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https://api.github.com/repos/huggingface/transformers/issues/2512 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2512/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2512/comments | https://api.github.com/repos/huggingface/transformers/issues/2512/events | https://github.com/huggingface/transformers/issues/2512 | 549,050,352 | MDU6SXNzdWU1NDkwNTAzNTI= | 2,512 | Getting started with the new 'FeatureExtractionPipeline' feature | {
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"@Stuffooh, the following is based on my understanding and experiment.\r\n\r\nThe default params for `nlp = pipeline('feature-extraction')` uses `distilbert-base-uncased` for both the model and tokenizer.\r\n\r\nThe `nlp` object takes as input a sentence and output token-level vectors; note that token-level doesn't... | 1,578 | 1,620 | 1,582 | NONE | null | Hi,
At the moment I'm trying to extract features of the second last layer using the "run_lm_finetuning.py" script in combination with the setting "output_hidden_sates=True".
I'm wondering if this new FeatureExtractionPipeline feature would be a good alternative and how to get started using this new feature. I hav... | {
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https://api.github.com/repos/huggingface/transformers/issues/2511 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2511/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2511/comments | https://api.github.com/repos/huggingface/transformers/issues/2511/events | https://github.com/huggingface/transformers/issues/2511 | 549,043,746 | MDU6SXNzdWU1NDkwNDM3NDY= | 2,511 | Saving full tensor output of hidden states instead of truncated output in lm_finetuning.py script | {
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"Hi, how are they truncated? When you call `tensor.shape`, is it not the shape you're expecting?",
"@LysandreJik thanks for mentioning tensor.shape. I was so convinced the data was truncated and forgot to check the shape to confirm. Because of your hint I realized the output that gets printed is truncated but the... | 1,578 | 1,579 | 1,579 | NONE | null | Hi,
The past few weeks I have been playing around with the "run_lm_finetuning.py" script to finetune a custom dataset and extract it's features by setting 'output_hidden_states=True' and saving the features of the second last layer by changing the code of the script as follows:
`model.train()`
`outputs = model(i... | {
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https://api.github.com/repos/huggingface/transformers/issues/2510 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2510/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2510/comments | https://api.github.com/repos/huggingface/transformers/issues/2510/events | https://github.com/huggingface/transformers/issues/2510 | 548,918,918 | MDU6SXNzdWU1NDg5MTg5MTg= | 2,510 | ModuleNotFoundError: No module named 'model_bertabs' AND RuntimeError: CUDA error: device-side assert triggered | {
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"I have the same CUDA error with a finetuning of offical bert downloaded from s3. I'll wait for clarifications too.",
"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"
] | 1,578 | 1,585 | 1,585 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):Bert
Language I am using the model on (English, Chinese....):Chinese
The problem arise when using:
* [ ] the official example scripts:
[1]ModuleNotFoundError: No module named 'model_bertabs' when run convert_bertabs_original_py... | {
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https://api.github.com/repos/huggingface/transformers/issues/2509 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2509/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2509/comments | https://api.github.com/repos/huggingface/transformers/issues/2509/events | https://github.com/huggingface/transformers/pull/2509 | 548,765,332 | MDExOlB1bGxSZXF1ZXN0MzYxOTgzMTIy | 2,509 | fix xlm roberta tokenizer mask id | {
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"Hey @stefan-it, mind taking a look at this?",
"Hi,\r\nI get the following error when trying to adapt the same code as BERT for Masked LM with XLM-Roberta For Masked LM, where I've replaced **'[MASK]'** with **'\\<mask>'** and '**[CLS]'** and **'[SEP]'** with **\\<s>** and **\\</s>** respectively.\r\n\r\n```\r\n/... | 1,578 | 1,582 | 1,582 | CONTRIBUTOR | null | As per issue #2508 the xlm_roberta_tokenizer has an error in the mask_id computation.
The sp_model already contains all the special tokens (bos, pad, eos, unk) but the mask id, which, according to the model specification should be 250001 instead of 250004:
```
self.fairseq_tokens_to_ids["<mask>"] = len(self.sp_model... | {
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https://api.github.com/repos/huggingface/transformers/issues/2508 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2508/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2508/comments | https://api.github.com/repos/huggingface/transformers/issues/2508/events | https://github.com/huggingface/transformers/issues/2508 | 548,755,536 | MDU6SXNzdWU1NDg3NTU1MzY= | 2,508 | XLMRobertaTokenizer is a wrong tokenizer for XLMRoberta | {
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"Hi, indeed this is an error. This will be fixed once #3198 is merged.",
"Hi, I also notice from [special token's mapping in XLM repo](https://github.com/facebookresearch/XLM/blob/cd281d32612d145c6742b4d3f048f80df8669c30/xlm/data/dictionary.py#L131) that the indexing of `self.fairseq_tokens_to_ids` looks differen... | 1,578 | 1,625 | 1,584 | CONTRIBUTOR | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): XLMRoberta
Language I am using the model on (English, Chinese....): multi-language, but mostly english
The problem arise when:
try to tokenise a sentence that contains the special <mask> token
The tasks I am working on is: tr... | {
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https://api.github.com/repos/huggingface/transformers/issues/2507 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2507/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2507/comments | https://api.github.com/repos/huggingface/transformers/issues/2507/events | https://github.com/huggingface/transformers/pull/2507 | 548,752,155 | MDExOlB1bGxSZXF1ZXN0MzYxOTcyMDAw | 2,507 | update probabilitiy to probability, misspelled the word | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2507?src=pr&el=h1) Report\n> Merging [#2507](https://codecov.io/gh/huggingface/transformers/pull/2507?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a3085020ed0d81d4903c50967687192e3101e770?src=pr&el=desc) will **n... | 1,578 | 1,579 | 1,579 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2506 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2506/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2506/comments | https://api.github.com/repos/huggingface/transformers/issues/2506/events | https://github.com/huggingface/transformers/issues/2506 | 548,731,344 | MDU6SXNzdWU1NDg3MzEzNDQ= | 2,506 | Discrepancy in results ( BertModel) between pytorch_pretrained_bert and transformers | {
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"Please edit your post and remove the images. Instead, post the code inside Python [code tags](https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks). It is hard to read your post like this and impossible to copy-paste and try it out ourselves.",
"@BramVanroy Thanks for your re... | 1,578 | 1,579 | 1,579 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using: BERT
Language I am using the model on (English, Chinese....): English
```
from transformers import BertTokenizer, BertModel
tokenizer2 = BertTokenizer.from_pretrained('bert-base-uncased')
model2 = BertModel.from_pretrained('bert-base-uncased', outp... | {
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https://api.github.com/repos/huggingface/transformers/issues/2505 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2505/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2505/comments | https://api.github.com/repos/huggingface/transformers/issues/2505/events | https://github.com/huggingface/transformers/issues/2505 | 548,726,834 | MDU6SXNzdWU1NDg3MjY4MzQ= | 2,505 | AttributeError: 'BertForTokenClassification' object has no attribute 'named_configeters' | {
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"Hi, what is the variable `bert_model` you're showing? Could you provide more information e.g. the version of transformers, your version of python, your version of torch?"
] | 1,578 | 1,579 | 1,579 | NONE | null | ```
model = BertForTokenClassification.from_pretrained(bert_model)
```
Error: AttributeError: 'BertForTokenClassification' object has no attribute 'named_configeters'
When I initialized the model as
```
model = BertForTokenClassification.from_pretrained(bert_model, 2)
```
Error: TypeError: from_pretrained(... | {
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https://api.github.com/repos/huggingface/transformers/issues/2504 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2504/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2504/comments | https://api.github.com/repos/huggingface/transformers/issues/2504/events | https://github.com/huggingface/transformers/issues/2504 | 548,622,153 | MDU6SXNzdWU1NDg2MjIxNTM= | 2,504 | BertTokenizerFast.encode() ignores max_length | {
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"I'll let @n1t0 chime in if needed, but in the `Fast` versions of the tokenizers you have to define the `max_length` at initialization, not when calling `.encode()`\r\n\r\nCan you try this and let me know if it works?",
"Oh You are right. When i init with max_length it works.\r\nIs this documented?\r\nThanks",
... | 1,578 | 1,584 | 1,584 | CONTRIBUTOR | null | ## 🐛 Bug
for this input: (from yelp review)
`text = "After a morning of Thrift Store hunting, a friend and I were thinking of lunch, and he suggested Emil's after he'd seen Chris Sebak do a bit on it and had tried it a time or two before, and I had not."`
If i use the standard BertTokenizer it works fine:
`token... | {
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https://api.github.com/repos/huggingface/transformers/issues/2503 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2503/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2503/comments | https://api.github.com/repos/huggingface/transformers/issues/2503/events | https://github.com/huggingface/transformers/issues/2503 | 548,598,633 | MDU6SXNzdWU1NDg1OTg2MzM= | 2,503 | BERT and cross entropy | {
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"Yes , you can use a MSEloss",
"thank you for replying me.\r\nCan I use cross entropy Loss, since BERT use it, and replacing the one hot vector by the weight of each class?",
"SO, What are the labeles of classes?",
"1 for positive and 0 for negative",
"I think it may work well ,and you may use NLLloss, it w... | 1,578 | 1,592 | 1,592 | NONE | null | ## ❓ Questions & Help
How can I feed probability of classes to BERT as label? For example, in sentiment analysis
let say we have this sentence "I like to sleep" instead of 0 or 1 I want to label it as 0.6 negative and 0.4 positive.
Thank you in advance | {
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https://api.github.com/repos/huggingface/transformers/issues/2502 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2502/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2502/comments | https://api.github.com/repos/huggingface/transformers/issues/2502/events | https://github.com/huggingface/transformers/issues/2502 | 548,582,909 | MDU6SXNzdWU1NDg1ODI5MDk= | 2,502 | Perform MultiLingual Name Matching | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | I am trying to perform multi-lingual name matching (entity-resolution). To build the pipeline the idea is to use :
- Byte level character embeddings and then use a dense vector similarity.
Anyone here has some experience in this approach? | {
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"The idea is very good, and has been discussed previously.\r\n\r\nhttps://github.com/huggingface/transformers/issues/2520\r\nhttps://github.com/huggingface/transformers/pull/2281#issuecomment-570574944\r\n\r\nI think HuggingFace is well aware of the challenges and intricacies that are involved, so I'm sure they'll ... | 1,578 | 1,588 | 1,584 | NONE | null | TL;DR help me testing and documenting models performance on datasets benchmarks provided with transformers (i.e. GLUE tasks). Anyone with Google and Weights&Biases account can help. It's super easy and costs nothing, just execute colab notebook and help communiy with gathering results! All checked tasks results are ava... | {
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"Closing, as I was logged in under wrong account"
] | 1,578 | 1,578 | 1,578 | NONE | null | my bad, logged in as wrong user | {
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https://api.github.com/repos/huggingface/transformers/issues/2499 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2499/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2499/comments | https://api.github.com/repos/huggingface/transformers/issues/2499/events | https://github.com/huggingface/transformers/issues/2499 | 548,350,211 | MDU6SXNzdWU1NDgzNTAyMTE= | 2,499 | Trouble fine tuning distilbertmodel | {
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"According to https://github.com/huggingface/transformers/issues/2418#issuecomment-571721526, until a fix is released you should change the `-100` in your script to `-1`. It worked for me with Albert.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if... | 1,578 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Trying to run lm_finetuning on the distilbert multilanguage
Getting the following error when I run:
python lm_finetuning.py \
--model_type='distilbert' \
--model_name_or_path=distilbert-base-multilingual-cased\
--train_data_file=small.txt \
--output... | {
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https://api.github.com/repos/huggingface/transformers/issues/2498 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2498/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2498/comments | https://api.github.com/repos/huggingface/transformers/issues/2498/events | https://github.com/huggingface/transformers/issues/2498 | 548,328,448 | MDU6SXNzdWU1NDgzMjg0NDg= | 2,498 | RuntimeError: Expected object of backend CUDA but got backend CPU for argument #3 'index' | {
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"same issue for me",
"Hi,\r\n\r\nCan you try with the latest 2.4.0 transformers release and let us know if you still observe the same ?",
"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.\... | 1,578 | 1,587 | 1,587 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Pipelines "question-answering" with the bert-large-cased-whole-word-masking-finetuned-squad model.
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [ ] the official example scripts: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2497 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2497/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2497/comments | https://api.github.com/repos/huggingface/transformers/issues/2497/events | https://github.com/huggingface/transformers/issues/2497 | 548,325,697 | MDU6SXNzdWU1NDgzMjU2OTc= | 2,497 | How to load tf1 BERT checkpoints and sentencepiece model from local folder? | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | ## ❓ Questions & Help
We have BERT checkpoints trained for [Mongolian](https://github.com/tugstugi/mongolian-bert) language and planning to upload it to transformers library.
In order to do that, we have to check compatibility. I have following questions.
- How to load sentencepiece model from local folder?
- H... | {
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https://api.github.com/repos/huggingface/transformers/issues/2496 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2496/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2496/comments | https://api.github.com/repos/huggingface/transformers/issues/2496/events | https://github.com/huggingface/transformers/issues/2496 | 548,315,138 | MDU6SXNzdWU1NDgzMTUxMzg= | 2,496 | Using Model2Model with Albert | {
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"I met the same problem when I use `T5Model`. I think it could be some minor error in the source code.",
"I think it's not a minor error, at least in my case. It seems `Albert` does not support language model fine tuning and `Albert` did not have same API with `Bert`. ",
"I found this problem in `T5` model and ... | 1,578 | 1,585 | 1,585 | NONE | null | Hi,
I am trying to use Albert model with Model2Model helper to build encoder decoder model. But it seems some variables missing in Albert implementation for language model fine tuning. I thought I could use the Albert just as I did with Bert.
Here is my script converted from `Model2Model` quickstart for Albert.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/2495 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2495/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2495/comments | https://api.github.com/repos/huggingface/transformers/issues/2495/events | https://github.com/huggingface/transformers/pull/2495 | 548,267,791 | MDExOlB1bGxSZXF1ZXN0MzYxNjA0MDY3 | 2,495 | T5: move rp_bucket to relative_attention_bias' device | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2495?src=pr&el=h1) Report\n> Merging [#2495](https://codecov.io/gh/huggingface/transformers/pull/2495?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/331065e62d11d5c26642cb92a597904eee4c159b?src=pr&el=desc) will **d... | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | otherwise, `rp_bucket` will always be on cpu and fail if `self.relative_attention_bias` is on cuda | {
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https://api.github.com/repos/huggingface/transformers/issues/2494 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2494/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2494/comments | https://api.github.com/repos/huggingface/transformers/issues/2494/events | https://github.com/huggingface/transformers/pull/2494 | 548,257,410 | MDExOlB1bGxSZXF1ZXN0MzYxNTk1NTky | 2,494 | AutoModels: model_type is defined in config.json, not hardcoded in model's name | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2494?src=pr&el=h1) Report\n> Merging [#2494](https://codecov.io/gh/huggingface/transformers/pull/2494?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/331065e62d11d5c26642cb92a597904eee4c159b?src=pr&el=desc) will **i... | 1,578 | 1,579 | 1,579 | MEMBER | null | {
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"Turns lout this is a non-issue; there is a subtle nuance that I have overlooked: on the very first iteration of V2 (using `past`) we do not have any `past` and therefore the code should be modified to take argmax differently fixed code produces the correct output:\r\n\r\nV2 (fixed):\r\n\r\n```python\r\ntokenizer =... | 1,578 | 1,578 | 1,578 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): GPT2
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)
The tasks I am working on is:... | {
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https://api.github.com/repos/huggingface/transformers/issues/2492 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2492/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2492/comments | https://api.github.com/repos/huggingface/transformers/issues/2492/events | https://github.com/huggingface/transformers/pull/2492 | 548,122,181 | MDExOlB1bGxSZXF1ZXN0MzYxNDg1MzEw | 2,492 | Configuration Documentation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2492?src=pr&el=h1) Report\n> Merging [#2492](https://codecov.io/gh/huggingface/transformers/pull/2492?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2b566c182efc5330e4753b6db74c5b0518716147?src=pr&el=desc) will **d... | 1,578 | 1,579 | 1,579 | MEMBER | null | Updating the documentation with types, better naming, making sure every argument is listed and explained. | {
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https://api.github.com/repos/huggingface/transformers/issues/2491 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2491/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2491/comments | https://api.github.com/repos/huggingface/transformers/issues/2491/events | https://github.com/huggingface/transformers/issues/2491 | 548,105,463 | MDU6SXNzdWU1NDgxMDU0NjM= | 2,491 | Masked tokens are -1 not -100? | {
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"To fast... Sorry :)\r\nhttps://github.com/huggingface/transformers/issues/2442"
] | 1,578 | 1,578 | 1,578 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [X] the official example scripts: (give details)
* [ ] my own modified scripts: (give details)
The tasks I am working on is:
* [ ] an of... | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | I am trying to export a query to a .csv file, but I am having some issues. Here is the code:
import pandas as pd
import cx_Oracle as cx_Oracle
print("Efetuando login...")
dsn_tns = cx_Oracle.makedsn(r'bdproddr-exad.pitagoras.apollo.br','1521', service_name='bdprodexa')
conn = cx_Oracle.connect(user=r'UserName'... | {
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https://api.github.com/repos/huggingface/transformers/issues/2489 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2489/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2489/comments | https://api.github.com/repos/huggingface/transformers/issues/2489/events | https://github.com/huggingface/transformers/issues/2489 | 547,999,278 | MDU6SXNzdWU1NDc5OTkyNzg= | 2,489 | Model trained on Wikipedia Articles | {
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"IIRC BERT was trained on BookCorpus and Wikipedia",
"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"
] | 1,578 | 1,584 | 1,584 | NONE | null | Is there any Model trained on Wikipedia Articles? | {
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https://api.github.com/repos/huggingface/transformers/issues/2488 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2488/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2488/comments | https://api.github.com/repos/huggingface/transformers/issues/2488/events | https://github.com/huggingface/transformers/issues/2488 | 547,998,735 | MDU6SXNzdWU1NDc5OTg3MzU= | 2,488 | NER Pipeline Issue | {
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"I am suffering from the same problem, trying to recover input texts from `examples/run_ner.py`.",
"Agree. I find the use of BIO very unorthodox in this case; if B actually represented the beginning of an entity (vs. the beginning of the new entity of the same type), we could reconstruct these spans ourselves. Cu... | 1,578 | 1,590 | 1,590 | NONE | null | I am trying to run NER Pipeline. Here, I am using the line, "Statue of Liberty is located in New York". I am getting the following output
[{'entity': 'I-MISC', 'score': 0.5469961762428284, 'word': 'St'},
{'entity': 'I-MISC', 'score': 0.7588933706283569, 'word': '##at'},
{'entity': 'I-MISC', 'score': 0.519406914710... | {
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https://api.github.com/repos/huggingface/transformers/issues/2487 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2487/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2487/comments | https://api.github.com/repos/huggingface/transformers/issues/2487/events | https://github.com/huggingface/transformers/issues/2487 | 547,997,785 | MDU6SXNzdWU1NDc5OTc3ODU= | 2,487 | "config.json" does not include correct "id2label" and "label2id" after finetuning on NER task | {
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"I checked the codes days before and 'label2id' and 'id2label' seemed not used and didn't influence the code execution."
] | 1,578 | 1,582 | 1,582 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): xlmroberta
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [ ] the official example scripts: (give details)
I use script `run_ner.py` in order to finetune xlmroberta on conll03 dat... | {
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https://api.github.com/repos/huggingface/transformers/issues/2486 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2486/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2486/comments | https://api.github.com/repos/huggingface/transformers/issues/2486/events | https://github.com/huggingface/transformers/issues/2486 | 547,994,010 | MDU6SXNzdWU1NDc5OTQwMTA= | 2,486 | Finding the right keras loss and metric for SQuAD | {
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"In case @jplu has an insight on this?",
"Hi @jwallat,\r\n\r\nYou might have two solutions to solve your issue:\r\n\r\n* Implement your own loss function that you can give to the compile method (see the official Tensorflow [doc](https://www.tensorflow.org/api_docs/python/tf/keras/Model?version=stable#compile))\r\... | 1,578 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I am trying to build a simple example with BERT for QA (on SQuAD). The goal is getting it similarly as simple as [the GLUE example from the repository](https://github.com/huggingface/transformers#quick-tour-tf-20-training-and-pytorch-in... | {
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"Thanks @loretoparisi that is awesome! \r\n\r\nWe _should_ be able to just load it using `RobertaModel` or `AutoModel`, though. I'll see if we need to make changes to enable this.",
"Work in progress on the (remote) tokenizer config in https://github.com/huggingface/transformers/pull/2535\r\n\r\n",
"@julien-c j... | 1,578 | 1,582 | 1,580 | CONTRIBUTOR | null | Adds umBERTo to Model architectures list
References and benchmarks:
https://github.com/musixmatchresearch/umberto | {
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<!-- Important information -->
Model I am using : DistilBert
Language I am using the model on : English
The problem arise when using:
* [x] the official example scripts: run_squad_w_distillation.py in examples/distillation
The tasks I am working on is:
* [x] an official GLUE/SQUaD task: SQu... | {
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https://api.github.com/repos/huggingface/transformers/issues/2483 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2483/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2483/comments | https://api.github.com/repos/huggingface/transformers/issues/2483/events | https://github.com/huggingface/transformers/issues/2483 | 547,724,579 | MDU6SXNzdWU1NDc3MjQ1Nzk= | 2,483 | Removing pretrained layers? | {
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"If this is important to anyone, I have found a solution:\r\n```\r\ndef deleteEncodingLayers(model, num_layers_to_keep): # must pass in the full bert model\r\n oldModuleList = model.bert.encoder.layer\r\n newModuleList = nn.ModuleList()\r\n\r\n # Now iterate over all layers, only keepign only the relevant... | 1,578 | 1,667 | 1,578 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I'm currently trying to use a pretrained BertModel for finetuning but I want to remove some of the layers from the model before fine-tuning.
How do I do this? | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | ## 🚀 Feature
the `model.generate` method should support `past` as an input (and return the hidden states so that the next time it can inject past)
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"I find that the first token in the original XLM is indeed using \\</s\\> rather than \\<s\\>. "
] | 1,578 | 1,579 | 1,579 | NONE | null | ## 🐛 Bug
The CLS token in XLM should be \<s\> rather than \</s\> in the current repo.
Here is the XLM's original BOS_WORD:
https://github.com/facebookresearch/XLM/blob/master/src/data/dictionary.py#L17
In the transformers' repo, cls_token is set to \</s\>.
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"Hi, I've pushed a fix that was just merged in `master`. Could you please try and install from source:\r\n```py\r\npip install git+https://github.com/huggingface/transformers\r\n```\r\nand tell me if you face the same error?",
"Having follow your reply from here (https://github.com/huggingface/transformers/issues... | 1,578 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Bert
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* the official example scripts: modeling_bert.py
The tasks I am working on is:
* my own task or dataset: fine-tuning Bert wit... | {
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https://api.github.com/repos/huggingface/transformers/issues/2479 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2479/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2479/comments | https://api.github.com/repos/huggingface/transformers/issues/2479/events | https://github.com/huggingface/transformers/issues/2479 | 547,686,582 | MDU6SXNzdWU1NDc2ODY1ODI= | 2,479 | Implement Layer-wise Relevance Propagation (LRP) for prediction explanation | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I second this! :+1: "
] | 1,578 | 1,600 | 1,585 | NONE | null | ## 🚀 Feature
Example Code:
https://github.com/lena-voita/the-story-of-heads/blob/master/lib/layers/attn.py#L154
## Motivation
The motivation is prediction explainability to be able to generate pictures like:
![image](https://user-images.githubusercontent.com/1810412/72099957-b5fc3a00-32ef-11ea-8740-0d0508... | {
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https://api.github.com/repos/huggingface/transformers/issues/2478 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2478/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2478/comments | https://api.github.com/repos/huggingface/transformers/issues/2478/events | https://github.com/huggingface/transformers/issues/2478 | 547,670,438 | MDU6SXNzdWU1NDc2NzA0Mzg= | 2,478 | ImportError: No module named 'transformers' | {
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"When you enter the command \"python\" what is the output? and what environment are you using? linux/Windows/mac/etc?\r\n\r\nAlso, could you copy the exact output of \"pip install transformers\" so that we can see?",
"Python 3.7.3 (default, Apr 24 2019, 15:29:51) [MSC v.1915 64 bit (AMD64)] :: Anaconda, Inc. on w... | 1,578 | 1,701 | 1,584 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I have installed transformers by "pip install transformers command"
However, when I tried to use it, it says no module.
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https://api.github.com/repos/huggingface/transformers/issues/2477 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2477/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2477/comments | https://api.github.com/repos/huggingface/transformers/issues/2477/events | https://github.com/huggingface/transformers/issues/2477 | 547,648,629 | MDU6SXNzdWU1NDc2NDg2Mjk= | 2,477 | TFDistilBERT ValueError when loading a saved model and running model.predict(), same with any sequence classification model in tensorflow | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | This issue happens when I save and reload a model. I am trying to distinguish between fake text and real text, and everything works just fine.
When I save and reload the model elsewhere, model.predict() gives me a value error, and I have to run model.fit() AGAIN otherwise it continues to raise a ValueError.
> Valu... | {
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https://api.github.com/repos/huggingface/transformers/issues/2476 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2476/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2476/comments | https://api.github.com/repos/huggingface/transformers/issues/2476/events | https://github.com/huggingface/transformers/issues/2476 | 547,647,833 | MDU6SXNzdWU1NDc2NDc4MzM= | 2,476 | DistilBertTokenizer defaults to tokenize_chinese_chars=True | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using DistilBert:
Language I am using the model on English
The problem arise when using:
* [ ] the official example [run_tf_ner.py](https://github.com/huggingface/transformers/blob/master/examples/run_tf_ner.py) scripts
The tasks I am working on is:
* ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2475 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2475/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2475/comments | https://api.github.com/repos/huggingface/transformers/issues/2475/events | https://github.com/huggingface/transformers/issues/2475 | 547,611,884 | MDU6SXNzdWU1NDc2MTE4ODQ= | 2,475 | help... | {
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"I haven't worked on TF code like this personally, but by looking [https://github.com/huggingface/transformers/blob/master/README.md#quick-tour-tf-20-training-and-pytorch-interoperability](url) It shows that they don't override the config like you have done.\r\n\r\nNow if that doesn't work - which I don't think it ... | 1,578 | 1,584 | 1,584 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
---------------------------------------------------------------------------
i saw great example in (https://huggingface.co/transformers/main_classes/model.html?highlight=from_pretrained#pretrainedmodel) but i got an error please help... | {
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https://api.github.com/repos/huggingface/transformers/issues/2474 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2474/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2474/comments | https://api.github.com/repos/huggingface/transformers/issues/2474/events | https://github.com/huggingface/transformers/issues/2474 | 547,570,220 | MDU6SXNzdWU1NDc1NzAyMjA= | 2,474 | ALBERT tokenizer : local variable 'tokenizer' referenced before assignment | {
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"The error is misleading, I’ll fix that. Your error stems from the tokenizer initialization: there is no pretrained checkpoint called `albert-base`, only `albert-base-v1` or `albert-base-v2`.\r\n\r\nYou can check the list of pretrained checkpoints [here](https://huggingface.co/transformers/pretrained_models.html)."... | 1,578 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using BERT and ALBERT
Language I am using the model on: English
The problem arise when using:
* my own script
The tasks I am working on is:
* my own task or dataset: text classification
## To Reproduce
Steps to reproduce the behavior:
```$ pi... | {
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https://api.github.com/repos/huggingface/transformers/issues/2473 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2473/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2473/comments | https://api.github.com/repos/huggingface/transformers/issues/2473/events | https://github.com/huggingface/transformers/issues/2473 | 547,457,430 | MDU6SXNzdWU1NDc0NTc0MzA= | 2,473 | Using Transformer Library for code prediction | {
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"You should probably train a model from scratch.\r\n\r\nHere a few links that are relevant:\r\n\r\n- our blog post on [how to train a model from scratch](https://huggingface.co/blog/how-to-train) using `transformers` and `tokenizers`.\r\n- specifically on the topic of code, we just uploaded [CodeBERTa](https://hugg... | 1,578 | 1,584 | 1,584 | NONE | null | Dear all,
I am new in exploring transformer library. I would like to use transformer models to train on my own text corpus (.txt) containing C++ source code tokens seperated with space characters. I would like to provide tokenized C++ source code files from multiple repositories in textual format (.txt) , and functi... | {
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https://api.github.com/repos/huggingface/transformers/issues/2472 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2472/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2472/comments | https://api.github.com/repos/huggingface/transformers/issues/2472/events | https://github.com/huggingface/transformers/issues/2472 | 547,452,304 | MDU6SXNzdWU1NDc0NTIzMDQ= | 2,472 | Pytorch T5 does not run on GPU | {
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"I can also confirm that T5 runs on CPU but not GPU -- thanks for the hack fix, will use that until GPU tensor is fixed. ",
"Hi,\r\nI was planning to run some examples with T5 on GPU. Is this already been fixed on GPU ?",
"@mohammedayub44, in v2.5.0 it works without any issue, I guess yes.\r\n\r\n```\r\nprint (... | 1,578 | 1,598 | 1,598 | CONTRIBUTOR | null | ## 🐛 Bug
When I try to run T5 from the latest transformers version (and also from the most recent git version) on the GPU, I get the following error:
```
Traceback (most recent call last):
File "T5_example.py", line 32, in <module>
outputs = model(input_ids=input_ids)
File "/home/reimers/anaconda3/en... | {
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https://api.github.com/repos/huggingface/transformers/issues/2471 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2471/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2471/comments | https://api.github.com/repos/huggingface/transformers/issues/2471/events | https://github.com/huggingface/transformers/issues/2471 | 547,425,635 | MDU6SXNzdWU1NDc0MjU2MzU= | 2,471 | Using T5 | {
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"I am also looking for inference example. I tried using GPT-2 style inference but it does not work at all",
"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"
] | 1,578 | 1,584 | 1,584 | NONE | null | How can i use T5 model like in the paper , input to the model "Machine Translation #Some Text#" and it outputs its translation ?
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https://api.github.com/repos/huggingface/transformers/issues/2470 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2470/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2470/comments | https://api.github.com/repos/huggingface/transformers/issues/2470/events | https://github.com/huggingface/transformers/issues/2470 | 547,423,916 | MDU6SXNzdWU1NDc0MjM5MTY= | 2,470 | How pipeline can use a ner finetuned model from a local directory ? | {
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"Hi,\r\nJust an update on this issue. I managed to get it work like this:\r\n`model = XLMRobertaForTokenClassification.from_pretrained('./2-out/')`\r\n`tokenizer = XLMRobertaTokenizer.from_pretrained('./2-out/')`\r\n`nlp = pipeline('ner',model= model,tokenizer=tokenizer)`\r\n`nlp('blabla').`\r\n\r\nThe problem is t... | 1,578 | 1,584 | 1,584 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi,
I fine tuned XLM-Roberta on my own NER dataset so I got a folder containing pytorch_model.bin and all the other stuff.
But the problem is that I do not figure out how to use this model with the pipeline.
Below is an example of h... | {
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https://api.github.com/repos/huggingface/transformers/issues/2469 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2469/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2469/comments | https://api.github.com/repos/huggingface/transformers/issues/2469/events | https://github.com/huggingface/transformers/pull/2469 | 547,413,646 | MDExOlB1bGxSZXF1ZXN0MzYwOTA1NTk5 | 2,469 | Add PRETRAINED_INIT_CONFIGURATION to DistilBERT tokenizer | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2469?src=pr&el=h1) Report\n> Merging [#2469](https://codecov.io/gh/huggingface/transformers/pull/2469?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f599623a99b808e3d5926d89cd13237457b9eeba?src=pr&el=desc) will **i... | 1,578 | 1,578 | 1,578 | MEMBER | null | The DistilBERT tokenizer does not make use of `PRETRAINED_INIT_CONFIGURATION`, instead loading BERT's.
This PR fixes this, fixing the issue detailed in #2423. | {
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"I also have the same problem with AlbertForMaskedLM. \r\nI have tried all version of the git repo as well as pip installs.\r\nBasically I add tokens\r\n`from transformers import AlbertForMaskedLM, AlbertTokenizer\r\ntokenizer = AlbertTokenizer.from_pretrained('albert-base-v2')\r\ntokenizer.add_tokens(myvocab.get_u... | 1,578 | 1,579 | 1,579 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Bert / BertForMaskedLM
Language I am using the model on (English, Chinese....): bert-base-multilingual-cased
The problem arise when using:
* [X] the official example scripts: (give details)
* [X] my own modified scripts: (give d... | {
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https://api.github.com/repos/huggingface/transformers/issues/2467 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2467/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2467/comments | https://api.github.com/repos/huggingface/transformers/issues/2467/events | https://github.com/huggingface/transformers/pull/2467 | 547,281,371 | MDExOlB1bGxSZXF1ZXN0MzYwNzk3MTg3 | 2,467 | Add japanese | {
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"sorry i made mistake again because i push create pullreq too early."
] | 1,578 | 1,578 | 1,578 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2466 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2466/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2466/comments | https://api.github.com/repos/huggingface/transformers/issues/2466/events | https://github.com/huggingface/transformers/issues/2466 | 547,267,422 | MDU6SXNzdWU1NDcyNjc0MjI= | 2,466 | GPT-2 XL PyTorch Quantization for use on a Cloud Server | {
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"I found that by changing `device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")` to `device = torch.device(\"cpu\")` the program was able to continue, except the quantized models are larger for some reason...\r\n\r\n| | Old Size | New Size |\r\n|-------------|----------|----------|\... | 1,578 | 1,702 | 1,585 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I want to run a fast (well, relatively) and interactive version of GPT-2 XL on an Ubuntu 18.04 Cloud Server using python. I have no intention of using the model for anything other than giving it a prompt and getting a generated response... | {
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https://api.github.com/repos/huggingface/transformers/issues/2465 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2465/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2465/comments | https://api.github.com/repos/huggingface/transformers/issues/2465/events | https://github.com/huggingface/transformers/pull/2465 | 547,251,779 | MDExOlB1bGxSZXF1ZXN0MzYwNzcyNTI3 | 2,465 | Fix Tokenizer.from_pretrained `raise OSError` | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2465?src=pr&el=h1) Report\n> Merging [#2465](https://codecov.io/gh/huggingface/transformers/pull/2465?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f599623a99b808e3d5926d89cd13237457b9eeba?src=pr&el=desc) will **n... | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | `raise` before OSError seems to be forgotten. | {
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https://api.github.com/repos/huggingface/transformers/issues/2464 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2464/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2464/comments | https://api.github.com/repos/huggingface/transformers/issues/2464/events | https://github.com/huggingface/transformers/issues/2464 | 547,236,184 | MDU6SXNzdWU1NDcyMzYxODQ= | 2,464 | How to run the "run_lm_finetuning.py" with my own corpus? | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hello! I am a phD student in Beijing Normal University. I'm trying to further pre-train the model "bert-base-chinese" with my own corpus using the "run_lm_finetuning.py". However in the Examples, there is only an example using WikiText... | {
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https://api.github.com/repos/huggingface/transformers/issues/2463 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2463/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2463/comments | https://api.github.com/repos/huggingface/transformers/issues/2463/events | https://github.com/huggingface/transformers/issues/2463 | 547,205,635 | MDU6SXNzdWU1NDcyMDU2MzU= | 2,463 | How to use GPU to do inference ? | {
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"Ok, I find the way. Just do it like the naive Pytorch code. "
] | 1,578 | 1,578 | 1,578 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
When I use pretrained model to infer, how can I use GPU?
```
tokenizer = XLNetTokenizer.from_pretrained('your-folder-name')
model = XLNetModel.from_pretrained('your-folder-name')
inputs = torch.tensor([tokenizer.encode("... | {
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https://api.github.com/repos/huggingface/transformers/issues/2462 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2462/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2462/comments | https://api.github.com/repos/huggingface/transformers/issues/2462/events | https://github.com/huggingface/transformers/issues/2462 | 547,149,228 | MDU6SXNzdWU1NDcxNDkyMjg= | 2,462 | TF2 version of Multilingual DistilBERT throws an exception [TensorFlow 2] | {
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"THe same error happens to me with the `distilbert-base-multilingual-cased`",
"Hello !\r\n\r\nI got the same error. After having investigated a bit, I found that the error is because the field `output_hidden_states` in the configuration file of the model `distilbert-base-multilingual-cased` is set to `true` inste... | 1,578 | 1,581 | 1,581 | NONE | null | ## 🐛 Bug
I'm finding that several of the TensorFlow 2.0 Sequence Classification models don't seem to work. Case in point: `distilbert-base-uncased` works but `distilbert-base-multilingual-cased` does not.
My environment is:
* Platform Linux-4.15.0-65-generic-x86_64-with-Ubuntu-18.04-bionic
* Python 3.6.8 (... | {
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https://api.github.com/repos/huggingface/transformers/issues/2461 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2461/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2461/comments | https://api.github.com/repos/huggingface/transformers/issues/2461/events | https://github.com/huggingface/transformers/issues/2461 | 546,992,694 | MDU6SXNzdWU1NDY5OTI2OTQ= | 2,461 | For Hugging Face transformer's hidden_states output, is the first hidden state tensor that is returned the out of the embeddings? | {
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"Indeed, the documentation might be misleading in that regard. The first value is the embedding output, every following value is the result of the preceding value being passed through an additional layer. I'll update the documentation shortly.",
"@LysandreJik So will output.hidden_states[-1] be the output of the ... | 1,578 | 1,632 | 1,578 | NONE | null | According to the Hugging Face Transformer documentation for the GPT2DoubleHeadsModel (under the 'output' section)
```
hidden_states: (optional, returned when config.output_hidden_states=True)
list of torch.FloatTensor (one for the output of each layer + the output of the embeddings)
```
So in this case, would... | {
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https://api.github.com/repos/huggingface/transformers/issues/2460 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2460/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2460/comments | https://api.github.com/repos/huggingface/transformers/issues/2460/events | https://github.com/huggingface/transformers/issues/2460 | 546,954,118 | MDU6SXNzdWU1NDY5NTQxMTg= | 2,460 | Fine-tuning pretrained BERT model using own dataset but with same training task | {
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"Here is very barebone but working example. It does not have next sentence prediction code but it will work for masked language model:\r\n\r\n```python\r\nimport numpy as np\r\nimport tensorflow as tf\r\nfrom transformers import *\r\n\r\nMODEL = 'distilbert-base-uncased'\r\nmodel = TFDistilBertForMaskedLM.from_pret... | 1,578 | 1,584 | 1,584 | NONE | null | ## ❓ Questions & Help
I would like to finetune a pretrained model using the same task as the original model was trained on, so this means that I want the model to predict masked words and do next sentence prediction. Is there anywhere some code snippet that achieves this or gives an idea on how I can implement this?... | {
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https://api.github.com/repos/huggingface/transformers/issues/2459 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2459/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2459/comments | https://api.github.com/repos/huggingface/transformers/issues/2459/events | https://github.com/huggingface/transformers/pull/2459 | 546,941,601 | MDExOlB1bGxSZXF1ZXN0MzYwNTIxNzc4 | 2,459 | Update pipelines.py | {
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"Hi @Perseus14, thanks for your contribution :).\r\n\r\nI took the liberty to apply black formatting so that tests are happy.\r\n\r\nLooks good to me 👍 ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2459?src=pr&el=h1) Report\n> Merging [#2459](https://codecov.io/gh/huggingface/transformers/p... | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | Modified QA pipeline to consider all features for each example before generating topk answers.
Current pipeline only takes one SquadExample, one SquadFeature, one start logit list, one end logit list to retrieve the answer, this is not correct as one SquadExample can produce multiple SquadFeatures. | {
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https://api.github.com/repos/huggingface/transformers/issues/2458 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2458/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2458/comments | https://api.github.com/repos/huggingface/transformers/issues/2458/events | https://github.com/huggingface/transformers/pull/2458 | 546,936,559 | MDExOlB1bGxSZXF1ZXN0MzYwNTE3NjU5 | 2,458 | Update QA pipeline | {
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Current pipeline only takes one SquadExample, one SquadFeature, one start logit list, one end logit list to retrieve the answer, this is not correct as one SquadExample can produce multiple SquadFeatures. | {
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https://api.github.com/repos/huggingface/transformers/issues/2457 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2457/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2457/comments | https://api.github.com/repos/huggingface/transformers/issues/2457/events | https://github.com/huggingface/transformers/pull/2457 | 546,925,768 | MDExOlB1bGxSZXF1ZXN0MzYwNTA4NzAy | 2,457 | New SQuAD API for distillation script | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2457?src=pr&el=h1) Report\n> Merging [#2457](https://codecov.io/gh/huggingface/transformers/pull/2457?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/16ce15ed4bd0865d24a94aa839a44cf0f400ef50?src=pr&el=desc) will **n... | 1,578 | 1,578 | 1,578 | MEMBER | null | The squad distillation script is still using methods from files that do not exist anymore (utils_squad and utils_squad_evaluate).
I updated the script to use the newer API. | {
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https://api.github.com/repos/huggingface/transformers/issues/2456 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2456/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2456/comments | https://api.github.com/repos/huggingface/transformers/issues/2456/events | https://github.com/huggingface/transformers/pull/2456 | 546,910,284 | MDExOlB1bGxSZXF1ZXN0MzYwNDk1OTQ3 | 2,456 | Adding usage example with Tensorflow | {
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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"
] | 1,578 | 1,585 | 1,585 | NONE | null | Simple training and fine-tuning example of DistilBERT in a Colab. | {
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https://api.github.com/repos/huggingface/transformers/issues/2455 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2455/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2455/comments | https://api.github.com/repos/huggingface/transformers/issues/2455/events | https://github.com/huggingface/transformers/issues/2455 | 546,887,072 | MDU6SXNzdWU1NDY4ODcwNzI= | 2,455 | ROBERTa model wrong padding for token_type_ids field if return_tensors=True | {
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"I've been able to fix the `return_attention_masks` error manually defining \r\n`tokenization_utils.is_tf_available = lambda: False`\r\nIt seems that tf2.0 can enable `_tf_available` in src/transformers/file_utils.py,\r\nwhich triggers the problematic branch (second stack in the second trace)",
"This issue has be... | 1,578 | 1,585 | 1,585 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using ROBERTa
ROBERTa model wrong padding for token_type_ids field if return_tensors=True.
Language I am using the model on English:
The problem arise when using:
* [ ] the official example scripts: (give details)
* [* ] my own modified scripts: (give d... | {
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https://api.github.com/repos/huggingface/transformers/issues/2454 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2454/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2454/comments | https://api.github.com/repos/huggingface/transformers/issues/2454/events | https://github.com/huggingface/transformers/pull/2454 | 546,859,470 | MDExOlB1bGxSZXF1ZXN0MzYwNDU3OTQ3 | 2,454 | Add XLM-RoBERTa model for TF2 | {
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"There is a little incompatibility between isort and black apparently https://github.com/psf/black/issues/251",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2454?src=pr&el=h1) Report\n> Merging [#2454](https://codecov.io/gh/huggingface/transformers/pull/2454?src=pr&el=desc) into [master](https... | 1,578 | 1,580 | 1,580 | CONTRIBUTOR | null | Hello,
I have implemented the XLM-RoBERTa model handling for Tensorflow 2. | {
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https://api.github.com/repos/huggingface/transformers/issues/2453 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2453/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2453/comments | https://api.github.com/repos/huggingface/transformers/issues/2453/events | https://github.com/huggingface/transformers/issues/2453 | 546,858,200 | MDU6SXNzdWU1NDY4NTgyMDA= | 2,453 | Installation of Transformers without Sacremoses | {
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"I commented sacramoses it out in the setup.py and installed it, everything worked as designed! As long as I don't use XLM",
"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",
"Having o... | 1,578 | 1,594 | 1,584 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi HuggingFace Team!
I was checking the dependencies of this library, and I found that sacremoses does not have an accepted licence type for my system. The setup.py file says that it's needed for XLM. If I don't plan on using XLM w... | {
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https://api.github.com/repos/huggingface/transformers/issues/2452 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2452/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2452/comments | https://api.github.com/repos/huggingface/transformers/issues/2452/events | https://github.com/huggingface/transformers/pull/2452 | 546,843,134 | MDExOlB1bGxSZXF1ZXN0MzYwNDQ0MTM4 | 2,452 | Remove redundant hidden states | {
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As I understand it, the `encoder_hidden_states` are already present in the `kwargs_decoder` dictionary, there is therefore no need to pass it to the decoder forward call.
W... | {
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https://api.github.com/repos/huggingface/transformers/issues/2451 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2451/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2451/comments | https://api.github.com/repos/huggingface/transformers/issues/2451/events | https://github.com/huggingface/transformers/pull/2451 | 546,833,082 | MDExOlB1bGxSZXF1ZXN0MzYwNDM1ODg2 | 2,451 | Add check for token_type_ids before tensorizing | {
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"Great, that looks good to me!"
] | 1,578 | 1,582 | 1,579 | CONTRIBUTOR | null | Fix an issue where `prepare_for_model()` gives a `KeyError` when
`return_token_type_ids` is set to `False` and `return_tensors` is
enabled. | {
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https://api.github.com/repos/huggingface/transformers/issues/2450 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2450/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2450/comments | https://api.github.com/repos/huggingface/transformers/issues/2450/events | https://github.com/huggingface/transformers/issues/2450 | 546,775,629 | MDU6SXNzdWU1NDY3NzU2Mjk= | 2,450 | Error when running run_generation.py | {
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"It seems to me that there is either another program that has a lock on the GPT-2 file or that you can't access our S3. Does the error still happen if you restart your machine?",
"yes. I restarted several times but the issue persist",
"Seems to be a file lock issue. Can't rename a file because it's being used.\... | 1,578 | 1,579 | 1,579 | NONE | null | I tried to run this code:
python ./examples/run_generation.py --model_type=gpt2 --length=20 --model_name_or_path=gpt2
However I am getting the error below:
PermissionError: [WinError 32] The process cannot access the file because it is being used by another process: 'C:\\Users\\GPT2\\.cache\\torch\\transformers\... | {
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https://api.github.com/repos/huggingface/transformers/issues/2449 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2449/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2449/comments | https://api.github.com/repos/huggingface/transformers/issues/2449/events | https://github.com/huggingface/transformers/issues/2449 | 546,723,867 | MDU6SXNzdWU1NDY3MjM4Njc= | 2,449 | Evaluation not working on distilbert-base-uncased-distilled-squad | {
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"Hello, thanks for raising this issue! This should have been fixed with 16ce15e, can you let me know if it fixes your issue?",
"Hi @LysandreJik, thanks for fixing the issue on such short notice. Yes, now it's working. "
] | 1,578 | 1,578 | 1,578 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using DistilBert: distilbert-base-uncased-distilled-squad
Language I am using the model on English:
The problem arise when using:
* [x] the official example scripts: run_squad.py in examples
The tasks I am working on is:
* [x] an official GLUE/SQUaD t... | {
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https://api.github.com/repos/huggingface/transformers/issues/2448 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2448/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2448/comments | https://api.github.com/repos/huggingface/transformers/issues/2448/events | https://github.com/huggingface/transformers/issues/2448 | 546,702,558 | MDU6SXNzdWU1NDY3MDI1NTg= | 2,448 | Tokenizer methods and padding | {
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"I have no strong opinion about this. Wdyt @LysandreJik?\r\n\r\nRelated to this though, this is how I'm proposing to mask the padding tokens in Masked language modeling batches in the `run_lm_finetuning` script: https://github.com/huggingface/transformers/pull/2570/commits/55939b5707066f612b0b2390787b325d30af728c#d... | 1,578 | 1,585 | 1,585 | CONTRIBUTOR | null | ## ❓ Questions & Help
I wanted to know whether there was a perticular reason why the `get_special_tokens_mask` method of the tokenizer does not also return as mask over padding tokens, only <CLS> and <SEP> tokens, in the case where `already_has_special_tokens=True` ? I had to rewrite a custom function for my usecase... | {
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https://api.github.com/repos/huggingface/transformers/issues/2447 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2447/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2447/comments | https://api.github.com/repos/huggingface/transformers/issues/2447/events | https://github.com/huggingface/transformers/issues/2447 | 546,694,910 | MDU6SXNzdWU1NDY2OTQ5MTA= | 2,447 | Reproducibility problem with DistilBERT paper | {
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"Does anyone have the same problem here?"
] | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | ## ❓ Questions & Help
We are currently working a follow-up to your work “DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter”. We’ve noticed some skeptical data in Table 1 of your paper. On MRPC, the reported averaged F1 and acc result is 90.2, which is even ~2% higher than BERT-base (teach... | {
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https://api.github.com/repos/huggingface/transformers/issues/2446 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2446/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2446/comments | https://api.github.com/repos/huggingface/transformers/issues/2446/events | https://github.com/huggingface/transformers/issues/2446 | 546,662,899 | MDU6SXNzdWU1NDY2NjI4OTk= | 2,446 | RuntimeError: index out of range: Tried to access index 512 out of table with 511 rows. | {
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"Different models have different sequence lengths. Some models don't, like XLNet and TransformerXL.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I have the same error.\r\n\r\nI... | 1,578 | 1,594 | 1,594 | NONE | null | ## ❓ Questions & Help
I am receiving the error RuntimeError: index out of range: Tried to access index 512 out of table with 511 rows.
What can I do to increase this source sentence length constraint?
<img width="1316" alt="Screen Shot 2020-01-08 at 2 01 49 pm" src="https://user-images.githubusercontent.com/4469... | {
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https://api.github.com/repos/huggingface/transformers/issues/2445 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2445/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2445/comments | https://api.github.com/repos/huggingface/transformers/issues/2445/events | https://github.com/huggingface/transformers/issues/2445 | 546,661,620 | MDU6SXNzdWU1NDY2NjE2MjA= | 2,445 | Error occurs in XLMRobertaModel when token_type_ids is given. | {
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"XLMRobertaModel does not support token types > 0. \r\nIf you look at the embedding you will see that there is only a single value. Basically the model does not rely on this embedding to understand when a sentence end. I think they included it only for API compatibility",
"@andompesta Thank you very much! :)"
] | 1,578 | 1,578 | 1,578 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): XLMRoberta
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* the official example scripts: (give details)
![image](https://user-images.githubusercontent.com/6512394/71953192-c2679080... | {
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https://api.github.com/repos/huggingface/transformers/issues/2444 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2444/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2444/comments | https://api.github.com/repos/huggingface/transformers/issues/2444/events | https://github.com/huggingface/transformers/pull/2444 | 546,653,417 | MDExOlB1bGxSZXF1ZXN0MzYwMjg4NzYz | 2,444 | Update | {
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"I'm sorry I made mistake.\r\nI just want to pullreq to our branch which forks from yours.\r\nSo, I close this pullreq."
] | 1,578 | 1,578 | 1,578 | NONE | null | 本家のupdateを取り込みました。 | {
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https://api.github.com/repos/huggingface/transformers/issues/2443 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2443/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2443/comments | https://api.github.com/repos/huggingface/transformers/issues/2443/events | https://github.com/huggingface/transformers/issues/2443 | 546,628,653 | MDU6SXNzdWU1NDY2Mjg2NTM= | 2,443 | porting XLM-Roberta to tensorflow 2.0 | {
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"Hi @andompesta hard to say without looking at the code – did you check out this related PR by @jplu : #2443"
] | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | ## ❓ Questions & Help
Yesterday I have ported XLM-Roberta from pytorch to tensorflow mainly following the instruction provided in [huggingface/from-tensorflow-to-pytorch](https://medium.com/huggingface/from-tensorflow-to-pytorch-265f40ef2a28).
The final error is computed using the DUMMY_INPUT as input values for th... | {
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https://api.github.com/repos/huggingface/transformers/issues/2442 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2442/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2442/comments | https://api.github.com/repos/huggingface/transformers/issues/2442/events | https://github.com/huggingface/transformers/issues/2442 | 546,616,024 | MDU6SXNzdWU1NDY2MTYwMjQ= | 2,442 | loss_fct = CrossEntropyLoss(ignore_index=-1) for BERT/RoBERTa MaksedLM | {
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"Hello! This is due to the pull request #2130. I believe you're running the examples with transformers 2.3.0 whereas they're maintained to work with the current master branch. Please install the library from master:\r\n\r\n```pip install git+https://github.com/huggingface/transformers```\r\n\r\nin order to get the ... | 1,578 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
The models I am using (Bert, RoBERTa....):
Language I am using the model on (English):
The problem arise when I tried to fine-tune the model using `MaskedLM` given the `masked_lm_labels`:
It seems that the model forward loop specifies that `loss_fct = CrossEntropy... | {
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https://api.github.com/repos/huggingface/transformers/issues/2441 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2441/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2441/comments | https://api.github.com/repos/huggingface/transformers/issues/2441/events | https://github.com/huggingface/transformers/issues/2441 | 546,570,271 | MDU6SXNzdWU1NDY1NzAyNzE= | 2,441 | is pytorch-pretrained-bert still being maintained in the future? | {
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"Hi, `pytorch-pretrained-BERT` is the name of this library as it was a year ago. It has since evolved into `pytorch-transformers` and now `transformers`. It is the same library.",
"Hi thank you for your reply. But my question really is that I'm now using apis from pytorch-pretrained-BERT directly and will this li... | 1,578 | 1,589 | 1,589 | NONE | null | ## 📚 Migration
<!-- Important information -->
Model I am using (Bert, XLNet....):
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [ ] the official example scripts: (give details)
* [ ] my own modified scripts: (give details)
The tasks I am working on is:
* [ ]... | {
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https://api.github.com/repos/huggingface/transformers/issues/2440 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2440/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2440/comments | https://api.github.com/repos/huggingface/transformers/issues/2440/events | https://github.com/huggingface/transformers/issues/2440 | 546,562,857 | MDU6SXNzdWU1NDY1NjI4NTc= | 2,440 | DistilBertForSequenceClassification returning nans | {
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"I'm facing this issue. How did you resolve this?",
"Me too, and how did you resolve this problem?"
] | 1,578 | 1,640 | 1,578 | NONE | null | ## DistilBertForSequenceClassification returning NaNs
<!-- A clear and concise description of the question. -->
DistilBertForSequenceClassification using the distilbert-base-uncased is returning Nans for both the logits and loss. Has anyone encountered this issue? | {
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https://api.github.com/repos/huggingface/transformers/issues/2439 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2439/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2439/comments | https://api.github.com/repos/huggingface/transformers/issues/2439/events | https://github.com/huggingface/transformers/issues/2439 | 546,384,168 | MDU6SXNzdWU1NDYzODQxNjg= | 2,439 | Generating text with fine-tuned TFGPT2LMHeadModel in python. | {
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"Did you resolve this? I think on the current commit `generate()` still doesn't exist.",
"There is no TensorFlow implementation for the `generate()` method yet. We're working on it, but in the meantime, you could do your own generation loop or use a PyTorch model with the `generate()` method.",
"I need to chang... | 1,578 | 1,619 | 1,578 | NONE | null | I've finetuned GPT2 using the following script:
```
from transformers import GPT2Tokenizer, TFGPT2LMHeadModel
import tensorflow as tf
model = TFGPT2LMHeadModel.from_pretrained("distilgpt2")
tokenizer = GPT2Tokenizer.from_pretrained("distilgpt2")
file_path = 'text.txt'
with open(file_path, encoding="utf-8") a... | {
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https://api.github.com/repos/huggingface/transformers/issues/2438 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2438/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2438/comments | https://api.github.com/repos/huggingface/transformers/issues/2438/events | https://github.com/huggingface/transformers/pull/2438 | 546,325,117 | MDExOlB1bGxSZXF1ZXN0MzYwMDIzNzE1 | 2,438 | Fix typograpical errors | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2438?src=pr&el=h1) Report\n> Merging [#2438](https://codecov.io/gh/huggingface/transformers/pull/2438?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/fb2ab869c6894ea05df97a1372ac9e016ec9c662?src=pr&el=desc) will **d... | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | Fixed few typos. | {
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https://api.github.com/repos/huggingface/transformers/issues/2437 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2437/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2437/comments | https://api.github.com/repos/huggingface/transformers/issues/2437/events | https://github.com/huggingface/transformers/pull/2437 | 546,321,062 | MDExOlB1bGxSZXF1ZXN0MzYwMDIwNDQ2 | 2,437 | Add CamemBERT model for TF2 | {
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"Humm I don't understand why this test is failing I haven't touched to DistilBERT...\r\n\r\n```=================================== FAILURES ===================================\r\n______________ TFDistilBertModelTest.test_pt_tf_model_equivalence ______________\r\n[gw2] linux -- Python 3.5.9 /usr/local/bin/python\r\n... | 1,578 | 1,580 | 1,580 | CONTRIBUTOR | null | Hello,
Here another contribution :) I have implemented the CamemBERT model handling for Tensorflow 2.
I now have the model on my disk, should I send it to you? Or will you generate it from your side? Or should I upload it on my account? As you wish :)
Best.
Julien. | {
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https://api.github.com/repos/huggingface/transformers/issues/2436 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2436/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2436/comments | https://api.github.com/repos/huggingface/transformers/issues/2436/events | https://github.com/huggingface/transformers/pull/2436 | 546,305,156 | MDExOlB1bGxSZXF1ZXN0MzYwMDA3NDQ3 | 2,436 | Added repetition penalty to PPLM example | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2436?src=pr&el=h1) Report\n> Merging [#2436](https://codecov.io/gh/huggingface/transformers/pull/2436?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/74755c89b92e0c0c027221c13fd034afed4d2136?src=pr&el=desc) will **n... | 1,578 | 1,580 | 1,578 | CONTRIBUTOR | null | It was giving awful results, so I added repetition penalty which improved things. | {
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https://api.github.com/repos/huggingface/transformers/issues/2435 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2435/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2435/comments | https://api.github.com/repos/huggingface/transformers/issues/2435/events | https://github.com/huggingface/transformers/pull/2435 | 546,300,699 | MDExOlB1bGxSZXF1ZXN0MzYwMDAzODI3 | 2,435 | update the config.is_decoder=True before initialize the decoder | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2435?src=pr&el=h1) Report\n> Merging [#2435](https://codecov.io/gh/huggingface/transformers/pull/2435?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9261c7f771fccfa2a2cb78ae544adef2f6eb402b?src=pr&el=desc) will **d... | 1,578 | 1,585 | 1,585 | NONE | null | Currently the PreTrainedEncoderDecoder class fails to initialize the "cross-attention layer" since it updates decoder.config.is_decoder = True after decoder initialization. | {
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https://api.github.com/repos/huggingface/transformers/issues/2434 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2434/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2434/comments | https://api.github.com/repos/huggingface/transformers/issues/2434/events | https://github.com/huggingface/transformers/pull/2434 | 546,298,937 | MDExOlB1bGxSZXF1ZXN0MzYwMDAyMzkx | 2,434 | spelling correction | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2434?src=pr&el=h1) Report\n> Merging [#2434](https://codecov.io/gh/huggingface/transformers/pull/2434?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/176d3b30798fce556613da31c698d31cfdfd02aa?src=pr&el=desc) will **n... | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2433 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2433/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2433/comments | https://api.github.com/repos/huggingface/transformers/issues/2433/events | https://github.com/huggingface/transformers/issues/2433 | 546,288,014 | MDU6SXNzdWU1NDYyODgwMTQ= | 2,433 | make test problem | {
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Hello all,
I recently installed this library/module and wanted to run a test with: `make test`
However, things do not go right and I got the following message:
> python -m pytest -n auto --dist=loadfile -s -v ./tests/
> /System/Library/Frameworks/Python.framework/Versions/2.7/Resour... | {
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https://api.github.com/repos/huggingface/transformers/issues/2432 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2432/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2432/comments | https://api.github.com/repos/huggingface/transformers/issues/2432/events | https://github.com/huggingface/transformers/pull/2432 | 546,265,349 | MDExOlB1bGxSZXF1ZXN0MzU5OTc0OTUx | 2,432 | Fix misleading RoBERTa token type ids | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2432?src=pr&el=h1) Report\n> Merging [#2432](https://codecov.io/gh/huggingface/transformers/pull/2432?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9261c7f771fccfa2a2cb78ae544adef2f6eb402b?src=pr&el=desc) will **n... | 1,578 | 1,579 | 1,579 | MEMBER | null | RoBERTa does not actually make use of token type ids. When feeding the output of `encode_plus` used with a pair of sequences to the model directly, it crashes as it cannot handle token type ids that have a value of 1.
This fix returns a list of zeros as the token type ids instead. | {
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https://api.github.com/repos/huggingface/transformers/issues/2431 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2431/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2431/comments | https://api.github.com/repos/huggingface/transformers/issues/2431/events | https://github.com/huggingface/transformers/issues/2431 | 546,264,834 | MDU6SXNzdWU1NDYyNjQ4MzQ= | 2,431 | How can I fine-tune XLM for sentence classification? | {
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"First of, your learning rate might be too low but even then it is odd to see the exact same accuracy all the time. You'll have to have a look at your dataset. Are all your classes in both training, validation, and test set? Are some classes weighted? It's quite hard to help with this.\r\n\r\nAlso, accuracy is a cr... | 1,578 | 1,617 | 1,587 | NONE | null | ## ❓ Questions & Help
I am using the `XLMTokenizer` and `XLMForSequenceClassification` for fine-tuning the `xlm-mlm-en-2048` model to work on a sentence classification problem.
I am using the same configuration as the one that I have used for fine-tuning BERT.
Surprisingly, XLM seems not to be improving at all (T... | {
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https://api.github.com/repos/huggingface/transformers/issues/2430 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2430/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2430/comments | https://api.github.com/repos/huggingface/transformers/issues/2430/events | https://github.com/huggingface/transformers/issues/2430 | 546,258,841 | MDU6SXNzdWU1NDYyNTg4NDE= | 2,430 | T5_INPUTS_DOCSTRING correct!? | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | Is this docstring even correct?
The [CLS] and [SEP] Tokens do not appear in the from google provided dictionaries for the pretrained "t5-base" model. If this is true could you then please provide a correct example of how to use the text generation feature of this almighty transformer? (BoolQ or QA) That would help m... | {
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https://api.github.com/repos/huggingface/transformers/issues/2429 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2429/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2429/comments | https://api.github.com/repos/huggingface/transformers/issues/2429/events | https://github.com/huggingface/transformers/issues/2429 | 546,243,332 | MDU6SXNzdWU1NDYyNDMzMzI= | 2,429 | It occurs error when python run_lm_finetuning.py | {
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"What is your version of transformers?",
"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"
] | 1,578 | 1,584 | 1,584 | NONE | null |
- Environment
> - python 3.6.9
> - torch 1.1.0
> - have installed transformers
- Command
> python run_lm_finetuning.py --output_dir=output --model_type=bert --model_name_or_path=bert-base-uncased --do_train --train_data_file=$TRAIN_FILE --do_eval --eval_data_file=$TEST_FILE --mlm
... | {
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https://api.github.com/repos/huggingface/transformers/issues/2428 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2428/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2428/comments | https://api.github.com/repos/huggingface/transformers/issues/2428/events | https://github.com/huggingface/transformers/issues/2428 | 546,183,316 | MDU6SXNzdWU1NDYxODMzMTY= | 2,428 | Padding part output in BERT NER task is not [PAD]? | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | ## ❓ Questions & Help
Hello ,my friends.
I have a problem while I am trying to do a Chinese NER task.
For easy to understand I will use some English words instead.
Assume padding length =128, here is the sentence:
> [CLS] Marilyn Monroe is an famous actress. [SEP] [PAD] [PAD] ... [PAD]
After I put... | {
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https://api.github.com/repos/huggingface/transformers/issues/2427 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2427/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2427/comments | https://api.github.com/repos/huggingface/transformers/issues/2427/events | https://github.com/huggingface/transformers/issues/2427 | 546,181,498 | MDU6SXNzdWU1NDYxODE0OTg= | 2,427 | ALBERT model does not work as expected | {
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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"
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<!-- A clear and concise description of the question. -->
Hi,
I am new to Transformers. I tried the example for class AlbertForQuestionAnswering from huggingface.co. The results in each run are different and not correct. Please help.
Thanks,
Tuan Anh | {
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https://api.github.com/repos/huggingface/transformers/issues/2426 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2426/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2426/comments | https://api.github.com/repos/huggingface/transformers/issues/2426/events | https://github.com/huggingface/transformers/pull/2426 | 546,167,467 | MDExOlB1bGxSZXF1ZXN0MzU5ODk1MTM4 | 2,426 | Make doc regarding masked indices more clear | {
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"Fantastic, thanks @r0mainK!"
] | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | See this [issue](https://github.com/huggingface/transformers/issues/2418) for details, basically there used to be different ways of specifying masked indices (either -1 or -100), which was fixed by this [commit](https://github.com/huggingface/transformers/commit/418589244d263087f1d48655f621a65f2a5fcba6).
However the... | {
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https://api.github.com/repos/huggingface/transformers/issues/2425 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2425/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2425/comments | https://api.github.com/repos/huggingface/transformers/issues/2425/events | https://github.com/huggingface/transformers/issues/2425 | 546,142,061 | MDU6SXNzdWU1NDYxNDIwNjE= | 2,425 | Tokenize whole sentence vs. tokenize words in sentence then concat | {
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"Seems like this is a duplicate of https://github.com/huggingface/transformers/issues/2140",
"Thank you for mentioning the same issue!"
] | 1,578 | 1,578 | 1,578 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
When using En-Fr XLMModel in transformers library,
I found that result from tokenizing a whole sentence is different from tokenizing words in the sentence and then concatenate.
My configuration is as below
**(XLMModel, XLMTokenizer... | {
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https://api.github.com/repos/huggingface/transformers/issues/2424 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2424/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2424/comments | https://api.github.com/repos/huggingface/transformers/issues/2424/events | https://github.com/huggingface/transformers/issues/2424 | 546,116,189 | MDU6SXNzdWU1NDYxMTYxODk= | 2,424 | convert tf ckpt to pytorch_model.bin, load back model(TFBertModel), will loss params | {
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"Try changing it from TFBERT model to BertModel. Since you already converted it to a pytorch checkpoint. ",
"@zanderkent \r\nIf have any tool can convert tf ckpt to tf_model.h5. So I can use TFBert Class to load.\r\n\r\nBecause I with use tf2 model.fit to train , and use the tf2 strategy to train dist.",
"If I... | 1,578 | 1,594 | 1,589 | NONE | null | ```
import os
pretrained_path = 'Models/chinese_L-12_H-768_A-12'
config_path = os.path.join(pretrained_path, 'bert_config.json')
checkpoint_path = os.path.join(pretrained_path, 'bert_model.ckpt.index')
config = BertConfig.from_pretrained(config_path)
model = BertForPreTraining.from_pretrained(checkpoint_path, f... | {
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https://api.github.com/repos/huggingface/transformers/issues/2423 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2423/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2423/comments | https://api.github.com/repos/huggingface/transformers/issues/2423/events | https://github.com/huggingface/transformers/issues/2423 | 546,093,851 | MDU6SXNzdWU1NDYwOTM4NTE= | 2,423 | [DistillBERT] tokenizer issue of multilingual-cased | {
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"Hi, thanks for raising this issue! This is due to the lower casing parameter which is not correctly initialized for DistilBERT. I'm fixing it in #2469.",
"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 ... | 1,578 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): DistilBERT
Language I am using the model on (English, Chinese....): Korean
The problem arise when using:
* [ ] the official example scripts: (give details)
* [x] my own modified scripts: (give details)
The tasks I am working ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2422 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2422/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2422/comments | https://api.github.com/repos/huggingface/transformers/issues/2422/events | https://github.com/huggingface/transformers/issues/2422 | 546,054,113 | MDU6SXNzdWU1NDYwNTQxMTM= | 2,422 | Is any possible for load local model ? | {
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"You can use that third option and use a directory. Alternatively, I think you can also do\r\n\r\n```python\r\nmodel = DistilBertModel(DistilBertConfig())\r\nmodel.load_state_dict(torch.load(<path>))\r\n```",
"Thanks for your advice . I'll have a try!",
"I found a solution. If you want use a pretrained model of... | 1,578 | 1,641 | 1,578 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
For some reason(GFW), I need download pretrained model first then load it locally. But I read the source code where tell me below:
```
pretrained_model_name_or_path: either:
- a string with the `shortcut name` of a pre-trained ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2421 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2421/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2421/comments | https://api.github.com/repos/huggingface/transformers/issues/2421/events | https://github.com/huggingface/transformers/issues/2421 | 546,015,893 | MDU6SXNzdWU1NDYwMTU4OTM= | 2,421 | [Albert] SentencePiece Error with AlbertTokenizer | {
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"Actually, looking more closely, this seems to be a `sentencepiece` issue, right?",
"Hi! Is there a way you could isolate where the error happens? Is it when you're initializing the tokenizer with the line `tokenizer = AlbertTokenizer.from_pretrained(\"albert-base-v2\")` ?",
"Hi! No initialization seems to work... | 1,578 | 1,619 | 1,584 | CONTRIBUTOR | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):Albert v2
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)
The tasks I am working on... | {
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https://api.github.com/repos/huggingface/transformers/issues/2420 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2420/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2420/comments | https://api.github.com/repos/huggingface/transformers/issues/2420/events | https://github.com/huggingface/transformers/issues/2420 | 546,015,044 | MDU6SXNzdWU1NDYwMTUwNDQ= | 2,420 | Bug Transformers 2.3.0 - ValueError: invalid literal for int() with base 10: 'pytorch' | {
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"Hi, thank you for raising this issue. Could you please let me know if 27c1b656cca75efa0cc414d3bf4e6aacf24829de fixed this issue by trying the updated script?",
"Hello, to solve this problem I added my checkpoint to a folder that has the same Transformer output.\r\n\r\n**new folder -> chekpoint-0**\r\n\r\nFolders... | 1,578 | 1,587 | 1,587 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): BERT
Language I am using the model on (English, Chinese....): PT-BR (Multilingual)
The problem arise when using:
* [ ] the official example scripts: (give details)
* [ ] my own modified scripts: (give details)
The tasks I am w... | {
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https://api.github.com/repos/huggingface/transformers/issues/2419 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2419/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2419/comments | https://api.github.com/repos/huggingface/transformers/issues/2419/events | https://github.com/huggingface/transformers/issues/2419 | 546,011,124 | MDU6SXNzdWU1NDYwMTExMjQ= | 2,419 | Is there a way to reduce the vocabulary size? | {
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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"
] | 1,578 | 1,584 | 1,584 | NONE | null | ## ❓ Questions & Help
For fine tuning task is it possible to reduce the vocabulary size?
does simply editing the vocab & config file work?
<!-- A clear and concise description of the question. -->
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https://api.github.com/repos/huggingface/transformers/issues/2418 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2418/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2418/comments | https://api.github.com/repos/huggingface/transformers/issues/2418/events | https://github.com/huggingface/transformers/issues/2418 | 545,797,360 | MDU6SXNzdWU1NDU3OTczNjA= | 2,418 | Unclear documentation for indice masking | {
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"Okay my bad it seems this was actually intentional, [this commit](https://github.com/huggingface/transformers/commit/418589244d263087f1d48655f621a65f2a5fcba6 ) was passed and integrated in either version 2.2.2 or 2.3, causing the error on my version. It seems the current proper way to do this is indeed by specifyi... | 1,578 | 1,597 | 1,585 | CONTRIBUTOR | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): CamemBERT but this probly applies to all MLMs.
Language I am using the model on (English, Chinese....): French
The problem arise when using:
* [x] my own modified scripts, but I suspect that `https://github.com/huggingface/transfo... | {
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https://api.github.com/repos/huggingface/transformers/issues/2417 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2417/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2417/comments | https://api.github.com/repos/huggingface/transformers/issues/2417/events | https://github.com/huggingface/transformers/issues/2417 | 545,733,209 | MDU6SXNzdWU1NDU3MzMyMDk= | 2,417 | Albert to torchscript is not working | {
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"Hi, the models can be traced using the `torch.jit.trace` method, not the `torch.jit.script`. This requires inputs of the same shape that will be used for inference. Here's an example:\r\n\r\n```py\r\nfrom transformers import AlbertForQuestionAnswering\r\nimport torch\r\n\r\ninputs = torch.tensor([[1,2,3]])\r\n\r\n... | 1,578 | 1,584 | 1,584 | NONE | null | Trying to export torchscript module for AlbertForQuestionAnswering.
```
self.model = AlbertForQuestionAnswering.from_pretrained(self.model_dir)
script_model = torch.jit.script(self.model)
script_model.save("script_model.pt")
```
Getting following exception:
```
Python builtin <built-in function next> is curre... | {
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https://api.github.com/repos/huggingface/transformers/issues/2416 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2416/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2416/comments | https://api.github.com/repos/huggingface/transformers/issues/2416/events | https://github.com/huggingface/transformers/pull/2416 | 545,723,015 | MDExOlB1bGxSZXF1ZXN0MzU5NTQwMjMy | 2,416 | Fixed answer structure for QAPipeline | {
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"Hi can you confirm this PR is a subset of #2459 and that we can close it now that #2459 is merged?",
"Sure, thanks!!\n________________________________\nFrom: Thomas Wolf <notifications@github.com>\nSent: Monday, January 13, 2020 8:33:47 PM\nTo: huggingface/transformers <transformers@noreply.github.com>\nCc: Rish... | 1,578 | 1,578 | 1,578 | CONTRIBUTOR | null | Updated answers list in QuestionAnswering pipeline to handle multiple (question, context) pair with (top-k >1) solutions | {
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"Took me most of the day to figure this out, set the `do_sample` arg to `True`\r\n\r\n```\r\noutputs = model.generate(input_ids=input_ids, num_beams=5, num_return_sequences=3, do_sample=True)\r\n```",
"Actually, I don't want to do sampling because that is random and would give different results each time I run fo... | 1,578 | 1,705 | 1,583 | NONE | null | ## ❓ Questions & Help
I am doing greedy beam search (without sampling to avoid randomness) using GPT-2. However, all the returned sequences are same. Why is that the case? Shouldn't it give N best and different sequences?
```python
model = GPT2LMHeadModel.from_pretrained('gpt2-medium').cuda()
tokenizer = GPT2To... | {
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https://api.github.com/repos/huggingface/transformers/issues/2414 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2414/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2414/comments | https://api.github.com/repos/huggingface/transformers/issues/2414/events | https://github.com/huggingface/transformers/pull/2414 | 545,691,060 | MDExOlB1bGxSZXF1ZXN0MzU5NTEzODQ4 | 2,414 | Serializing XLMRobertaTokenizer | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2414?src=pr&el=h1) Report\n> Merging [#2414](https://codecov.io/gh/huggingface/transformers/pull/2414?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0ffc8eaf53542092271a208a52e881668e753e72?src=pr&el=desc) will **d... | 1,578 | 1,579 | 1,579 | CONTRIBUTOR | null | I am currently trying to use the XLMRobertaTokenizer in a multiprocessor setting. To do this, the XLMRobertaTokenizer needs to be serializable. Currently XLMRobertaTokenizer is not serializable while other tokenizers such as AlbertTokenizer are.
This PR adds the __getstate__ and __setstate__ methods to XLMRobertaTok... | {
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https://api.github.com/repos/huggingface/transformers/issues/2413 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2413/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2413/comments | https://api.github.com/repos/huggingface/transformers/issues/2413/events | https://github.com/huggingface/transformers/issues/2413 | 545,652,276 | MDU6SXNzdWU1NDU2NTIyNzY= | 2,413 | How to use transformers-cli serve , how to set up on the server side? | {
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"Hi @zhoudoufu ! You need to fully specify the model:\r\n\r\n```bash\r\ntransformers-cli serve --task feature-extraction --model distilbert-base-uncased --config distilbert-base-uncased --tokenizer distilbert-base-uncased\r\n```\r\n\r\nThen you should be able to call:\r\n\r\n```bash\r\ncurl -X POST \"http://localho... | 1,578 | 1,579 | 1,579 | NONE | null | ## ❓ Questions & Help
Hi, I would like to make the transformers based models running as a server on a remote machine, as the way bert-as-server did.
I suppose I could call the transformers-cli serve command on the server side, but I haven't find much clue on how to make it running on the client part.
BTW. I am ... | {
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