine-tuning a CTRL model | {
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"Can you post the code for the `run_lm_finetuning`? I am not as familiar with what this error message might entail. ",
"Sure. Here it is.\r\n\r\n[run_ctrl_finetuning.py.zip](https://github.com/huggingface/transformers/files/3852748/run_ctrl_finetuning.py.zip)\r\n",
"This issue has been automatically marked as s... | 1,573 | 1,579 | 1,579 | NONE | null | Hi,
cc @keskarnitish
I'm using a slightly modified version of the exapmles/run_lm_finetuning.py code to fine-tune a CTRL model and getting this BPE warning:
```
WARNING - transformers.tokenization_ctrl - Saving vocabulary to /home/ubuntu/data/ctrl/pytrained4/merges.txt: BPE merge indices are not consecutiv... | {
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https://api.github.com/repos/huggingface/transformers/issues/1840 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1840/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1840/comments | https://api.github.com/repos/huggingface/transformers/issues/1840/events | https://github.com/huggingface/transformers/pull/1840 | 523,372,225 | MDExOlB1bGxSZXF1ZXN0MzQxMzg3NTA5 | 1,840 | Sampling sequence generator for transformers | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1840?src=pr&el=h1) Report\n> Merging [#1840](https://codecov.io/gh/huggingface/transformers/pull/1840?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8618bf15d6edc8774cedc0aae021d259d89c91fc?src=pr&el=desc) will **i... | 1,573 | 1,651 | 1,576 | CONTRIBUTOR | null | [@thomwolf version]: In this PR I introduce a flexible API to generate sequences for the models of the library provided with LM heads.
The API is designed to have a very flexible and quite exhaustive API:
- with/without a prompt
- with/without beam search
- with/without greedy decoding/sampling
- with any (and com... | {
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https://api.github.com/repos/huggingface/transformers/issues/1839 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1839/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1839/comments | https://api.github.com/repos/huggingface/transformers/issues/1839/events | https://github.com/huggingface/transformers/pull/1839 | 523,332,675 | MDExOlB1bGxSZXF1ZXN0MzQxMzU3MjM5 | 1,839 | Add support for Japanese BERT models by cl-tohoku | {
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"This looks great @singletongue. For the file upload, I will send you a way to upload to our S3, early next week, if that works for you.",
"That will be great. Thank you!",
"I could try it on my side, it seems to work well! \r\n\r\nI don't believe I've seen any benchmark on Japanese tasks in your repository, ho... | 1,573 | 1,576 | 1,576 | CONTRIBUTOR | null | This PR adds new BERT models for Japanese text.
Details of the models can be found in [this repository](https://github.com/cl-tohoku/bert-japanese).
Since the way of tokenization is Japanese-specific, a new file is added for the tokenizers.
And, the locations of the files (models, configs, etc.) should be updated ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1838 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1838/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1838/comments | https://api.github.com/repos/huggingface/transformers/issues/1838/events | https://github.com/huggingface/transformers/issues/1838 | 523,176,982 | MDU6SXNzdWU1MjMxNzY5ODI= | 1,838 | resize_token_embeddings not implemented for TFBert* | {
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"Did you get this to work for you? I'm currently trying to do the same thing but with TFGPT-2",
"Any update on when this would be completed?",
"I have the same issue, I wanted to use \"resize_token_embeddings\" with TFAlbert model but it's not implemented yet.",
"Hi, we have no plans of implementing this on o... | 1,573 | 1,588 | 1,587 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hey,
I noticed for the Tensorflow 2 implementation of BERT, the `resize_token_embeddings` function is not implemented, while the Pytorch BERT class does.
### Questions:
* Is the implementation of `resize_token_embeddings` for T... | {
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https://api.github.com/repos/huggingface/transformers/issues/1837 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1837/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1837/comments | https://api.github.com/repos/huggingface/transformers/issues/1837/events | https://github.com/huggingface/transformers/issues/1837 | 523,145,270 | MDU6SXNzdWU1MjMxNDUyNzA= | 1,837 | Error started happening today: ImportError: cannot import name 'get_linear_schedule_with_warmup' | {
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"try edit:\r\nfrom transformers import AdamW\r\nfrom transformers import WarmupLinearSchedule as get_linear_schedule_with_warmup",
"I tried the WarmupLinearSchedule, but I have a problem no key num_warmup_steps and num_training_steps. \r\n scheduler = WarmupLinearSchedule(optimizer, num_warmup_steps=args.warmu... | 1,573 | 1,575 | 1,575 | CONTRIBUTOR | 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:
* [ x] the official example scripts: (give details)
The squad script:
https://github.com/huggingface/transformers/blob/master/... | {
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https://api.github.com/repos/huggingface/transformers/issues/1836 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1836/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1836/comments | https://api.github.com/repos/huggingface/transformers/issues/1836/events | https://github.com/huggingface/transformers/issues/1836 | 523,116,867 | MDU6SXNzdWU1MjMxMTY4Njc= | 1,836 | Model parallelism support? | {
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"How do you training CTRL ? Did you check this: https://github.com/huggingface/transformers/blob/0477b307c7501ea76e01b03cb387a2312db752b3/examples/run_lm_finetuning.py#L198\r\n\r\nYou can also decrease batch size up to 1.\r\n\r\nAnd also gradients can be accumulated:\r\nhttps://github.com/huggingface/transformers/b... | 1,573 | 1,596 | 1,579 | NONE | null | Hi. I'm running into memory issues when trying to fine tune the CTRL language model on a 16 GB GPU. Is there any built-in support for splitting models across more than one GPU? I suppose that mapping the input embedding layer to a different GPU or even the CPU would do the trick.
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https://api.github.com/repos/huggingface/transformers/issues/1835 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1835/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1835/comments | https://api.github.com/repos/huggingface/transformers/issues/1835/events | https://github.com/huggingface/transformers/issues/1835 | 523,033,574 | MDU6SXNzdWU1MjMwMzM1NzQ= | 1,835 | Parallell compute failing for finetuning GPT2 using GPU | {
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**SYSTEM**
OS: Ubuntu 18.04
Python version: 3.6.8
Torch version: 1.0.0
Transformers version: 2.1.1
I am trying to finetune GPT2 using a GPU and am getting an error. I run the `run_lm_finetuning.py` example script with the following parameters:
```python
python run_lm_finetuning.py \
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/1834 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1834/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1834/comments | https://api.github.com/repos/huggingface/transformers/issues/1834/events | https://github.com/huggingface/transformers/issues/1834 | 523,021,308 | MDU6SXNzdWU1MjMwMjEzMDg= | 1,834 | Where is Model2Model PreTrainedEncoderDecoder in run_summerization_finetune | {
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"@yeliu918 was there any ```run_summerization_finetune``` script before? Since I cannot find it now.",
"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"
] | 1,573 | 1,583 | 1,583 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
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https://api.github.com/repos/huggingface/transformers/issues/1833 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1833/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1833/comments | https://api.github.com/repos/huggingface/transformers/issues/1833/events | https://github.com/huggingface/transformers/pull/1833 | 522,938,456 | MDExOlB1bGxSZXF1ZXN0MzQxMDM5OTgz | 1,833 | Token indices sequence length is longer than the specified maximum sequence length for this model | {
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```
Token indices sequence length is longer than the specified maximum sequence length for this model (X > 1024). Running this sequence through the model will re... | {
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https://api.github.com/repos/huggingface/transformers/issues/1832 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1832/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1832/comments | https://api.github.com/repos/huggingface/transformers/issues/1832/events | https://github.com/huggingface/transformers/pull/1832 | 522,902,198 | MDExOlB1bGxSZXF1ZXN0MzQxMDEwMjUw | 1,832 | replace LambdaLR scheduler wrappers by function | {
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"Yes, great job tracking and fixing this.\r\nCan you update all the examples as well?",
"Great job finding the issue!",
"I updated the docs and examples. I am confused because the tests fail on this function:\r\n\r\n```\r\n=================================== FAILURES ===================================\r\n_____... | 1,573 | 1,573 | 1,573 | CONTRIBUTOR | null | Custom schedulers are currently initiated by wrapping Pytorch's LambdaLR
class and passing a method of the wrapping class to the __init__
function of LambdaLR. This approach is not appropriate for several
reasons:
1. one does not need to define a class when it only defines a
__init__() method;
2. instantiating ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1831 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1831/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1831/comments | https://api.github.com/repos/huggingface/transformers/issues/1831/events | https://github.com/huggingface/transformers/pull/1831 | 522,883,756 | MDExOlB1bGxSZXF1ZXN0MzQwOTk1MDg5 | 1,831 | sum() is replaced by itertools.chain.from_iterable() | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1831?src=pr&el=h1) Report\n> Merging [#1831](https://codecov.io/gh/huggingface/transformers/pull/1831?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/155c782a2ccd103cf63ad48a2becd7c76a7d2115?src=pr&el=desc) will **d... | 1,573 | 1,573 | 1,573 | CONTRIBUTOR | null | sum() is the leanest method to flatten a string list, so it's been replaced by itertools.chain.from_iterable() . Please check #1830 | {
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https://api.github.com/repos/huggingface/transformers/issues/1830 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1830/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1830/comments | https://api.github.com/repos/huggingface/transformers/issues/1830/events | https://github.com/huggingface/transformers/issues/1830 | 522,835,313 | MDU6SXNzdWU1MjI4MzUzMTM= | 1,830 | GPT2 tokenizer is so slow because of sum() | {
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"Thank you for taking the time to look into this and opening a pull request!",
"You are welcome,\r\nThis thing has big effort and I always support as a community member :) .\r\nIf you merge PR I would be appreciated because I want to use it originally as provided in the master branch, for my ongoing project.\r\nT... | 1,573 | 1,573 | 1,573 | CONTRIBUTOR | null | ## 🐛 Bug
Hi,
As the discussion started in that #1621 issue, GPT2 tokenization is so slow even with 50MB of the dataset.
I'm using `run_lm_finetuning.py` and here are the steps to reproduce the problem:
- Have a dataset not an even bigger one. 20MB of a dataset is enough.
- Call `run_lm_finetuning.py` to trai... | {
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https://api.github.com/repos/huggingface/transformers/issues/1829 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1829/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1829/comments | https://api.github.com/repos/huggingface/transformers/issues/1829/events | https://github.com/huggingface/transformers/issues/1829 | 522,808,987 | MDU6SXNzdWU1MjI4MDg5ODc= | 1,829 | NotImplementedError when using TFDistilBertModel | {
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"In my environemnt, it **works as expected**.\r\n\r\n**Environment:**\r\n\r\n- **O.S.** Linux Ubuntu\r\n- **Python**: 3.6.9\r\n- **HuggingFace's Transformers**: 2.1.1 (installed **today** from source with `pip install git+https://github.com/huggingface/transformers`)\r\n- **PyTorch**: 1.3.1\r\n- **TensorFlow**: 2.0... | 1,573 | 1,573 | 1,573 | NONE | null | ## 🐛 Bug
<!-- Important information -->
I have this error when I train a model with TFDistilBertModel. The same code works if I change to BERT for example. The transformers is loaded with `TFDistilBertModel.from_pretrained("distilbert-base-uncased")`
```
File "/home/<user>/miniconda3/envs/nlp/lib/python3... | {
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https://api.github.com/repos/huggingface/transformers/issues/1828 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1828/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1828/comments | https://api.github.com/repos/huggingface/transformers/issues/1828/events | https://github.com/huggingface/transformers/issues/1828 | 522,745,287 | MDU6SXNzdWU1MjI3NDUyODc= | 1,828 | GPT2 tokenizer is so slow because of regex.findall | {
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Hi,
As the discussion started in that #1621 issue, GPT2 tokenization is so slow even with 50MB of the dataset.
I'm using `run_lm_finetuning.py` and here are the steps to reproduce the problem:
- Have a dataset not an even bigger one. 50MB of a dataset is enough.
- Call `run_lm_finetuning.py` to trai... | {
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https://api.github.com/repos/huggingface/transformers/issues/1827 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1827/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1827/comments | https://api.github.com/repos/huggingface/transformers/issues/1827/events | https://github.com/huggingface/transformers/issues/1827 | 522,696,567 | MDU6SXNzdWU1MjI2OTY1Njc= | 1,827 | How to get all layers(12) hidden states of BERT? | {
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"You should have obtained the 12 layers as well as the embedding output. Are you sure you're not mistaking the output of the forward call (which is a tuple as well) with the hidden states?\r\n\r\nJust to make sure, this is the correct way to obtain the hidden states:\r\n\r\n```py\r\nfrom transformers import BertMod... | 1,573 | 1,689 | 1,575 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I tried to set the output_hidden_states=True, but only got 3 layers of the hidden states of model outputs for BERT, but theoricaly it should be 12, how can I get that? | {
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https://api.github.com/repos/huggingface/transformers/issues/1826 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1826/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1826/comments | https://api.github.com/repos/huggingface/transformers/issues/1826/events | https://github.com/huggingface/transformers/issues/1826 | 522,660,745 | MDU6SXNzdWU1MjI2NjA3NDU= | 1,826 | Regarding Fine-Tuning for Abstractive Summarization | {
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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"
] | 1,573 | 1,579 | 1,579 | NONE | null | Hi,
What result did you obtain with your Abstractive Summarization code for CNN-DM? Also, is it implemented based on this paper: https://arxiv.org/abs/1908.08345 ?
It will be great if you provide some details regarding it. | {
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https://api.github.com/repos/huggingface/transformers/issues/1825 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1825/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1825/comments | https://api.github.com/repos/huggingface/transformers/issues/1825/events | https://github.com/huggingface/transformers/pull/1825 | 522,659,984 | MDExOlB1bGxSZXF1ZXN0MzQwODE1NjYx | 1,825 | 合并 | {
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"Is this related to this repository?"
] | 1,573 | 1,573 | 1,573 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/1824 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1824/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1824/comments | https://api.github.com/repos/huggingface/transformers/issues/1824/events | https://github.com/huggingface/transformers/issues/1824 | 522,627,457 | MDU6SXNzdWU1MjI2Mjc0NTc= | 1,824 | Issue testing run_squad.py example | {
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"Try adding `--version_2_with_negative \\` to your `run_squad.py `script.",
"That fixed it, thanks!"
] | 1,573 | 1,573 | 1,573 | CONTRIBUTOR | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I am trying to run the squad example here
https://github.com/huggingface/transformers/blob/master/examples/run_squad.py
Using the Squad data from here
https://rajpurkar.github.io/SQuAD-explorer/
But I get this error
>Va... | {
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https://api.github.com/repos/huggingface/transformers/issues/1823 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1823/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1823/comments | https://api.github.com/repos/huggingface/transformers/issues/1823/events | https://github.com/huggingface/transformers/issues/1823 | 522,589,963 | MDU6SXNzdWU1MjI1ODk5NjM= | 1,823 | how to use convert_pytorch_checkpoint_to_tf2.py | {
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"Hi, you can show the help with the following command:\r\n\r\n```\r\npython transformers/convert_pytorch_checkpoint_to_tf2.py --help \r\n```\r\n\r\nWhat is your use-case?",
"> Hi, you can show the help with the following command:\r\n> \r\n> ```\r\n> python transformers/convert_pytorch_checkpoint_to_tf2.py --help... | 1,573 | 1,574 | 1,574 | NONE | null | ## ❓ Questions & Help
I am wondering how to use convert_pytorch_checkpoint_to_tf2.py to convert pytorch checkpoint to tensorflow checkpoint. I found Comparing-PT-and-TF-models.ipynb have an example to use pytorch_pretrained_bert. But It doesn't work for convert_pytorch_checkpoint_to_tf2. Could you please give me any ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1822?src=pr&el=h1) Report\n> Merging [#1822](https://codecov.io/gh/huggingface/transformers/pull/1822?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/155c782a2ccd103cf63ad48a2becd7c76a7d2115?src=pr&el=desc) will **d... | 1,573 | 1,574 | 1,573 | CONTRIBUTOR | null | Code for the CamemBERT model, adapted from https://github.com/pytorch/fairseq/tree/master/examples/camembert | {
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https://api.github.com/repos/huggingface/transformers/issues/1821 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1821/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1821/comments | https://api.github.com/repos/huggingface/transformers/issues/1821/events | https://github.com/huggingface/transformers/issues/1821 | 522,548,301 | MDU6SXNzdWU1MjI1NDgzMDE= | 1,821 | Generated text makes no sense. Trying to auto-generate sentences like https://transformer.huggingface.co/doc/distil-gpt2 | {
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"Have you ever tried to finetune some hyper-paremeters, such as **temperature** or **seed**? You can also modify the **length** of the generated text by OpenAI GPT-2.\r\n\r\n_Tip_: if you want to make OpenAI GPT-2 model more comfortable and sure about its results, please set the temperature value lower than 0,5 (e.... | 1,573 | 1,579 | 1,579 | NONE | null | I would like to replicate the text-generation behavior of https://transformer.huggingface.co/doc/distil-gpt2 on my MacOS. I went to that URL and typed "A doula is a person" and kept tabbing for auto-text generation, and got this:
```
A doula is a person who cares for a child or infant. A doula is not a midwife. But t... | {
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https://api.github.com/repos/huggingface/transformers/issues/1820 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1820/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1820/comments | https://api.github.com/repos/huggingface/transformers/issues/1820/events | https://github.com/huggingface/transformers/issues/1820 | 522,490,984 | MDU6SXNzdWU1MjI0OTA5ODQ= | 1,820 | Is there a way of finetuning DistilGPT2? | {
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"Yes you can, call `run_lm_finetuning` via these parameters:\r\n\r\n```\r\n--model_type gpt2 \\\r\n--model_name_or_path distilgpt2 \r\n```",
"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.... | 1,573 | 1,599 | 1,579 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hello! I am trying to finetune GPT2 for a project of mine but my aim is to deploy the model on a server and hence, I would like the final model file to be small. I was thinking of using the Distil* models especially the DistilGPT2 but c... | {
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https://api.github.com/repos/huggingface/transformers/issues/1819 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1819/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1819/comments | https://api.github.com/repos/huggingface/transformers/issues/1819/events | https://github.com/huggingface/transformers/issues/1819 | 522,464,584 | MDU6SXNzdWU1MjI0NjQ1ODQ= | 1,819 | CUDA out of memory on loss.backward when fine-tuning GPT2 (117M) | {
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"If your gpu is out of memory, try decreasing the batch size (this will save memory). In order to retain the same effective batch size, use gradient accumulation. \r\n\r\nBasically, do `loss.backward()` for each step, but only every, say, 10 steps, do `optimizer.step()` and `optimizer.backward()`.",
"Hi @aced125,... | 1,573 | 1,593 | 1,581 | NONE | null | ## ❓ Questions & Help
File "run_lm_finetuning.py", line 551, in <module>
main()
File "run_lm_finetuning.py", line 503, in main
global_step, tr_loss = train(args, train_dataset, model, tokenizer)
File "run_lm_finetuning.py", line 240, in train
loss.backward()
File "/home/antonio/anaconda3/lib/... | {
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https://api.github.com/repos/huggingface/transformers/issues/1818 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1818/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1818/comments | https://api.github.com/repos/huggingface/transformers/issues/1818/events | https://github.com/huggingface/transformers/issues/1818 | 522,355,444 | MDU6SXNzdWU1MjIzNTU0NDQ= | 1,818 | Trouble running fine tuned language model script | {
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"Hi, could you specify the versions on which you are running? (especially PyTorch).\r\n\r\n`bool` was introduced in PyTorch 1.2 so, unfortunately, this example will crash if using an anterior version.",
"Sorry, forgot to give that info. As you preempted, I'm running torch 1.1.0. Guess I should update?",
"The co... | 1,573 | 1,573 | 1,573 | NONE | null | ## 🐛 Bug
I'm having trouble running the finetuning script. When I run
```
TRAIN_FILE='/home/khev/research/transformers/data/wikitext-2-raw/wiki.train.raw'
TEST_FILE='/home/khev/research/transformers/data/wikitext-2-raw/wiki.test.raw'
%run run_lm_finetuning.py \
--output_dir=output \
--model_type... | {
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https://api.github.com/repos/huggingface/transformers/issues/1817 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1817/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1817/comments | https://api.github.com/repos/huggingface/transformers/issues/1817/events | https://github.com/huggingface/transformers/issues/1817 | 522,275,626 | MDU6SXNzdWU1MjIyNzU2MjY= | 1,817 | Using multiple inputs for GPT-2 | {
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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"
] | 1,573 | 1,579 | 1,579 | NONE | null | ## ❓ Questions & Help
A current project I am working on, to utilize a tuned approach in text generation, is creating a cover letter based off of a job description and some personal qualifications. From researching, I found the convAI blog that you used and thought to apply the concept with OpenAIGPTDoubleHeadsModel. I... | {
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https://api.github.com/repos/huggingface/transformers/issues/1816 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1816/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1816/comments | https://api.github.com/repos/huggingface/transformers/issues/1816/events | https://github.com/huggingface/transformers/issues/1816 | 522,074,509 | MDU6SXNzdWU1MjIwNzQ1MDk= | 1,816 | Best way to fine tune GPT-2 in order to create a custom text generator? | {
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"Hi, you can use a combination of the scripts `run_lm_finetuning.py` and `run_generation.py` to accomplish what you want:\r\n\r\n- Fine-tune GPT-2 to your dataset using `run_lm_finetuning.py`. The default parameters should work well enough, I usually use three epochs (rather than the default 1) when training on sma... | 1,573 | 1,595 | 1,579 | NONE | null | Hello to everyone, and thanks for this wonderful work.
I am new to this library and I would appreciate an help for a task that i want to accomplish, just to know if I am acting right, to create a custom english text generator, such that giving it an input (title/sentence) it would generate 200-300 words based on tha... | {
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https://api.github.com/repos/huggingface/transformers/issues/1815 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1815/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1815/comments | https://api.github.com/repos/huggingface/transformers/issues/1815/events | https://github.com/huggingface/transformers/issues/1815 | 521,939,024 | MDU6SXNzdWU1MjE5MzkwMjQ= | 1,815 | computing self-attention for tokens in a sentence | {
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"To get the attention score of each heads, refer to the [documentation](https://huggingface.co/transformers/model_doc/bert.html#transformers.BertModel) : see `outputs`.\r\n\r\n---\r\n\r\n> how do I know which heads give the best scores ?\r\n\r\nYou can't really know. Each heads will compute some kind of attention. ... | 1,573 | 1,581 | 1,581 | NONE | null | ## ❓ Questions & Help
Hi,
Please refer to this [issue](https://github.com/google-research/bert/issues/914).
Thanks!
| {
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https://api.github.com/repos/huggingface/transformers/issues/1814 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1814/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1814/comments | https://api.github.com/repos/huggingface/transformers/issues/1814/events | https://github.com/huggingface/transformers/pull/1814 | 521,913,516 | MDExOlB1bGxSZXF1ZXN0MzQwMjAzNDgy | 1,814 | Sample a constant number of tokens for masking in LM finetuning | {
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"Hi @rakeshchada, we've thought about this. It is interesting and we might merge it, but will probably will be behind a flag :)\r\n\r\nThanks for contributing!",
"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 fo... | 1,573 | 1,583 | 1,583 | CONTRIBUTOR | null | @thomwolf @LysandreJik @julien-c Re-creating this PR as the original PR https://github.com/huggingface/transformers/pull/1555 that I created about a month ago has become quite stale. Please review.
For Masked LM fine-tuning, I think both the original BERT and RoBERTa implementations uniformly sample x number of to... | {
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https://api.github.com/repos/huggingface/transformers/issues/1813 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1813/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1813/comments | https://api.github.com/repos/huggingface/transformers/issues/1813/events | https://github.com/huggingface/transformers/issues/1813 | 521,832,057 | MDU6SXNzdWU1MjE4MzIwNTc= | 1,813 | LM Fine-tuning for XLNET? | {
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"I'm also looking forward to it! ",
"I might be naive here, but will adding xlnet's config, LMHeadModel, and tokenizer to MODEL_CLASSES work?\r\nhttps://github.com/huggingface/transformers/blob/74ce8de7d8e0375a9123f9542f3483f46cc8df9b/examples/run_lm_finetuning.py#L61",
"I don't think adding the Python classes ... | 1,573 | 1,583 | 1,580 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi there, is there any plan to add support for fine-tuning XLNET? This one currently isn't available in run_lm_finetuning.py.
Thanks! | {
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https://api.github.com/repos/huggingface/transformers/issues/1812 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1812/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1812/comments | https://api.github.com/repos/huggingface/transformers/issues/1812/events | https://github.com/huggingface/transformers/pull/1812 | 521,824,315 | MDExOlB1bGxSZXF1ZXN0MzQwMTMwNTYz | 1,812 | Update conversion script to convert XLM-R | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1812?src=pr&el=h1) Report\n> Merging [#1812](https://codecov.io/gh/huggingface/transformers/pull/1812?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/155c782a2ccd103cf63ad48a2becd7c76a7d2115?src=pr&el=desc) will **n... | 1,573 | 1,573 | 1,573 | NONE | null | It requires a few changes to the existing RoBERTa conversion script because `fairseq` has updated the RoBERTa model definition.
Specifically, the definition of multiheaded attention is changed at https://github.com/pytorch/fairseq/blob/2a9b4ec2374574cd0315f95e126788e4fe795f0d/fairseq/modules/multihead_attention.py#... | {
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https://api.github.com/repos/huggingface/transformers/issues/1811 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1811/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1811/comments | https://api.github.com/repos/huggingface/transformers/issues/1811/events | https://github.com/huggingface/transformers/pull/1811 | 521,786,021 | MDExOlB1bGxSZXF1ZXN0MzQwMDk4NzM1 | 1,811 | Fix special tokens addition in decoder #1807 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1811?src=pr&el=h1) Report\n> Merging [#1811](https://codecov.io/gh/huggingface/transformers/pull/1811?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/155c782a2ccd103cf63ad48a2becd7c76a7d2115?src=pr&el=desc) will **d... | 1,573 | 1,573 | 1,573 | MEMBER | null | Fixes the issue detailed in #1807
Added special tokens should not be present when decoding with the `skip_special_tokens` flag set to `True`.
Using the `convert_tokens_to_ids` checks whether those added tokens are present and removes them if necessary. | {
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