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https://api.github.com/repos/huggingface/transformers/issues/9229 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9229/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9229/comments | https://api.github.com/repos/huggingface/transformers/issues/9229/events | https://github.com/huggingface/transformers/issues/9229 | 771,927,000 | MDU6SXNzdWU3NzE5MjcwMDA= | 9,229 | Generate function does not work with GPU | {
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"Hey @contribcode,\r\n\r\ncould you please provide a complete code snippet that would allow us to reproduce the error? Thanks!",
"@patrickvonplaten thank you for your response. \r\n\r\n```python\r\nimport torch\r\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\r\nfrom transformers import GP... | 1,608 | 1,622 | 1,614 | NONE | null | Hello,
I want to use generate function with single GPU. Specifically, I fine tuned a GPT-2 model (on GPU) and subsequently, I want to generate text with it.
When I run this
```
input_ids.to(device)
sample_output = model.generate(
input_ids,
do_sample=True,
max_length=150,
top_k=50,
... | {
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https://api.github.com/repos/huggingface/transformers/issues/9228 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9228/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9228/comments | https://api.github.com/repos/huggingface/transformers/issues/9228/events | https://github.com/huggingface/transformers/issues/9228 | 771,882,102 | MDU6SXNzdWU3NzE4ODIxMDI= | 9,228 | Differences between original implementation and HuggingFace implementation | {
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"Hi there,\r\n\r\nI made some [integration tests](https://github.com/NielsRogge/transformers/blob/e5431da34ab2d03d6114303f18fd70192c880913/tests/test_modeling_layoutlm.py#L318) for both the base model (`LayoutLM`) as well as the model with a token classification head on top (`LayoutLMForTokenClassification`). These... | 1,608 | 1,614 | 1,614 | 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: **4.0.0**
- Platform: **Windows**
- Python version: **3.6.5**
- PyTorch version (GPU?): **1.6.0+cu101**... | {
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https://api.github.com/repos/huggingface/transformers/issues/9227 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9227/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9227/comments | https://api.github.com/repos/huggingface/transformers/issues/9227/events | https://github.com/huggingface/transformers/issues/9227 | 771,880,443 | MDU6SXNzdWU3NzE4ODA0NDM= | 9,227 | Can't lazy initialize BART model on GPU | {
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"@jethrokuan - Please try this on the transformers 4.1.0; issue looks to be fixed in this version",
"Actually it looks like the problem is exasperated in newer HF. In a devbox with no CUDA:\r\n\r\n```\r\nPython 3.7.9 (default, Nov 18 2020, 11:18:33)\r\n[GCC 6.3.0 20170516] on linux\r\nType \"help\", \"copyright\"... | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 3.5.1
- Platform: Linux-4.14.81.bm.15-amd64-x86_64-with-debian-9.11
- Python version: 3.7.9
- PyTorch version (GPU?): 1.7.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: Yes
##... | {
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https://api.github.com/repos/huggingface/transformers/issues/9226 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9226/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9226/comments | https://api.github.com/repos/huggingface/transformers/issues/9226/events | https://github.com/huggingface/transformers/issues/9226 | 771,755,483 | MDU6SXNzdWU3NzE3NTU0ODM= | 9,226 | n_gpus is set to 1 in case of distributed training on multiple gpus, how to access to the correct n_gpus | {
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"Please do not spam the issues: this is a duplicate of #9225. You can edit the title and the description, there is no need to send a new notification to everyone watching the repo.\r\nAlso, please use the [forum](https://discuss.huggingface.co/) for questions like this, we keep the issues for bugs and features requ... | 1,608 | 1,608 | 1,608 | NONE | null | Hi
I am using transformer 4.1.1 on multiple gpus with distributed launch script below, the n_gpu set in this case is 1 instead of actual n_gpus, could you tell me how I can access to the total number of ranks calling the launcher with? Is there any variable in huggingface library which could show the number of gpus th... | {
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https://api.github.com/repos/huggingface/transformers/issues/9225 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9225/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9225/comments | https://api.github.com/repos/huggingface/transformers/issues/9225/events | https://github.com/huggingface/transformers/issues/9225 | 771,755,274 | MDU6SXNzdWU3NzE3NTUyNzQ= | 9,225 | n_gpu=1 in case of using distributed pytorch launcher | {
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"Duplicate of #9226"
] | 1,608 | 1,608 | 1,608 | NONE | null | Hi
I am using transformer 4.1.1 on multiple gpus with distributed launch script below, the n_gpu set in this case is 1 instead of actual n_gpus, could you tell me how I can access to the total number of ranks calling the launcher with? Is there any variable in huggingface library which could show the number of gpus th... | {
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https://api.github.com/repos/huggingface/transformers/issues/9224 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9224/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9224/comments | https://api.github.com/repos/huggingface/transformers/issues/9224/events | https://github.com/huggingface/transformers/issues/9224 | 771,698,366 | MDU6SXNzdWU3NzE2OTgzNjY= | 9,224 | allowing the user to set booleans with HfArgumentParser | {
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"Hey @rabeehkarimimahabadi, \r\n\r\nOne should not call the `HfArgumentParser` with \r\n\r\n`--overwrite_output_dir True`, but just with `--overwrite_output_dir` to set the bool from `False` to `True`. If one wants to leave it as `False`, the arg should just not be passed. If the default field of this variable is a... | 1,608 | 1,608 | 1,608 | NONE | null | Hi
this is more general issue, if the user defines some booleans as arguments like --flag false/true once calling the finetune_trainer.py one would get following error as below with HfArgumentParser, it would be great to allow users set explicit values for booleans too, currently this is only possible with config file... | {
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https://api.github.com/repos/huggingface/transformers/issues/9223 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9223/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9223/comments | https://api.github.com/repos/huggingface/transformers/issues/9223/events | https://github.com/huggingface/transformers/issues/9223 | 771,689,498 | MDU6SXNzdWU3NzE2ODk0OTg= | 9,223 | passing config file to train with on multiple gpus | {
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"this does not work since finetuner_trainer.py gets config as only one argument and local_rank is also passed with this command, is there an easy fix for this without parsing arguments from config? thanks ",
"I solved it with updating finetune_trainer accepting --local_rank + config file"
] | 1,608 | 1,608 | 1,608 | NONE | null | ## Environment info
- transformers 3.5.1
- Python version: 3.7
- PyTorch version (GPU?): 1.6
- Tensorflow version (GPU?): -
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: yes
### Who can help
Trainer: @sgugger
T5: @patrickvonplaten
FSMT: @stas00
examples/seq2seq: @pa... | {
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https://api.github.com/repos/huggingface/transformers/issues/9222 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9222/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9222/comments | https://api.github.com/repos/huggingface/transformers/issues/9222/events | https://github.com/huggingface/transformers/issues/9222 | 771,512,991 | MDU6SXNzdWU3NzE1MTI5OTE= | 9,222 | Does provide any scripts about how to convert mpnet pretrain model to transformers pretrain one? | {
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"Maybe the author of MPNet can help here, @StillKeepTry ",
"@patrickvonplaten problem is fix"
] | 1,608 | 1,608 | 1,608 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
I want to convert my pretrain chinese mpnet with the fairseq format to transformers format
<!-- Please outline the motivation for the pro... | {
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https://api.github.com/repos/huggingface/transformers/issues/9221 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9221/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9221/comments | https://api.github.com/repos/huggingface/transformers/issues/9221/events | https://github.com/huggingface/transformers/issues/9221 | 771,511,217 | MDU6SXNzdWU3NzE1MTEyMTc= | 9,221 | TAPAS: IndexError: index out of range in self | {
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"cc @NielsRogge ",
"It doesn't work because `type_vocab_sizes=[3, 256, 256, 2, 256, 256, 10]` which means the default max size of a table is 256*256. However, the tokenizer doesn't check it. \r\nStrictly speaking, it's not a bug but I think in that kind of tasks, many tables' size can exceed the default value.\r\... | 1,608 | 1,701 | 1,610 | 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: 4.1.0.dev0
- Platform: Linux-4.15.0-122-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.9
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/9220 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9220/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9220/comments | https://api.github.com/repos/huggingface/transformers/issues/9220/events | https://github.com/huggingface/transformers/pull/9220 | 771,509,767 | MDExOlB1bGxSZXF1ZXN0NTQzMDE0Nzk1 | 9,220 | Proposed Fix : [RagSequenceForGeneration] generate "without" input_ids | {
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"@ratthachat - thanks a lot for your PR! I agree that option 2) is the better option and think the general approach is exactly right. I left a couple of statements making that improve readability a bit IMO. Also could we add one test here: \r\nhttps://github.com/huggingface/transformers/blob/f38c4ad302dd34faef1137b... | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | # What does this PR do?
Proposal of option (2) mentioned in the issue `RagSequenceForGeneration.generate()` without `input_ids`
https://github.com/huggingface/transformers/issues/9184
### Re-paste here:
In `RagSequenceForGeneration` method `generate()` function, the doc said that both `input_ids` and `context_in... | {
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https://api.github.com/repos/huggingface/transformers/issues/9219 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9219/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9219/comments | https://api.github.com/repos/huggingface/transformers/issues/9219/events | https://github.com/huggingface/transformers/pull/9219 | 771,476,408 | MDExOlB1bGxSZXF1ZXN0NTQyOTkyNjM0 | 9,219 | Fix beam search generation for GPT2 and T5 on model parallelism | {
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"@sgugger can you maybe review as well and merge if ok?"
] | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | # What does this PR do?
This PR fixes beam search generation crash when the model layers are distributed on several devices (model parallelism). I have also added a test which showcase the bug on master and pass with the provided fix. Fixes issue #9200
This is my first contribution to Transformers, so please let... | {
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https://api.github.com/repos/huggingface/transformers/issues/9218 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9218/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9218/comments | https://api.github.com/repos/huggingface/transformers/issues/9218/events | https://github.com/huggingface/transformers/issues/9218 | 771,462,949 | MDU6SXNzdWU3NzE0NjI5NDk= | 9,218 | run_clm.py AttributeError: 'NoneType' object has no attribute 'keys' | {
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"Hey @mukhtar-algezoli,\r\n\r\nIt seems like you are using tensorflow, but the script `run_clm.py` only works for PyTorch -> I'm afraid you have to use PyTorch in order to use `run_clm.py`.",
"@patrickvonplaten thank you.",
"hi @patrickvonplaten ,\r\nif i want use tensorflow to pretrain bert model with transfor... | 1,608 | 1,632 | 1,608 | 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: 4.2.0dev0
- Platform: Linux-4.19.0-13-cloud-amd64-x86_64-with-debian-10.7
- Python version: 3.7.8
- PyT... | {
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https://api.github.com/repos/huggingface/transformers/issues/9217 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9217/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9217/comments | https://api.github.com/repos/huggingface/transformers/issues/9217/events | https://github.com/huggingface/transformers/pull/9217 | 771,433,755 | MDExOlB1bGxSZXF1ZXN0NTQyOTYzOTU2 | 9,217 | Fix documentation links always pointing to master. | {
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"Thanks for merging @LysandreJik but I want to know why the errors occurred when I ran `make style ` as I see in https://github.com/huggingface/transformers/pull/9217#discussion_r548898170"
] | 1,608 | 1,609 | 1,609 | CONTRIBUTOR | null | # What does this PR do?
This PR fixes documentation issue. The issue is that hyperlinks pointing to code file in the docs always point to the master.
Reference issue : https://github.com/huggingface/transformers/issues/7988
I found [extlinks](https://www.sphinx-doc.org/en/master/usage/extensions/extlinks.html) m... | {
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https://api.github.com/repos/huggingface/transformers/issues/9216 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9216/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9216/comments | https://api.github.com/repos/huggingface/transformers/issues/9216/events | https://github.com/huggingface/transformers/issues/9216 | 771,426,566 | MDU6SXNzdWU3NzE0MjY1NjY= | 9,216 | checkpoint callbacks | {
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"In particular I need to define a callback with on_save function, for this I need to be able to acces \"is_world_process_zero\" and I am not sure how to do it. If I want to pass trainer to callback, how can I make sure this is passed? thanks",
"solved with understanding is_world_process_zero is accessible via st... | 1,608 | 1,608 | 1,608 | NONE | null | Hi
I need to save more things during checkpoint and I am using finetune_trainer.py not the pytorch lightening one, could you provide me with example on how I can modify the save part of the checkpoints? thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/9215 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9215/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9215/comments | https://api.github.com/repos/huggingface/transformers/issues/9215/events | https://github.com/huggingface/transformers/issues/9215 | 771,415,258 | MDU6SXNzdWU3NzE0MTUyNTg= | 9,215 | File "/opt/conda/envs/updated/lib/python3.7/site-packages/fairscale/nn/data_parallel/sharded_ddp.py", line 280, in _setup_backward_hooks assert p_tmp.grad_fn is not None | {
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"As I tried to explain earlier it's not ready yet for general consumption.\r\n\r\nIf you want it sooner see: https://github.com/huggingface/transformers/issues/9156#issuecomment-748501582"
] | 1,608 | 1,608 | 1,608 | NONE | null | Hi
@stas00 @sgugger
I am testing last version of finetune_trainer on multiple gpus, with this command
`export BS=4; CUDA_VISIBLE_DEVICES=0,1 USE_TF=0 python -m torch.distributed.launch --nproc_per_node=2 --master_port=9910 finetune_trainer.py --model_name_or_path t5-small --output_dir output_dir --adam_eps 1e... | {
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https://api.github.com/repos/huggingface/transformers/issues/9214 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9214/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9214/comments | https://api.github.com/repos/huggingface/transformers/issues/9214/events | https://github.com/huggingface/transformers/issues/9214 | 771,390,621 | MDU6SXNzdWU3NzEzOTA2MjE= | 9,214 | Save underlying BertModel only | {
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"If your bert model is an instance of `BertModel` then you should be able to save it using `self.your_model.bert.save_pretrained(path)` and load using `.from_pretrained`",
"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n... | 1,608 | 1,614 | 1,614 | NONE | null | I currently have a custom model on top of a pretrained BERT Model, which is effectively just dropout and a linear layer on top for classification. I want to be able to train this classifier, updating the underlying weights, but then to save the `BERTModel` underneath (w/o linear classification layer) so that I can load... | {
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https://api.github.com/repos/huggingface/transformers/issues/9213 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9213/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9213/comments | https://api.github.com/repos/huggingface/transformers/issues/9213/events | https://github.com/huggingface/transformers/issues/9213 | 771,387,662 | MDU6SXNzdWU3NzEzODc2NjI= | 9,213 | bert-mlm-converting from tensorflow to pytorch | {
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"hello, i convert bert model from tensorflow to pytorch to fine tune it and in train function specially in loss , pred_masks = model(inputs, labels) i got this error not enough values to unpack (expected 2, got 1) why model return one only it should return two one for loss and the second for pred_masks",
"This is... | 1,608 | 1,614 | 1,614 | 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:
- Platform:
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in s... | {
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https://api.github.com/repos/huggingface/transformers/issues/9212 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9212/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9212/comments | https://api.github.com/repos/huggingface/transformers/issues/9212/events | https://github.com/huggingface/transformers/issues/9212 | 771,351,348 | MDU6SXNzdWU3NzEzNTEzNDg= | 9,212 | LXMERT cross_modality_matching logits order in code vs. documentation | {
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"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n\nIf you think this still needs to be addressed please comment on this thread."
] | 1,608 | 1,614 | 1,614 | NONE | null | Issue #7266 evolved into an entirely different issue described below.
# Possible documentation error
Independently of considering #8333 or not, it is clear that the results of the cross-modality matching in LXMERT (for example in [this demo](https://colab.research.google.com/drive/18TyuMfZYlgQ_nXo-tr8LCnzUaoX0KS-h?... | {
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https://api.github.com/repos/huggingface/transformers/issues/9211 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9211/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9211/comments | https://api.github.com/repos/huggingface/transformers/issues/9211/events | https://github.com/huggingface/transformers/pull/9211 | 771,325,824 | MDExOlB1bGxSZXF1ZXN0NTQyODg5OTc4 | 9,211 | [trainer] deepspeed integration | {
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"Thanks @stas00 for putting this together! I think there might be a few things we can do on the deepspeed side to smooth a few pain points out. Most of us our out of office until the new year but will definitely be taking a close look at this soon and help where we can.",
"Thank you, @jeffra! \r\n\r\nNew year sou... | 1,608 | 1,610 | 1,610 | CONTRIBUTOR | null | This PR adds experimental support for Deepspeed <https://github.com/microsoft/deepspeed>, whose main feature is ZeRO covered by the paper [ZeRO: Memory Optimizations Toward Training Trillion Parameter Models, by Samyam Rajbhandari, Jeff Rasley, Olatunji Ruwase, Yuxiong He](https://arxiv.org/abs/1910.02054).
Recentl... | {
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https://api.github.com/repos/huggingface/transformers/issues/9210 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9210/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9210/comments | https://api.github.com/repos/huggingface/transformers/issues/9210/events | https://github.com/huggingface/transformers/issues/9210 | 771,318,697 | MDU6SXNzdWU3NzEzMTg2OTc= | 9,210 | MLFlow logger breaks training | {
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"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n\nIf you think this still needs to be addressed please comment on this thread."
] | 1,608 | 1,614 | 1,614 | NONE | null | I'm running into two issues when I try and train with mflow installed.
The main one is transformers logs every single parameter and mlflow has restrictions on parameter size. So when I tried to train a `AutoModelForSequenceClassification` using the code below
```
num_labels=25
config = AutoConfig.from_pretraine... | {
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https://api.github.com/repos/huggingface/transformers/issues/9209 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9209/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9209/comments | https://api.github.com/repos/huggingface/transformers/issues/9209/events | https://github.com/huggingface/transformers/issues/9209 | 771,314,862 | MDU6SXNzdWU3NzEzMTQ4NjI= | 9,209 | Error while loading model file - .ckpt file :: Missing key(s) in state_dict | {
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"Hi @adithyaan-creator \r\n\r\nSeems like you used `pytorch-lightning` for training, `pl` prefixes every `state_dict` key with `model.` so to load the `pl` checkpoint to hf format, remove the `model.` prefix from `state_dict` keys.\r\n\r\n```python3\r\ndef remove_prefix(text: str, prefix: str):\r\n if text.start... | 1,608 | 1,616 | 1,608 | NONE | null | @julien-c @patrickvonplaten @thomwolf
transformers version == 4.0.0
I trained a T5 model for classification and I am trying to load the checkpoint model saved after 3 epochs.
While trying to load the model, getting the below error.
![image](https://user-images.githubusercontent.com/54103522/102682082-a0281200-4... | {
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https://api.github.com/repos/huggingface/transformers/issues/9208 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9208/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9208/comments | https://api.github.com/repos/huggingface/transformers/issues/9208/events | https://github.com/huggingface/transformers/pull/9208 | 771,312,144 | MDExOlB1bGxSZXF1ZXN0NTQyODgwODE4 | 9,208 | [docs] outline sharded ddp doc | {
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We won't merge this until fairscale merged all the required fixes and released a new version, but I thought it'd be good to start the doc going ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9207/comments | https://api.github.com/repos/huggingface/transformers/issues/9207/events | https://github.com/huggingface/transformers/issues/9207 | 771,304,235 | MDU6SXNzdWU3NzEzMDQyMzU= | 9,207 | Saving Pretrained Tokenizer | {
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"I realised that\r\n\r\n`tokenizer.model.save(\"./tokenizer\")`\r\n\r\nIs unnecessary. I've started saving only the `tokenizer.json` since this contains not only the merges and vocab but also the pipeline.\r\n\r\nAnd I noticed that `tokenizer.save_pretrained()` has a parameter `legacy_format` which defaults to Tru... | 1,608 | 1,614 | 1,614 | NONE | null | I created a custom `tokenizers.Tokenizer` and saved it as follows
```
tokenizer.model.save("./tokenizer")
tokenizer.save("./tokenizer.json")
```
This produces 3 files, merges.txt, vocab.json and tokenizer.json
Then I created a `transformers.RobertaTokenizerFast` and saved it to the same folder
```
toke... | {
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https://api.github.com/repos/huggingface/transformers/issues/9206 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9206/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9206/comments | https://api.github.com/repos/huggingface/transformers/issues/9206/events | https://github.com/huggingface/transformers/issues/9206 | 771,290,740 | MDU6SXNzdWU3NzEyOTA3NDA= | 9,206 | DataTrainingArguments: __init__() got an unexpected keyword argument 'evaluate_during_training' | {
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"Indeed, will fix that notebook on Monday. Thanks for reporting!",
"Note that this notebook is quite old, so you might prefer the most recent one [here](https://github.com/huggingface/notebooks/blob/master/examples/text_classification.ipynb). I fixed the issue by pinning the transformers version inside it, we wil... | 1,608 | 1,608 | 1,608 | 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: 4.0
- Platform: Google Colab
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7
- Tensorflow versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/9205 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9205/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9205/comments | https://api.github.com/repos/huggingface/transformers/issues/9205/events | https://github.com/huggingface/transformers/issues/9205 | 771,286,176 | MDU6SXNzdWU3NzEyODYxNzY= | 9,205 | [model_utils] very slow model instantiation | {
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"Doesn't that script also loads and preprocess the data? From what you're reporting, I don't interpret this as \"transformers takes a long time to load the model\" (since the line that does that takes the same time as a torch load) but as \"stuff that happens in that script before the model loading takes a lot of t... | 1,608 | 1,664 | 1,620 | CONTRIBUTOR | null | For some reason I'm noticing a very slow model instantiation time.
For example to load `shleifer/distill-mbart-en-ro-12-4` it takes
* 21 secs to instantiate the model
* 0.5sec to `torch.load` its weights.
If I'm not changing how the model is created and want to quickly fast forward to the area of debug how cou... | {
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https://api.github.com/repos/huggingface/transformers/issues/9204 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9204/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9204/comments | https://api.github.com/repos/huggingface/transformers/issues/9204/events | https://github.com/huggingface/transformers/issues/9204 | 771,264,897 | MDU6SXNzdWU3NzEyNjQ4OTc= | 9,204 | Load saved Pytorch model into Tensorflow or convert from Pytorch model to TF | {
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"Hey @Jess0-0,\r\n\r\nYou can load TF checkpoints into PT and vice-versa via:\r\n\r\n`XLMRoberta.from_pretrained(...., from_tf=True)`\r\n\r\nor \r\n\r\n`TFXLMRoberta.from_pretrained(...., from_pt=True)`.\r\n\r\nSince `XLMRobertaForSequenceClassification` is just an alias of `RobertaForSequenceClassification` there ... | 1,608 | 1,610 | 1,610 | NONE | null | Hi,
Thanks for this awesome framework!
I have trained and saved an XLMRoberta model in PyTorch and I'm wondering if there is any way I can load the model into TFRobertaForSequenceClassification class. Or if there are ways to convert the checkpoint to TensorFlow checkpoints so that it can be load by TF2.
I came a... | {
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https://api.github.com/repos/huggingface/transformers/issues/9203 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9203/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9203/comments | https://api.github.com/repos/huggingface/transformers/issues/9203/events | https://github.com/huggingface/transformers/pull/9203 | 771,260,315 | MDExOlB1bGxSZXF1ZXN0NTQyODQ3MjUw | 9,203 | [finetune trainer] better logging and help | {
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* documents that `--val_max_target_length` is also used during `generate`
* disambiguates `use_task_specific_params` logger so that it's clear that it dumps just... | {
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https://api.github.com/repos/huggingface/transformers/issues/9202 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9202/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9202/comments | https://api.github.com/repos/huggingface/transformers/issues/9202/events | https://github.com/huggingface/transformers/issues/9202 | 771,239,511 | MDU6SXNzdWU3NzEyMzk1MTE= | 9,202 | [wanted] explicit docs for inherited methods | {
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"I don't agree on an always-document-everything basis, as the documentation page of each model is already quite long (which may be the reason not a lot of people seem to be reading them...) In the case of generate, since there is no link to the part where the generate method is documented, we could add the document... | 1,608 | 1,622 | 1,622 | CONTRIBUTOR | null | # 🚀 Feature request
The HF approach is to unroll most of the code for the ease of understanding, but somehow this is not the case with docs.
If possible, could we explicitly add documentation for inherited methods in the specific model documentation page?
e.g. why https://huggingface.co/transformers/model_do... | {
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https://api.github.com/repos/huggingface/transformers/issues/9201 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9201/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9201/comments | https://api.github.com/repos/huggingface/transformers/issues/9201/events | https://github.com/huggingface/transformers/issues/9201 | 771,232,178 | MDU6SXNzdWU3NzEyMzIxNzg= | 9,201 | when to use sortish sampler | {
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"Is there any update on this? \r\n\r\nSeems like it allows dynamic batching. ",
"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n\nIf you think this still needs to be addressed please comment on this thread."
] | 1,608 | 1,614 | 1,614 | NONE | null | Hi,
I appreciate adding to the documentation on when to use sortish sampler and which platform this works/how much it impacts the speed, this is related to seq2seq folder of huggingface, for Seq2seqDataset.
thanks
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https://api.github.com/repos/huggingface/transformers/issues/9200 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9200/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9200/comments | https://api.github.com/repos/huggingface/transformers/issues/9200/events | https://github.com/huggingface/transformers/issues/9200 | 771,227,462 | MDU6SXNzdWU3NzEyMjc0NjI= | 9,200 | Beam search fails when using model parallelism | {
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"As the trace suggests, the error seem to come from the `_reorder_cache` method in `generation_utils.py`. Since the model is parallelized among multiple devices, it fails since the device of `beam_idx` and `layer_past` don't match for all layers.\r\n\r\nI just tried to modify line 229 in `generation_utils.py` to:\r... | 1,608 | 1,620 | 1,608 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.1.1
- Platform: Linux-4.4.0-194-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes, two GTX 1080, on a single node
- Using distributed or... | {
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https://api.github.com/repos/huggingface/transformers/issues/9199 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9199/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9199/comments | https://api.github.com/repos/huggingface/transformers/issues/9199/events | https://github.com/huggingface/transformers/pull/9199 | 771,215,551 | MDExOlB1bGxSZXF1ZXN0NTQyODEyMjg4 | 9,199 | [t5 doc] typos | {
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Sylvain, why do we not have documentation for `T5ForConditionalGeneration.generate`? This doc is trying to link to it, but there is no such entry in https://huggingface.co/transformers/model_doc/t5.html
@sgugger
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https://api.github.com/repos/huggingface/transformers/issues/9198 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9198/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9198/comments | https://api.github.com/repos/huggingface/transformers/issues/9198/events | https://github.com/huggingface/transformers/pull/9198 | 771,189,349 | MDExOlB1bGxSZXF1ZXN0NTQyNzg5OTE2 | 9,198 | [run_glue] add speed metrics | {
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* train: (sync with finetune_trainer):
- prints and saves train speed metrics - needed for benchmarking
- saves the state,
* eval: sorts metrics logging info
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/9197 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9197/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9197/comments | https://api.github.com/repos/huggingface/transformers/issues/9197/events | https://github.com/huggingface/transformers/pull/9197 | 771,123,018 | MDExOlB1bGxSZXF1ZXN0NTQyNzM1ODkx | 9,197 | [RAG] Add Ray implementation for distributed retrieval | {
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"cc @sgugger @patrickvonplaten @LysandreJik @lhoestq ",
"Nice, good to merge then!",
"Awesome, thank you so much for the reviews @lhoestq @patrickvonplaten -- happy holidays!",
"Thanks guys!",
"@amogkam @patrickvonplaten I need some help to implement an end-to-end retrieval training feature for the rag wit... | 1,608 | 1,613 | 1,608 | COLLABORATOR | null | # What does this PR do?
This PR adds a new distributed retriever implementation for RAG built on Ray, as an alternative to the current retriever implementation that uses torch.distributed. With Ray it's possible to load the index on multiple processes instead of just the rank 0 training worker, allowing fine tuning to... | {
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https://api.github.com/repos/huggingface/transformers/issues/9196 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9196/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9196/comments | https://api.github.com/repos/huggingface/transformers/issues/9196/events | https://github.com/huggingface/transformers/pull/9196 | 771,098,115 | MDExOlB1bGxSZXF1ZXN0NTQyNzE2MDc4 | 9,196 | Add timing inside Trainer | {
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"may I ask for one more bit, while you're at it - sorting the metrics before printing them out?\r\n\r\nI added this already into the final json file writing, but it'd make it easier to read the info logs.\r\n\r\nNow we have:\r\n\r\n```\r\n2020-12-18 11:51:55 | INFO | __main__ | val_loss = 368.4116\r\n2020-12-18 1... | 1,608 | 1,608 | 1,608 | COLLABORATOR | null | # What does this PR do?
Add timing reports for training/evaluation and test inside the Trainer. Also, change the default repr of `TrainingArguments` to avoid printing the deprecated arguments.
There is a breaking change in this PR: the output of `Trainer.train` gains a new field `metrics`, so the length of the na... | {
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https://api.github.com/repos/huggingface/transformers/issues/9195 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9195/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9195/comments | https://api.github.com/repos/huggingface/transformers/issues/9195/events | https://github.com/huggingface/transformers/issues/9195 | 771,066,100 | MDU6SXNzdWU3NzEwNjYxMDA= | 9,195 | Error "if input.dim() == 2 and bias is not None" | {
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"Please try\r\n`_, cls_hs = self.bert(sent_id, attention_mask=mask)`\r\nto\r\n`_, cls_hs = self.bert(sent_id, attention_mask=mask)[:2]`\r\nor\r\n`_, cls_hs = self.bert(sent_id, attention_mask=mask, return_dict=False)`",
"It fixes the issue. Thanks!",
"> Please try\r\n> `_, cls_hs = self.bert(sent_id, attention_... | 1,608 | 1,612 | 1,608 | NONE | null | Pytorch version: pytorch-1.7.1-py3.8_cuda11.0.221_cudnn8.0.5_0
Transformer version: 4.0.0
Code:
```
import torch
import torch.nn as nn
from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
from transformers import AutoModel, BertTokenizerFast
class BERT_Arch(nn.Module):
... | {
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https://api.github.com/repos/huggingface/transformers/issues/9194 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9194/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9194/comments | https://api.github.com/repos/huggingface/transformers/issues/9194/events | https://github.com/huggingface/transformers/issues/9194 | 771,042,301 | MDU6SXNzdWU3NzEwNDIzMDE= | 9,194 | Loading MPNet from disc: ValueError: An instance of tokenizer class MPNetTokenizer cannot be converted in a Fast tokenizer instance. | {
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"Looking into it!\r\n\r\nAn easy fix for now would be the following:\r\n\r\n```python\r\nfrom transformers import AutoTokenizer, AutoModel\r\n\r\nlocal_dir = 'mpnet-model/'\r\n\r\nmodel = AutoModel.from_pretrained('microsoft/mpnet-base')\r\ntokenizer = AutoTokenizer.from_pretrained('microsoft/mpnet-base')\r\nmodel.... | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.1.1 (pip version)
- Platform: Ubuntu 20.04
- Python version: 3.7
- PyTorch version (GPU?): Pytorch 1.7 GPU
## Information
Hi,
thanks for adding MPNet. I got quite promising results when using it for generating sentence embeddings.
However, there is an is... | {
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https://api.github.com/repos/huggingface/transformers/issues/9193 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9193/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9193/comments | https://api.github.com/repos/huggingface/transformers/issues/9193/events | https://github.com/huggingface/transformers/pull/9193 | 771,014,844 | MDExOlB1bGxSZXF1ZXN0NTQyNjQ4OTMx | 9,193 | Full rework of the TF input/output embeddings and bias resizing | {
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"I haven't reviewed in detail yet, but just looking at the API with the number of things to change for ALBERT (and in terms of line of code) is a hard pass for me. Overriding the resize method as was done before was way easier, this adds too much complexity.",
"I understand that it is a big update. Nevertheless, ... | 1,608 | 1,610 | 1,610 | CONTRIBUTOR | null | # What does this PR do?
This PR 100% reworks the entire process of input/output and bias resizing. Now the exceptions are better handled including the names that now are always similar. The corresponding tests have also been entirely reworked and now have a better coverage of this feature.
This PR adds a small br... | {
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https://api.github.com/repos/huggingface/transformers/issues/9192 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9192/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9192/comments | https://api.github.com/repos/huggingface/transformers/issues/9192/events | https://github.com/huggingface/transformers/issues/9192 | 771,008,138 | MDU6SXNzdWU3NzEwMDgxMzg= | 9,192 | example code for fine-tuning CLM does not work for GPT | {
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"Could you try putting `--block_size=512` in your command to see if it changes something?",
"@LysandreJik Thank you it solved the issue! "
] | 1,608 | 1,608 | 1,608 | NONE | null | ## Environment info
- `transformers` version: 3.5.0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.6
- PyTorch version (GPU?): 1.7.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: NO
### Who can help
@patrickvonplaten @TevenLeScao
## Information
Model... | {
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https://api.github.com/repos/huggingface/transformers/issues/9191 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9191/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9191/comments | https://api.github.com/repos/huggingface/transformers/issues/9191/events | https://github.com/huggingface/transformers/issues/9191 | 770,965,175 | MDU6SXNzdWU3NzA5NjUxNzU= | 9,191 | Segfault on python 3.9 exit | {
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"I encountered a similar issue, in a context where `transformers` was not imported. I've [reported](https://github.com/pytorch/pytorch/issues/50858) the issue to the PyTorch project.",
"I too have similar problem when running unittests for a Python package on travis, using Python 3.9. Specifically, all unit tests... | 1,608 | 1,639 | 1,611 | NONE | null | Ok, that's a weird one
## Environment info
- `transformers` version: 4.1.1
- Platform: Linux-5.8.0-34-generic-x86_64-with-glibc2.32
- Python version: 3.9.0+
- PyTorch version (GPU?): 1.7.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no
- Using distributed or parallel... | {
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https://api.github.com/repos/huggingface/transformers/issues/9190 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9190/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9190/comments | https://api.github.com/repos/huggingface/transformers/issues/9190/events | https://github.com/huggingface/transformers/pull/9190 | 770,955,064 | MDExOlB1bGxSZXF1ZXN0NTQyNTk5Njgz | 9,190 | Addition of MuRIL - BERT based model for 17 Indian Languages to the library | {
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"Hello! Yes, feel free to. However, you seem to have based yourself off of a `tf` branch that is very old?",
"@LysandreJik Yeah sorry. Should I raise a new issue so that it can be changed accordingly?",
"If you want to contribute this model, I invite you to base yourself off of the `master` branch and create a ... | 1,608 | 1,651 | 1,608 | CONTRIBUTOR | null | Hi,
This PR is regarding the addition of MuRIL, a BERT-based model trained specifically for 17 Indian Languages to the hugging face library.
MuRIL is released on tfhub. Link to the repo: [https://tfhub.dev/google/MuRIL/1](https://tfhub.dev/google/MuRIL/1)
I am interested to work on this contribution to the lib... | {
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https://api.github.com/repos/huggingface/transformers/issues/9189 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9189/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9189/comments | https://api.github.com/repos/huggingface/transformers/issues/9189/events | https://github.com/huggingface/transformers/pull/9189 | 770,953,440 | MDExOlB1bGxSZXF1ZXN0NTQyNTk4MzY5 | 9,189 | GPT-model attention heads pruning example | {
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"One last detail: could you run `make style` on your branch? There seems to be some bad formatting.",
"> One last detail: could you run `make style` on your branch? There seems to be some bad formatting.\r\n\r\nI did, but let me recheck it"
] | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | # What does this PR do?
This script is adapted from the [BERT attention heads pruning code](https://github.com/huggingface/transformers/blob/master/examples/research_projects/bertology/run_bertology.py) AKA Bertology to make it possible to prune GPT-model heads as well.
It basically works the same way as run_bert... | {
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https://api.github.com/repos/huggingface/transformers/issues/9188 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9188/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9188/comments | https://api.github.com/repos/huggingface/transformers/issues/9188/events | https://github.com/huggingface/transformers/issues/9188 | 770,859,577 | MDU6SXNzdWU3NzA4NTk1Nzc= | 9,188 | MRPC Reproducibility with transformers-4.1.0 | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,608 | 1,608 | 1,608 | NONE | null | I always get lower precision following the MRPC example, what's the reason?
```
python run_glue.py \
--model_name_or_path bert-base-cased \
--task_name $TASK_NAME \
--do_train \
--do_eval \
--max_seq_length 128 \
--per_device_train_batch_size 32 \
--learning_rate 2e-5 \
--num_train_epochs 3.0 ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9187 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9187/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9187/comments | https://api.github.com/repos/huggingface/transformers/issues/9187/events | https://github.com/huggingface/transformers/issues/9187 | 770,806,519 | MDU6SXNzdWU3NzA4MDY1MTk= | 9,187 | Problem with pretraining GPT-2 on TPU with Pytorch/XLA | {
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"I realized that I didn't follow [instructions](https://github.com/pytorch/xla/blob/master/README.md) properly.",
"@redrussianarmy What`s the problem? I have the same issue but can not find a solution."
] | 1,608 | 1,610 | 1,608 | NONE | null | ### **Environment info**
transformers version: 4.0.1
Platform: Ubuntu 18.04.4 LTS
Python version: 3.6.9
PyTorch version: 1.7.1
Torch-XLA version: 1.7
Tensorflow version: 2.3.1
### **Information**
Model I am intended to pretrain (Bert, XLNet ...): GPT2
The problem arises when using:
- my own modified script... | {
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https://api.github.com/repos/huggingface/transformers/issues/9186 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9186/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9186/comments | https://api.github.com/repos/huggingface/transformers/issues/9186/events | https://github.com/huggingface/transformers/pull/9186 | 770,739,076 | MDExOlB1bGxSZXF1ZXN0NTQyNDI4MjM2 | 9,186 | fixed not JSON serializable error in run_qa.py with fp16 | {
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Fixed an issue where running the run_qa.py script in a Squad-like dataset with fp16 enabled, would lead to a JSON serialization error:
```
TypeError: Object of type 'float16' is not JSON serializable
```
The bug is caused by not converting `np.float16` to `float` on line 209 and 397 in th... | {
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https://api.github.com/repos/huggingface/transformers/issues/9185 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9185/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9185/comments | https://api.github.com/repos/huggingface/transformers/issues/9185/events | https://github.com/huggingface/transformers/issues/9185 | 770,717,055 | MDU6SXNzdWU3NzA3MTcwNTU= | 9,185 | can we use ckpt model file generated after finetuning the pre-trained models on custom dataset | {
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"hi @SagarPalyal not sure what you mean here. by ckpt file do you mean a saved checkpoint ?",
"Yes you are right. This is saved checkpoint file only.",
"One thing to note: `pytorch_model.bin` is the name of the weights file, and every torch HF model will have that file.\r\n\r\nTo load the checkpoint simply pas... | 1,608 | 1,685 | 1,614 | NONE | null | Hi Team,
I have fine tuned pegasus huggingface wikihow model with my own custom dataset and end up with below files:
model.ckpt-1000.data-00000-of-00001
model.ckpt-1000.index
model.ckpt-1000.meta
events.out.tfevents.1608192436.ip-xxx-xx-x-xx
events.out.tfevents.1608192510.ip-xxx-xx-x-xx.v2
When I am runnin... | {
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https://api.github.com/repos/huggingface/transformers/issues/9184 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9184/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9184/comments | https://api.github.com/repos/huggingface/transformers/issues/9184/events | https://github.com/huggingface/transformers/issues/9184 | 770,707,837 | MDU6SXNzdWU3NzA3MDc4Mzc= | 9,184 | [RagSequenceForGeneration] generate "without" input_ids | {
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In `RagSequenceForGeneration` method `generate()` function, the doc said that both `input_ids` and `context_input_ids` are optional (one of them must be specified) .
However, in the code https://github.com/ratthachat/transformers/blob/ragseq_context_id/src/transformers/models/rag/modeling_rag.py#L907
I... | {
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https://api.github.com/repos/huggingface/transformers/issues/9183 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9183/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9183/comments | https://api.github.com/repos/huggingface/transformers/issues/9183/events | https://github.com/huggingface/transformers/pull/9183 | 770,699,787 | MDExOlB1bGxSZXF1ZXN0NTQyMzk3NTQ4 | 9,183 | Add caching mechanism to BERT, RoBERTa | {
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"`python utils/check_copies.py --fix_and_overwrite` should be run to make the `check_code_quality` test pass",
"> `python utils/check_copies.py --fix_and_overwrite` should be run to make the `check_code_quality` test pass\r\n\r\nYeah, did that, for some reason, it's not working for `RobertaEmbeddings`, the code i... | 1,608 | 1,608 | 1,608 | MEMBER | null | # What does this PR do?
- This PR adds past key/values caching mechanism to `BertLMHeadModel`, `BertGenerationDecoder`, and `RobertaForCausalLM` to speed up the generation of `EncoderDecoder` models
- delete the `CausalLMOutputWithPastAndCrossAttentions` class and add `past_key_values` to `CausalLMOutputWithCross... | {
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https://api.github.com/repos/huggingface/transformers/issues/9182 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9182/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9182/comments | https://api.github.com/repos/huggingface/transformers/issues/9182/events | https://github.com/huggingface/transformers/pull/9182 | 770,466,926 | MDExOlB1bGxSZXF1ZXN0NTQyMjA5MTA3 | 9,182 | Fix link to old NER fine-tuning script | {
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https://api.github.com/repos/huggingface/transformers/issues/9181 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9181/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9181/comments | https://api.github.com/repos/huggingface/transformers/issues/9181/events | https://github.com/huggingface/transformers/pull/9181 | 770,461,400 | MDExOlB1bGxSZXF1ZXN0NTQyMjA0NjU4 | 9,181 | Fix link to old SQUAD fine-tuning script | {
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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/9180 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9180/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9180/comments | https://api.github.com/repos/huggingface/transformers/issues/9180/events | https://github.com/huggingface/transformers/pull/9180 | 770,460,348 | MDExOlB1bGxSZXF1ZXN0NTQyMjAzODE0 | 9,180 | [trainer] apex fixes and tests | {
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* [x] fixes a bug in with `fp16_backend` apex (`is_apex_available` + `amp` weren't getting imported w/ pt>=1.6)
* [x] adds test
* [x] adds a logger info on which fp16 backend will be used
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/9179 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9179/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9179/comments | https://api.github.com/repos/huggingface/transformers/issues/9179/events | https://github.com/huggingface/transformers/issues/9179 | 770,429,173 | MDU6SXNzdWU3NzA0MjkxNzM= | 9,179 | [trainer] speed issues: --fp16 doesn't improve speed, DP runs really slow | {
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"Could you run the other examples script to check? On my end they result in a roughly x2 speedup but I'm not on pytorch-nightly.",
"Any recommendations and specific command lines that you use? \r\n\r\nI have been using the finetune and other scripts in seq2seq as a go-to scripts for testing, so I'm not quite expe... | 1,608 | 1,614 | 1,614 | CONTRIBUTOR | null | Splitting from https://github.com/huggingface/transformers/issues/9156#issuecomment-747636108 where while running benchmarks for fairscale's sharded ddp support I noticed that there was almost no difference between having or not having `--fp16` to the training runtime.
Not sure whether this impacts trainer in genera... | {
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https://api.github.com/repos/huggingface/transformers/issues/9178 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9178/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9178/comments | https://api.github.com/repos/huggingface/transformers/issues/9178/events | https://github.com/huggingface/transformers/issues/9178 | 770,421,607 | MDU6SXNzdWU3NzA0MjE2MDc= | 9,178 | [ci] install fairscale on self-runner CIs | {
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"Probably should change CI to do:\r\n```\r\npip install fairscale --no-build-isolation\r\n```\r\nwhich is much faster then the new pip system, as it doesn't need to fetch dependent packages\r\n",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still nee... | 1,608 | 1,619 | 1,619 | CONTRIBUTOR | null | The tests for the new sharded ddp fairscale integration are in place, https://github.com/huggingface/transformers/pull/9177
but CIs don't have `fairscale` installed so they won't run on CI.
This is an issue to track this need so we will eventually run these tests.
Blocking event: needing a more reliable/quick w... | {
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https://api.github.com/repos/huggingface/transformers/issues/9177 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9177/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9177/comments | https://api.github.com/repos/huggingface/transformers/issues/9177/events | https://github.com/huggingface/transformers/pull/9177 | 770,412,546 | MDExOlB1bGxSZXF1ZXN0NTQyMTY0NzQw | 9,177 | add tests for the new sharded ddp fairscale integration | {
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"I made a request for a quicker/simpler binary: https://github.com/facebookresearch/fairscale/issues/264\r\n\r\nAnd added an issue to track this so we won't forget: https://github.com/huggingface/transformers/issues/9178\r\n"
] | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | This PR adds tests for the just added sharded ddp fairscale integration https://github.com/huggingface/transformers/pull/9139
Obviously these won't run on CIs w/o having fairscale installed... hope we will sort this out down the road. the problem is building fairscale - no binary wheel - I will ask them if they coul... | {
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https://api.github.com/repos/huggingface/transformers/issues/9176 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9176/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9176/comments | https://api.github.com/repos/huggingface/transformers/issues/9176/events | https://github.com/huggingface/transformers/pull/9176 | 770,409,555 | MDExOlB1bGxSZXF1ZXN0NTQyMTYyMTMw | 9,176 | [setup] correct transformers version format | {
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```
x.y.z
x.y.z.dev0
x.y.z.rc1
```
This PR fixes the dev version number and adds a comment with correct formats for the future editors
This fix removes this warning on `make fixup|style|etc` or any other time `setup.py` is being run.
```
setup... | {
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https://api.github.com/repos/huggingface/transformers/issues/9175 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9175/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9175/comments | https://api.github.com/repos/huggingface/transformers/issues/9175/events | https://github.com/huggingface/transformers/pull/9175 | 770,360,515 | MDExOlB1bGxSZXF1ZXN0NTQyMTE5ODU1 | 9,175 | Add new run_swag example | {
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This PR adds a new example for multiple-choice using Trainer and Datasets, and moves the older one to the legacy folder. | {
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https://api.github.com/repos/huggingface/transformers/issues/9174 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9174/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9174/comments | https://api.github.com/repos/huggingface/transformers/issues/9174/events | https://github.com/huggingface/transformers/pull/9174 | 770,323,063 | MDExOlB1bGxSZXF1ZXN0NTQyMDg4OTY4 | 9,174 | [WIP] Adapt Cookie Cutter For EncoderDecoder | {
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"Cleaner version here: https://github.com/huggingface/transformers/pull/9251"
] | 1,608 | 1,608 | 1,608 | MEMBER | 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/9173 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9173/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9173/comments | https://api.github.com/repos/huggingface/transformers/issues/9173/events | https://github.com/huggingface/transformers/issues/9173 | 770,265,980 | MDU6SXNzdWU3NzAyNjU5ODA= | 9,173 | GPT2 eval with attention_mask not returning expected result | {
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"Hey @dan-i, \r\n\r\n1) You should mask the labels of the first token it's not enough to set the attention_mask to 0 -> `labels=torch.tensor([-100, ...])`\r\n2) You have to change the `position_ids` to ensure the expected behavior in GPT2, *i.e.* make sure that in the second case the position_ids are [0, 0, 1, 2] i... | 1,608 | 1,608 | 1,608 | NONE | null | is this not correct use of attention_mask with padding (trying to batch sentence eval) or is it a bug? Shouldn't the return result be the same in each case because of the mask?
import torch
from transformers import GPT2LMHeadModel
model = GPT2LMHeadModel.from_pretrained('gpt2', return_dict=True)
```
with torch... | {
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https://api.github.com/repos/huggingface/transformers/issues/9172 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9172/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9172/comments | https://api.github.com/repos/huggingface/transformers/issues/9172/events | https://github.com/huggingface/transformers/pull/9172 | 770,261,089 | MDExOlB1bGxSZXF1ZXN0NTQyMDM4MDE3 | 9,172 | [Flax] Implement FlaxElectraModel, FlaxElectraForMaskedLM, FlaxElectraForPreTraining | {
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"Hi @chris-tng -- thanks for trying out Flax in HF Transformers!\r\n\r\nA quick comment on `nn.compact` and `setup` (I work on Flax) -- indeed if you want access to submodules such as for transfer learning then using `setup` is the way to go. I skimmed the PR and see that you use `setup` in some places and `nn.comp... | 1,608 | 1,648 | null | CONTRIBUTOR | null | # What does this PR do?
1. Implement Flax version of Electra model : `FlaxElectraModel`, `FlaxElectraForMaskedLM`, `FlaxElectraForPreTraining`. Most of the code taken from FlaxBert version with changes in parameters and forward pass.
2. Adjust `convert_to_pytorch` to load weights for Electra
3. Implement `FlaxElec... | {
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https://api.github.com/repos/huggingface/transformers/issues/9171 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9171/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9171/comments | https://api.github.com/repos/huggingface/transformers/issues/9171/events | https://github.com/huggingface/transformers/issues/9171 | 770,220,529 | MDU6SXNzdWU3NzAyMjA1Mjk= | 9,171 | Trainer returns logits of only one sequence instead of entire evaluation dataset | {
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"**Update:** I slightly changed my script based on the [text_classification example notebook](https://github.com/huggingface/notebooks/blob/master/examples/text_classification.ipynb) and now it works. Don't know what made the difference, but in case someone else has a similar problem, I recommend following the step... | 1,608 | 1,608 | 1,608 | 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: 4.0.1 (also reproduced the same issue with 3.5.1)
- Platform: Google Colab
- Python version: 3.6
- PyT... | {
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https://api.github.com/repos/huggingface/transformers/issues/9170 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9170/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9170/comments | https://api.github.com/repos/huggingface/transformers/issues/9170/events | https://github.com/huggingface/transformers/pull/9170 | 770,171,673 | MDExOlB1bGxSZXF1ZXN0NTQxOTY1MDU3 | 9,170 | Put all models in the constants | {
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"An alternative is to remove all content, but the previous state where one variable as some keys but the others not leads to failures.",
"Yes, we really need to remove all of this @LysandreJik @thomwolf ",
"We do, but right now we still use them in the tests",
"It was a bit confusing to me which to add in the... | 1,608 | 1,608 | 1,608 | COLLABORATOR | null | # What does this PR do?
It was impossible to use all pretrained checkpoints in the tapas tokenzier file because they were not in the constants of the file. This PR fixes that. | {
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https://api.github.com/repos/huggingface/transformers/issues/9169 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9169/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9169/comments | https://api.github.com/repos/huggingface/transformers/issues/9169/events | https://github.com/huggingface/transformers/pull/9169 | 770,132,619 | MDExOlB1bGxSZXF1ZXN0NTQxOTMzNDg4 | 9,169 | Added TF TransfoXL Sequence Classification | {
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TFTransfoXLForSequenceClassification uses the last token in order to do the classification, as other causal models (e.g. GPT-1 ,GPT-2) do.
Fixes #7623
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the othe... | {
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https://api.github.com/repos/huggingface/transformers/issues/9168 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9168/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9168/comments | https://api.github.com/repos/huggingface/transformers/issues/9168/events | https://github.com/huggingface/transformers/pull/9168 | 770,091,454 | MDExOlB1bGxSZXF1ZXN0NTQxOTAwODY4 | 9,168 | Fix gradient clipping for Sharded DDP | {
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As mentioned in the discussion of #9156, `Trainer` does not do gradient clipping correctly when using a sharded optimizer. This PR fixes that, and also allows `Trainer` to not perform any gradient clipping (by passing `None` or `0` to the corresponding argument). | {
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https://api.github.com/repos/huggingface/transformers/issues/9167 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9167/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9167/comments | https://api.github.com/repos/huggingface/transformers/issues/9167/events | https://github.com/huggingface/transformers/pull/9167 | 770,089,471 | MDExOlB1bGxSZXF1ZXN0NTQxODk5MzYz | 9,167 | Add disclaimer to TAPAS rst file | {
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https://api.github.com/repos/huggingface/transformers/issues/9166 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9166/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9166/comments | https://api.github.com/repos/huggingface/transformers/issues/9166/events | https://github.com/huggingface/transformers/issues/9166 | 770,061,905 | MDU6SXNzdWU3NzAwNjE5MDU= | 9,166 | Language modeling logging | {
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"I think @LysandreJik will know more what to do for the logging. Also, we usually ask questions like this on the [forum](https://discuss.huggingface.co/) and keep issues for bugs/feature requests.",
"If you want to output everything to a file, you can redirect the standard output/standard error to a file. We use ... | 1,608 | 1,608 | 1,608 | 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:4.0.0-rc-1
- Platform:Linux
- Python version:Python 3.7.9
- PyTorch version (GPU?):1.4.0
- Tensorflow v... | {
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"Hi, note that 'suicide' and ' suicide' are indeed different tokens with respect to SentencePieces, which is used by Roberta.\r\n\r\nSentencePieces keeps white space intact. So we expect different tokens from 'suicide' and ' suicide'. \r\n\r\nI assume in the old transformers 2.x, strip was applied in the tokenizer ... | 1,608 | 1,608 | 1,608 | 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: 2.11 vs 4.0.1
- Platform: Any
- Python version: 3.8.3
- PyTorch version (GPU?): Any
- Tensorflow versi... | {
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"@patrickvonplaten @LysandreJik @julien-c @zhiheng-huang",
"Hey @hadaev8,\r\n\r\nThanks for your PR. It would be awesome if you could provide a code snippet to this PR that shows a case where the current implementation of BERT's relative positional embeddings would fail. Hope it's fine to tag the original author ... | 1,608 | 1,622 | 1,622 | CONTRIBUTOR | null | # What does this PR do?
This PR adds clipping to distance embedding as described in the paper [Improve Transformer Models with Better Relative Position Embeddings](https://arxiv.org/abs/2009.13658)
Without this addition, the model with relative positional embedding will return an error if the input length above max... | {
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https://api.github.com/repos/huggingface/transformers/issues/9163 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9163/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9163/comments | https://api.github.com/repos/huggingface/transformers/issues/9163/events | https://github.com/huggingface/transformers/pull/9163 | 769,990,931 | MDExOlB1bGxSZXF1ZXN0NTQxODQ1Mjk2 | 9,163 | Fix mixed precision in TF models | {
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This PR aims to fix the mixed precision issues when `tf.keras.mixed_precision.experimental.set_policy()` is set to something else than `tf.float32`. In the same page, this PR aims to fix some TFLite quantization issues.
Before to further continue this PR, the PR #9418 has to be merged.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/9162 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9162/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9162/comments | https://api.github.com/repos/huggingface/transformers/issues/9162/events | https://github.com/huggingface/transformers/issues/9162 | 769,695,682 | MDU6SXNzdWU3Njk2OTU2ODI= | 9,162 | IndexError: index out of range in self while using longformers when i try to pass token_type_ids | {
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"Can we assume that \"token_type_ids\" will not support in longformer?",
"Yes, actually yesterday a PR (#9152) was merged to update the docs stating the LongFormer does not support token type ids. ",
"@NielsRogge Thank you",
"This issue has been automatically marked as stale and been closed because it has not... | 1,608 | 1,614 | 1,614 | NONE | null |
- `transformers` version: 3.0.0
- Platform: windows
- Python version: 3.6.10 :: Anaconda, Inc.
- PyTorch version (GPU?): 1.7.0+cu101
- Tensorflow version (GPU?):
- Using GPU in script?:
- Using distributed or parallel set-up in script?:
### Who can help
<!-- Your issue will be replied to more quickly i... | {
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"Definitely not correct. Additionally, the final batch might be much smaller (and still weighted evenly). To get \"perfect\" bleu scores use `run_distributed_eval.py`\r\n",
"Right, that's what I thought as well. If we think saving all the intermediate output and computing the bleu score once at the end of each va... | 1,608 | 1,614 | 1,614 | CONTRIBUTOR | null | ### Who can help
@sshleifer, @patil-suraj
## Information
Currently, the seq2seq finetune script calculates the final metrics (bleu or rouge) per batch, and then simply averages these numbers across batches. Is it correct? For example, I just took a brief look at sacrebleu (which the script uses), and it seems th... | {
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https://api.github.com/repos/huggingface/transformers/issues/9160 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9160/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9160/comments | https://api.github.com/repos/huggingface/transformers/issues/9160/events | https://github.com/huggingface/transformers/issues/9160 | 769,358,412 | MDU6SXNzdWU3NjkzNTg0MTI= | 9,160 | Trainer bug? Loss and logits are “nan” when fine-tuning NLI model (both RoBERTa/BART) | {
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"**Update:** \r\nI reran the training in native PyTorch with the following code and I did not get the same issue. This means that there is some issue with the trainer?\r\n\r\n```\r\nimport torch\r\n\r\nclass XDataset(torch.utils.data.Dataset):\r\n def __init__(self, encodings, labels):\r\n self.encodings ... | 1,608 | 1,630 | 1,608 | 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: 4.0.1 (also reproduced the same issue with 3.5.1)
- Platform: Google Colab
- Python version: 3.6
- PyT... | {
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https://api.github.com/repos/huggingface/transformers/issues/9159 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9159/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9159/comments | https://api.github.com/repos/huggingface/transformers/issues/9159/events | https://github.com/huggingface/transformers/issues/9159 | 769,335,819 | MDU6SXNzdWU3NjkzMzU4MTk= | 9,159 | Unified transformer interface | {
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"Hi @ZhaofengWu, thank you for proposing this feature. \r\n\r\nYou're noting a decision that we've made very early on in the design of the `transformers` library, which is to have standalone model files, **without any abstraction**, including the `Transformer` abstraction you're noting here. We believe it's much ea... | 1,608 | 1,614 | 1,614 | CONTRIBUTOR | null | # 🚀 Feature request
As we're called `transformers`, it would be nice if there's a `Transformer` class that is not associated with any pretrained model and that we can directly instantiate, like
```python
from transformers import Transformer, Seq2SeqTransformer
transformer = Transformer(n_layers=8, dim=512)
seq... | {
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https://api.github.com/repos/huggingface/transformers/issues/9158 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9158/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9158/comments | https://api.github.com/repos/huggingface/transformers/issues/9158/events | https://github.com/huggingface/transformers/issues/9158 | 769,247,862 | MDU6SXNzdWU3NjkyNDc4NjI= | 9,158 | Getting a 404 error when loading 'model=facebook/bart-large-mnli' from pipeline('zero-shot-classification') | {
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"After the full restart PC, works fine. "
] | 1,608 | 1,608 | 1,608 | NONE | null | Getting a 404 when trying to load the model.
model='joeddav/bart-large-mnli-yahoo-answers' also not working.
`404 Client Error: Not Found for url: https://huggingface.co/facebook/bart-large-mnli/resolve/main/tf_model.h5
---------------------------------------------------------------------------
HTTPError ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9157 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9157/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9157/comments | https://api.github.com/repos/huggingface/transformers/issues/9157/events | https://github.com/huggingface/transformers/issues/9157 | 769,215,920 | MDU6SXNzdWU3NjkyMTU5MjA= | 9,157 | T5 checkpoint contains weights missing on current model. | {
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"Yes we should fix the warning. It's no problem that those weights are missing i.e.:\r\n#8933",
"Thank you! "
] | 1,608 | 1,608 | 1,608 | NONE | null | ## Environment info
Colab (16 december 2020), transformers 4.0.1
### Who can help
T5: @patrickvonplaten
## Information
When loading the pre-trained T5 weights, directy with .from_pretrained, with the newest version, it returns the following warning:
> Some weights of the model checkpoint at t5-small were ... | {
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"This is just a brief log of the 2 distinct errors mentioned in OP:\r\n\r\nw/ `--fp16` the failure is:\r\n```\r\n File \"./finetune_trainer.py\", line 379, in <module>\r\n main()\r\n File \"./finetune_trainer.py\", line 315, in main\r\n trainer.train(\r\n File \"/mnt/nvme1/code/huggingface/transformers-mas... | 1,608 | 1,633 | 1,609 | COLLABORATOR | null | ## Information
Model I am using (Bert, XLNet ...): T5/BART/mBART/Marian
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [x] an official GLUE/SQUaD task: seq2seq
* [ ] my own task or d... | {
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"This argument was deprecated in transformers version 3.5 and removed in version 4.0, as indicated in the [release notes](https://github.com/huggingface/transformers/releases/). It needs to be replaced by `evaluation_strategy=\"steps\"` or `evaluation_strategy=\"epoch\"`"
] | 1,608 | 1,608 | 1,608 | 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: 4.0.0
- Platform: Linux-3.10.0-1127.19.1.el7.x86_64-x86_64-with-centos-7.9.2009-Core
- Python version: ... | {
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"BERT and DistilBERT are different models. DistilBERT isn't simply a BERT model with fewer layers, but a BERT model without the pooling layer as you have seen, and with no token type embeddings.\r\n\r\nWe try to stay as close to the original implementations as possible, hence why BERT is done this way, and why Dist... | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | Hi,
The `BertForSequenceClassification` includes a forward pass of the BertModel, and it takes the second element (index 1) from its output before moving forward, as shown [here ](https://github.com/huggingface/transformers/blob/master/src/transformers/models/bert/modeling_bert.py#L1378 )
This is the return of `BertM... | {
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https://api.github.com/repos/huggingface/transformers/issues/9152 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9152/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9152/comments | https://api.github.com/repos/huggingface/transformers/issues/9152/events | https://github.com/huggingface/transformers/pull/9152 | 768,989,315 | MDExOlB1bGxSZXF1ZXN0NTQxMjM3ODAx | 9,152 | Add message to documentation that longformer doesn't support token_type_ids | {
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"Thanks for your PR! It looks like you did not run the `make style` command to format properly your changes.",
"@sgugger Sorry about that. It should be good now.",
"Thanks a lot!"
] | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | # What does this PR do?
Fixes #9111. This pull request adds a notice to the Longformer model documentation that it does not have `token_type_ids`, similarly to the message on the [RoBERTa documentation](https://huggingface.co/transformers/model_doc/roberta.html).
## Before submitting
- [x] This PR fixes a typo... | {
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TFCTRLForSequenceClassification uses the last token in order to do the classification, as other causal models (e.g. Transformer XL ,GPT-2) do.
Fixes #7623
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other... | {
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https://api.github.com/repos/huggingface/transformers/issues/9150 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9150/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9150/comments | https://api.github.com/repos/huggingface/transformers/issues/9150/events | https://github.com/huggingface/transformers/pull/9150 | 768,836,641 | MDExOlB1bGxSZXF1ZXN0NTQxMTQ2MzI2 | 9,150 | Add flags to return scores, hidden states and / or attention weights in GenerationMixin | {
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"@patrickvonplaten ready for a second review\r\nI guess the next steps are to implement GreedySearchOutput for TF and to update the pipelines using generation?",
"Think it should now be relatively straight-forward to implement the outputs for the other generate methods. Seems like circle ci is in holiday...let's ... | 1,608 | 1,610 | 1,609 | CONTRIBUTOR | null | # What does this PR do?
Add flags and logic to return attention scores, hidden states, and/or logits when using a model in generation mode.
Fixes #9121
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contri... | {
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https://api.github.com/repos/huggingface/transformers/issues/9149 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9149/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9149/comments | https://api.github.com/repos/huggingface/transformers/issues/9149/events | https://github.com/huggingface/transformers/issues/9149 | 768,797,124 | MDU6SXNzdWU3Njg3OTcxMjQ= | 9,149 | Log metrics along with hparams in TensorBoardCallback | {
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"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n\nIf you think this still needs to be addressed please comment on this thread."
] | 1,608 | 1,614 | 1,614 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
Log metrics along with hparams in TensorBoardCallback.
## Motivation
<!-- Please outline the motivation for the proposal. Is your feature request
... | {
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fix small shape error in comments | {
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https://api.github.com/repos/huggingface/transformers/issues/9147 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9147/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9147/comments | https://api.github.com/repos/huggingface/transformers/issues/9147/events | https://github.com/huggingface/transformers/issues/9147 | 768,579,182 | MDU6SXNzdWU3Njg1NzkxODI= | 9,147 | BertTokenizer.from_pretrained fails for local_files_only=True when added_tokens.json is missing | {
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"Actually, all of the files 404 here except `vocab.txt`. I have `added_tokens.json`, `special_tokens_map.json`, `tokenizer_config.json`, and `tokenizer.json` all missing for this model.",
"> Actually, all of the files 404 here except `vocab.txt`. I have `added_tokens.json`, `special_tokens_map.json`, `tokenizer_c... | 1,608 | 1,611 | 1,611 | 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: 4.0.1
- Platform: Linux-3.10.0-957.el7.x86_64-x86_64-with-centos-7.6.1810-Core
- Python version: 3.7.6
... | {
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"I googled for the error and it may be related to sending a large object to redis. Was it because the datasets are too large?",
"Hi! Did you try to open an issue at ray directly? It seems to be linked to their library rather than `transformers`",
"> Hi! Did you try to open an issue at ray directly? It seems to ... | 1,608 | 1,611 | 1,611 | 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: 4.1.0.dev0
- Platform: Linux-4.4.0-139-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch versi... | {
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https://api.github.com/repos/huggingface/transformers/issues/9145 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9145/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9145/comments | https://api.github.com/repos/huggingface/transformers/issues/9145/events | https://github.com/huggingface/transformers/pull/9145 | 768,389,676 | MDExOlB1bGxSZXF1ZXN0NTQwODQzMTY2 | 9,145 | TableQuestionAnsweringPipeline | {
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"@NielsRogge I can't ping you for review but I would love your input on this!",
"Thanks for your comments @patrickvonplaten @sgugger, applied your changes. This PR includes the `AutoModelForTableQuestionAnswering` defined [here](https://github.com/huggingface/transformers/pull/9154), adds a check on `pandas` whic... | 1,608 | 1,608 | 1,608 | MEMBER | null | ## TableQuestionAnsweringPipeline
Introduces the `TableQuestionAnsweringPipeline` which will be used for the `TableQuestionAnswering` widget:
<p align="center">
<img src="https://user-images.githubusercontent.com/30755778/102266591-a9606880-3ee6-11eb-9f16-7173a9a85b58.gif" width="500">
</p>
There are exa... | {
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"Hi, I'm sorry but I don't know spell.ml or how it works; if it works in a colab notebook and saves correctly, it seems the issue comes from spell.ml rather than transformers.",
"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributi... | 1,608 | 1,614 | 1,614 | NONE | null | I am trying to fine-tune distillbert for a multilabel task using a V100 gpu and latest transformers from pip. When i try to save the model i get this error:
```
Traceback (most recent call last):
File "script/fine_tune_distillbert.py", line 51, in <module>
model.save_pretrained(ROOT_DIR)
File "/usr/local/... | {
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https://api.github.com/repos/huggingface/transformers/issues/9143 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9143/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9143/comments | https://api.github.com/repos/huggingface/transformers/issues/9143/events | https://github.com/huggingface/transformers/pull/9143 | 768,271,532 | MDExOlB1bGxSZXF1ZXN0NTQwNzY2NzAx | 9,143 | Pass kwargs to Pipeline's tokenizer call | {
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"cc @Narsil who probably knows better.",
"Hi @guyrosin , we actually don't want to enable that.\r\nThe problem is that kwargs are used both by `_parse_and_tokenize` and by `generate`/`forward`.\r\nSee discussion here: https://github.com/huggingface/transformers/pull/9432#discussion_r552550844\r\n\r\nI'm guessing ... | 1,608 | 1,610 | 1,610 | CONTRIBUTOR | null | # What does this PR do?
When calling a Pipeline, the `kwargs` argument is not passed to the tokenizer (it is actually not used at all).
I think the intended behavior is to pass it (as the base tokenizer's `__call__()` method already supports `kwargs`), and that's what this PR does.
[Related to #8180]
The call ord... | {
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https://api.github.com/repos/huggingface/transformers/issues/9142 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9142/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9142/comments | https://api.github.com/repos/huggingface/transformers/issues/9142/events | https://github.com/huggingface/transformers/issues/9142 | 768,249,379 | MDU6SXNzdWU3NjgyNDkzNzk= | 9,142 | RAGRetriever loads dataset in the default cache dir even if a different one is specified | {
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"Indeed! Would you like to open a PR with your fix?",
"I am dealing with this issue too, would love to find a way around this. ",
"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... | 1,608 | 1,619 | 1,619 | 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: latest
- Platform: any
- Python version: 3.8
- PyTorch version (GPU?): any
- Tensorflow version (GPU?)... | {
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https://api.github.com/repos/huggingface/transformers/issues/9141 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9141/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9141/comments | https://api.github.com/repos/huggingface/transformers/issues/9141/events | https://github.com/huggingface/transformers/pull/9141 | 768,242,109 | MDExOlB1bGxSZXF1ZXN0NTQwNzQ3MTM0 | 9,141 | Support for private models from huggingface.co | {
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"@patrickvonplaten I don't follow here. In this PR we want to have a way to either pass a token directly, or to opt in to use the one that's store in `~/`. Don't see how I can do that with just an optional string?",
"> @patrickvonplaten I don't follow here. In this PR we want to have a way to either pass a token ... | 1,608 | 1,608 | 1,608 | MEMBER | null | Add a `use_auth_token` flag (or string) to all `from_pretrained` entry points, to specify token to use as Bearer authorization for remote files.
- if it's a string, use it
- If it's true, will get token from `~/.huggingface/token` (will throw if no token there)
You can test this with:
```python
model = Auto... | {
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https://api.github.com/repos/huggingface/transformers/issues/9140 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9140/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9140/comments | https://api.github.com/repos/huggingface/transformers/issues/9140/events | https://github.com/huggingface/transformers/pull/9140 | 768,202,340 | MDExOlB1bGxSZXF1ZXN0NTQwNzE4NDg0 | 9,140 | Fix T5 Encoder model parallel tests | {
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https://api.github.com/repos/huggingface/transformers/issues/9139 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9139/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9139/comments | https://api.github.com/repos/huggingface/transformers/issues/9139/events | https://github.com/huggingface/transformers/pull/9139 | 768,183,956 | MDExOlB1bGxSZXF1ZXN0NTQwNzAzOTc3 | 9,139 | Experimental support for fairscale ShardedDDP | {
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"wrt your notes on GPU memory consumption improvements - from what I have seen checking GPU allocation often doesn't show the real difference, as pytorch tends to use more than it absolutely needs if there is spare memory - or rather it can go with less when the memory is tight - so to get the best improvements sta... | 1,608 | 1,608 | 1,608 | COLLABORATOR | null | # What does this PR do?
This PR adds support for [FairScale](https://github.com/facebookresearch/fairscale)'s shared DDP training to save GPU memory when training distributed models. Initial tests see a nice reduction of GPU memory used indeed!
This follows the steps of the [main example](https://github.com/faceb... | {
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https://api.github.com/repos/huggingface/transformers/issues/9138 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9138/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9138/comments | https://api.github.com/repos/huggingface/transformers/issues/9138/events | https://github.com/huggingface/transformers/issues/9138 | 768,085,875 | MDU6SXNzdWU3NjgwODU4NzU= | 9,138 | adapting trainer.py for multiple optimizers | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,608 | 1,608 | 1,608 | NONE | null | Hi
I was wondering if there can be an easy way to adapt trainer.py for multiple optimizers, where each optimizer is responsible for updating a part of model. thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/9137 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9137/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9137/comments | https://api.github.com/repos/huggingface/transformers/issues/9137/events | https://github.com/huggingface/transformers/pull/9137 | 768,083,743 | MDExOlB1bGxSZXF1ZXN0NTQwNjE3NDM4 | 9,137 | Add possibility to switch between APEX and AMP in Trainer | {
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"This PR also removes `_use_ddp_no_sync` since presumably `transformers` no longer supports pytorch < 1.2",
"There was one nit that you agreed with but didn't integrate - but I'm fine if it remains as merged - just a potential for divergence down the road...",
"Oh, which one did I miss?",
"https://github.com/... | 1,608 | 1,608 | 1,608 | COLLABORATOR | null | # What does this PR do?
When PyTorch >= 1.6 is installed, Trainer is always using native AMP right now. This PR adds the option to switch between AMP and APEX, which can be useful:
- because of the memory leak in AMP fixed (fixed in 1.7.1 but present in 1.6)
- to benchmark APEX vs. AMP
It also simplifies a litt... | {
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https://api.github.com/repos/huggingface/transformers/issues/9136 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9136/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9136/comments | https://api.github.com/repos/huggingface/transformers/issues/9136/events | https://github.com/huggingface/transformers/pull/9136 | 768,007,494 | MDExOlB1bGxSZXF1ZXN0NTQwNTUyNTkx | 9,136 | Update notebook table and transformers intro notebook | {
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"Discussion on pinning/testing notebooks needs to be global on all notebooks (not just one) so merging this for now. We can think of a strategy and implement it in a follow-up PR."
] | 1,608 | 1,608 | 1,608 | COLLABORATOR | null | # What does this PR do?
Update the examples table and the notebooks table to include all recent examples. Also fix the intro notebook to the transformers library, in particular, the image that was missing.
Fixes #9083
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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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https://api.github.com/repos/huggingface/transformers/issues/9134 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9134/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9134/comments | https://api.github.com/repos/huggingface/transformers/issues/9134/events | https://github.com/huggingface/transformers/pull/9134 | 767,874,020 | MDExOlB1bGxSZXF1ZXN0NTQwNDUwNjg0 | 9,134 | [Bart] Correct wrong order in shift token to right in Bart | {
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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/9133 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9133/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9133/comments | https://api.github.com/repos/huggingface/transformers/issues/9133/events | https://github.com/huggingface/transformers/pull/9133 | 767,857,178 | MDExOlB1bGxSZXF1ZXN0NTQwNDM3Nzc3 | 9,133 | [Examples] Add automatic dataset splitting in language-modeling examples | {
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"Ah, the commit from #9127 seems to have snuck its way in there. Should I remove it?",
"If you can do it easily, that would be best!",
"> If you can do it easily, that would be best!\r\n\r\nI've tried for a bit but I think I just made things worse ! If that's OK I'll leave it there and I'll fix things at merge ... | 1,608 | 1,608 | 1,608 | CONTRIBUTOR | null | # What does this PR do?
Currently, language-modeling examples support passing a HF-datasets dataset as training data. However, this dataset needs to have a `train` and `validation` split, which is not the case for many language-modeling datasets, which are just unstructured text. The updated scripts automatically pa... | {
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Fixes a typo in trainer_tf.py
Fixes #9053
@sgugger
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] | 1,608 | 1,608 | 1,608 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/9130 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9130/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9130/comments | https://api.github.com/repos/huggingface/transformers/issues/9130/events | https://github.com/huggingface/transformers/issues/9130 | 767,791,245 | MDU6SXNzdWU3Njc3OTEyNDU= | 9,130 | Trainer: support iterable datasets for evaluation | {
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"This is more complex than this as the `Trainer` needs to knows in advance the number of elements in your evaluation dataset, so you need to implement a `__len__` method in your evaluation dataset to have `Trainer` work on it.\r\n\r\nAn iterable dataset might make sense for training since you want to yield \"infini... | 1,608 | 1,608 | 1,608 | NONE | null | The trainer seems to support passing iterable datasets as the `train_dataset` (see #5829) but misses to support the same for the `eval_dataset`. I have implemented an iterable dataset for training and now I cannot use the same implementation for evaluation. This doesn't make much sense as evaluation could easily be do... | {
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