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https://api.github.com/repos/huggingface/transformers/issues/3413 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3413/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3413/comments | https://api.github.com/repos/huggingface/transformers/issues/3413/events | https://github.com/huggingface/transformers/pull/3413 | 586,999,880 | MDExOlB1bGxSZXF1ZXN0MzkzMDIzNjQ0 | 3,413 | Add t5 to pipeline(task='summarization') | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3413?src=pr&el=h1) Report\n> Merging [#3413](https://codecov.io/gh/huggingface/transformers/pull/3413?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e392ba6938f50655a195ea7ec8a260b1e9fc6058&el=desc) will **increase... | 1,585 | 1,585 | 1,585 | MEMBER | null | This PR:
- adds T5 to summarization piplines.
- adds warnings and better defaults to Bart/T5 summarization
- removes unnecessary assert in generate() function
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"This should be fixed on master since a8e3336a850e856188350a93e67d77c07c85b8af.\r\n\r\nFeel free to re-open if that's not the case.",
"You might want to upgrade your repo.\r\n`pip install --upgrade .`"
] | 1,585 | 1,585 | 1,585 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): BERT
Language I am using the model on (English, Chinese ...): ENglish
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3411 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3411/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3411/comments | https://api.github.com/repos/huggingface/transformers/issues/3411/events | https://github.com/huggingface/transformers/pull/3411 | 586,904,415 | MDExOlB1bGxSZXF1ZXN0MzkyOTQ1NTk3 | 3,411 | Add t5 summarization example | {
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"> pending my comments\r\n\r\nVery much down to share the summarization code in another PR!",
"Code quality test fails because of unpinned isort library (see https://github.com/huggingface/transformers/pull/3449)"
] | 1,585 | 1,585 | 1,585 | MEMBER | null | Adds TF 2.0 Example for T5 summarization.
Adds dataset download file via `tensorflow_datasets` and a rouge scorer.
Example is currently being tested on T5-large on GPU to see how rouge scorer performs in comparsion to `examples/summarization/bart` rouge scorer. | {
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https://api.github.com/repos/huggingface/transformers/issues/3410 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3410/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3410/comments | https://api.github.com/repos/huggingface/transformers/issues/3410/events | https://github.com/huggingface/transformers/pull/3410 | 586,900,490 | MDExOlB1bGxSZXF1ZXN0MzkyOTQyNDg0 | 3,410 | Added precisions in SciBERT-NLI model card | {
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- Added training time and training hardware
- Added lowercasing and Max. Seq. Length to parameters table | {
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https://api.github.com/repos/huggingface/transformers/issues/3408 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3408/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3408/comments | https://api.github.com/repos/huggingface/transformers/issues/3408/events | https://github.com/huggingface/transformers/pull/3408 | 586,850,275 | MDExOlB1bGxSZXF1ZXN0MzkyOTAxNTA3 | 3,408 | [model_cards] 🇹🇷 Add new BERTurk models | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3408?src=pr&el=h1) Report\n> Merging [#3408](https://codecov.io/gh/huggingface/transformers/pull/3408?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e392ba6938f50655a195ea7ec8a260b1e9fc6058&el=desc) will **decrease... | 1,585 | 1,585 | 1,585 | COLLABORATOR | null | Hi,
this PR adds three new BERT models for Turkish:
* `dbmdz/bert-base-turkish-uncased` - uncased model with a vocab size of 32k
* `dbmdz/bert-base-turkish-128k-cased` - cased model with a vocab size of 128k
* `dbmdz/bert-base-turkish-128k-uncased` - uncased model with a vocab size of 128k
Models (incl. `tok... | {
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https://api.github.com/repos/huggingface/transformers/issues/3407 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3407/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3407/comments | https://api.github.com/repos/huggingface/transformers/issues/3407/events | https://github.com/huggingface/transformers/issues/3407 | 586,784,494 | MDU6SXNzdWU1ODY3ODQ0OTQ= | 3,407 | AdamW in HuggingFace is different from AdamW in Pytorch | {
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"@songsuoyuan , if you notice the line:\r\n p.data.mul_(1 - group['lr'] * group['weight_decay'])\r\nThe multiplication factor is (1 - group['lr'] * group['weight_decay']) .\r\nAll subsequent first and second order moment calculations are not using p.data anymore.\r\nThis means we would get the same result if... | 1,585 | 1,670 | 1,590 | NONE | null | # ❓ Question
I just noticed that the implementation of AdamW in HuggingFace is different from PyTorch. The previous AdamW first updates the gradient then apply the weight decay. However, in the paper (Decoupled Weight Decay Regularization, link: https://arxiv.org/abs/1711.05101) and the implementation of Pytorch, th... | {
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* elgeish/cs224n-squad2.0-albert-base-v2
* elgeish/cs224n-squad2.0-albert-large-v2
* elgeish/cs224n-squad2.0-albert-xxlarge-v1
* elgeish/cs224n-squad2.0-distilbert-base-uncased
* elgeish/cs224n-squad2.0-roberta-base
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https://api.github.com/repos/huggingface/transformers/issues/3405 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3405/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3405/comments | https://api.github.com/repos/huggingface/transformers/issues/3405/events | https://github.com/huggingface/transformers/pull/3405 | 586,719,590 | MDExOlB1bGxSZXF1ZXN0MzkyNzk3ODQx | 3,405 | Glue test processors and predictions | {
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"hm my local isort passes even on a clean env\r\n```\r\n(transformers) shoarora@sho-5:~/transformers ‹glue-test-processors›\r\n$ make style\r\nblack --line-length 119 --target-version py35 examples templates tests src utils\r\nAll done! ✨ 🍰 ✨\r\n243 files left unchanged.\r\nisort --recursive examples templates tes... | 1,585 | 1,590 | 1,590 | CONTRIBUTOR | null | Adress #3176
- Adds a function to load the test dataset for each GLUE task processor.
- Update `run_glue.py` example script to add a `--do_test` flag for producing test set predictions in a `.tsv` file, submittable to the [GLUE scoreboard](https://gluebenchmark.com/).
- Adds a couple extra feature flags to `run_g... | {
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https://api.github.com/repos/huggingface/transformers/issues/3404 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3404/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3404/comments | https://api.github.com/repos/huggingface/transformers/issues/3404/events | https://github.com/huggingface/transformers/issues/3404 | 586,656,991 | MDU6SXNzdWU1ODY2NTY5OTE= | 3,404 | [Bart]example---BartForConditionalGeneration | {
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from transformers import BartTokenizer, BartForConditionalGeneration, BartConfig
model = BartForConditionalGeneration.from_pretrained('bart-large-cnn')
tokenizer = BartTokenizer.from_pretrained('bart-large-cnn')
ARTICLE_TO_SUMMARIZE = "My friends are cool but they eat too many carbs."
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https://api.github.com/repos/huggingface/transformers/issues/3403 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3403/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3403/comments | https://api.github.com/repos/huggingface/transformers/issues/3403/events | https://github.com/huggingface/transformers/pull/3403 | 586,590,983 | MDExOlB1bGxSZXF1ZXN0MzkyNjk4NDk5 | 3,403 | [examples] Use AutoModels in more examples | {
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- [ ] run_multiple_choice
- [ ] run_xnli
- [ ] test_hans
- [ ] run_mmimdb
- [ ] (maybe) run_generation | {
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"As a non-blocking question, I do note that a lot of the examples use argparse to parse comparatively long lists of arguments. I've maintained the extant style in this PR to avoid causing noise and confusion Would it be acceptable if I broke with this style to use a JSON file to store all the arguments for an exper... | 1,585 | 1,591 | 1,591 | CONTRIBUTOR | null | This PR presents an example seq2seq use case and bug fixes necessary for this to execute with reasonable accuracy.
The utils_seq2seq.py file defines the data format for training data, and the run_seq2seq.py file takes training, development, and test data and produces a model. The README.md discusses how to execute ... | {
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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"
] | 1,584 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3400 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3400/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3400/comments | https://api.github.com/repos/huggingface/transformers/issues/3400/events | https://github.com/huggingface/transformers/pull/3400 | 586,488,024 | MDExOlB1bGxSZXF1ZXN0MzkyNjE0Mjcy | 3,400 | [Bart: example] drop columns that are exclusively pad_token_id from input_ids | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3400?src=pr&el=h1) Report\n> Merging [#3400](https://codecov.io/gh/huggingface/transformers/pull/3400?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f7dcf8fcea4d486544f221032625a97ad7dc5405&el=desc) will **not chan... | 1,584 | 1,585 | 1,585 | CONTRIBUTOR | null | reasoning: These columns slow down computation, but do not change output.
impact: this reduces the runtime to compute EVAL on the CNN examples from 2h to 1:37 before any other changes.
I'm open to putting this as a method on `PretrainedTokenizer` if others find it useful.
@joeddav you might find this useful.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3399 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3399/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3399/comments | https://api.github.com/repos/huggingface/transformers/issues/3399/events | https://github.com/huggingface/transformers/issues/3399 | 586,314,065 | MDU6SXNzdWU1ODYzMTQwNjU= | 3,399 | Trying to train a GPT2 from scratch | {
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"This [blogpost](https://huggingface.co/blog/how-to-train) might be interesting, have you seen it?",
"Yes, saddly the part in which I am interested in, namely, instantiating and training/testing from scratch with my own data are not almost not or not at all described.\r\n\r\nDo you know if it is possible to feed ... | 1,584 | 1,625 | 1,585 | NONE | null | Hi !
I am trying to use a GPT2 architecture for musical applications and consequently need to train it from scratch. After a bit of googling I found that the issue #1714 already had "solved" the question but when I try the to run
```Python
from transformers import GPT2Config, GPT2Model
NUMLAYER = 4
NUMHEAD =... | {
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"Merging with deep suspicion that circleci failure is spurious."
] | 1,584 | 1,585 | 1,585 | CONTRIBUTOR | null | This fixes `test_dummy_inputs`, which was failing on GPU because dummy inputs were put on CPU even if model was on GPU. | {
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https://api.github.com/repos/huggingface/transformers/issues/3397 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3397/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3397/comments | https://api.github.com/repos/huggingface/transformers/issues/3397/events | https://github.com/huggingface/transformers/issues/3397 | 586,242,351 | MDU6SXNzdWU1ODYyNDIzNTE= | 3,397 | Supported language information by model | {
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"Hi Alex, language support is described in the metadata in the models' [model cards](https://github.com/huggingface/transformers/tree/master/model_cards) and then rendered in a searchable way on the https://huggingface.co/models website.\r\n\r\nThe mapping is not exhaustive right now because a lot of the canonical/... | 1,584 | 1,591 | 1,591 | CONTRIBUTOR | null | Hi there,
Another feature/documentation request. I am evaluating the language support of all pre-trained models distributed via huggingface :)
I have quickly looked into the code and happily found that XLNet and FlauBERT models have that information: https://github.com/huggingface/transformers/search?q=lang&unsco... | {
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https://api.github.com/repos/huggingface/transformers/issues/3396 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3396/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3396/comments | https://api.github.com/repos/huggingface/transformers/issues/3396/events | https://github.com/huggingface/transformers/issues/3396 | 586,234,245 | MDU6SXNzdWU1ODYyMzQyNDU= | 3,396 | Cannnot Import from transformers | {
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"In order to import the tensorflow models, you need to have TF2+ installed. Please update your environment info if you *do* have TF2 installed in the environment in which you're running your script.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if n... | 1,584 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
I am trying to import TFGPT2LMHeadModel in transformers.Python giving below error.
cannot import name 'TFGPT2LMHeadModel' from 'transformers
## To reproduce
import tensorflow as tf
from transformers import TFGPT2LMHeadModel,GPT2Tokenizer
tokenizer = GPT2Tokenizer.from_pretrained("gpt... | {
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"As for guidelines about making MMBT work, here is an example on the mm-imdb dataset: https://github.com/huggingface/transformers/blob/master/examples/mm-imdb/run_mmimdb.py.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs... | 1,584 | 1,620 | 1,592 | NONE | null | Hello, it would be great if more **multimodal** BERT models are included in the library. I have noticed that MMBT from Facebook is provided; however, I was unable to find some guidelines about how to make it work with the help of 🤗 Transformers.
Possible models can be [VilBERT](https://arxiv.org/abs/1908.02265), [... | {
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"Thanks for sharing! Any way you could format the training results as a Markdown table? Might be more readable.",
"I'll merge for now"
] | 1,584 | 1,585 | 1,585 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3392 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3392/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3392/comments | https://api.github.com/repos/huggingface/transformers/issues/3392/events | https://github.com/huggingface/transformers/pull/3392 | 586,137,187 | MDExOlB1bGxSZXF1ZXN0MzkyMzI2NTQz | 3,392 | Add comparison table with older brother in family | {
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https://api.github.com/repos/huggingface/transformers/issues/3391 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3391/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3391/comments | https://api.github.com/repos/huggingface/transformers/issues/3391/events | https://github.com/huggingface/transformers/pull/3391 | 586,131,207 | MDExOlB1bGxSZXF1ZXN0MzkyMzIxNTcz | 3,391 | Create card for the model | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3391?src=pr&el=h1) Report\n> Merging [#3391](https://codecov.io/gh/huggingface/transformers/pull/3391?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cf72479bf11bf7fbc499a518896dfd3cafdd0b21&el=desc) will **increase... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3390 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3390/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3390/comments | https://api.github.com/repos/huggingface/transformers/issues/3390/events | https://github.com/huggingface/transformers/issues/3390 | 586,120,611 | MDU6SXNzdWU1ODYxMjA2MTE= | 3,390 | adding --fp16 to run_language_modeling and increase batch size but cuda out of memory error | {
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"Hi all\r\n\r\nI am using colab , 1 GPU , Tesla P100-PCIE-16GB\r\n\r\ncode below ran OK \r\n\r\n!python /content/transformers/examples/run_language_modeling.py \\\r\n --output_dir=/content/outputs \\\r\n --model_type=bert \\\r\n --model_name_or_path=bert-base-cased \\\r\n --num_train_epochs 1\\\r\n ... | 1,584 | 1,587 | 1,587 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"Hey @jia-zhuang,\r\n\r\nAs you can see [here](https://github.com/huggingface/transformers/blob/master/examples/ner/run_tf_ner.py#L525) I update the classification layer to add a softmax as activation, then the `from_logits=True` is not necessary.",
"@jplu Thanks for your reply! I learn a lot from your code."
] | 1,584 | 1,585 | 1,585 | NONE | null | Found a bug in [run_tf_ner.py](https://github.com/huggingface/transformers/blob/master/examples/ner/run_tf_ner.py) at line 170 and 325:
```python
loss_fct = tf.keras.losses.SparseCategoricalCrossentropy(reduction=tf.keras.losses.Reduction.NONE)
```
refer to [tf.keras.losses.SparseCategoricalCrossentropy](https://... | {
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https://api.github.com/repos/huggingface/transformers/issues/3388 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3388/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3388/comments | https://api.github.com/repos/huggingface/transformers/issues/3388/events | https://github.com/huggingface/transformers/pull/3388 | 586,107,172 | MDExOlB1bGxSZXF1ZXN0MzkyMzAxODE0 | 3,388 | Lazy text dataset loading for language modelling with PyTorch | {
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"Can anyone advise on the failed tests? Seems to failing in parts of the code-base I haven't touched.",
"@GCHQResearcher92457 Yes, the failures are unrelated.",
"Most recent failures are unrelated.",
"Quick question in passing because I am working on something close, did you run some benchmark to see how this... | 1,584 | 1,589 | 1,589 | NONE | null | #3083
Added a lazy text dataset using linecache to run_language_modeling.py. Slightly refactored collate_fn construction to accommodate the different collate functions needed for a lazy dataset vs a in-memory dataset. | {
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"**Update:**\r\n\r\nWhen I pre-process a token not applied lower case, its EM from the initial weights was almost 76.85. (I couldn't remember exact score.)\r\n\r\nIn the TensorFlow version, its initial weights outputs 76.30 EM.\r\nHowever, their pre-processing has been applied to lower case for a question, document... | 1,584 | 1,588 | 1,585 | NONE | null | Hi, I am implementing T5 model on the SQuAD 1.1 dataset.
When I fine-tune the model with the Adam or AdaFactor optimizier, validation accuracy goes down.
But, the training accuracy goes up.
Could you give to me any advice for me?
I feed into the model as below:
input_ids = ['(QUESTION)', Q_W1, Q_W2, ..., '... | {
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"Proposed a fix that didn't work out-of-the-box with official ALBERT models. Still looking into it, will keep you posted.",
"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",
"Closing s... | 1,584 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🐛 Bug
## Information
The model conversion script `convert_pytorch_checkpoint_to_tf2.py` seems to be not working properly for ALBERT models.
It fails on the pre-trained models officially released by Google which are converted to PyTorch models with `convert_albert_original_tf_checkpoint_to_pytorch.py`.
## T... | {
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"Indeed, those notebooks are not up-to-date and should be deprecated.",
"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"
] | 1,584 | 1,591 | 1,591 | CONTRIBUTOR | null | On this page [https://huggingface.co/transformers/notebooks.html](https://huggingface.co/transformers/notebooks.html)
The first link is fine. The others give 404. Just thought you would like to know | {
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"Hi @yagelardan ,\r\n\r\nIn order to fine-tune gpt2 you should be able to use this example [script](https://github.com/huggingface/transformers/blob/master/examples/run_language_modeling.py)\r\n\r\nAlso, you can refer to this issue https://github.com/huggingface/transformers/issues/1407 where people already trained... | 1,584 | 1,585 | 1,585 | NONE | null | I'm trying to fine-tune GPT2 to generate shakespeare text.
I have variable "train_examples", which is list of InputExamples:
```
>> print(train_examples)
<__main__.InputExample at 0x7f55e0fafd68>,
<__main__.InputExample at 0x7f55e0fafda0>,
<__main__.InputExample at 0x7f55e0fafef0>,
<__main__.InputExample at... | {
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`tests/test_modeling_encoder_decoder.py`.
Tests include:
- forward `input_ids` and `decoder_input_ids` for Bert-Bert
- backprop using masked language model loss for Bert-Bert
- backprop using "conventional" language model loss for Be... | {
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"We would need a bit more information to understand the issue. A reproducible code example would be even better.",
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https://api.github.com/repos/huggingface/transformers/issues/3381 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3381/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3381/comments | https://api.github.com/repos/huggingface/transformers/issues/3381/events | https://github.com/huggingface/transformers/issues/3381 | 585,761,943 | MDU6SXNzdWU1ODU3NjE5NDM= | 3,381 | [BART] test_dummy_inputs fails on GPU | {
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RuntimeError: Expected object of device type cuda but got device type cpu for argument #3 'index' in call to _th_index_select
```
Easy fix, but putting here so I don't forget! | {
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https://api.github.com/repos/huggingface/transformers/issues/3380 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3380/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3380/comments | https://api.github.com/repos/huggingface/transformers/issues/3380/events | https://github.com/huggingface/transformers/issues/3380 | 585,746,714 | MDU6SXNzdWU1ODU3NDY3MTQ= | 3,380 | Can't save DistilBert model. | {
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"Could you provide all the information related to your environment as the bug template recommends?\r\n\r\nCan you try installing from master? In the latest pypi version, we only handled the `save_pretrained` method, not the `save`/`save_weights` methods. This should have been changed with #3103.",
"The changes in... | 1,584 | 1,591 | 1,591 | NONE | null | Model:
```
input_layer = tf.keras.layers.Input(shape = (attention_mask.shape[1],), dtype='int64')
bert = TFDistilBertModel.from_pretrained("distilbert-base-cased")(input_layer)
bert = bert[0][:,0,:]
bert = tf.keras.layers.Dense(units=20, activation='relu')(bert)
classifier = tf.keras.layers.Dense(un... | {
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"Agree and I follow you. ",
"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"
] | 1,584 | 1,590 | 1,590 | CONTRIBUTOR | null | # 🚀 Feature request
For a clearly, flexible packages, I think there is no need including data processor for certain data.
## Motivation
In the past, it was easy using transformers to do research, since the module is explicit and clear.
When reading example, it was easy tracing the code to apply on a new data... | {
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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"
] | 1,584 | 1,592 | 1,592 | CONTRIBUTOR | null | Here is the existing logic: copied below for convenience
https://github.com/huggingface/transformers/blob/bbf26c4e619cf42106163e1e2cd5ff98b936ff93/tests/test_modeling_common.py#L489)
```python
model_embed = model.resize_token_embeddings(config.vocab_size)
cloned_embeddings = model_embed.weight.clone()
# Check th... | {
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https://api.github.com/repos/huggingface/transformers/issues/3377 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3377/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3377/comments | https://api.github.com/repos/huggingface/transformers/issues/3377/events | https://github.com/huggingface/transformers/issues/3377 | 585,727,878 | MDU6SXNzdWU1ODU3Mjc4Nzg= | 3,377 | RobertaTokenizer doesn't have 'batch_encode_plus' | {
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"Hi, this is probably because you're using an old version of `transformers`. Version 2.8 doesn't exist, the latest is 2.5.1 ...",
"Sorry, I accidently put 2.8. The version I have is: 2.5.1\r\nI am going to edit the post. ",
"This issue has been automatically marked as stale because it has not had recent activit... | 1,584 | 1,624 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): RoBERTa
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [X] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
Following the tutorial on how ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3373 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3373/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3373/comments | https://api.github.com/repos/huggingface/transformers/issues/3373/events | https://github.com/huggingface/transformers/issues/3373 | 585,642,574 | MDU6SXNzdWU1ODU2NDI1NzQ= | 3,373 | Add example code for CRF heads | {
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"Also https://github.com/huggingface/transformers/pull/2249/",
"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"
] | 1,584 | 1,590 | 1,590 | CONTRIBUTOR | null |
# Add example `crf/` with heads that force structural output dependencies.
(Mostly a note to myself as a side project)
## Model description
As requested in: https://github.com/huggingface/transformers/pull/3009 there are some tasks and languages where it is useful to have final layer structural dependenci... | {
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https://api.github.com/repos/huggingface/transformers/issues/3372 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3372/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3372/comments | https://api.github.com/repos/huggingface/transformers/issues/3372/events | https://github.com/huggingface/transformers/issues/3372 | 585,641,315 | MDU6SXNzdWU1ODU2NDEzMTU= | 3,372 | BERT pretrained checkpoints | {
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"We converted them from Google's checkpoints."
] | 1,584 | 1,584 | 1,584 | NONE | null | # ❓ Questions & Help
Did you pretrain the BERT cased checkpoints with huggingface or convert it from google's checkpoints? | {
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https://api.github.com/repos/huggingface/transformers/issues/3371 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3371/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3371/comments | https://api.github.com/repos/huggingface/transformers/issues/3371/events | https://github.com/huggingface/transformers/pull/3371 | 585,632,240 | MDExOlB1bGxSZXF1ZXN0MzkxOTQ4MzU2 | 3,371 | [Bart/Memory] Two separate, smaller decoder attention masks | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3371?src=pr&el=h1) Report\n> Merging [#3371](https://codecov.io/gh/huggingface/transformers/pull/3371?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cf72479bf11bf7fbc499a518896dfd3cafdd0b21&el=desc) will **decrease... | 1,584 | 1,585 | 1,585 | CONTRIBUTOR | null | ### Background
The bart decoder requires two masks: one to ignore padding tokens, the other (`causal_mask`), to avoid attending to future tokens during training.
Previously, `_prepare_bart_decoder_inputs` combined these two masks into one float_mask of shape `(bsz, 1, tgt_len, tgt_len)` filled with -inf for tokens... | {
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https://api.github.com/repos/huggingface/transformers/issues/3370 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3370/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3370/comments | https://api.github.com/repos/huggingface/transformers/issues/3370/events | https://github.com/huggingface/transformers/pull/3370 | 585,580,968 | MDExOlB1bGxSZXF1ZXN0MzkxOTEzNjQz | 3,370 | [Seq2Seq Generation] Call encoder before expanding input_ids | {
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"Like the change a lot! \r\nOne question I asked myself: With this change the `encoder_outputs` which are the same point to the same memory address -> could that lead to problems? Probably not because the `encoder_outputs` are never changed, right? \r\n\r\nI'd just propose some renaming."
] | 1,584 | 1,585 | 1,585 | CONTRIBUTOR | null | Proposing to call model.encoder before expanding `input_ids` to `effective_batch_size*num_beams`.
For Bart, this saves 1.5 GB of GPU mem on batch_size=6. Savings probably similar for T5 (untested).
Requires knowing which index of the encoder_outputs is associated with the batch dim (we need to expand this dimensi... | {
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https://api.github.com/repos/huggingface/transformers/issues/3369 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3369/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3369/comments | https://api.github.com/repos/huggingface/transformers/issues/3369/events | https://github.com/huggingface/transformers/pull/3369 | 585,568,400 | MDExOlB1bGxSZXF1ZXN0MzkxOTAzNzEx | 3,369 | [Bart/Memory] SelfAttention only returns weights if config.output_attentions | {
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The `attn_weights` tensor is fairly large, with shape = `(bs, num_heads, tgt_len, src_len)`
This meant that the memory allocated for `attn_weights` could not be... | {
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https://api.github.com/repos/huggingface/transformers/issues/3368 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3368/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3368/comments | https://api.github.com/repos/huggingface/transformers/issues/3368/events | https://github.com/huggingface/transformers/issues/3368 | 585,565,098 | MDU6SXNzdWU1ODU1NjUwOTg= | 3,368 | Why does huggingface bert pooler hack make mixed precission training stable? | {
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"Any update on this?",
"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"
] | 1,584 | 1,590 | 1,590 | NONE | null | # ❓ Questions & Help
## Details
Huggigface BERT implementation has a hack to remove the pooler from optimizer.
https://github.com/huggingface/transformers/blob/b832d5bb8a6dfc5965015b828e577677eace601e/examples/run_squad.py#L927
```
# hack to remove pooler, which is not used
# thus it produce None grad that ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3367 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3367/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3367/comments | https://api.github.com/repos/huggingface/transformers/issues/3367/events | https://github.com/huggingface/transformers/pull/3367 | 585,509,216 | MDExOlB1bGxSZXF1ZXN0MzkxODY1MTQ3 | 3,367 | [Generate] Add bad words list argument to the generate function | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3367?src=pr&el=h1) Report\n> Merging [#3367](https://codecov.io/gh/huggingface/transformers/pull/3367?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ae6834e028ecdf7fdbe886c1f86d0e02d5fef6f0&el=desc) will **increase... | 1,584 | 1,585 | 1,585 | MEMBER | null | The `bad_words_ids` argument allows to insert a list of lists of `input_ids` that cannot be generated, *e.g.* bad words.
That's a proposed feature request (I think there were actually multiple ones):
#3061
Also adds tests for all language models to verify behavior. | {
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https://api.github.com/repos/huggingface/transformers/issues/3366 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3366/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3366/comments | https://api.github.com/repos/huggingface/transformers/issues/3366/events | https://github.com/huggingface/transformers/issues/3366 | 585,385,380 | MDU6SXNzdWU1ODUzODUzODA= | 3,366 | GPT2TokenizerFast does not preserve special tokens' ids after a save and load. | {
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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"
] | 1,584 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT2 Fast Tokenizer
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am wor... | {
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https://api.github.com/repos/huggingface/transformers/issues/3365 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3365/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3365/comments | https://api.github.com/repos/huggingface/transformers/issues/3365/events | https://github.com/huggingface/transformers/pull/3365 | 585,341,657 | MDExOlB1bGxSZXF1ZXN0MzkxNzUyNDIy | 3,365 | fixes lr_scheduler warning | {
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"Not sure why we missed this one. Thanks!"
] | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | For more details, see https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate | {
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https://api.github.com/repos/huggingface/transformers/issues/3364 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3364/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3364/comments | https://api.github.com/repos/huggingface/transformers/issues/3364/events | https://github.com/huggingface/transformers/issues/3364 | 585,338,621 | MDU6SXNzdWU1ODUzMzg2MjE= | 3,364 | Generate all possible sentences using a fine-tuned GPT-2 model | {
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"What do you mean exactly be all possible sentences? \r\n\r\nThe space of possible sentence that could be generated grows exponentially with the length of the sentences. Having **V** words in your vocabulary, there are **V^N** possible sentences of length **N** that could be sampled. If **V ~ 50,000** and **N = 10*... | 1,584 | 1,584 | 1,584 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/3363 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3363/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3363/comments | https://api.github.com/repos/huggingface/transformers/issues/3363/events | https://github.com/huggingface/transformers/pull/3363 | 585,308,290 | MDExOlB1bGxSZXF1ZXN0MzkxNzI1NDY4 | 3,363 | Added total_save_limit feature similar to run_langauge_modeling.py | {
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"I feel its not necessary"
] | 1,584 | 1,585 | 1,585 | NONE | null | Added args.total_save_limit in order to save only the last specific checkpoints similar to the feature in run_langauge_modeling.py. This might be helpful for a student like me who has limited space storage quota on the school's remote server. | {
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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",
"@bourrel \r\nWhy do you use `jplu/tf-flaubert-base-cased`? (https://huggingface.co/jplu/tf-flaubert-base-cased)\r\nAny particular reaso... | 1,584 | 1,660 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
`jplu/tf-camembert-base`
Language I am using the model on (English, Chinese ...):
French
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I ... | {
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"@mariamabarham didn't you have a similar issue? ",
"Yes I encountered the same issue. I solved it by adding --fp16(need to install apex first). You can also reduce the block_size to 512. Both worked out for me.",
"You should probably set the `per_gpu_train_batch_size` to 1. That is the default behavior for `gp... | 1,584 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT2
Language I am using the model on (English, Chinese ...): eng
**The tasks I am working on is:**
!python /content/transformers/examples/run_language_modeling.py --train_data_file=shakespeare.txt --model_type=gpt2 --model_name_or_path=gpt2 --out... | {
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"- Item `1) a) i.` is fixed (list of model ids below for reference)\r\n- For models which don't have a tokenizer, or an auto-detected model type, we'll add a notice on their model page (and remove the code sample which is misleading as it lists AutoModel and AutoConfig)\r\n\r\n```\r\nalbert-base\r\nalbert-large\r\n... | 1,584 | 1,629 | 1,585 | MEMBER | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Community Models
Language I am using the model on (English, Chinese ...): Multiple different ones
Quite some community models can't be loaded. The stats are here:
## Stats
1. **68** can't load either their config (n)or their tokenizer:
... | {
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"@julien-c ",
"This was a bogus model file, rm'ed it."
] | 1,584 | 1,585 | 1,585 | MEMBER | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): mlm-17-1280
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on ... | {
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"Good question. As far as I can tell (I don't think there's a definitive a.k.a legally tested answer to that question) a model is not considered as a derivative work from the dataset(s) it was trained on, so the person who trained the model can choose whatever licensing option they want.\r\n\r\nFor instance, the or... | 1,584 | 1,588 | 1,588 | CONTRIBUTOR | null | Hi,
First of all, thanks for the good work. Very useful.
Would it be possible to add the license information for each model listed on https://huggingface.co/transformers/pretrained_models.html?
The reason is that for production, I need to know which models can be bundled in my app. Some licenses do not allow bun... | {
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"For some reference, check out https://github.com/pytorch/pytorch/issues/12042 and https://github.com/facebookresearch/maskrcnn-benchmark/pull/40. These address the same issue.\r\n\r\nAlso, one of the checks that failed, `check_code_quality`, would fail for the existing version of the script as well. There's a chec... | 1,584 | 1,594 | 1,594 | CONTRIBUTOR | null | In the case of multi-node distributed training, reads and writes typically happen to a common networked filesystem.
In the current version of the `run_language_modeling.py` script, processes that have `local_rank` as 0 perform the writes to disk (tensorboard, dataset cache and model checkpointing). In the case of m... | {
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"Do you solve the problem?"
] | 1,584 | 1,608 | 1,590 | NONE | null | # ❓ Questions & Help
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3354?src=pr&el=h1) Report\n> Merging [#3354](https://codecov.io/gh/huggingface/transformers/pull/3354?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3bedfd334763cb5676c2fe92705390ac57d8de5f&el=desc) will **increase... | 1,584 | 1,584 | 1,584 | MEMBER | null | closes #3262 | {
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"I didn't know that worked, thanks @BramVanroy. @aaugustin what do you think?",
"I'm not familiar with the syntax, but if it works, go for it. I really hope we have a release of sort and we can remove this soon.",
"Works on my machine so I'll merge :)\r\n\r\nThanks @BramVanroy, this will simplify @LysandreJik a... | 1,584 | 1,584 | 1,584 | COLLABORATOR | null | The CONTRIBUTING file pins to a specific version of isort, so we might as well install that in `dev` . This makes it easier for contributors so they don't have to manually install the specific commit. | {
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"Looks good! [**Model page**](https://huggingface.co/huseinzol05/bert-base-bahasa-cased)\r\n\r\nI've also added a filter for the Malay language here:\r\n<img width=\"792\" alt=\"Screenshot 2020-03-19 at 15 28 42\" src=\"https://user-images.githubusercontent.com/326577/77106980-58beec00-69f6-11ea-8145-4d273d605693.p... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | {
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"Memory complexity ReformerLayer\r\n vs BertLayer: \r\n\r\n\r\n\r\n",
"Time complexity ReformerLayer vs. BertLayer:\r\n\r\n
### First steps to take:
- [x] Copy Bert PT code to Reformer PT file.
- [x] Replace self-attention with LSH attention
- [x] Make forward pass work for Bert Layer
### Forward-Pass: Get 1-to-1 same outputs as original Flax code for forward pa... | {
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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"
] | 1,584 | 1,590 | 1,590 | NONE | null | Hi, first of all, thanks for the great library you guys are providing. I'm currently using the latest version of huggingface/transformers, and I'm trying to get a score for the SQuAD V1.1 with XLNET base-cased. However, it seems that the performance I get is only 0.10 for EM and 0.64 for F1.
When getting the score ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3347?src=pr&el=h1) Report\n> Merging [#3347](https://codecov.io/gh/huggingface/transformers/pull/3347?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cec3cdda1599541b033e07a9838386189a5d0010&el=desc) will **increase... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | - Only 17MB of Model weights!!
- The smalles model fine-tuned on SQUaD v2? | {
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"Thanks for pointing out @lazarevskiVsg and @julien-c !",
"@julien-c , will merge right away - small change!",
"Why don’t you just use input_shape (which is always defined), to be consistent with other models?",
"> Why don’t you just use input_shape (which is always defined), to be consistent with other model... | 1,584 | 1,584 | 1,584 | MEMBER | null | Make sure `batch_size` is correct for gpt2 and ctrl - these models need a slightly different behavior since the shape of `input_ids` can change depending on whether the past variable is inserted or not.
See also:
PR: https://github.com/huggingface/transformers/pull/3033
and its issue:
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3344?src=pr&el=h1) Report\n> Merging [#3344](https://codecov.io/gh/huggingface/transformers/pull/3344?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f6d813aaaa96cc43fcf55f255b9439ebc22a31a0&el=desc) will **not chan... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | For the tutorial of "How to generate text", the URL link was wrong (it was linked to the tutorial of "How to train a language model").
I fixed the URL. | {
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The original sentences:
- **If your was** made of multiple \"parts\" such as (question, context), then this would be a vector with for each token the segment it belongs to
- **If your has** been truncated into multip... | {
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"Well this just indicates that you didn't correctly install the library. Try creating a new environment and installing from scratch.\r\n",
"You have to install the library first to use any module from it\r\nFirst type `pip install transformers` in your terminal and then you can import the necessary modules",
"I... | 1,584 | 1,606 | 1,590 | NONE | null | # 🐛 Bug
No module found transformers
## Information
Package Version
------------------------ ----------
absl-py 0.9.0
astor 0.8.1
boto3 1.12.22
botocore 1.15.22
cachetools 4.0.0
cert... | {
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"tweaked version of #3247 ",
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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"
] | 1,584 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):'albert_xxlarge_zh'
Language I am using the model on (English, Chinese ...):Chinese
Two problems are all related to method `transformers.PreTrainedTokenizer.tokenize`:
1. How can I not let this method automatically lower the case of the English w... | {
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"Hi @jkangsta,\r\n\r\nThanks for posting your question here. The docstring was out of date and an in-detail description for T5 will be added here #3507 ."
] | 1,584 | 1,585 | 1,585 | NONE | null | Hi there. I am trying to fine tune T5, but I have noticed your documentation gives conflicting instructions.
In modeling_t5.py you say
> To match pre-training, T5 input sequence should be formatted with [CLS] and [SEP] tokens
but then in tokenization_t5.py both of those tokens are set to None and the only tokens... | {
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https://api.github.com/repos/huggingface/transformers/issues/3332 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3332/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3332/comments | https://api.github.com/repos/huggingface/transformers/issues/3332/events | https://github.com/huggingface/transformers/issues/3332 | 583,987,314 | MDU6SXNzdWU1ODM5ODczMTQ= | 3,332 | run_tf_ner.py doesn't work with unlabelled test data | {
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"I have noticed the same issue and posted a question here: https://stackoverflow.com/questions/60732509/label-handling-confusion-in-run-tf-ner-example\r\n\r\nI think `pad_token_label_id` should definitely not fall into the range of actual labels. Maybe we can make it `-1` or `num(label)` or something. Also as shown... | 1,584 | 1,591 | 1,591 | NONE | null | When running `run_tf_ner.py` in `predict` mode if all the labels in test data are `O`, script errors out with
` File "/home/himanshu/.local/lib/python3.7/site-packages/numpy/lib/function_base.py", line 423, in average
"Weights sum to zero, can't be normalized")
ZeroDivisionError: Weights sum to zero, can't be ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3331?src=pr&el=h1) Report\n> Merging [#3331](https://codecov.io/gh/huggingface/transformers/pull/3331?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/20139b7c8d88f380f1e4e0ae2baf0b0ac9351039&el=desc) will **decrease... | 1,584 | 1,591 | 1,584 | CONTRIBUTOR | null | These are a copy of https://github.com/TurkuNLP/FinBERT/blob/master/README.md. | {
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"This seems related to the classes that you use in NLLLoss, That loss function expects a torch.LongTensor with values in the range [0, nb_classes-1] with no values left out in between.",
"Which version of `transformers` do you have installed? There was a recent change from using -1 to -100 for tokens that should ... | 1,584 | 1,607 | 1,590 | NONE | null | I am trying to run this script[run_language_modeling.py](https://github.com/huggingface/transformers/blob/master/examples/run_language_modeling.py)
I can load the pre-trained roberta model without a problem. However, when it starts training (loss.backward()), then there are issues like these:
> /pytorch/aten/src/... | {
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https://api.github.com/repos/huggingface/transformers/issues/3325 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3325/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3325/comments | https://api.github.com/repos/huggingface/transformers/issues/3325/events | https://github.com/huggingface/transformers/issues/3325 | 583,628,541 | MDU6SXNzdWU1ODM2Mjg1NDE= | 3,325 | Cubla Error on DistilBert | {
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"After some investigation, I have really no clue on what's happening. This issue is only referred through Tensorflow questions such as [this](https://stackoverflow.com/questions/41117740/tensorflow-crashes-with-cublas-status-alloc-failed) or [this issue](https://github.com/tensorflow/tensorflow/issues/9489) on Tens... | 1,584 | 1,624 | 1,595 | NONE | null | # 🐛 Bug
When using DistilBert I get `CUBLAS_STATUS_ALLOC_FAILED` when trying to forward
## Information
Exact error is : `RuntimeError : Cuda Error: CUBLAS_STATUS_ALLOC_FAILED when calling cublasCreate(handle)` and traceback indicates i happens on `output = input.matmul(weight.t())` which is probably not informati... | {
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https://api.github.com/repos/huggingface/transformers/issues/3324 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3324/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3324/comments | https://api.github.com/repos/huggingface/transformers/issues/3324/events | https://github.com/huggingface/transformers/issues/3324 | 583,541,406 | MDU6SXNzdWU1ODM1NDE0MDY= | 3,324 | Error loading finetuned bert model AttributeError: 'NoneType' object has no attribute 'endswith' | {
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"The `from_pretrained` method should point to a directory. Could you try to point it to a directory containing both the model weights and the config.json file?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you fo... | 1,584 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/3323 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3323/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3323/comments | https://api.github.com/repos/huggingface/transformers/issues/3323/events | https://github.com/huggingface/transformers/pull/3323 | 583,508,378 | MDExOlB1bGxSZXF1ZXN0MzkwMjUyNjc3 | 3,323 | [Bart/Memory] don't create lm_head | {
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"@LysandreJik \r\n```python\r\n if hasattr(output_embeddings, \"out_features\") and hasattr(input_embeddings, \"num_embeddings\"):\r\n output_embeddings.out_features = input_embeddings.num_embeddings\r\n```\r\nwas breaking because bart-large-cnn doesn't have a mask token.\r\nI can investigate more... | 1,584 | 1,585 | 1,585 | CONTRIBUTOR | null | ### Summary
previously we created a `self.lm_head = nn.Linear()` with the exact same weight matrix as the input embeddings, and then skipped `tie_weights`.
This presented 3 problems:
1) 200 MB of extra GPU RAM
2) Can't `tie_weights`
3) Can't `resize_token_embeddings`
This PR alleviates all the concerns by us... | {
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https://api.github.com/repos/huggingface/transformers/issues/3322 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3322/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3322/comments | https://api.github.com/repos/huggingface/transformers/issues/3322/events | https://github.com/huggingface/transformers/pull/3322 | 583,470,952 | MDExOlB1bGxSZXF1ZXN0MzkwMjIxMzEz | 3,322 | [BART] torch 1.0 compatibility | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3322?src=pr&el=h1) Report\n> Merging [#3322](https://codecov.io/gh/huggingface/transformers/pull/3322?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/38a555a83c8aceae77895d325174af5bd576cec7&el=desc) will **decrease... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | This PR contains two minor fixes and one piece of cleanup for the BartModel.
**1.** Previously, Bart's encoder padding mask used -10000. to represent tokens that should be ignored, then called `masked_fill(mask.to(torch.bool), -inf)` to use the mask.
There are two problems with this:
- it's confusing to set a va... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3321?src=pr&el=h1) Report\n> Merging [#3321](https://codecov.io/gh/huggingface/transformers/pull/3321?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/38a555a83c8aceae77895d325174af5bd576cec7&el=desc) will **decrease... | 1,584 | 1,584 | 1,584 | CONTRIBUTOR | null | We create card for this model. | {
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https://api.github.com/repos/huggingface/transformers/issues/3320 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3320/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3320/comments | https://api.github.com/repos/huggingface/transformers/issues/3320/events | https://github.com/huggingface/transformers/issues/3320 | 583,435,169 | MDU6SXNzdWU1ODM0MzUxNjk= | 3,320 | TF BERT not FP16 compatible? | {
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"I've aced same issue. Maybe it's hard coded the data type somewhere? Have you found solution?",
"Tried this on Colab TPU, same error.",
"Same here, would be convenient as hell :)",
"Having the same error also for `transformers` version 2.11.0. \r\nHere some code to easily reproduce the error:\r\n\r\n```pytho... | 1,584 | 1,605 | 1,605 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): TFBertForQuestionAnswering
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] my own modified scripts:
The tasks I am working on is:
* [x] an official GLUE/SQUaD task: SQUaD
## To reproduc... | {
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https://api.github.com/repos/huggingface/transformers/issues/3319 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3319/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3319/comments | https://api.github.com/repos/huggingface/transformers/issues/3319/events | https://github.com/huggingface/transformers/pull/3319 | 583,426,127 | MDExOlB1bGxSZXF1ZXN0MzkwMTg0MDI5 | 3,319 | [BART] cleanup: remove redundant kwargs, improve docstrings | {
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### Cleanup
- Deletes unused `value` argument for SelfAttention. (`value` is always the same as `key`.) This might be moderately controversial as most attention modules take query, key, value as arguments, but this change reduces the signature to just query and key (sinc... | {
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https://api.github.com/repos/huggingface/transformers/issues/3318 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3318/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3318/comments | https://api.github.com/repos/huggingface/transformers/issues/3318/events | https://github.com/huggingface/transformers/issues/3318 | 583,424,759 | MDU6SXNzdWU1ODM0MjQ3NTk= | 3,318 | pipelines.ipynb mask should be [MASK] | {
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"Hi @shibing624, \r\n\r\nThanks for opening this issue.\r\n\r\n`fill-mask` pipeline uses Roberta under the hood and the mask token is actually `<mask>` which is the one used in the notebook.\r\n\r\nHowever, it's not the safest way to use the pipeline I agree. I'll update the notebook with \r\n\r\n```python\r\nnlp_f... | 1,584 | 1,584 | 1,584 | NONE | null | transformers/notebooks/03-pipelines.ipynb fill-mask task, use newest version, <mask> is error, should be [MASK]. | {
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https://api.github.com/repos/huggingface/transformers/issues/3317 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3317/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3317/comments | https://api.github.com/repos/huggingface/transformers/issues/3317/events | https://github.com/huggingface/transformers/issues/3317 | 583,360,248 | MDU6SXNzdWU1ODMzNjAyNDg= | 3,317 | output value of XLNetModel changes for the same input | {
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"It seems that after fine-tuning if I don't use `model=model.eval()`, this can happen.\r\n"
] | 1,584 | 1,584 | 1,584 | NONE | null | I was trying to use the pre-trained `XLNetModel` model. I found that for the same input, each time I run the model and the output values are different, which is wired to me. Here is a code that I just used:
```
tokenizer =XLNetTokenizer.from_pretrained("xlnet-base-cased")
model=XLNetModel.from_pretrained('xlnet-base... | {
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https://api.github.com/repos/huggingface/transformers/issues/3316 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3316/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3316/comments | https://api.github.com/repos/huggingface/transformers/issues/3316/events | https://github.com/huggingface/transformers/issues/3316 | 583,302,486 | MDU6SXNzdWU1ODMzMDI0ODY= | 3,316 | TextClassificationPipeline does not work with pretrained BERT model | {
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"That would be because you're using a `BertModel` instead of a `BertModelForSequenceClassification`.",
"What model should we be using, and where can we download it from?"
] | 1,584 | 1,591 | 1,585 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): 'nlptown/bert-base-multilingual-uncased-sentiment'
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give detai... | {
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https://api.github.com/repos/huggingface/transformers/issues/3315 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3315/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3315/comments | https://api.github.com/repos/huggingface/transformers/issues/3315/events | https://github.com/huggingface/transformers/issues/3315 | 583,296,904 | MDU6SXNzdWU1ODMyOTY5MDQ= | 3,315 | how does masked_lm_labels work ? | {
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"Hi all\r\nfrom hugging face{https://huggingface.co/transformers/model_doc/bert.html#bertformaskedlm}\r\n\r\nin this code :\r\n{\r\nfrom transformers import BertTokenizer, BertForMaskedLM\r\nimport torch\r\n\r\ntokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\r\nmodel = BertForMaskedLM.from_pretrained... | 1,584 | 1,590 | 1,590 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/3314 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3314/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3314/comments | https://api.github.com/repos/huggingface/transformers/issues/3314/events | https://github.com/huggingface/transformers/issues/3314 | 583,242,412 | MDU6SXNzdWU1ODMyNDI0MTI= | 3,314 | Mismatch in the accuracy figures | {
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Hi Just wanted to know if "bert-base-multilingual-cased" model and https://storage.googleapis.com/bert_models/2018_11_23/multi_cased_L-12_H-768_A-12.zip are same.
I tried using the tokenizer from the multi_cased_L-12_H-768_A-12 and bert-base-multilingual-cased model which performed better th... | {
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