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https://api.github.com/repos/huggingface/transformers/issues/11744 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11744/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11744/comments | https://api.github.com/repos/huggingface/transformers/issues/11744/events | https://github.com/huggingface/transformers/pull/11744 | 893,172,542 | MDExOlB1bGxSZXF1ZXN0NjQ1NzMxMjc2 | 11,744 | [BigBird Pegasus] Make tests faster | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,624 | 1,624 | NONE | null | Hi,
According to the [documentation](https://huggingface.co/transformers/model_doc/roberta.html#transformers.RobertaForSequenceClassification) classification head should work `on top of the pooled output`, which makes sense, considering the fact that RoBERTa, unlike BERT, wasn't trained on Next Sentence Prediction t... | {
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https://api.github.com/repos/huggingface/transformers/issues/11742 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11742/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11742/comments | https://api.github.com/repos/huggingface/transformers/issues/11742/events | https://github.com/huggingface/transformers/pull/11742 | 893,158,827 | MDExOlB1bGxSZXF1ZXN0NjQ1NzE5NzAw | 11,742 | Issue with symbolic tracing for T5 | {
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This solves the issue for symbolic tracing with T5.
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https://api.github.com/repos/huggingface/transformers/issues/11741 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11741/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11741/comments | https://api.github.com/repos/huggingface/transformers/issues/11741/events | https://github.com/huggingface/transformers/issues/11741 | 893,134,525 | MDU6SXNzdWU4OTMxMzQ1MjU= | 11,741 | Convert blenderbot checkpoint to tensorflow (TF) | {
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"@patrickvonplaten Can you help me?",
"I convert Parl-AI's checkpoint to huggingface using `convert_blenderbot_original_pytorch_checkpoint_to_pytorch.py`. \r\nAnd I convert pytorch checkpoint to tf checkpoint using `convert_pytorch_checkpoint_to_tf2.py`. \r\n \r\nIf there is something wrong, please comment.",
... | 1,621 | 1,623 | 1,623 | NONE | null | Hi! Thank you for a great project.
I wonder if I can convert blenderbot checkpoint to tensorflow.
If I can, how I convert checkpoint? Give me some comment. | {
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https://api.github.com/repos/huggingface/transformers/issues/11740 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11740/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11740/comments | https://api.github.com/repos/huggingface/transformers/issues/11740/events | https://github.com/huggingface/transformers/pull/11740 | 893,118,113 | MDExOlB1bGxSZXF1ZXN0NjQ1Njg1NzM5 | 11,740 | Add visual + link to Premium Support webpage | {
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"Built docs is at https://212403-155220641-gh.circle-artifacts.com/0/docs/_build/html/index.html\r\n\r\n<img width=\"1360\" alt=\"Screenshot 2021-05-17 at 11 08 58\" src=\"https://user-images.githubusercontent.com/326577/118463639-ff238180-b6cd-11eb-8c45-a6a1e6471b60.png\">\r\n",
"CI failure seems unrelated"
] | 1,621 | 1,621 | 1,621 | MEMBER | null | Close #11635 | {
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cc @NielsRogge | {
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"This is a PR against an older version of Transformers, which we do not accept. This code has been completely removed since then and is now fully integrated into Trainer.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed plea... | 1,621 | 1,623 | 1,623 | NONE | null | Currently this code is completely broken with non-distributed training. I'm not clear on how it has ever worked:
```
File "run.py", line 152, in <module>
trainer.train() #resume_from_checkpoint=get_last_checkpoint("/opt/ml/checkpoints"))
File "/opt/conda/lib/python3.6/site-packages/transformers/trainer.py... | {
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"rebased on master",
"This PR is ready for review please. @LysandreJik @sgugger \r\n\r\nThe failing test is connected to #11731",
"> Cool, thanks a lot for working on these tests! I think that these are already somewhat covered by the common tests, but they're fast and should help identify issues faster.\r\n> \... | 1,621 | 1,622 | 1,622 | CONTRIBUTOR | null | This PR adds regression tests for slow sentencepiece tokenizers. These tests are needed for a refactoring in PR #11716
## Strange findings
- s2t: `_convert_token_to_id` of `"<s>"` does not give 0
## ToDo
- <s>add test for `_convert_token_to_id`</s> - done, see `test_convert_token_and_id`
- <s>add test for `_c... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,624 | 1,624 | NONE | null | # What does this PR do?
It adds functionality to allow gpt-Neo 2.7B to run in 6gb vram.
If it detects that some modules are on gpu and there is not enough vram, a dict called extrastorage is created which holds the data for model.transformer.h
These weights are loaded from ram to vram one at a time, reducing vram ... | {
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"disabling fp16 seems to solve the issue of nan loss, but I wouldn't call this issue closed because this doubles the training time :(",
"Hey @demegire,\r\n\r\nSadly MT5 doesn't really work with fp16. There are a bunch of issues regarding this problem...see:\r\n- https://discuss.huggingface.co/t/t5-fp16-issue-is-f... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
- `transformers` version: 4.6.0
- Platform: Linux-5.4.109+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (True)
- Tensorflow version (GPU?): 2.4.1 (True)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
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https://api.github.com/repos/huggingface/transformers/issues/11734 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11734/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11734/comments | https://api.github.com/repos/huggingface/transformers/issues/11734/events | https://github.com/huggingface/transformers/issues/11734 | 892,433,426 | MDU6SXNzdWU4OTI0MzM0MjY= | 11,734 | Cant load google/reformer-enwik8 | {
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"Duplicate of #11649\r\n"
] | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null |
OSError: Can't load tokenizer for 'google/reformer-enwik8'. Make sure that:
- 'google/reformer-enwik8' is a correct model identifier listed on 'https://huggingface.co/models'
- or 'google/reformer-enwik8' is the correct path to a directory containing relevant tokenizer files
https://huggingface.co/google/ref... | {
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https://api.github.com/repos/huggingface/transformers/issues/11733 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11733/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11733/comments | https://api.github.com/repos/huggingface/transformers/issues/11733/events | https://github.com/huggingface/transformers/issues/11733 | 892,382,926 | MDU6SXNzdWU4OTIzODI5MjY= | 11,733 | CPU Memory Leak when using RoBERTa for just word vector representation | {
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"Hi @ZahraGithub, \r\n1) Please use `model.eval()` to reduce your memory consumption.\r\n2) From what I understood, you're processing 64 tokens in one go and total tokens are 1024. This means you'll get vector representation of (16,768) for each document right? How are you storing these representations? You won't b... | 1,621 | 1,624 | 1,624 | NONE | null | Hi,
I do not use model for training or fine tuning. I just want to give strings and take their representations. My dataset is Robust04 (about 2G) and max length of each document is truncated to 1024 tokens. So, I break each documents to pieces of 64 tokens and represent it and then concatenate the representation of ea... | {
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https://api.github.com/repos/huggingface/transformers/issues/11732 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11732/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11732/comments | https://api.github.com/repos/huggingface/transformers/issues/11732/events | https://github.com/huggingface/transformers/issues/11732 | 892,370,886 | MDU6SXNzdWU4OTIzNzA4ODY= | 11,732 | Import `SPIECE_UNDERLINE` from `file_utils` instead of WET definition | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,623 | null | CONTRIBUTOR | null | Many places define `SPIECE_UNDERLINE` in the code like this: `SPIECE_UNDERLINE = "▁"`
Instead it should me imported: `from transformers.file_utils import SPIECE_UNDERLINE`.
I can provide a PR... | {
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https://api.github.com/repos/huggingface/transformers/issues/11731 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11731/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11731/comments | https://api.github.com/repos/huggingface/transformers/issues/11731/events | https://github.com/huggingface/transformers/issues/11731 | 892,364,143 | MDU6SXNzdWU4OTIzNjQxNDM= | 11,731 | `ci/circleci: run_tests_torch` reaches 10 min. time limit | {
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"An other one here: https://app.circleci.com/pipelines/github/huggingface/transformers/23647/workflows/b0de5fa6-3f1d-446f-8ce9-11461ff1fb10/jobs/214869",
"@sgugger are you aware of this issue?",
"Yes we are aware. This is something we will work on in the next weeks, we're just wrapping another project first.",
... | 1,621 | 1,622 | 1,622 | CONTRIBUTOR | null | `ci/circleci: run_tests_torch` reaches 10 min. time limit - see here:
https://app.circleci.com/pipelines/github/huggingface/transformers/23426/workflows/349bd527-b66a-46ed-a168-365794da6856/jobs/211948 | {
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https://api.github.com/repos/huggingface/transformers/issues/11730 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11730/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11730/comments | https://api.github.com/repos/huggingface/transformers/issues/11730/events | https://github.com/huggingface/transformers/issues/11730 | 892,256,350 | MDU6SXNzdWU4OTIyNTYzNTA= | 11,730 | Bert2bert on Swag with very low accuracy | {
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"Hey @helloworld123-lab,\r\n\r\nThanks for the issue :-) Is there a specific reason to use Bert2bert for SWAG instead of just a BERT model?",
"I am sorry for the issue :) actually i am new in this field. i just started working on models using transformers. T5 is a text-to-text model, I just wanted to try how it c... | 1,621 | 1,623 | 1,623 | NONE | null | Hello everyone,
I try to build multiple choice QA system using Bert2Bert. I follow the model given for Swag using t5 in [https://colab.research.google.com/github/patil-suraj/exploring-T5/blob/master/t5_fine_tuning.ipynb](url)
My complete code is here.[https://colab.research.google.com/drive/1MAGCi5TC1S6GNW3CFEB0f2... | {
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https://api.github.com/repos/huggingface/transformers/issues/11729 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11729/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11729/comments | https://api.github.com/repos/huggingface/transformers/issues/11729/events | https://github.com/huggingface/transformers/issues/11729 | 892,122,258 | MDU6SXNzdWU4OTIxMjIyNTg= | 11,729 | [Benchmark] | {
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## Benchmark
Which part of `transformers` did you benchmark?
## Set-up
What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization did you use?
## Results
Put your results here!
| {
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https://api.github.com/repos/huggingface/transformers/issues/11728 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11728/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11728/comments | https://api.github.com/repos/huggingface/transformers/issues/11728/events | https://github.com/huggingface/transformers/issues/11728 | 892,066,680 | MDU6SXNzdWU4OTIwNjY2ODA= | 11,728 | ImportError: cannot import name 'load_dataset' from 'datasets' | {
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"Hi ! When you `import datasets`, python looks at your installed packages, but also at the modules defined in the directory from which you run your code. It is the case because the current working directory is added to your python path when you run your code.\r\n\r\nIn your case I think it tries to load your `datas... | 1,621 | 1,708 | 1,624 | NONE | null | ## Environment info
- `transformers` version: 4.6.0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.3
- PyTorch version (GPU?): 1.7.1 (True)
- Using GPU in script?: Possibly?
- Using distributed or parallel set-up in script?: No
### Who can help
@LysandreJik and @lhoestq helped on the other issu... | {
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https://api.github.com/repos/huggingface/transformers/issues/11727 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11727/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11727/comments | https://api.github.com/repos/huggingface/transformers/issues/11727/events | https://github.com/huggingface/transformers/pull/11727 | 891,965,470 | MDExOlB1bGxSZXF1ZXN0NjQ0NzQ4ODc0 | 11,727 | Improvements to Flax finetuning script | {
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- Ensures we actually use the `weight_decay` command-line argument
- Simplified `jax.value_and_grad` by removing the auxiliary (which we don't use)
- Simplified replication logic in eval step
- Fixes a bug in RNG handling. We weren’t splitting them appropriately before sharding them during... | {
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https://api.github.com/repos/huggingface/transformers/issues/11726 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11726/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11726/comments | https://api.github.com/repos/huggingface/transformers/issues/11726/events | https://github.com/huggingface/transformers/pull/11726 | 891,828,116 | MDExOlB1bGxSZXF1ZXN0NjQ0NjMzMzk3 | 11,726 | [Flax] Correct example script | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11725 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11725/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11725/comments | https://api.github.com/repos/huggingface/transformers/issues/11725/events | https://github.com/huggingface/transformers/pull/11725 | 891,813,907 | MDExOlB1bGxSZXF1ZXN0NjQ0NjIxNDI3 | 11,725 | Fix#11724 | {
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https://api.github.com/repos/huggingface/transformers/issues/11724 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11724/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11724/comments | https://api.github.com/repos/huggingface/transformers/issues/11724/events | https://github.com/huggingface/transformers/issues/11724 | 891,808,210 | MDU6SXNzdWU4OTE4MDgyMTA= | 11,724 | A bug in modeling_tf_marian.py and modeling_tf_pegasus.py SinusoidalPositionalEmbedding _init_weight | {
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"Hey @JunnYu,\r\n\r\nCould you give a bit more context on what the issue is exactly? And how your solution solves the issue?",
"@patrickvonplaten \r\nAfter this line `position_enc[:, 0 : dim // 2] = np.sin(position_enc[:, 0::2]) ` and\r\n` position_enc[:, 0 : dim // 2] ` value will be overridden in place.\r\nIf w... | 1,620 | 1,626 | 1,626 | CONTRIBUTOR | null |
## Information
should create a new np.array and then store np.sin&np.cos result in it
```python
table = np.zeros_like(position_enc)
# index 0 is all zero
table[:, 0 : dim // 2] = np.sin(position_enc[:, 0::2])
table[:, dim // 2 :] = np.cos(position_enc[:, 1::2])
# convert to tensor
table = tf.convert_to_ten... | {
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https://api.github.com/repos/huggingface/transformers/issues/11723 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11723/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11723/comments | https://api.github.com/repos/huggingface/transformers/issues/11723/events | https://github.com/huggingface/transformers/issues/11723 | 891,778,434 | MDU6SXNzdWU4OTE3Nzg0MzQ= | 11,723 | Warnings about some weights that were not initialized in Greek BERT | {
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"It tells you that you are initializing a `BertModel` without the heads that were used for pre-training (namely next sentence prediction and masked language modeling). That's not a problem, as you probably don't need these weights for a downstream task of interest (such as question answering or sequence classificat... | 1,620 | 1,624 | 1,624 | NONE | null | Hello,
in order to use the Greek BERT model, I use `AutoModel` class, and specifically
`greek_bert = AutoModel.from_pretrained("nlpaueb/bert-base-greek-uncased-v1")`
When I load the model with the above command I get this warning:
```
Some weights of the model checkpoint at nlpaueb/bert-base-greek-uncased... | {
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https://api.github.com/repos/huggingface/transformers/issues/11722 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11722/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11722/comments | https://api.github.com/repos/huggingface/transformers/issues/11722/events | https://github.com/huggingface/transformers/issues/11722 | 891,745,768 | MDU6SXNzdWU4OTE3NDU3Njg= | 11,722 | Plug a custom tokenizer into PreTrainedTokenizer | {
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"Would this [documentation](https://huggingface.co/transformers/fast_tokenizers.html) help you out?",
"This is exactly what I was looking for! No idea how I missed it. Thank you :)"
] | 1,620 | 1,620 | 1,620 | NONE | null | Is there a clean way to use a customer tokenizer trained from the tokenizers library in a PretrainedTokenizer interface?
```
from tokenizers import Tokenizer
tokenizer = Tokenizer.from_file(config_file)
```
The config file is generated using tokenizer.save() method.
I want to use this tokenizer in a Pre... | {
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https://api.github.com/repos/huggingface/transformers/issues/11721 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11721/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11721/comments | https://api.github.com/repos/huggingface/transformers/issues/11721/events | https://github.com/huggingface/transformers/issues/11721 | 891,684,212 | MDU6SXNzdWU4OTE2ODQyMTI= | 11,721 | ValueError: could not broadcast input array from shape (2816,384) into shape (2698,384) | {
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"@sgugger i saw you have a PR to fix similar error, could you help to take a look?\r\n\r\n",
"You should upgrade your version of Transformers: this code is not used anymore inside the `Trainer`.",
"i am installing transformers from source, the issue still threr.\r\n\r\nand issue throw from https://github.com/hu... | 1,620 | 1,621 | 1,621 | NONE | null | the command to reproduce:
cd huggingface-transformers/examples/pytorch/question-answering
python -m torch.distributed.launch --nproc_per_node=8 ./run_qa.py \
--model_name_or_path roberta-large \
--dataset_name squad \
--do_train --do_eval \
--per_device_train_batch_size 16 \
--per_device_eva... | {
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https://api.github.com/repos/huggingface/transformers/issues/11720 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11720/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11720/comments | https://api.github.com/repos/huggingface/transformers/issues/11720/events | https://github.com/huggingface/transformers/issues/11720 | 891,517,085 | MDU6SXNzdWU4OTE1MTcwODU= | 11,720 | RagRetriever fails to find faiss-gpu installed with pip not conda | {
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"Got it to work with rebuild... and pip install faiss and faiss-gpu\r\ngit clone https://...github.../rag\r\nexport TOKENIZERS_PARALLELISM=false\r\npip install torch torchvision ray[default] datasets faiss faiss-gpu matplotlib seaborn pandas transformers awscli s3fs scikit-plot\r\npython use_own_knowledge_dataset.... | 1,620 | 1,621 | 1,621 | CONTRIBUTOR | null | - `transformers` version: 4.5.1
- Platform: Linux-4.14.231-173.361.amzn2.x86_64-x86_64-with-glibc2.9
- Python version: 3.6.10
- PyTorch version (GPU?): 1.8.1+cu102 (True)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: yes nVidia V100 16Gb
- Using distributed or parallel set-up in script?: just... | {
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https://api.github.com/repos/huggingface/transformers/issues/11719 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11719/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11719/comments | https://api.github.com/repos/huggingface/transformers/issues/11719/events | https://github.com/huggingface/transformers/issues/11719 | 891,488,219 | MDU6SXNzdWU4OTE0ODgyMTk= | 11,719 | parameter `ignore_keys` of `trainer.predict` not accessible in `Trainer` or `TrainingArguments` | {
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"We could add an argument for this (like `ignore_keys_for_eval`) yes. Let me know if you want to tackle this!",
"I very much wanna do this and will get right down to it! 👍 Admittedly though, I am relatively new to making contributions.",
"Hi! As a short update: I will not be able to work on this until 23rd of... | 1,620 | 1,625 | 1,625 | CONTRIBUTOR | null | # 🚀 Feature request
The [`predict`](https://huggingface.co/transformers/main_classes/trainer.html#transformers.Trainer.predict) and [`evaluate`](https://huggingface.co/transformers/main_classes/trainer.html#transformers.Trainer.evaluate) methods of the Trainer class provide an excellent option of `ignore_keys`. Her... | {
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https://api.github.com/repos/huggingface/transformers/issues/11718 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11718/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11718/comments | https://api.github.com/repos/huggingface/transformers/issues/11718/events | https://github.com/huggingface/transformers/pull/11718 | 891,284,506 | MDExOlB1bGxSZXF1ZXN0NjQ0MTc1ODEw | 11,718 | Fix loading the best model on the last stage of training | {
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"Great! Lat thing is to run `make style` on your branch to make the CI pass. Let me know if you run into any issue, I can also push on your branch.",
"> Great! Lat thing is to run `make style` on your branch to make the CI pass. Let me know if you run into any issue, I can also push on your branch.\r\n\r\nCI is a... | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
It fixes the best model loading on the last stage of the training.
Fixes #11666
## Who can review?
@sgugger
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https://api.github.com/repos/huggingface/transformers/issues/11717 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11717/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11717/comments | https://api.github.com/repos/huggingface/transformers/issues/11717/events | https://github.com/huggingface/transformers/pull/11717 | 891,250,865 | MDExOlB1bGxSZXF1ZXN0NjQ0MTQ3MTAx | 11,717 | Fix T5 beam search when using parallelize | {
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"@OyvindTafjord Hi, I am trying to figure out how to use model parallelization on T5 but having some problems. I tried to reproduce your result but got the following error:\r\n```\r\nfrom transformers import AutoTokenizer, AutoModelForSeq2SeqLM \r\ntokenizer = AutoTokenizer.from_pretrained(\"allenai/unifiedqa-t5-... | 1,620 | 1,624 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
As requested by @patrickvonplaten in conversation on issue https://github.com/huggingface/transformers/issues/9200, this fixes a crash when trying to use beam search on T5 models split across multiple GPUs using `model.parallelize()`. It uses the fix from https://github.com/huggingface/transf... | {
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https://api.github.com/repos/huggingface/transformers/issues/11716 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11716/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11716/comments | https://api.github.com/repos/huggingface/transformers/issues/11716/events | https://github.com/huggingface/transformers/pull/11716 | 891,039,539 | MDExOlB1bGxSZXF1ZXN0NjQzOTcwMzMz | 11,716 | Refactor slow sentencepiece tokenizers. | {
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"`SentencePieceProcessor.decode` is doing \"the same but more than `SentencePieceProcessor.decode_pieces`. \r\nThat is why we replace `SentencePieceProcessor.decode_pieces` with `SentencePieceProcessor.decode` in this PR.\r\n\r\nSee here:\r\n\r\nhttps://github.com/google/sentencepiece/blob/6256ef243844e5848499cf519... | 1,620 | 1,626 | 1,626 | CONTRIBUTOR | null | PR for #11646
## ToDo
- [x] `AlbertTokenizer`
- [x] `BarthezTokenizer`
- [x] `BertGenerationTokenizer`
- [x] `BigBirdTokenizer`
- [x] `CamembertTokenizer`
- [x] `DebertaV2Tokenizer`
- [x] `M2M100Tokenizer`
- [x] `MarianTokenizer`
- [x] `MBart50Tokenizer`
- [x] `PegasusTokenizer`
- [x] `ReformerTokenizer... | {
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https://api.github.com/repos/huggingface/transformers/issues/11715 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11715/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11715/comments | https://api.github.com/repos/huggingface/transformers/issues/11715/events | https://github.com/huggingface/transformers/issues/11715 | 890,937,304 | MDU6SXNzdWU4OTA5MzczMDQ= | 11,715 | Request for feature for setting batch size in pipeline when inference | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,624 | 1,624 | NONE | null | ```
from transformers import pipeline
from transformers import AutoModelWithLMHead, AutoTokenizer
model = AutoModelWithLMHead.from_pretrained("Helsinki-NLP/opus-mt-en-fr")
tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-fr")
nlp = pipeline("translation_en_to_fr", model=model, tokenizer=tokeniz... | {
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https://api.github.com/repos/huggingface/transformers/issues/11714 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11714/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11714/comments | https://api.github.com/repos/huggingface/transformers/issues/11714/events | https://github.com/huggingface/transformers/issues/11714 | 890,851,753 | MDU6SXNzdWU4OTA4NTE3NTM= | 11,714 | Blender 9B model | {
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"I think @patil-suraj talked about it at some point?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.... | 1,620 | 1,623 | 1,623 | CONTRIBUTOR | null | Are there any plans to release the blender 9B model in the transformers library? | {
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https://api.github.com/repos/huggingface/transformers/issues/11713 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11713/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11713/comments | https://api.github.com/repos/huggingface/transformers/issues/11713/events | https://github.com/huggingface/transformers/issues/11713 | 890,835,260 | MDU6SXNzdWU4OTA4MzUyNjA= | 11,713 | Unable to import transformers: ImportError: numpy>=1.17 is required for a normal functioning of this module, but found numpy==1.16.3 | {
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"What is your working environment? Is it a Colab notebook, a Linux machine?",
"I'm working on my PC with Windows 10 system.\r\n\r\n> What is your working environment? Is it a Colab notebook, a Linux machine?\r\n\r\n",
"Probably your environments have different versions as @LysandreJik mentioned. Can you run the... | 1,620 | 1,681 | 1,621 | NONE | null | I'd installed transformers via `pip install transformers`
And made sure my python packages is up-to-date, however when I import transformers it shows the error message:
```
ImportError: numpy>=1.17 is required for a normal functioning of this module, but found numpy==1.16.3.
Try: pip install transformers -U or ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11712 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11712/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11712/comments | https://api.github.com/repos/huggingface/transformers/issues/11712/events | https://github.com/huggingface/transformers/issues/11712 | 890,823,994 | MDU6SXNzdWU4OTA4MjM5OTQ= | 11,712 | Reformer for questions answering(squad) | {
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"It hasn't changed yet. The problem is not code, the problem is the lack of a decent pre-trained model.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not f... | 1,620 | 1,624 | 1,624 | NONE | null | I want to use Reformer for Questions Answering. I tried to use pretrained model 'google/reformer-crime-and-punishment'. I was using this example https://huggingface.co/transformers/custom_datasets.html#qa-squad just replaced with reformer. I get the exception related with pad, cls tokens, sequence length and so on, bu... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,646 | 1,624 | NONE | null | > transformers version: 4.6.0.dev0
> torch version:1.8.1+cu102
I am using the simple API - pipeline, to do inference, where the input are tens of thousands of sentences.
```
nlp = pipeline("text-generation", model= 'gpt2', device=0, return_full_text=False)
results = nlp(df_train['content'].tolist(), max_lengt... | {
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https://api.github.com/repos/huggingface/transformers/issues/11710 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11710/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11710/comments | https://api.github.com/repos/huggingface/transformers/issues/11710/events | https://github.com/huggingface/transformers/issues/11710 | 890,819,417 | MDU6SXNzdWU4OTA4MTk0MTc= | 11,710 | AssertionError: internal model should be a reference to self.model | {
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"You should update your version of Transformers to solve this issue.",
"thanks",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing... | 1,620 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.2.2
- Platform: Linux
- Python version: 3.6
- PyTorch version (GPU?): 1.7 CPU
- Tensorflow version (GPU?... | {
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https://api.github.com/repos/huggingface/transformers/issues/11709 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11709/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11709/comments | https://api.github.com/repos/huggingface/transformers/issues/11709/events | https://github.com/huggingface/transformers/pull/11709 | 890,807,218 | MDExOlB1bGxSZXF1ZXN0NjQzNzczMDMy | 11,709 | Fix gpt-2 warnings | {
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https://api.github.com/repos/huggingface/transformers/issues/11708 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11708/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11708/comments | https://api.github.com/repos/huggingface/transformers/issues/11708/events | https://github.com/huggingface/transformers/issues/11708 | 890,637,912 | MDU6SXNzdWU4OTA2Mzc5MTI= | 11,708 | stop at load tokenizer_config.json when run barthez for mrpc | {
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"No problem.It is just loading too long as 9 minute."
] | 1,620 | 1,620 | 1,620 | NONE | null | run code
```shell
python examples/text-classification/run_glue_tune.py --model_name_or_path /home2/zhenggo1/checkpoint/barthez_mrpc --task_name $TASK_NAME --do_eval --tune --max_seq_length 512 --output_dir /home2/zhenggo1/checkpoint/barthez_mrpc --tuned_checkpoint="/home2/zhenggo1/checkpoint/barthez_mrpc"
```
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"These warnings mention that buffers are not loaded, which is normal - they're created during the model initialization.\r\n\r\nThere was an attribute missing on the `GPT2Model` which led the warnings to still be raised, I'm fixing this in #11709!",
"Installing from source should resolve the warnings issue :) "
] | 1,620 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0
- Platform: Linux-4.19.0-16-cloud-amd64-x86_64-with-debian-10.9
- Python version: 3.7.10
- PyTorch ver... | {
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Clarifies the date and timezone for retrieving the prices to avoid future complaints about incorrectness.
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure i... | {
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https://api.github.com/repos/huggingface/transformers/issues/11705 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11705/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11705/comments | https://api.github.com/repos/huggingface/transformers/issues/11705/events | https://github.com/huggingface/transformers/pull/11705 | 890,141,760 | MDExOlB1bGxSZXF1ZXN0NjQzMjA2NzIz | 11,705 | [Lazy init] Force fall back to slow init for composite models | {
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11704 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11704/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11704/comments | https://api.github.com/repos/huggingface/transformers/issues/11704/events | https://github.com/huggingface/transformers/issues/11704 | 890,078,931 | MDU6SXNzdWU4OTAwNzg5MzE= | 11,704 | [RAG] official facebook example code for RAG is not working anymore. | {
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- `transformers` version: 4.6.0.dev0
- Platform: Linux-3.10.0-1127.10.1.el7.x86_64-x86_64-with-debian-buster-sid
- Python version: 3.6.13
- PyTorch version (GPU?): 1.8.1+cu102 (True)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: no
- Using distributed or parallel set-up i... | {
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https://api.github.com/repos/huggingface/transformers/issues/11702 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11702/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11702/comments | https://api.github.com/repos/huggingface/transformers/issues/11702/events | https://github.com/huggingface/transformers/issues/11702 | 890,022,646 | MDU6SXNzdWU4OTAwMjI2NDY= | 11,702 | channel_len specified but not used | {
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https://github.com/huggingface/transformers/blob/f063c56d942737d2c7aac93895cd8310afd9c7a4/src/transformers/models/ibert/quant_modules.py#L133 | {
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0.dev0
- Platform: kaggle
- Python version: 3.7
- PyTorch version (GPU?): 1.7.0 (yes)
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https://api.github.com/repos/huggingface/transformers/issues/11699 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11699/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11699/comments | https://api.github.com/repos/huggingface/transformers/issues/11699/events | https://github.com/huggingface/transformers/issues/11699 | 889,965,255 | MDU6SXNzdWU4ODk5NjUyNTU= | 11,699 | Mixed precision training : link broken | {
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"Yes, it's here: https://github.com/huggingface/transformers/tree/master/examples/pytorch/text-classification#mixed-precision-training\r\n\r\n",
"Cool, thank you!"
] | 1,620 | 1,620 | 1,620 | NONE | null | A few weeks ago this link
https://github.com/huggingface/transformers/tree/master/examples/text-classification#mixed-precision-training
showed a comparison between models trained with and without mixed precision for a bunch of sequence/text classification tasks.
Now I think that link is broken and something (examp... | {
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"The idea is to use ViT as the encoder and then a LM as the decoder for Image captioning generation, *e.g.*? @patil-suraj and I were also thinking of using `EncoderDecoder` for Speech2Text. \r\n\r\nAt the moment, I see two solutions: -> adapt `EncoderDecoder` to be usable for all modalities not just text2text **or*... | 1,620 | 1,681 | 1,651 | MEMBER | null | {
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"Both two ways work well on my own process, but `add_columns` is 4x faster than the original method.\r\n\r\nLGTM!",
"This issue has been automatically marked as stale becaus... | 1,620 | 1,624 | 1,624 | NONE | null | # What does this PR do?
@wlhgtc
It eats my 200+GB memory when adding the chinese refs, OOM killed, can't go further.
My train corpus has 17067704 lines (size: 1GB)
datasets 1.6.2 come with a new in-place add_column function, which saves the heavy coping. | {
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"I don't think this is a suitable feature, so I would recommend you override and subclass `get_train_dataloader` to simply return a training dataloader without using a sampler or `shuffle=True`."
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | # 🚀 Feature request
Currently, Trainer is shuffling the train_dataset by default and there is no flag to enable/disable it.
@sgugger
## Motivation
Even if shuffling the dataset brings a lot of benefits like preventing overfitting, at some point, one can need to disable it for experimental motivation. It... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,624 | 1,624 | NONE | null | # What does this PR do?
In the current version of the example, the `--validation_split_percentage` only works for datasets loaded from the hub but not for custom datasets. If `--do_eval` is set for custom dataset, it requires `--validation_file`.
This PR makes `--validation_split_percentage` works for a custom data... | {
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform: 4.6.0.dev0
- Python version: 3.6
- PyTorch version (GPU?): 1.6
- Tensorflow version (GPU?):
- ... | {
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"I'm really sorry to may have bothered you with that. Turns out, it works when using a different GPU :) \r\n\r\nIt struck me when I tested the same code with less data on my local machine, the trainer logged epochs (which it did not before), so I tested it on several devices. I was just a bit confused to be honest,... | 1,620 | 1,620 | 1,620 | NONE | null | I'm fine-tuning the gpt2 model using TFTrainer.
As I have to save some computational power, I needed to part the data set and train it one after another.
The first training (from TFGPT2LMHeadModel.from_pretrained('gpt2')) works well. After storing the model in a folder under a different name, and reloading it aga... | {
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https://api.github.com/repos/huggingface/transformers/issues/11687 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11687/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11687/comments | https://api.github.com/repos/huggingface/transformers/issues/11687/events | https://github.com/huggingface/transformers/issues/11687 | 888,209,359 | MDU6SXNzdWU4ODgyMDkzNTk= | 11,687 | Remove "`optional`, defaults to :obj:`None`" | {
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"Please go ahead if you want to clean this! A quick serach shows me 17 \\`optional\\`, defaults to :obj:\\`None\\` and two `optional`, defaults to None",
"ok - see #11703 @sgugger "
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | There are some docstrings with "`optional`, defaults to :obj:`None`" arguments.
According to @sgugger this should be avoided: https://github.com/huggingface/transformers/pull/11417#discussion_r629320375
PS: I can provide a PR if wanted... | {
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https://api.github.com/repos/huggingface/transformers/issues/11686 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11686/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11686/comments | https://api.github.com/repos/huggingface/transformers/issues/11686/events | https://github.com/huggingface/transformers/issues/11686 | 887,866,289 | MDU6SXNzdWU4ODc4NjYyODk= | 11,686 | Routing Transformers / Add Google PG-19 Models | {
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"There is an open-source pytorch implementation already - https://github.com/lucidrains/routing-transformer\r\nCan't we adapt RT @lucidrains wrote to HF? ",
"I've checked the repo before and was hoping with the release of the models\nthis would be possible.\n\nThe original models may be tf1 and not tf2 format. Th... | 1,620 | 1,631 | null | NONE | null | # 🌟 New model addition - Google PG-19 Models
## Model description
Model checkpoints finally released as discussed in "Efficient Content-Based Sparse Attention with Routing Transformers'
Aurko Roy, Mohammad Saffar, Ashish Vaswani, David Grangier (https://arxiv.org/abs/2003.05997)
## Open source status
* [X... | {
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https://api.github.com/repos/huggingface/transformers/issues/11685 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11685/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11685/comments | https://api.github.com/repos/huggingface/transformers/issues/11685/events | https://github.com/huggingface/transformers/pull/11685 | 887,815,656 | MDExOlB1bGxSZXF1ZXN0NjQxMDI0NjI5 | 11,685 | [WIP] Add flax generate | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11684 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11684/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11684/comments | https://api.github.com/repos/huggingface/transformers/issues/11684/events | https://github.com/huggingface/transformers/pull/11684 | 887,797,422 | MDExOlB1bGxSZXF1ZXN0NjQxMDA3MjA1 | 11,684 | Add new model RoFormer (use rotary position embedding ) | {
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"@patil-suraj I have updated some codes, please review again. Thanks~",
"@patil-suraj \r\n- I fixed the docstrings format and the build_doc tests pass\r\n- I have resolved the merge conflicts\r\n- I have run make style and make quality\r\n\r\nThank you for reviewing on this PR. ∩▂∩\r\n",
"@patrickvonplaten i h... | 1,620 | 1,621 | 1,621 | CONTRIBUTOR | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11683 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11683/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11683/comments | https://api.github.com/repos/huggingface/transformers/issues/11683/events | https://github.com/huggingface/transformers/issues/11683 | 887,754,100 | MDU6SXNzdWU4ODc3NTQxMDA= | 11,683 | Issue getting prediction_scores from TransfoXLHeadLM model when labels are provided | {
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"Hey @RedneckedCrake,\r\n\r\nI think I agree with you here! It should be a very easy fix simply by change this line: https://github.com/huggingface/transformers/blob/6ee1a4fd3e80feef8fe7dc65aabb4c5270524f8a/src/transformers/models/transfo_xl/modeling_transfo_xl.py#L1100. Would you like to give it a try to fix it?",... | 1,620 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1
- Platform: Colab
- Python version: 3.8.1
- PyTorch version (GPU?): 1.8.1+cu101 (Yes), same bug reprod... | {
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https://api.github.com/repos/huggingface/transformers/issues/11682 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11682/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11682/comments | https://api.github.com/repos/huggingface/transformers/issues/11682/events | https://github.com/huggingface/transformers/pull/11682 | 887,693,479 | MDExOlB1bGxSZXF1ZXN0NjQwOTA4Nzky | 11,682 | Test checkpointing | {
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This fixes how weights are loading when resuming training from a checkpoint, in the instances some weights are tied with other (and thus not saved). It also adds a test in the common tests to make sure the mechanism used is not broken by mistake.
Fixes #11666 | {
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"It's subtle but frustratingly important: your hypothesis template needs to have a period at the end. `This text is about {}.` Try that and let me know.",
"With the period at the end (and the proper argument name `hypothesis_template`), I'm getting\r\n\r\n```\r\n[\r\n ('science and electronics', 0.143524199724197... | 1,620 | 1,626 | 1,626 | NONE | null | Using the same text and the same labels I cannot "exactly" reproduce the result from the zeroshot app here https://huggingface.co/zero-shot/, using the "XLM Roberta XNLI" option. See below for my attempt to get the same result.
## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-5.6.0-1055-oem-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11680 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11680/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11680/comments | https://api.github.com/repos/huggingface/transformers/issues/11680/events | https://github.com/huggingface/transformers/pull/11680 | 887,453,769 | MDExOlB1bGxSZXF1ZXN0NjQwNjg0NzMw | 11,680 | [TokenClassification] Label realignment for subword aggregation | {
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"Thank you @Narsil, I'll take a look!\r\n\r\n@francescorubbo, @elk-cloner, this PR originated from yours and is based on the same approach. If you approve of this PR, can I add you as co-authors, as you've greatly contributed to its current shape? ",
"> @francescorubbo, @elk-cloner, this PR originated from yours ... | 1,620 | 1,621 | 1,621 | CONTRIBUTOR | null | # What does this PR do?
Tentative to replace #11622
- Added `AggregationStrategy`
- `ignore_subwords` and `grouped_entities` arguments are now fused
into `aggregation_strategy`. It makes more sense anyway because
`ignore_subwords=True` with `grouped_entities=False` did not have a
meaning anyway.
- Add... | {
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https://api.github.com/repos/huggingface/transformers/issues/11679 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11679/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11679/comments | https://api.github.com/repos/huggingface/transformers/issues/11679/events | https://github.com/huggingface/transformers/pull/11679 | 887,371,072 | MDExOlB1bGxSZXF1ZXN0NjQwNjA3MDU2 | 11,679 | Grammar and style edits for the frontpage README | {
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"The reason is likely padding. When passed through as a batch, the shorter sequences have to be padded to the length of the longest sequence. On GPU, you'll still get a speedup because batching allows so much more parallel computing to happen that it makes up for the padding. But on CPU you just end up with more pa... | 1,620 | 1,620 | 1,620 | NONE | null | Hi, I'm getting weird performance results using the zeroshot pipeline on a laptop with CPU. Essentially piping 5 texts through it at the same time is about 3x _slower_ than just iterating over the texts one by one:
``` python
texts = ...
classifier = pipeline("zero-shot-classification", model="joeddav/xlm-roberta-... | {
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"And one more possible venue of just tracing start/stop of each test, so perhaps this can help to identify which test doesn't complete.\r\n\r\nHere is a poor man's start/stop tracer\r\n\r\n```\r\n# add to conftest.py\r\nimport pytest\r\nimport os\r\ntrace = os.environ.get('TRACE_START_STOP', \"\")\r\n@pytest.hookim... | 1,620 | 1,651 | 1,651 | MEMBER | null | Pull request to try and identify the source of the hangs in the torch slow CI. Torch slow CI was taking three hours per run until a few days ago, and has since jumped to 6+ hours, for an unknown reason. The job ends up being killed as it goes over the timeout, so the resulting time might end up being even larger than s... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,624 | 1,624 | NONE | null | After fa84ae26d6, some strings are needlessly concatenated even though
they are not wrapped to multiple lines.
This change makes the code slightly less confusing and more grepable.
# What does this PR do?
## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks i... | {
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https://api.github.com/repos/huggingface/transformers/issues/11675 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11675/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11675/comments | https://api.github.com/repos/huggingface/transformers/issues/11675/events | https://github.com/huggingface/transformers/pull/11675 | 886,532,114 | MDExOlB1bGxSZXF1ZXN0NjM5ODA4NTQz | 11,675 | Fix TF Roberta for mixed precision training | {
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"It looks good to me too. Thanks for the PR!"
] | 1,620 | 1,686 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
This PR fixes the TF Roberta model for mixed precision training and is now aligned with the other models.
# Fixes
#11282 | {
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https://api.github.com/repos/huggingface/transformers/issues/11674 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11674/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11674/comments | https://api.github.com/repos/huggingface/transformers/issues/11674/events | https://github.com/huggingface/transformers/pull/11674 | 886,440,000 | MDExOlB1bGxSZXF1ZXN0NjM5NzIyMDk0 | 11,674 | Add MacOS TF version | {
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"As far as I have been tested until now, yes looks working quite well! I would even say that the work done by the Apple team on it is very impressive!!\r\n\r\nI will push new PRs if I encounter new issues with it :)",
"Great, thanks a lot @jplu :) "
] | 1,620 | 1,686 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
This PR adds the MacOS TensorFlow version mostly for the M1 Apple laptop that is the recommended version to use. | {
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https://api.github.com/repos/huggingface/transformers/issues/11673 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11673/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11673/comments | https://api.github.com/repos/huggingface/transformers/issues/11673/events | https://github.com/huggingface/transformers/pull/11673 | 886,241,363 | MDExOlB1bGxSZXF1ZXN0NjM5NTMzOTU3 | 11,673 | Add --text_column to run_summarization_no_trainer | {
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"Hi there and thanks for the PR! It doesn't really make sense to have `text_column` without `summary_column` to go with it. Could you add this one too?",
"Hi @sgugger ! `summary_column` is already there, it's only `text_column` missing. 😄 "
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
Add the `--text_column` option to `run_summarization_no_trainer.py`
(mostly copy from `run_summarization.py`)
Also removed a duplicated line:
`padding = "max_length" if args.pad_to_max_length else False`
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/11672 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11672/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11672/comments | https://api.github.com/repos/huggingface/transformers/issues/11672/events | https://github.com/huggingface/transformers/pull/11672 | 886,211,473 | MDExOlB1bGxSZXF1ZXN0NjM5NTA1NjUw | 11,672 | Fix docstring of description about input_ids | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11671 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11671/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11671/comments | https://api.github.com/repos/huggingface/transformers/issues/11671/events | https://github.com/huggingface/transformers/issues/11671 | 886,097,812 | MDU6SXNzdWU4ODYwOTc4MTI= | 11,671 | Why run_translation.py automatically runs on CPU? | {
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"Duplicate of https://github.com/huggingface/transformers/issues/11548#issuecomment-831159016\r\n\r\nCould you please answer to \r\n\r\n> Hi! Is your CUDA environment correctly set up? What is the output of the following in your environment?\r\n> \r\n> `python -c \"import torch;print(torch.cuda.is_available())\"`\r... | 1,620 | 1,620 | 1,620 | NONE | null | I use examples/pytorch/translation/run_translation.py fine-tune mbart-large-cc25 on my datasets, it automatically runs on CPU. I have 2 GPU, but only one is Nvidia.It is RTX 2080super.
python main.py \
--model_name_or_path facebook/mbart-large-cc25 \
--do_train \
--do_eval \
--source_lang en_XX \
--target_la... | {
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https://api.github.com/repos/huggingface/transformers/issues/11670 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11670/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11670/comments | https://api.github.com/repos/huggingface/transformers/issues/11670/events | https://github.com/huggingface/transformers/issues/11670 | 885,915,266 | MDU6SXNzdWU4ODU5MTUyNjY= | 11,670 | license missing for xlm-roberta-large, and bert-base-spanish-wwm models | {
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"xlm-roberta should be licensed under MIT like all models available through [fairseq](https://github.com/pytorch/fairseq#license). @aconneau could you please confirm?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please c... | 1,620 | 1,624 | 1,624 | CONTRIBUTOR | null | Hi HuggingFace team,
I am gratefully using many of huggingface models, but I have found 'xlm-roberta-large' model is missing its license policy.
also 'dccuchile/bert-base-spanish-wwm-uncased' and 'dccuchile/bert-base-spanish-wwm-cased'
[xlm-roberta-large](https://huggingface.co/xlm-roberta-large)
[dccuchile/ber... | {
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https://api.github.com/repos/huggingface/transformers/issues/11669 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11669/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11669/comments | https://api.github.com/repos/huggingface/transformers/issues/11669/events | https://github.com/huggingface/transformers/issues/11669 | 885,432,554 | MDU6SXNzdWU4ODU0MzI1NTQ= | 11,669 | [Question] How to serialize and load a trained RoBERTa model? | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,624 | 1,624 | NONE | null | First, I apologize for my English, I am learning the language, I am also learning a little about the networks transformers, tensorflow, keras, Bert and Roberta, I am new to this.
For a kaggle challenge, I wrote a code based on RoBERTa, the results were very good, but wanting to replicate the same code in Colab Pro, ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11668 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11668/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11668/comments | https://api.github.com/repos/huggingface/transformers/issues/11668/events | https://github.com/huggingface/transformers/issues/11668 | 884,681,155 | MDU6SXNzdWU4ODQ2ODExNTU= | 11,668 | KeyError: 'bigbird_pegasus' | {
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"Hey @loretoparisi,\r\n\r\nIt's working perfectly for me when running this:\r\n\r\n```shell\r\npip3 uninstall transformers\r\npip3 install git+https://github.com/huggingface/transformers@master\r\n```\r\n\r\n```python\r\nfrom transformers import BigBirdPegasusForConditionalGeneration, AutoTokenizer, AutoModelForSeq... | 1,620 | 1,651 | 1,620 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0.dev0
- Platform: Linux-5.10.25-linuxkit-x86_64-with-debian-10.1
- Python version: 3.7.4
- PyTorch vers... | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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"@xusky69 , does the fix work for you? I'm still getting an error upon Gpt-neo training:\r\n```bash\r\n...\r\n File \"huggingface/transformers_local/src/transformers/trainer.py\", line 1366, in train\r\n self.model.load_state_dict(state_dict)\r\n File \"huggingface-SJGCx2Wk/lib/python3.7/site-packages/torch/nn... | 1,620 | 1,620 | 1,620 | NONE | null | ## Environment info
- `transformers` version: 4.6.0.dev0 (also happens with pip 4.5.1)
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic (Google Colab)
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (True)
- Tensorflow version (GPU?): Not installed
- Using GPU in script?: Yes
- Using ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11665 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11665/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11665/comments | https://api.github.com/repos/huggingface/transformers/issues/11665/events | https://github.com/huggingface/transformers/issues/11665 | 884,522,679 | MDU6SXNzdWU4ODQ1MjI2Nzk= | 11,665 | [Question] How to move and reuse preprocessed dataset? | {
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"cc @lhoestq the preprocessed dataset should be cached, right?",
"Hi ! Yes it should, as long as you didn't change any parameter passed to the `map` function. They must be exactly the same.\r\n\r\nCould you open an issue on the `datasets` repo at https://github.com/huggingface/datasets if you want to discuss this... | 1,620 | 1,623 | 1,623 | NONE | null | Hi, I am training a gpt-2 from scratch using run_clm.py.
I want to move and reuse the preprocessed dataset (It take 2 hour to preprocess),
I tried to :
1. copy `path_to_cache_dir/datasets` to `new_cache_dir/datasets`
2. set `export HF_DATASETS_CACHE="new_cache_dir/"`
but the program still re-preprocess the... | {
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https://api.github.com/repos/huggingface/transformers/issues/11664 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11664/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11664/comments | https://api.github.com/repos/huggingface/transformers/issues/11664/events | https://github.com/huggingface/transformers/issues/11664 | 884,502,370 | MDU6SXNzdWU4ODQ1MDIzNzA= | 11,664 | RuntimeError: Error(s) in loading state_dict for Wav2Vec2ForCTC | {
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"Hey @Kamilbentounes,\r\n\r\nIt looks like your `config.vocab_size` does not match the `config.vocab_size` of the fine-tuned French Wav2Vec2 model. It looks like you want to initialize the model with 132 characters, but the original vocab size is 123. Could you try to align the vocab size to the one of the fine-tun... | 1,620 | 1,624 | 1,624 | NONE | null | ## Environment info
- `transformers` version: 4.5.0
- Platform: Ubuntu 18.04
- Python version: 3.7.4
### Who can help
- @patrickvonplaten
## Information
Model Im using is Wav2vec 2.0.
The problem arises when loading the pretrained/fintuned model:
```
RuntimeError: Error(s) in loading state_dict fo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11663 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11663/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11663/comments | https://api.github.com/repos/huggingface/transformers/issues/11663/events | https://github.com/huggingface/transformers/pull/11663 | 884,381,728 | MDExOlB1bGxSZXF1ZXN0NjM3NzY4ODU5 | 11,663 | Save scaler state dict when checkpointing | {
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One last thing was missing for resuming with checkpoints and have exactly the same results as a complete training: the gradient scaler state when using mixed precision with AMP in PyTorch. This PR addresses that.
Fixes #11323 | {
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https://api.github.com/repos/huggingface/transformers/issues/11662 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11662/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11662/comments | https://api.github.com/repos/huggingface/transformers/issues/11662/events | https://github.com/huggingface/transformers/issues/11662 | 884,365,157 | MDU6SXNzdWU4ODQzNjUxNTc= | 11,662 | IBERT: Testing the speedup | {
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"Hi! You may find the discussion in https://github.com/huggingface/transformers/issues/11312 by @kssteven418 interesting!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that is... | 1,620 | 1,635 | 1,623 | NONE | null | Hi,
I want to test IBERT's speedup, and I have done exactly what is said in https://huggingface.co/kssteven/ibert-roberta-base. For the quantization part, when I set quant_mode to true and run the evaluation again, I get a much slower model. What am I doing wrong?
Thank you for your reply! | {
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https://api.github.com/repos/huggingface/transformers/issues/11661 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11661/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11661/comments | https://api.github.com/repos/huggingface/transformers/issues/11661/events | https://github.com/huggingface/transformers/pull/11661 | 884,178,831 | MDExOlB1bGxSZXF1ZXN0NjM3NTg0NzM3 | 11,661 | Update pretrained_models.rst | {
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"Hi @patil-suraj , \r\nI added the (N encoder and decoder layers) to the existing descriptions for facebook/bart-base and facebook/bart-large. Thanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this t... | 1,620 | 1,623 | 1,623 | NONE | null | # What does this PR do?
Updates the description of facebook/bart-base and facebook/bart-large in Pretrained models to specify the number of encoder and decoder layers according to #11574 | {
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https://api.github.com/repos/huggingface/transformers/issues/11660 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11660/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11660/comments | https://api.github.com/repos/huggingface/transformers/issues/11660/events | https://github.com/huggingface/transformers/pull/11660 | 884,087,772 | MDExOlB1bGxSZXF1ZXN0NjM3NTAyNDI2 | 11,660 | run_text_classification.py fix | {
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https://api.github.com/repos/huggingface/transformers/issues/11659 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11659/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11659/comments | https://api.github.com/repos/huggingface/transformers/issues/11659/events | https://github.com/huggingface/transformers/issues/11659 | 884,070,670 | MDU6SXNzdWU4ODQwNzA2NzA= | 11,659 | [Doc] Something wrong in description of 'DistilBertForSequenceClassification' in doc | {
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"That's correct, thanks for spotting! Could you open a PR to fix this?\r\n\r\nThanks!"
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | I think the description of input_ids (one of the parameters) of [DistilBertForSequenceClassification](https://huggingface.co/transformers/model_doc/distilbert.html#distilbertforsequenceclassification) is not correct.
I think the input_ids should be `torch.LongTensor of shape (batch_size, sequence_length)`, rather than... | {
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https://api.github.com/repos/huggingface/transformers/issues/11658 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11658/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11658/comments | https://api.github.com/repos/huggingface/transformers/issues/11658/events | https://github.com/huggingface/transformers/issues/11658 | 883,995,692 | MDU6SXNzdWU4ODM5OTU2OTI= | 11,658 | NCLL No space left on device Error while training with deepspeed | {
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"I am closing the issue, because I see that it is a docker shm issue that is not related to HF. I have solved the issue thanks to [this stackoverflow issue](https://stackoverflow.com/a/46434614/11758585)"
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.4.0
- Platform: docker
- Python version: 3.8
- PyTorch version (GPU?): pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 -f https://download.pytorch.org/whl/torch_stable.html
- Using distributed or parallel set-up in script?: DDP
Models:
- LayoutLMForTo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11657 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11657/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11657/comments | https://api.github.com/repos/huggingface/transformers/issues/11657/events | https://github.com/huggingface/transformers/issues/11657 | 883,919,773 | MDU6SXNzdWU4ODM5MTk3NzM= | 11,657 | Memory Leak in Deberta (v1) Base | {
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"Hello @alexvaca0, thank you for opening an issue! Is there a way for you to provide a collab with a reproducer so that we may take a look at the memory issue?\r\n\r\nRegarding the very bad performance, and your query that you hope the \"architecture itself is not wrongly coded\" - rest assured, the architecture wa... | 1,620 | 1,630 | 1,630 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0.dev0
- Platform: Linux-5.4.0-1047-aws-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11656 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11656/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11656/comments | https://api.github.com/repos/huggingface/transformers/issues/11656/events | https://github.com/huggingface/transformers/issues/11656 | 883,908,018 | MDU6SXNzdWU4ODM5MDgwMTg= | 11,656 | DISTILBERT: run_squad.py not working | {
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"Hi! This script is a legacy script that we will not be maintaining anymore. Have you tried with the `run_qa.py` script available [here](https://github.com/huggingface/transformers/tree/master/examples/pytorch/question-answering)? This script should be simpler to understand and more complete.\r\n\r\nLet us know if ... | 1,620 | 1,623 | 1,623 | NONE | null | Hi,
I am trying to use the transformers/examples/legacy/question-answering/run_squad.py script to train and evaluate DistilBERT on squad2.0. Unfortunately it throws the following error:
**TypeError: forward() got an unexpected keyword argument 'token_type_ids'**
I used the following tokenizer: distilbert-base... | {
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https://api.github.com/repos/huggingface/transformers/issues/11655 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11655/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11655/comments | https://api.github.com/repos/huggingface/transformers/issues/11655/events | https://github.com/huggingface/transformers/pull/11655 | 883,818,743 | MDExOlB1bGxSZXF1ZXN0NjM3MjU4NzY5 | 11,655 | Fine-tuning the Entire RAG Architecture (including DPR retriever) | {
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"> Great, I think we are very close to merging this PR :-)\r\n> \r\n> Could we add a test in both `test_modeling_rag` and `test_retrieval_rag` ? We should test there that the model behaves correctly when `set_context_encoder_for_training` is set\r\n\r\non it!",
"Hello, I tried running the code in this pull reques... | 1,620 | 1,623 | 1,622 | CONTRIBUTOR | null | # What does this PR do?
The original RAG implementation is able to end-to-end train the question encoder and the generator.
This extension enables the end-to-end training of RAG including the context encoder in the retriever component.
Please read the [accompanying blog post](https://shamanesiri.medium.com/how-t... | {
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Add bigbird-pegasus evaluation notebook
@patrickvonplaten | {
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https://api.github.com/repos/huggingface/transformers/issues/11653 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11653/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11653/comments | https://api.github.com/repos/huggingface/transformers/issues/11653/events | https://github.com/huggingface/transformers/pull/11653 | 883,601,253 | MDExOlB1bGxSZXF1ZXN0NjM3MDYxMTcx | 11,653 | Add DETR | {
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"@LysandreJik all comments are addressed, also added 2 community notebooks. PR is ready!"
] | 1,620 | 1,626 | 1,623 | CONTRIBUTOR | null | # What does this PR do?
It adds Facebook AI's DETR model (end-to-end object detection with Transformers). It's a clean PR based on #11506.
The 3 models are called `DetrModel`, `DetrForObjectDetection` and `DetrForSegmentation`. The latter was first called `DetrForPanopticSegmentation`, but as it can also be used... | {
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https://api.github.com/repos/huggingface/transformers/issues/11652 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11652/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11652/comments | https://api.github.com/repos/huggingface/transformers/issues/11652/events | https://github.com/huggingface/transformers/issues/11652 | 883,540,331 | MDU6SXNzdWU4ODM1NDAzMzE= | 11,652 | [DOC] Fine-Tuning NER Custom Dataset Clarification | {
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"When did you encounter that `ValueError`? Normally, if you pass text into the `__call__` method of a tokenizer with `truncation` set to `True`, you shouldn't encounter any errors, as sequences that are too long are truncated.",
"Hi Niels, thanks for your feedback. The Exception is raised when calling `encode_tag... | 1,620 | 1,660 | 1,625 | NONE | null | I'm following [this](https://huggingface.co/transformers/custom_datasets.html#tok-ner) guide for fine-tuning for NER with a custom dataset. I struggled with the example code for `def encode_tags()` until I realized, that the tokens per sample are limited to 512 and my dataset exceeded this in some instances. This resul... | {
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https://api.github.com/repos/huggingface/transformers/issues/11651 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11651/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11651/comments | https://api.github.com/repos/huggingface/transformers/issues/11651/events | https://github.com/huggingface/transformers/pull/11651 | 883,524,707 | MDExOlB1bGxSZXF1ZXN0NjM2OTkyMDg5 | 11,651 | BigBird on TPU | {
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"Hi, do you guys have any idea whether we can still train with `trainer` on TPU with BigBird? I am still facing this same error.\r\n\r\nIs there any tentative timeline by which this problem can be fixed?",
"BigBird will be merged in Flax soon. It is recommend to use `FlaxBigBird` for TPU ",
"That's great news! ... | 1,620 | 1,623 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
This PR will enable BigBird working on TPUs. Problem was happening because we were concatenating tensors of different dtypes. This PR will fix it.
See this notebook to infer BigBird on TPUs: https://colab.research.google.com/drive/1ptZlDuEgmoElWmPmrZXHA7uWjvra9G8T#scrollTo=sR2Yk-HzmGnw
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https://api.github.com/repos/huggingface/transformers/issues/11650 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11650/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11650/comments | https://api.github.com/repos/huggingface/transformers/issues/11650/events | https://github.com/huggingface/transformers/pull/11650 | 882,742,203 | MDExOlB1bGxSZXF1ZXN0NjM2MjU4NjE5 | 11,650 | [Examples] Fix invalid links after reorg | {
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The link in some examples' README didn't being updated after example reorg (#11350).
I simply `grep -R https://github.com/huggingface/transformers/blob/master/examples` in examples and fix those invalid links.
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https://api.github.com/repos/huggingface/transformers/issues/11649 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11649/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11649/comments | https://api.github.com/repos/huggingface/transformers/issues/11649/events | https://github.com/huggingface/transformers/issues/11649 | 882,591,491 | MDU6SXNzdWU4ODI1OTE0OTE= | 11,649 | Reformer inference widget is broken | {
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"Yeah Reformer has no tokenizer so this doesn't work...sadly I also think since Reformer doesn't work super well, it's low priority to fix this (cc @Narsil )",
"Seems like the tokenizer fix is not that hard to make given the README (simply byte shift+2).\r\n\r\nHowever the code seems to refer to a spiece.model : ... | 1,620 | 1,623 | 1,623 | CONTRIBUTOR | null | From: https://huggingface.co/google/reformer-enwik8?text=My+name+is+Julien+and+I+like+to
@patrickvonplaten | {
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https://api.github.com/repos/huggingface/transformers/issues/11648 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11648/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11648/comments | https://api.github.com/repos/huggingface/transformers/issues/11648/events | https://github.com/huggingface/transformers/issues/11648 | 882,565,132 | MDU6SXNzdWU4ODI1NjUxMzI= | 11,648 | Very large difference between the results after resume | {
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"Please do not open a duplicate issue, you can reopen the old one.",
"Dear Sylvain\r\nIf huggingFace team closes an issue, the user is not able to reopen it, at least on my side, I also attached the screenshot of it. \r\n\r\nhttps://ibb.co/56S00LT\r\n\r\nThank you. ",
"Your screenshot does not show the bottom o... | 1,620 | 1,620 | 1,620 | NONE | null | Dear HuggingFace team,
There is unfortunately no option to reopen the bugs, the issue I reported here [1] still exists with testing the last version of transformers. I add my comments on the same ticket. Could you kindly reopen this bug?
The variations are very high after resume, which makes the results not usabl... | {
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https://api.github.com/repos/huggingface/transformers/issues/11647 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11647/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11647/comments | https://api.github.com/repos/huggingface/transformers/issues/11647/events | https://github.com/huggingface/transformers/issues/11647 | 882,062,899 | MDU6SXNzdWU4ODIwNjI4OTk= | 11,647 | Key Error: 'pre-processing' during conversion from tatoeba to Marian model | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,632 | null | NONE | null | ## Environment info
- `transformers` version: `4.6.0.dev0`
- Platform: `CentOS Linux release 7.7.1908 (Core)`
- Python version: `3.8.5`
- PyTorch version: `1.8.1 + cuda 10.2`
- Tensorflow version: N/A
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### Who can help
Marian... | {
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https://api.github.com/repos/huggingface/transformers/issues/11646 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11646/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11646/comments | https://api.github.com/repos/huggingface/transformers/issues/11646/events | https://github.com/huggingface/transformers/issues/11646 | 881,776,145 | MDU6SXNzdWU4ODE3NzYxNDU= | 11,646 | Strange implementation of `convert_tokens_to_string` in albert tokenizer. | {
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"Indeed, you're probably right! When updating the ALBERT tokenizer to use the `sentencepiece.decode` instead of the manual handling - do all tests pass? Even the integration test?\r\n\r\nMakes me think we really should have integration tests for all tokenizers, as scenarios like this one are bound to happen.",
"W... | 1,620 | 1,626 | 1,626 | CONTRIBUTOR | null | Hi,
the albert tokenizer implements the `convert_tokens_to_string` function:
https://github.com/huggingface/transformers/blob/ba0d50f2148f0db0e04a80cddb1f57ce0c91c182/src/transformers/models/albert/tokenization_albert.py#L222-L223
While the deberta v2 and some other tokenizer just delegate this to the sentence... | {
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https://api.github.com/repos/huggingface/transformers/issues/11645 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11645/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11645/comments | https://api.github.com/repos/huggingface/transformers/issues/11645/events | https://github.com/huggingface/transformers/issues/11645 | 880,765,948 | MDU6SXNzdWU4ODA3NjU5NDg= | 11,645 | Bad result in fine-tuning XLNet for SQuAD | {
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"Hi @Timothy023 \r\n\r\nPlease use the [forum](https://discuss.huggingface.co/) to post such questions. Thanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that ... | 1,620 | 1,623 | 1,623 | NONE | null | Hello,
I'am fine-tuning XLNet for SQuAD V1.1 task, but I get the bad result. I got checkpoint of XLNet in [model hub](https://huggingface.co/xlnet-base-cased).
GPU: single GeForce RTX 3090 24G
running scripy:
`CUDA_VISIBLE_DEVICES=4 python ./examples/pytorch/question-answering/run_qa.py --model_name_or_path... | {
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