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https://api.github.com/repos/huggingface/transformers/issues/9630 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9630/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9630/comments | https://api.github.com/repos/huggingface/transformers/issues/9630/events | https://github.com/huggingface/transformers/issues/9630 | 787,331,313 | MDU6SXNzdWU3ODczMzEzMTM= | 9,630 | key error when use trainer to fine_tuning a dataset | {
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"Duplicate of #9636"
] | 1,610 | 1,610 | 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: 4.1.1
- Platform: Linux-3.10.0-693.5.2.el7.x86_64-x86_64-with-centos-7.4.1708-Core
- Python version: 3.7.9
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/9629 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9629/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9629/comments | https://api.github.com/repos/huggingface/transformers/issues/9629/events | https://github.com/huggingface/transformers/issues/9629 | 787,301,182 | MDU6SXNzdWU3ODczMDExODI= | 9,629 | [Question] How to use threads for huggingface transformers | {
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"Hi, thank you for opening an issue! Could you put the full stack-trace?\r\n\r\nI guess this comes from the tokenizer, rather than the model as we've already seen this error in [tokenizers](https://github.com/huggingface/tokenizers/issues/537).\r\n\r\nAs a means of debugging, can you let me know what happens if you... | 1,610 | 1,619 | 1,619 | NONE | null | I'm trying to run a hugging face model, mode exactly **"cardiffnlp/twitter-roberta-base-sentiment"** on threads. But at the same time, I want just one single instance of it because it's really costly in terms of time.
In other words, I have multiple CSV files (several thousand) and each of them has around 20k-30k l... | {
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https://api.github.com/repos/huggingface/transformers/issues/9628 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9628/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9628/comments | https://api.github.com/repos/huggingface/transformers/issues/9628/events | https://github.com/huggingface/transformers/issues/9628 | 787,299,592 | MDU6SXNzdWU3ODcyOTk1OTI= | 9,628 | Issue with TrainingArguments docs. | {
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"Hi! Do you want to open a PR to fix it? Thanks!"
] | 1,610 | 1,611 | 1,611 | CONTRIBUTOR | null | Hi Team,
This is a minor issue but on this [link](https://huggingface.co/transformers/main_classes/trainer.html#transformers.TrainingArguments), the default optimizer mentioned is Adam in the docs. However, the `Trainer` uses AdamW by default.
This is slightly misleading.
Thanks,
Gunjan
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https://api.github.com/repos/huggingface/transformers/issues/9627 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9627/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9627/comments | https://api.github.com/repos/huggingface/transformers/issues/9627/events | https://github.com/huggingface/transformers/issues/9627 | 787,257,598 | MDU6SXNzdWU3ODcyNTc1OTg= | 9,627 | Passing in custom BartForConditionalGeneration model as generator to RagSequenceForGeneration | {
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"Solved by using `RagConfig` and initializing it with a `DPRQuestionEncoder` and the custom `BartForConditionalGeneration` generator configs. Passed the `RagConfig`, question encoder, generator, and retriever, to `RagModel` to initialize the model.",
"Could you provide a complete sample code about how to do it? I... | 1,610 | 1,630 | 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: 4.2.1
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9626 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9626/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9626/comments | https://api.github.com/repos/huggingface/transformers/issues/9626/events | https://github.com/huggingface/transformers/pull/9626 | 787,195,125 | MDExOlB1bGxSZXF1ZXN0NTU1OTQ4MjUw | 9,626 | Fix: torch.utils.checkpoint.checkpoint attribute error. | {
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Fixes #9617 along with the other `modeling_<modelname>.py` as well where the import statements are missing.
## Who can review?
@LysandreJik, @patrickvonplaten | {
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https://api.github.com/repos/huggingface/transformers/issues/9625 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9625/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9625/comments | https://api.github.com/repos/huggingface/transformers/issues/9625/events | https://github.com/huggingface/transformers/issues/9625 | 787,157,526 | MDU6SXNzdWU3ODcxNTc1MjY= | 9,625 | Weighted Loss in BertForTokenClassification | {
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"In PyTorch, [`nn.CrossEntropyLoss`](https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html) has an optional `weight` parameter which you can specify. This should be a 1D Tensor assigning a weight to each of the classes.\r\n\r\nSo if you want `BertForTokenClassification` with a weighted cross entr... | 1,610 | 1,626 | 1,611 | NONE | null | # 🚀 Feature request
BertForTokenClassification models can compute cross entropy loss currently is only weighted. The option to have different weights for different classes can be useful in several use cases, including but not restricted to the problem of unbalanced output classes
## Motivation
Right now, alth... | {
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https://api.github.com/repos/huggingface/transformers/issues/9624 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9624/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9624/comments | https://api.github.com/repos/huggingface/transformers/issues/9624/events | https://github.com/huggingface/transformers/pull/9624 | 787,119,905 | MDExOlB1bGxSZXF1ZXN0NTU1ODg1NTk3 | 9,624 | [wip] [deepspeed] AdamW is now supported by default | {
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* [x] AdamW is now supported by default so we can remove the now redundant config options and comments https://github.com/mic... | {
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https://api.github.com/repos/huggingface/transformers/issues/9623 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9623/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9623/comments | https://api.github.com/repos/huggingface/transformers/issues/9623/events | https://github.com/huggingface/transformers/issues/9623 | 787,077,821 | MDU6SXNzdWU3ODcwNzc4MjE= | 9,623 | wandb breaks tests - importlib.util.find_spec-related under forked process | {
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"@sgugger, I think the culprit for the 2nd error, when I uninstalled wandb is:\r\n```\r\ndef is_wandb_available():\r\n if os.getenv(\"WANDB_DISABLED\"):\r\n return False\r\n return importlib.util.find_spec(\"wandb\") is not None\r\n```\r\nas it returns `True`, when it shouldn't since:\r\n```\r\nls -l /... | 1,610 | 1,614 | 1,614 | CONTRIBUTOR | null | This has to do with a forked process environment:
I was running:
```
pytest -sv examples/seq2seq/test_finetune_trainer.py -k deepspeed
```
and was getting:
```
stderr: Traceback (most recent call last):
stderr: File "/mnt/nvme1/code/huggingface/transformers-ds-optim-fix/examples/seq2seq/finetune_trainer.py"... | {
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https://api.github.com/repos/huggingface/transformers/issues/9622 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9622/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9622/comments | https://api.github.com/repos/huggingface/transformers/issues/9622/events | https://github.com/huggingface/transformers/pull/9622 | 787,074,546 | MDExOlB1bGxSZXF1ZXN0NTU1ODQ2NzM3 | 9,622 | [deepspeed] --gradient_accumulation_steps fix | {
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Thank you @jncasey for detecting this bug in https://github.com/microsoft/DeepSpeed/issues/671
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/9621 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9621/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9621/comments | https://api.github.com/repos/huggingface/transformers/issues/9621/events | https://github.com/huggingface/transformers/pull/9621 | 787,039,388 | MDExOlB1bGxSZXF1ZXN0NTU1ODE3NzEw | 9,621 | Remove duplicated extras["retrieval"] | {
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https://github.com/huggingface/transformers/blob/28b26013abea3a49afeb46d36993a568ec98f39e/setup.py#L217-L222
and then it seems to be overridden just below, probably linking to `faiss-cpu` being included even on windows.
This PR removes the second assignmen... | {
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https://api.github.com/repos/huggingface/transformers/issues/9620 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9620/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9620/comments | https://api.github.com/repos/huggingface/transformers/issues/9620/events | https://github.com/huggingface/transformers/issues/9620 | 787,023,836 | MDU6SXNzdWU3ODcwMjM4MzY= | 9,620 | SQuAD 2.0 metric not supported | {
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"@sgugger would know about this TODO; I think the fix has landed in `datasets`, right?",
"Yes, this should be fixed directly from `datasets` now, will update the script this afternoon."
] | 1,610 | 1,611 | 1,611 | NONE | null | Hello.
I'm trying to run the official `run_qa.py` code for SQuAD 2.0.
You have an open TODO here that is causing a bug: https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_qa.py#L436
I would like to know what is the status of this TODO, and if it is going to be updated, or is ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9619 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9619/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9619/comments | https://api.github.com/repos/huggingface/transformers/issues/9619/events | https://github.com/huggingface/transformers/issues/9619 | 786,865,584 | MDU6SXNzdWU3ODY4NjU1ODQ= | 9,619 | Train robertatokenizer failed due to pad token not found | {
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"Roberta was train on a causal language model objective, therefore the `LineByLineDataset` is not adapted to train it: it considers one line for one text when the roberta objective is to have several lines concatenated and separated by the sep token until it reaches the block size, to avoid padding. \r\n\r\nYou nee... | 1,610 | 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: Windows
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7? 3080 RTX
- Tensorflow version (... | {
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https://api.github.com/repos/huggingface/transformers/issues/9618 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9618/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9618/comments | https://api.github.com/repos/huggingface/transformers/issues/9618/events | https://github.com/huggingface/transformers/issues/9618 | 786,855,831 | MDU6SXNzdWU3ODY4NTU4MzE= | 9,618 | Text generation pipeline - output_scores parameter | {
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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!",
"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank... | 1,610 | 1,614 | 1,614 | NONE | null | In `text-generation` pipeline, I am looking for a parameter which calculates the confidence score of the generated text. Source: [here](https://huggingface.co/transformers/main_classes/pipelines.html#transformers.TextGenerationPipeline)
I am assuming that, `output_scores` (from [here](https://huggingface.co/transfo... | {
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https://api.github.com/repos/huggingface/transformers/issues/9617 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9617/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9617/comments | https://api.github.com/repos/huggingface/transformers/issues/9617/events | https://github.com/huggingface/transformers/issues/9617 | 786,798,712 | MDU6SXNzdWU3ODY3OTg3MTI= | 9,617 | Error in GPT2 while using gradient checkpointing. | {
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"Hitting this issue as well."
] | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.2.0
- Platform: Linux | 5.4.0-60-generic | 18.04.1-Ubuntu SMP | x86_64
- Python version: 3.7.7
- PyTorch v... | {
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https://api.github.com/repos/huggingface/transformers/issues/9616 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9616/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9616/comments | https://api.github.com/repos/huggingface/transformers/issues/9616/events | https://github.com/huggingface/transformers/pull/9616 | 786,767,099 | MDExOlB1bGxSZXF1ZXN0NTU1NTkxODgx | 9,616 | Fix label datatype in TF Trainer | {
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"I agree with Sylvain that while this is not tested, it's hard to recommend using it."
] | 1,610 | 1,611 | 1,611 | CONTRIBUTOR | null | # What does this PR do?
This PR fixes the case where `labels` can be either a `dict` or a `tf.Tensor` when doing gradient accumulation.
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https://api.github.com/repos/huggingface/transformers/issues/9615 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9615/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9615/comments | https://api.github.com/repos/huggingface/transformers/issues/9615/events | https://github.com/huggingface/transformers/pull/9615 | 786,747,866 | MDExOlB1bGxSZXF1ZXN0NTU1NTc2MTEx | 9,615 | Ignore lm_head decoder bias warning | {
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"Is it normal that this bias is missing?",
"By answering your question I realized this could be upstreamed directly in the RoBERTa model, which I just did.\r\n\r\nYou can take a look at my answer this morning to a similar question: https://github.com/huggingface/transformers/issues/6193#issuecomment-760797867.\r\... | 1,610 | 1,610 | 1,610 | MEMBER | null | Removes the warning that's currently happening when importing `xlm-roberta-base` with any of the XLM-R models.
Closes https://github.com/huggingface/transformers/issues/9579 | {
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https://api.github.com/repos/huggingface/transformers/issues/9614 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9614/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9614/comments | https://api.github.com/repos/huggingface/transformers/issues/9614/events | https://github.com/huggingface/transformers/issues/9614 | 786,670,969 | MDU6SXNzdWU3ODY2NzA5Njk= | 9,614 | Conditional branching logic in modeling_tf_xlnet.py causing error with TF Graph | {
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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."
] | 1,610 | 1,614 | 1,614 | NONE | null | Hi @TevenLeScao ,
I am encountering an error when running the TFXLNet model inside of a tensorflow graph.
Here is some code to reproduce the issue:
```
from transformers import XLNetTokenizer, TFXLNetModel
import tensorflow as tf
tokenizer = XLNetTokenizer.from_pretrained('xlnet-base-cased')
model = TFXL... | {
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https://api.github.com/repos/huggingface/transformers/issues/9613 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9613/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9613/comments | https://api.github.com/repos/huggingface/transformers/issues/9613/events | https://github.com/huggingface/transformers/pull/9613 | 786,656,690 | MDExOlB1bGxSZXF1ZXN0NTU1NDk5MTM3 | 9,613 | training_loss in TFTrainer | {
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"Here the logs of a training with\r\n```\r\npython run_tf_glue.py --task_name mrpc --model_name_or_path bert-base-cased --output_dir model --num_train_epochs 4 --per_device_train_batch_size 16 --per_device_eval_batch_size 16 --do_train --do_eval --do_predict --logging_steps 10 --overwrite_output_dir --gradient_accu... | 1,610 | 1,611 | 1,611 | CONTRIBUTOR | null | # What does this PR do?
The purpose of ```training_loss``` in``` TFTrainer``` is logging.
However, ```training_loss``` shows a very large number while it decreases.
And it is doubled with twice the ```gradient_accumulation_steps```
1. ```training_loss``` is accumulated during epochs. Now, it is only calculated in... | {
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https://api.github.com/repos/huggingface/transformers/issues/9612 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9612/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9612/comments | https://api.github.com/repos/huggingface/transformers/issues/9612/events | https://github.com/huggingface/transformers/issues/9612 | 786,644,000 | MDU6SXNzdWU3ODY2NDQwMDA= | 9,612 | Why do not use 'torch.nn.MultiheadAttention' to substitude 'Class BertSelfAttention+BertSelfOutput' for pytorch | {
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"'BertSelfAttention+BertSelfOutput' is tensorflow style\r\n'torch.nn.MultiheadAttention' is real pytorch style",
"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 co... | 1,610 | 1,680 | 1,614 | NONE | null | # 📚 Migration
## Information
pytorch has 'torch.nn.MultiheadAttention'
https://pytorch.org/docs/1.3.0/nn.html?highlight=multihead#torch.nn.MultiheadAttention
## Details
1. For Better performace and generality, I suggest to use 'torch.nn.MultiheadAttention' instead of 'Class BertSelfAttention+BertSelfOutput... | {
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] | 1,610 | 1,614 | 1,614 | CONTRIBUTOR | null |
# What does this PR do?
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* [x] how to run DeepSpeed with a 1 gpu which is not GPU 0 (`CUDA_VISIBLE_DEVICES` can'... | {
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"Hi, thank you for opening a PR!\r\n\r\nOur goal is to stay as close to the initial implementation as possible. The original implementation by OpenAI uses -1e4, so we will keep it this way.",
"I find the initial implementation is `-1e10` in https://github.com/openai/gpt-2/blob/master/src/model.py#L88\r\n\r\n```py... | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | # What does this PR do?
change masked_bias to -inf
## 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 [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributi... | {
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https://api.github.com/repos/huggingface/transformers/issues/9608 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9608/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9608/comments | https://api.github.com/repos/huggingface/transformers/issues/9608/events | https://github.com/huggingface/transformers/issues/9608 | 786,497,692 | MDU6SXNzdWU3ODY0OTc2OTI= | 9,608 | Convert ckpt from TFTrainer to huggingface format. | {
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"Hello!\r\n\r\nYou have to use the `save_model` method of the trainer.",
"ok. thanks!"
] | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | I trained models with ```Trainer(pytorch)``` and ```TfTrainer(tensorflow)```, repectively.
With ```Trainer```, everything is ok. Saved models are directly applicable to huggingface pipeline (eg, AutoModel('model_name')).
But with save models from ```TFTrainer``` (ckpt format), I can not do that with ```AutoModel```... | {
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https://api.github.com/repos/huggingface/transformers/issues/9607 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9607/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9607/comments | https://api.github.com/repos/huggingface/transformers/issues/9607/events | https://github.com/huggingface/transformers/issues/9607 | 786,470,266 | MDU6SXNzdWU3ODY0NzAyNjY= | 9,607 | [run_ner.py]You need to instantiate RobertaTokenizerFast with add_prefix_space=True to use it with pretokenized inputs | {
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"Hi,\r\n\r\nI would like to report the same problem. I see this problem only with RoBERTa base or large and I am also using transformers4.2.2.\r\n\r\nAny suggestions or help would be appreciated. \r\nThanks.",
"Hi, \r\nI had the same issue. I solved it by adding add_prefix_space=True to the tokenizer.\r\n\r\nBest... | 1,610 | 1,623 | 1,623 | NONE | null | ## Environment info
- `transformers` version: 4.2.0
- Platform: Linux-5.4.0-53-generic-x86_64-with-debian-buster-sid
- Python version: 3.6.12
- PyTorch version (GPU?): 1.7.1 (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/9606 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9606/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9606/comments | https://api.github.com/repos/huggingface/transformers/issues/9606/events | https://github.com/huggingface/transformers/issues/9606 | 786,390,547 | MDU6SXNzdWU3ODYzOTA1NDc= | 9,606 | [DeepSpeed] Features to integrate / Optimizations to add / Experiments to do | {
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"hi，we noticed Deepspeed transformer kernel is much faster than the original PyTorch version with less memory consumption. I would like to know if you have any future plan to integrate Deepspeed transformer kernel in huggingface.\r\nThanks!",
"Personally my focus at the moment is to enable fitting big models on ... | 1,610 | 1,686 | null | CONTRIBUTOR | null | # 🚀 Feature request
While we have the support for main DeepSpeed features integrated, there are other powerful features that haven't been explored yet and which can provide even more various performance boosts. Some will probably require no changes on our side, while others require changes in the model and/or train... | {
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https://api.github.com/repos/huggingface/transformers/issues/9605 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9605/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9605/comments | https://api.github.com/repos/huggingface/transformers/issues/9605/events | https://github.com/huggingface/transformers/pull/9605 | 786,386,616 | MDExOlB1bGxSZXF1ZXN0NTU1MjY0ODk3 | 9,605 | New run_seq2seq script | {
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"Could we discuss the naming of this script and others?\r\n\r\nThe description goes:\r\n\r\n> Fine-tuning the library models for sequence to sequence.\r\n\r\n`run_seq2seq.py` is much less descriptive or intuitive than `finetune_trainer.py `- why not go back to `finetune.py` to replace the script that was PL-based a... | 1,610 | 1,611 | 1,611 | COLLABORATOR | null | # What does this PR do?
This PR adds a new version of `finetune_trainer` using datasets and completely self-contained (not using anything in the `utils` module or any other python script of the seq2seq folder). I renamed a few args from the old script, mainly:
- `n_train` -> `max_train_samples`
- `n_val` -> `max_v... | {
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https://api.github.com/repos/huggingface/transformers/issues/9604 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9604/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9604/comments | https://api.github.com/repos/huggingface/transformers/issues/9604/events | https://github.com/huggingface/transformers/issues/9604 | 786,254,814 | MDU6SXNzdWU3ODYyNTQ4MTQ= | 9,604 | Mistake in the "Summary of the tasks" article | {
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"Indeed! Do you want to open a PR with a doc fix?",
"I would like to, but I couldn't find where that exact doc in the repo is",
"Also, a built-in tool for pointing out mistakes in the docs would be usable (like those when you highlight an error and press Ctrl+Enter). I notice a few mistakes and typos from time ... | 1,610 | 1,614 | 1,614 | NONE | null | Two first points of the translation process are duplicating two first points of summarization process:
[https://huggingface.co/transformers/task_summary.html#translation](https://huggingface.co/transformers/task_summary.html#translation)
> 1. Instantiate a tokenizer and a model from the checkpoint name. Summarizati... | {
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https://api.github.com/repos/huggingface/transformers/issues/9603 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9603/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9603/comments | https://api.github.com/repos/huggingface/transformers/issues/9603/events | https://github.com/huggingface/transformers/issues/9603 | 786,233,716 | MDU6SXNzdWU3ODYyMzM3MTY= | 9,603 | TypeError: on_init_end() got an unexpected keyword argument 'model' | {
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"You are using a pytorch lightning callback instead of a Hugging Face `TrainerCallback`, I'm unsure of why you would think this will work. If you want to use pytorch ligthning, you will have to user their `Trainer` as well.",
"thanks @sgugger . The reason I used pytorch lightning callback is because I couldn't fi... | 1,610 | 1,667 | 1,614 | NONE | null | ## Environment info
- `transformers` version: 4.0.0
- Python 3.6.10
- Pytorch version: 1.6.0
- pytorch-lightning version: 1.0.3
I'm using aws_neuron_pytorch_p36 virtual environment (on p3 ec2 instance). Regarding pytorch-lightning version, the above version is the highest one I can currently use (higher versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/9602 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9602/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9602/comments | https://api.github.com/repos/huggingface/transformers/issues/9602/events | https://github.com/huggingface/transformers/issues/9602 | 786,233,139 | MDU6SXNzdWU3ODYyMzMxMzk= | 9,602 | TypeError: on_init_end() got an unexpected keyword argument 'model' | {
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- `transformers` version: 4.0.0
- Python 3.6.10
- Python version: 1.6.0
I'm using aws_neuron_pytorch_p36 virtual environment (on p3 ec2 instance)
### Who can help
@LysandreJik
@sgugger
## Information
Model I am using RobertaForSequenceClassification
## To reproduce
The cod... | {
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https://api.github.com/repos/huggingface/transformers/issues/9601 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9601/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9601/comments | https://api.github.com/repos/huggingface/transformers/issues/9601/events | https://github.com/huggingface/transformers/pull/9601 | 786,178,872 | MDExOlB1bGxSZXF1ZXN0NTU1MDg3MDQx | 9,601 | [TF Led] Fix wrong decoder attention mask behavior | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/9600 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9600/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9600/comments | https://api.github.com/repos/huggingface/transformers/issues/9600/events | https://github.com/huggingface/transformers/pull/9600 | 786,167,104 | MDExOlB1bGxSZXF1ZXN0NTU1MDc3MjY4 | 9,600 | Speed up RepetitionPenaltyLogitsProcessor (pytorch) | {
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Speeds up RepetitionPenaltyLogitsProcessor using torch gather-scatter functions. Tested on pytorch 1.4.0.
Here's a minimal example to reproduce the slow behavior (and test speed of improvements):
```
import torch
from transformers import RepetitionPenaltyLogitsProcessor, LogitsProcessor
im... | {
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https://api.github.com/repos/huggingface/transformers/issues/9599 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9599/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9599/comments | https://api.github.com/repos/huggingface/transformers/issues/9599/events | https://github.com/huggingface/transformers/issues/9599 | 786,094,586 | MDU6SXNzdWU3ODYwOTQ1ODY= | 9,599 | saving the model during run_mlm | {
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"Please avoid spamming the repository with multiple duplicate issues.\r\nAlso, those questions should go in the [forums](https://discuss.huggingface.co/), the issues are kept for bugs and feature requests only.",
"sorry...I created two streams by mistake.\r\n"
] | 1,610 | 1,610 | 1,610 | NONE | null | Hi friends-
I am trying to train a Roberta on a large corpus with a server with time limitation.
Is there any way to save the model like every 3000 steps to keep record of the training, and resume it later?
Really need it with the project…Thanks for helping. | {
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https://api.github.com/repos/huggingface/transformers/issues/9598 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9598/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9598/comments | https://api.github.com/repos/huggingface/transformers/issues/9598/events | https://github.com/huggingface/transformers/issues/9598 | 786,094,294 | MDU6SXNzdWU3ODYwOTQyOTQ= | 9,598 | saving the model during run_mlm.py | {
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"Please avoid spamming the repository with multiple duplicate issues.\r\nAlso, those questions should go in the [forums](https://discuss.huggingface.co/), the issues are kept for bugs and feature requests only."
] | 1,610 | 1,610 | 1,610 | NONE | null | Hi friends-
I am trying to train a Roberta on a large corpus with a server with time limitation.
Is there any way to save the model like every 3000 steps to keep record of the training, and resume it later?
Really need it with the project…Thanks for helping.
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https://api.github.com/repos/huggingface/transformers/issues/9597 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9597/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9597/comments | https://api.github.com/repos/huggingface/transformers/issues/9597/events | https://github.com/huggingface/transformers/issues/9597 | 786,091,405 | MDU6SXNzdWU3ODYwOTE0MDU= | 9,597 | [Model Exporting] How to export a fine tuned model to a single pytorch or tensorflow model file? | {
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"_Note:_ that'd be a better question for the forums at discuss.huggingface.co\r\n\r\nThe `optimizer.pt` is a snapshot of the optimizer's internal state, for inference you can delete it and only keep your `model.bin` (= the weights)",
"Thank you, that is very helpful and for directing me to the forums, I did not e... | 1,610 | 1,610 | 1,610 | NONE | null | Apologies if this is a very basic question, but I just cant seem to find any help or documentation for this online.
I want to use google cloud to generate text from a trained model and the maximum size for a model there is ``500MB``. Currently when finetuning a model the checkpoints folder has the ``model.bin`` file... | {
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https://api.github.com/repos/huggingface/transformers/issues/9596 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9596/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9596/comments | https://api.github.com/repos/huggingface/transformers/issues/9596/events | https://github.com/huggingface/transformers/pull/9596 | 786,054,862 | MDExOlB1bGxSZXF1ZXN0NTU0OTg1MzM1 | 9,596 | Update `past_key_values` in GPT-2 | {
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"CircleCI error messages says as below.\r\n\r\nIn `run_tests_torch`:\r\n``` \r\n-- Docs: https://docs.pytest.org/en/stable/warnings.html\r\n=========================== short test summary info ============================\r\nFAILED tests/test_modeling_gpt2.py::GPT2ModelTest::test_beam_sample_generate\r\nFAILED tests... | 1,610 | 1,611 | 1,611 | CONTRIBUTOR | null | # What does this PR do?
It seems GPT-2 and BartDecoder has a different style of `past_key_values`.
Advised by @patrickvonplaten,
I opened this PR to change GPT-2's cache format from a single tensor to a tuple of 2 tensors.
Once this problem is solved, it is expected that `past_key_values` in GPT-2 will be handled... | {
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https://api.github.com/repos/huggingface/transformers/issues/9595 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9595/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9595/comments | https://api.github.com/repos/huggingface/transformers/issues/9595/events | https://github.com/huggingface/transformers/issues/9595 | 786,034,370 | MDU6SXNzdWU3ODYwMzQzNzA= | 9,595 | Order of inputs (difference between doc and output) | {
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"Hi! Order doesn’t matter in a dictionary. \r\n\r\nIt only matters if you use the arguments as positional arguments, which is not recommended.",
"@LysandreJik \r\n\r\nSo, order does matter when using lists? What is now the right order?\r\n",
"This issue has been automatically marked as stale and been closed bec... | 1,610 | 1,614 | 1,614 | NONE | null | Hey,
when using a dictionary as model input does the order matters? Eg:
`model({"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask})
`
and
`model({"input_ids": input_ids, "attention_mask": attention_mask, "token_type_ids": token_type_ids})
`
When using tokenizer... | {
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https://api.github.com/repos/huggingface/transformers/issues/9594 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9594/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9594/comments | https://api.github.com/repos/huggingface/transformers/issues/9594/events | https://github.com/huggingface/transformers/issues/9594 | 786,027,159 | MDU6SXNzdWU3ODYwMjcxNTk= | 9,594 | why set masked_bias as -10000 in GPT2 | {
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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."
] | 1,610 | 1,652 | 1,614 | CONTRIBUTOR | null | ## Information
`masked_bias` is set as `-10000` in GPT2, why not `-inf`?
https://github.com/huggingface/transformers/blob/e43f3b6190cfd98a38912411b8bc8ecbb6629280/src/transformers/models/gpt2/modeling_gpt2.py#L133
## openai/gpt-2
In [openai/gpt2](https://github.com/openai/gpt-2/blob/a74da5d99abaaba920de8131... | {
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https://api.github.com/repos/huggingface/transformers/issues/9593 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9593/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9593/comments | https://api.github.com/repos/huggingface/transformers/issues/9593/events | https://github.com/huggingface/transformers/issues/9593 | 785,964,828 | MDU6SXNzdWU3ODU5NjQ4Mjg= | 9,593 | Difference in decoded strings between a tokenizer and the corresponding fast tokenizer | {
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"For the `WordPiece` decoder, which is used in `BertTokenizerFast`, It seems that `cleanup` cannot be changed after initialization.\r\nhttps://github.com/huggingface/tokenizers/blob/python-v0.10.0/tokenizers/src/tokenizer/mod.rs#L762\r\nhttps://github.com/huggingface/tokenizers/blob/python-v0.10.0/tokenizers/src/de... | 1,610 | 1,614 | 1,614 | NONE | null | ## Environment info
- `transformers` version: 4.2.0
- Platform: Linux-4.15.0-130-generic-x86_64-with-debian-10.5
- Python version: 3.7.8
- PyTorch version (GPU?): 1.7.1+cpu (False)
- Tensorflow version (GPU?): 2.4.0 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
###... | {
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https://api.github.com/repos/huggingface/transformers/issues/9592 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9592/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9592/comments | https://api.github.com/repos/huggingface/transformers/issues/9592/events | https://github.com/huggingface/transformers/issues/9592 | 785,928,156 | MDU6SXNzdWU3ODU5MjgxNTY= | 9,592 | disable message "Some layers from the model checkpoint ..." | {
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"You can change the logging level:\r\n\r\n```py\r\nfrom transformers import logging as hf_logging\r\n\r\nhf_logging.set_verbosity_error()\r\n```"
] | 1,610 | 1,610 | 1,610 | NONE | null | I wonder how can I disable this message? v3.4
```
Some layers from the model checkpoint at bert-base-cased were not used when initializing TFBertForSequenceClassification: ['nsp___cls', 'mlm___cls']
- This IS expected if you are initializing TFBertForSequenceClassification from the checkpoint of a model trained on... | {
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https://api.github.com/repos/huggingface/transformers/issues/9591 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9591/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9591/comments | https://api.github.com/repos/huggingface/transformers/issues/9591/events | https://github.com/huggingface/transformers/issues/9591 | 785,927,752 | MDU6SXNzdWU3ODU5Mjc3NTI= | 9,591 | disable message "Some layers from the model checkpoint at bert-base-cased were not used when initializing" | {
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"You can change the logging level:\r\n\r\n```\r\nfrom transformers import logging as hf_logging\r\n\r\nhf_logging.set_verbosity_error()\r\n```"
] | 1,610 | 1,610 | 1,610 | NONE | null | I wonder how can I disable this message? v3.4
```
Some layers from the model checkpoint at bert-base-cased were not used when initializing TFBertForSequenceClassification: ['nsp___cls', 'mlm___cls']
- This IS expected if you are initializing TFBertForSequenceClassification from the checkpoint of a model trained on... | {
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https://api.github.com/repos/huggingface/transformers/issues/9590 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9590/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9590/comments | https://api.github.com/repos/huggingface/transformers/issues/9590/events | https://github.com/huggingface/transformers/issues/9590 | 785,890,518 | MDU6SXNzdWU3ODU4OTA1MTg= | 9,590 | WARNING:tensorflow:AutoGraph | {
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"Hello !\r\n\r\nYou can safely ignore those warnings, no worries.",
"@jplu Thanks. Might the results of training a model may different to new version (like because of the new kind of tokenizer)?\r\n\r\nBut \"why\" do I get the same output as in v3, since in the doc is stated that the ouput structure somehow chnag... | 1,610 | 1,618 | 1,618 | NONE | null | Since v4.2 I get those strange outputs while finetuning a TFBert Model:
Using
`bert_model = TFBertForSequenceClassification.from_pretrained('bert-base-cased')`
```
WARNING:tensorflow:AutoGraph could not transform <bound method Socket.send of <zmq.sugar.socket.Socket object at 0x7fb902ce88d0>> and will run it ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9588 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9588/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9588/comments | https://api.github.com/repos/huggingface/transformers/issues/9588/events | https://github.com/huggingface/transformers/issues/9588 | 785,856,455 | MDU6SXNzdWU3ODU4NTY0NTU= | 9,588 | Longformer version of RoBERTa error | {
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"Comparing codebase of version `3.0.2` and `4.2.0` I have noticed that `forward` function differs. I have added deleted lines right at the beginning of the function:\r\n```python\r\n def forward(\r\n self,\r\n hidden_states,\r\n attention_mask=None,\r\n is_index_masked=None,\r\n ... | 1,610 | 1,614 | 1,614 | NONE | null | ## Environment info
- `transformers` version: 4.2.0
- Platform: Linux-4.15.0-123-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No
### ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9587 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9587/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9587/comments | https://api.github.com/repos/huggingface/transformers/issues/9587/events | https://github.com/huggingface/transformers/issues/9587 | 785,807,931 | MDU6SXNzdWU3ODU4MDc5MzE= | 9,587 | How to fine-tune T5/Bart for other languages on summarization? | {
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"Hi! The `BertJapaneseTokenizer` you mention was created specifically for Japanese, so it should encode the Japanese language well.\r\n\r\nYou can find the list of models that have Japanese checkpoints [here](https://huggingface.co/models?filter=ja).",
"Tokenizers can be decoupled from their models, so you can in... | 1,610 | 1,613 | 1,613 | CONTRIBUTOR | null | Assume that I have a Japanese dataset for fine-tuning. How could I fine-tune it?
I think that the original tokenizer like `BartTokenizer` or `T5Tokenizer` can't be used for Japanese, right?
So is it possible to use a Japanese tokenizer like `BertJapaneseTokenizer` to fine-tune a Bart model? Please give me some advic... | {
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https://api.github.com/repos/huggingface/transformers/issues/9586 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9586/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9586/comments | https://api.github.com/repos/huggingface/transformers/issues/9586/events | https://github.com/huggingface/transformers/pull/9586 | 785,806,346 | MDExOlB1bGxSZXF1ZXN0NTU0Nzc5MDY3 | 9,586 | [bugs] 1. fix chinese_ref column will ignore even we add it in to Datasets. | {
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"You can avoid removing that column by setting `remove_unused_columns=False` in your `TrainingArguments`.",
"I will try it,thank you so much "
] | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | [bugs] 1. fix chinese_ref column will ignore even we add it in to Datasets.
[bugs] 2. DataCollatorForWholeWordMask e["chinese_ref"] is a list, fix the get length method.
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to a... | {
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https://api.github.com/repos/huggingface/transformers/issues/9585 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9585/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9585/comments | https://api.github.com/repos/huggingface/transformers/issues/9585/events | https://github.com/huggingface/transformers/pull/9585 | 785,800,939 | MDExOlB1bGxSZXF1ZXN0NTU0Nzc0NTYw | 9,585 | Gradient accumulation for TFTrainer | {
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"Sorry we have to revert this PR as `labels` is not a dict but a tensor and makes fails all our examples.",
"Thanks a lot for having spotted this cas, a more adapted fix will be available here #9616 very sorry for the inconvenience.",
"Never mind. Thanks again for the fix."
] | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | # What does this PR do?
```TFTrainer``` does not work with ```gradient_accumulation_steps``` > 1 (I am doing with ```TFGPT2LMHeadModel```).
Similar treatment of #6479 is done for labels.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9584 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9584/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9584/comments | https://api.github.com/repos/huggingface/transformers/issues/9584/events | https://github.com/huggingface/transformers/pull/9584 | 785,792,093 | MDExOlB1bGxSZXF1ZXN0NTU0NzY3MjQz | 9,584 | BatchEncoding.to with device with tests | {
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The `torch` module isn't imported directly in the `tokenization_utils.py` file. In a similar fashion to the tensor checks, this PR adds a device check to identify if a variable is a torch device.
Adds a test that fails previous to this PR. | {
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https://api.github.com/repos/huggingface/transformers/issues/9583 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9583/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9583/comments | https://api.github.com/repos/huggingface/transformers/issues/9583/events | https://github.com/huggingface/transformers/issues/9583 | 785,726,491 | MDU6SXNzdWU3ODU3MjY0OTE= | 9,583 | Custom mask when performing forward pass | {
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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!"
] | 1,610 | 1,610 | 1,610 | NONE | null | Suppose I have a sequence that consists of 2 sentences separated by \<\/SEP\> tokens like A \<\/SEP\> B. When performing forward pass with RoBERTa model, I want tokens in sentence A only attend to tokens in sentence A and vice versa for sentence B. The mask will be look like this:
![image](https://user-images.githubus... | {
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https://api.github.com/repos/huggingface/transformers/issues/9582 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9582/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9582/comments | https://api.github.com/repos/huggingface/transformers/issues/9582/events | https://github.com/huggingface/transformers/pull/9582 | 785,670,529 | MDExOlB1bGxSZXF1ZXN0NTU0NjYwMTUx | 9,582 | [deepspeed doc] install issues + 1-gpu deployment | {
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"Thank you for your awesome suggestions and tweaks - all done."
] | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | This PR extends the DeepSpeed/FairScale integration documentation to:
* add extensive general troubleshooting for CUDA-extensions (applies to fairscale, deepspeed, apex or any other python pytorch extension with CUDA C++ code) - these are very likely to be encountered by our users - all notes are based on my first h... | {
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https://api.github.com/repos/huggingface/transformers/issues/9581 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9581/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9581/comments | https://api.github.com/repos/huggingface/transformers/issues/9581/events | https://github.com/huggingface/transformers/issues/9581 | 785,665,522 | MDU6SXNzdWU3ODU2NjU1MjI= | 9,581 | A question about the weight decay | {
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Should this by `layer_norm.weight`? Even seems you are not using weight decay at all. | {
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https://api.github.com/repos/huggingface/transformers/issues/9580 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9580/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9580/comments | https://api.github.com/repos/huggingface/transformers/issues/9580/events | https://github.com/huggingface/transformers/issues/9580 | 785,575,488 | MDU6SXNzdWU3ODU1NzU0ODg= | 9,580 | BatchEncoding.to() throwing torch NameError in 4.2.0; identical code works in 4.1.1 | {
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"Hi, thanks for raising an issue!\r\nIndeed, this is problematic. We're going to do a patch release this morning (v4.2.1) with a fix for this.",
"Ths fix is here: https://github.com/huggingface/transformers/pull/9584\r\n\r\nIt should be merged in a couple of hours, after which we'll release a patch."
] | 1,610 | 1,610 | 1,610 | NONE | null | ## Environment info
- `transformers` version: 4.2.0
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101 (True)
- Tensorflow version (GPU?): 2.4.0 (True)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: Haven't e... | {
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https://api.github.com/repos/huggingface/transformers/issues/9579 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9579/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9579/comments | https://api.github.com/repos/huggingface/transformers/issues/9579/events | https://github.com/huggingface/transformers/issues/9579 | 785,564,112 | MDU6SXNzdWU3ODU1NjQxMTI= | 9,579 | Some weights of XLMRobertaForMaskedLM were not initialized from the model checkpoint at xlm-roberta-base and are newly initialized | {
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"Could you put the full error in the description of the issue rather than in the title? We don't know which weights are not initialized.",
"> Could you put the full error in the description of the issue rather than in the title? We don't know which weights are not initialized.\r\nCode:\r\nmodel = XLMRobertaForMas... | 1,610 | 1,610 | 1,610 | NONE | null | Where can I find weight that won't give the following error?
The code:
model = XLMRobertaForMaskedLM.from_pretrained('xlm-roberta-base') | {
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https://api.github.com/repos/huggingface/transformers/issues/9578 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9578/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9578/comments | https://api.github.com/repos/huggingface/transformers/issues/9578/events | https://github.com/huggingface/transformers/pull/9578 | 785,535,078 | MDExOlB1bGxSZXF1ZXN0NTU0NTQ4NzA1 | 9,578 | Fix Trainer with a parallel model | {
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The test introduced in #9566 wasn't actually working as the default batch size is 8, not 16...
So the problem was still there, the reason because `_setup_devices` in `TrainingArguments` is a `cached_property`, so its result is computed once and for all at init. Had to change the behavior sli... | {
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https://api.github.com/repos/huggingface/transformers/issues/9577 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9577/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9577/comments | https://api.github.com/repos/huggingface/transformers/issues/9577/events | https://github.com/huggingface/transformers/issues/9577 | 785,493,555 | MDU6SXNzdWU3ODU0OTM1NTU= | 9,577 | Trainer is using DataParallel on parallelized models | {
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"The `self.args._n_gpu = 1` is to avoid parallelizing the data so it has nothing to do with your problem (and it is right, we can't set `self.args.n_gpu` which is a property but that's a whole different story!)\r\n\r\nHow is your model parallelized? Without that piece of code we can't reproduce the bug and help you... | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.2.0
- Platform: Ubuntu 20.04
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1 / CUDA 11.2
- Using GPU in script?:
- Using distributed or parallel set-up in script?:
### Who can help
@sgugger @stas00
## Information
I'm trying out the 4.2.0 rele... | {
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https://api.github.com/repos/huggingface/transformers/issues/9576 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9576/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9576/comments | https://api.github.com/repos/huggingface/transformers/issues/9576/events | https://github.com/huggingface/transformers/issues/9576 | 785,481,617 | MDU6SXNzdWU3ODU0ODE2MTc= | 9,576 | Pipeline - Truncation Keyword not Recognized | {
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"The [documentation](https://huggingface.co/transformers/main_classes/pipelines.html#transformers.pipeline) of the pipeline function clearly shows the `truncation` argument is not accepted, so i'm not sure why you are filing this as a bug.\r\n\r\nThe `__call__` method of a class is not what is used when you create ... | 1,610 | 1,610 | 1,610 | NONE | null | ## Environment info
- `transformers` version: 4.2.0
- Platform: Linux-5.4.0-58-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.1+cpu (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9575 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9575/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9575/comments | https://api.github.com/repos/huggingface/transformers/issues/9575/events | https://github.com/huggingface/transformers/issues/9575 | 785,472,942 | MDU6SXNzdWU3ODU0NzI5NDI= | 9,575 | Converting original BERT tf checkpoints to BertForMaskedLM | {
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"The `BertForPreTraining` contains two heads: the NSP and the MLM heads. Therefore, by using the tf1 conversion script, you're already porting the entire model!\r\n\r\nFor the configuration, it should align pretty seamlessly to Google's configurations, but you can check the expected field here: https://github.com/h... | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | Hi! I have some BERT models that I've trained using the original Google code for BERT, and I was hoping to port them over to `transformers`. I noticed that there are two scripts to do this conversion: one for [the original tf1.x code](https://github.com/huggingface/transformers/blob/master/src/transformers/models/ber... | {
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https://api.github.com/repos/huggingface/transformers/issues/9574 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9574/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9574/comments | https://api.github.com/repos/huggingface/transformers/issues/9574/events | https://github.com/huggingface/transformers/pull/9574 | 785,448,387 | MDExOlB1bGxSZXF1ZXN0NTU0NDc2MDEw | 9,574 | Upstream (and rename) sortish sampler | {
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This PR moves the logic of the "sortish sampler" from examples/seq2seq utils to `trainer_pt_utils` to make this behavior available for all types of training in the main `Trainer`. It also fixes a bug in the previous implementation of the distributed sortish sampler that did not synchronize th... | {
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https://api.github.com/repos/huggingface/transformers/issues/9573 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9573/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9573/comments | https://api.github.com/repos/huggingface/transformers/issues/9573/events | https://github.com/huggingface/transformers/issues/9573 | 785,390,325 | MDU6SXNzdWU3ODUzOTAzMjU= | 9,573 | Multilingual MiniLM | {
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"Alright! I found the solution. For the tokenizer, XLMRobertaTokenizer should be used instead of AutoTokenizer. ",
"Thanks for reporting. Now that we have model versioning, the author(s) of [`\"microsoft/Multilingual-MiniLM-L12-H384\"`](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) could update t... | 1,610 | 1,622 | 1,610 | NONE | null | Hello everyone!
I am trying to load this model from Microsoft using the path provided [here](huggingface.co/microsoft/Multilingual-MiniLM-L12-H384). I am applying the same code provided there:
`tokenizer = AutoTokenizer.from_pretrained("microsoft/Multilingual-MiniLM-L12-H384")`
But I am facing this error mess... | {
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https://api.github.com/repos/huggingface/transformers/issues/9572 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9572/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9572/comments | https://api.github.com/repos/huggingface/transformers/issues/9572/events | https://github.com/huggingface/transformers/issues/9572 | 785,338,804 | MDU6SXNzdWU3ODUzMzg4MDQ= | 9,572 | How to train the models in smaller spochs | {
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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!",
"yes,. I asked but forum is inactive, please do not close it I really need\nhelp on this.\n\nOn Thu, Jan 14, 202... | 1,610 | 1,610 | 1,610 | NONE | null | Hi
I am under low compute hours, could you tell me how I can train finetune_trainer.py for smaller iterations and then continue retraining from the saved checkpoint to reproduce the same results as full training? what are the cares to be taken, and things to pay attention, thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/9571 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9571/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9571/comments | https://api.github.com/repos/huggingface/transformers/issues/9571/events | https://github.com/huggingface/transformers/issues/9571 | 785,295,228 | MDU6SXNzdWU3ODUyOTUyMjg= | 9,571 | Tensorflow pretrained FlauBERT mixed precision error | {
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"Hello!\r\n\r\nUnfortunately the TF models are not yet compliant with the \"float16\" mixed precision. This is our main goal for the next release (the one after 4.2.X) as we are actively working on this.\r\n\r\nSorry the the inconvenience. I will update this post once done. ",
"This issue has been automatically m... | 1,610 | 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
- Python version: 3.7.6
- Tensorflow version (GPU?): 2.3.0
- Using GPU in script?: Yes - GPU Tesla V... | {
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https://api.github.com/repos/huggingface/transformers/issues/9570 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9570/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9570/comments | https://api.github.com/repos/huggingface/transformers/issues/9570/events | https://github.com/huggingface/transformers/pull/9570 | 785,268,285 | MDExOlB1bGxSZXF1ZXN0NTU0MzIyODAw | 9,570 | Compliancy with tf-nightly | {
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"Ok, just restored the previous version checking."
] | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | # What does this PR do?
This PR makes the lib able to be used with the nightly builds of TensorFlow. And fix an issue with the min TensorFlow version. | {
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https://api.github.com/repos/huggingface/transformers/issues/9569 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9569/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9569/comments | https://api.github.com/repos/huggingface/transformers/issues/9569/events | https://github.com/huggingface/transformers/pull/9569 | 785,247,520 | MDExOlB1bGxSZXF1ZXN0NTU0MzA1NTUz | 9,569 | Add head_mask/decoder_head_mask for BART | {
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"Thanks for opening a new PR. Let me know if you need a review (It's also ok if I go into the PR and fix some things if your stuck :-) )",
"@patrickvonplaten I hope this PR is again ready for review. The only thing remaining to resolve is that issue in `test_headmasking` described above. Currently, I've been tryi... | 1,610 | 1,611 | 1,610 | CONTRIBUTOR | null | This PR implement `head_mask` and `decoder_head_mask` for PyTorch BART-based models. The full list, please, see below:
- **BART**
- **MBart**
- **Blenderbot**
- **BlenderbotSmall**
- **Marian**
- **Pegasus**
This PR is a follow up on the closed PR #9404.
**Motivation**:
According to HuggingFace's websites ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9568 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9568/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9568/comments | https://api.github.com/repos/huggingface/transformers/issues/9568/events | https://github.com/huggingface/transformers/issues/9568 | 785,245,164 | MDU6SXNzdWU3ODUyNDUxNjQ= | 9,568 | pegasus fine-tune: TypeError: shift_tokens_right() missing 1 required positional argument: 'decoder_start_token_id' | {
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"Hey @cheop-byeon, \r\n\r\nwe no longer actively maintain the `research_projects` folder ourselves. To solve your problem you can however just add \r\n`model.config.decoder_start_token_id` as the third argument to the function.",
"Note that we recommend that you use the research project with it's proposed version... | 1,610 | 1,611 | 1,610 | NONE | null | ## Environment info
- `transformers` version: 4.2.0dev0
- Platform: Linux-3.10.0-1062.18.1.el7.x86_64-x86_64-with-centos-7.7.1908-Core
- Python version: 3.7.3
- PyTorch version (GPU?): 1.7.1 (False)
- Tensorflow version (GPU?): 2.4.0 (False)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-u... | {
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https://api.github.com/repos/huggingface/transformers/issues/9567 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9567/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9567/comments | https://api.github.com/repos/huggingface/transformers/issues/9567/events | https://github.com/huggingface/transformers/pull/9567 | 785,201,630 | MDExOlB1bGxSZXF1ZXN0NTU0MjY3MTk2 | 9,567 | Switch metrics in run_ner to datasets | {
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This PR uses `datasets` to compute the metrics in the `run_ner` script. This allows us to grab the entity level metrics on top of the overall ones if we want them, which is controlled by the newly added flag `--return_entity_level_metrics`.
Fixes #9546
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https://api.github.com/repos/huggingface/transformers/issues/9566 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9566/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9566/comments | https://api.github.com/repos/huggingface/transformers/issues/9566/events | https://github.com/huggingface/transformers/pull/9566 | 785,156,938 | MDExOlB1bGxSZXF1ZXN0NTU0MjI5ODY0 | 9,566 | Fix data parallelism in Trainer | {
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A bug in data parallelism was introduced in #9451 (mostly because of some weird behavior of dataclasses in python) and data was... well not parallelized anymore (more like the batch size ended up divided by the number of GPUs).
This PR fixes that and to make sure it didn't break the behavi... | {
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"Okey for me"
] | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | # What does this PR do?
Currently when TensorFlow model is run in graph mode, the logs are displayed as many time the method is called even if the confition is not respected. This is because in graph mode the logs are not compiled in the graph and then are displayed all the time. To fix this, we use now `tf.print` t... | {
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https://api.github.com/repos/huggingface/transformers/issues/9564 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9564/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9564/comments | https://api.github.com/repos/huggingface/transformers/issues/9564/events | https://github.com/huggingface/transformers/pull/9564 | 785,031,408 | MDExOlB1bGxSZXF1ZXN0NTU0MTI0MDQ0 | 9,564 | Remove unused token_type_ids in MPNet | {
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"I'm totally fine to definitely suppress this argument in once if this is prefered (I would prefer as well)",
"Not an expert neither. Maybe @LysandreJik knows better.",
"> Thanks for adapting @jplu!\r\n> \r\n> Not an expert on the tokenization part, but is the method `build_inputs_with_special_tokens` still nec... | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | # What does this PR do?
This PR adds a warning when the argument `token_type_ids` is given a show a message saying that this argument is never used. I just supressed the internal appearance of this argument without modifying the method signatures in order to do not integrates a breaking change.
Should I update th... | {
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https://api.github.com/repos/huggingface/transformers/issues/9563 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9563/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9563/comments | https://api.github.com/repos/huggingface/transformers/issues/9563/events | https://github.com/huggingface/transformers/issues/9563 | 785,030,315 | MDU6SXNzdWU3ODUwMzAzMTU= | 9,563 | finetune_trainer.py script is not using given config file | {
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"Hi @marcoabrate \r\n\r\nthe script uses the provided `config` file, the reason you see `max_length` 56 because the script replaces the generate params (max/min_len etc) in `config` using `task_specific_params` \r\n\r\nhttps://github.com/huggingface/transformers/blob/245cdb469d2a7f47316926fdbac925e0ed149332/example... | 1,610 | 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: 4.1.1 (stable)
- Platform: Google Colab
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101
- Usi... | {
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https://api.github.com/repos/huggingface/transformers/issues/9562 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9562/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9562/comments | https://api.github.com/repos/huggingface/transformers/issues/9562/events | https://github.com/huggingface/transformers/pull/9562 | 785,013,709 | MDExOlB1bGxSZXF1ZXN0NTU0MTA5MDMx | 9,562 | Fix barthez tokenizer | {
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Running the [following code](https://github.com/huggingface/transformers/issues/9422#issuecomment-759327863) works now:
```py
from transformers import AutoTokenizer
barthez_tokenize... | {
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https://api.github.com/repos/huggingface/transformers/issues/9561 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9561/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9561/comments | https://api.github.com/repos/huggingface/transformers/issues/9561/events | https://github.com/huggingface/transformers/pull/9561 | 784,987,458 | MDExOlB1bGxSZXF1ZXN0NTU0MDg3MDE3 | 9,561 | Fix slow tests v4.2.0 | {
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https://api.github.com/repos/huggingface/transformers/issues/9560 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9560/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9560/comments | https://api.github.com/repos/huggingface/transformers/issues/9560/events | https://github.com/huggingface/transformers/issues/9560 | 784,914,527 | MDU6SXNzdWU3ODQ5MTQ1Mjc= | 9,560 | Adding Megatron models. | {
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"Since DeepSpeed both integrates and uses Megatron-LM almost everywhere in its tutorials it most likely should just work. Of course, the devil is in the detail.\r\n\r\nAs I haven't had a chance to study/work with GPT2 yet, I will let others comment on the more important part of your query.",
"Any plans of adding ... | 1,610 | 1,658 | 1,658 | CONTRIBUTOR | null | # 🌟 New model addition
Is it feasible to add Megatron models ? It seems the architecture is really just a GPT2, most of the work should be in creating the config, fusing layers from the available weights here: https://github.com/pytorch/fairseq/tree/master/examples/megatron_11b and making them available.
There ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9559 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9559/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9559/comments | https://api.github.com/repos/huggingface/transformers/issues/9559/events | https://github.com/huggingface/transformers/issues/9559 | 784,910,865 | MDU6SXNzdWU3ODQ5MTA4NjU= | 9,559 | tokenizer decode method | {
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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."
] | 1,610 | 1,614 | 1,614 | NONE | null | <!-- 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: 4.1.1
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.7.9
- PyTorch version (GPU?): 1.7.1+cu101 (True)
- Tensorflow ve... | {
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https://api.github.com/repos/huggingface/transformers/issues/9558 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9558/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9558/comments | https://api.github.com/repos/huggingface/transformers/issues/9558/events | https://github.com/huggingface/transformers/issues/9558 | 784,875,039 | MDU6SXNzdWU3ODQ4NzUwMzk= | 9,558 | SMITH Google | {
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"This is a duplicate. See #9526 ",
"Oh ok, thanks. "
] | 1,610 | 1,610 | 1,610 | NONE | null | # 🌟 New model addition
## Google´s SMITH Algorithm
## https://github.com/google-research/google-research/tree/master/smith
* [x] the model implementation is available: (give details)
* [ ] the model weights are available: (give details)
* [ ] who are the authors: (mention them, if possible by @gh-username... | {
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https://api.github.com/repos/huggingface/transformers/issues/9557 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9557/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9557/comments | https://api.github.com/repos/huggingface/transformers/issues/9557/events | https://github.com/huggingface/transformers/pull/9557 | 784,860,429 | MDExOlB1bGxSZXF1ZXN0NTUzOTgxODAz | 9,557 | Speed up TopKLogitsWarper and TopPLogitsWarper (pytorch) | {
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"This looks great @LSinev! ",
"Ok, looks good to merge. I checked that your implementation works with Pytorch 1.4 as well"
] | 1,610 | 1,619 | 1,610 | CONTRIBUTOR | null | # What does this PR do?
Speeds up TopKLogitsWarper and TopPLogitsWarper using torch filling functions.
Here's a minimal example to reproduce the slow behavior (and test speed of improvements):
```
import torch
from transformers import TopPLogitsWarper, TopKLogitsWarper, LogitsWarper
import timeit
class Top... | {
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https://api.github.com/repos/huggingface/transformers/issues/9556 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9556/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9556/comments | https://api.github.com/repos/huggingface/transformers/issues/9556/events | https://github.com/huggingface/transformers/issues/9556 | 784,741,946 | MDU6SXNzdWU3ODQ3NDE5NDY= | 9,556 | Where is convert_bert_original_tf_checkpoint_to_pytorch.py? | {
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"Its current location is [here](https://github.com/huggingface/transformers/blob/master/src/transformers/models/bert/convert_bert_original_tf_checkpoint_to_pytorch.py).",
"Hi @sednaasil, what are you trying to do? Could you show the code that you're using so that we may help you debug it? Thanks.",
"Hi! \r\n\r... | 1,610 | 1,614 | 1,614 | NONE | null | HI:
I am getting the following error when implementing entity extraction in BERT. OSError: Error no file named ['pytorch_model.bin', 'tf_model.h5', 'model.ckpt.index']
I am very new to using BERT, and noted that [issue 2110](https://github.com/huggingface/transformers/issues/2110) had a similar issue. Issue 2... | {
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https://api.github.com/repos/huggingface/transformers/issues/9555 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9555/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9555/comments | https://api.github.com/repos/huggingface/transformers/issues/9555/events | https://github.com/huggingface/transformers/issues/9555 | 784,741,233 | MDU6SXNzdWU3ODQ3NDEyMzM= | 9,555 | DPRReaderTokenizer does not generate the attention_mask properly | {
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"Indeed, it doesn't! We would gladly welcome a PR!",
"Closed by #9663 :)"
] | 1,610 | 1,611 | 1,611 | CONTRIBUTOR | null | Hello,
It seems like the DPRReaderTokenizer does not generate the `attention_mask` properly.
Steps to reproduce on the master branch
```bash
(venv) sergey_mkrtchyan test (master) $ python
Python 3.8.6 (v3.8.6:db455296be, Sep 23 2020, 13:31:39)
[Clang 6.0 (clang-600.0.57)] on darwin
Type "help", "copyright... | {
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https://api.github.com/repos/huggingface/transformers/issues/9554 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9554/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9554/comments | https://api.github.com/repos/huggingface/transformers/issues/9554/events | https://github.com/huggingface/transformers/pull/9554 | 784,710,487 | MDExOlB1bGxSZXF1ZXN0NTUzODU4MTEw | 9,554 | Fix classification script: enable dynamic padding with truncation | {
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To fix the issue (below) in the run_glue.pl script, tokenizer's `max_length` value is now assigned directly with `max_seq_length` argument. Now it is possible to truncate the sequence and use dynamic padding. By default `max_length` is 128, which means truncation to 128 tokens. To disable tru... | {
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https://api.github.com/repos/huggingface/transformers/issues/9553 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9553/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9553/comments | https://api.github.com/repos/huggingface/transformers/issues/9553/events | https://github.com/huggingface/transformers/pull/9553 | 784,690,416 | MDExOlB1bGxSZXF1ZXN0NTUzODQxODQw | 9,553 | [setup.py] note on how to get to transformers exact dependencies from shell | {
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e.g if you want to install deps for a group of packages we control and with their correct versions, you just need to run:
```
pip install -U $(python -c 'import sys; from transformers.depend... | {
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https://api.github.com/repos/huggingface/transformers/issues/9552 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9552/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9552/comments | https://api.github.com/repos/huggingface/transformers/issues/9552/events | https://github.com/huggingface/transformers/pull/9552 | 784,685,711 | MDExOlB1bGxSZXF1ZXN0NTUzODM3ODcw | 9,552 | [CI] use correct deps for torchhub | {
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"Is there a way to leverage this to also update the dependencies in [`hubconf.py`](https://github.com/huggingface/transformers/blob/master/hubconf.py)?",
"From what I understand, you need to install the dependencies by hand before, so what would it add to have this in hubconf? From what I gathered this list of \"... | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | As a follow up to https://github.com/huggingface/transformers/pull/9550, here is a clean solution that requires only one source (`setup.py`) to edit for dependencies and groups of thereof.
The PR
1. defines a new dependency group for `torchhub` in `setup.py`
2. installs the exact dependencies of that group insid... | {
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https://api.github.com/repos/huggingface/transformers/issues/9551 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9551/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9551/comments | https://api.github.com/repos/huggingface/transformers/issues/9551/events | https://github.com/huggingface/transformers/issues/9551 | 784,679,542 | MDU6SXNzdWU3ODQ2Nzk1NDI= | 9,551 | Dynamic padding + truncation in classification script | {
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"Yes, the `max_length` should be passed the same way. Would like to open a PR to fix `run_glue.py`?",
"Okay, I will do that."
] | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | 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
<!-- Please outline the motivation for the proposal. Is your feature request
related to a problem? e.g., I'm always frustrated when [.... | {
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https://api.github.com/repos/huggingface/transformers/issues/9550 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9550/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9550/comments | https://api.github.com/repos/huggingface/transformers/issues/9550/events | https://github.com/huggingface/transformers/pull/9550 | 784,662,863 | MDExOlB1bGxSZXF1ZXN0NTUzODE4OTY1 | 9,550 | Use the right version of tokenizers | {
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"Test passes, so merging to get the CI green."
] | 1,610 | 1,610 | 1,610 | COLLABORATOR | null | # What does this PR do?
Pulls the version of tokenziers from our deps in the `hubconf.py` otherwise it might install a version of tokenizers that is more recent (if available on pypi). When that is the case, the check of our packages fails at import. | {
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https://api.github.com/repos/huggingface/transformers/issues/9549 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9549/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9549/comments | https://api.github.com/repos/huggingface/transformers/issues/9549/events | https://github.com/huggingface/transformers/pull/9549 | 784,661,339 | MDExOlB1bGxSZXF1ZXN0NTUzODE3NjU5 | 9,549 | Use the right version of tokenizers for torchhub | {
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"Branched from my last PR and not master..."
] | 1,610 | 1,610 | 1,610 | COLLABORATOR | null | # What does this PR do?
The hubconf.py is using `tokenizers` without checking the version transformers needs, which yields to an import error if a more recent version of tokenziers is available on pypi (like right now). | {
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https://api.github.com/repos/huggingface/transformers/issues/9548 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9548/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9548/comments | https://api.github.com/repos/huggingface/transformers/issues/9548/events | https://github.com/huggingface/transformers/issues/9548 | 784,598,332 | MDU6SXNzdWU3ODQ1OTgzMzI= | 9,548 | Quick tour runs into OOM on Colab | {
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"If you don't have any memory left, you should use a lower batch size. In the line:\r\n``` \r\n>>> tfdataset = tf.data.Dataset.from_tensor_slices((features, dataset[\"labels\"])).batch(32)\r\n```\r\nreplace 32 by something lower.\r\n\r\nAlso, please use the [forums](https://discuss.huggingface.co/) for this kind of... | 1,610 | 1,610 | 1,610 | NONE | null | ## Environment info
Google Colab
### Who can help
@jplu @LysandreJik @sgugger
## Information
Followed the quick tour using a Colab notebook https://huggingface.co/docs/datasets/quicktour.html#fine-tuning-a-deep-learning-model
Colab Runtime type: GPU
But the training process runs into OOM
```
----------... | {
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https://api.github.com/repos/huggingface/transformers/issues/9547 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9547/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9547/comments | https://api.github.com/repos/huggingface/transformers/issues/9547/events | https://github.com/huggingface/transformers/issues/9547 | 784,589,757 | MDU6SXNzdWU3ODQ1ODk3NTc= | 9,547 | Fine-tuning LMwithNSP | {
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"Hi, could you please provide everything asked in the issue template? Information relative to your environment as well as the code that triggered the error. Thanks.",
"environment transformers 4.0.0 and my code below and message error you can get it after code\r\n\r\n```py\r\nfrom __future__ import absolute_impo... | 1,610 | 1,614 | 1,614 | NONE | null | when i fine tuning bert using BertForPreTraining i got error here --> outputs = model(input_ids=input_ids, attention_mask=input_mask, token_type_ids=segment_ids,
labels=lm_label_ids, next_sentence_label=is_next)
and in this line also loss.backward()
i got this error RuntimeError: CUDA err... | {
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https://api.github.com/repos/huggingface/transformers/issues/9546 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9546/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9546/comments | https://api.github.com/repos/huggingface/transformers/issues/9546/events | https://github.com/huggingface/transformers/issues/9546 | 784,587,186 | MDU6SXNzdWU3ODQ1ODcxODY= | 9,546 | Entity level F-1 scores in run_ner.py | {
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"Oh this makes me realize this script hasn't been switched to use the datasets metrics for seqeval. This would solve the issue as it computes all scores. Will do that tomorrow.",
"Thank you @sgugger"
] | 1,610 | 1,610 | 1,610 | NONE | null | # 🚀 Feature request
The run_ner.py script in examples/token_classification reports evaluation metrics in terms of token F-1 scores (from what I can tell by examining the code). This issue is to request entity level F-1 scores as an evaluation metric. Token level scores will evaluate the F-1 score over an input such... | {
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https://api.github.com/repos/huggingface/transformers/issues/9545 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9545/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9545/comments | https://api.github.com/repos/huggingface/transformers/issues/9545/events | https://github.com/huggingface/transformers/pull/9545 | 784,585,169 | MDExOlB1bGxSZXF1ZXN0NTUzNzU0NDUx | 9,545 | Doc: Update pretrained_models wording | {
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https://api.github.com/repos/huggingface/transformers/issues/9544 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9544/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9544/comments | https://api.github.com/repos/huggingface/transformers/issues/9544/events | https://github.com/huggingface/transformers/issues/9544 | 784,582,811 | MDU6SXNzdWU3ODQ1ODI4MTE= | 9,544 | RFC: ternary assignment style in transformers code revisited | {
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"here is @patrickvonplaten's follow up posted with his permission (we initially did it over gist):\r\n\r\n------------------\r\n\r\n\r\nThanks for the write-up!\r\nI guess everybody has a slightly different opinion regarding ternary assignmens . My opinion is:\r\n\r\n1) I would never write a if-elif-else statement ... | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | I run this by @patrickvonplaten and he encouraged I post it here, and he wrote a follow up which I will post next.
---------------------------
As `transformers`'s mandate is to be super user-friendly code-wise I wanted to ask whether very frequently used in the `transformers` code ternary assignment `a = x if z e... | {
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https://api.github.com/repos/huggingface/transformers/issues/9543 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9543/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9543/comments | https://api.github.com/repos/huggingface/transformers/issues/9543/events | https://github.com/huggingface/transformers/issues/9543 | 784,425,573 | MDU6SXNzdWU3ODQ0MjU1NzM= | 9,543 | Generating sequence from two input sequences | {
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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? You'll get more answers there.\r\n\r\nThanks!"
] | 1,610 | 1,610 | 1,610 | NONE | null | The code here
https://github.com/huggingface/transformers/blob/master/examples/seq2seq/finetune_trainer.py
enables training `distilbart-xsum-12-6` model that gets an input sequence and outputs an input sequence. Is there a simple way to adapt the code to enable it to get two input sequences (e.g sentence and cont... | {
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https://api.github.com/repos/huggingface/transformers/issues/9542 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9542/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9542/comments | https://api.github.com/repos/huggingface/transformers/issues/9542/events | https://github.com/huggingface/transformers/issues/9542 | 784,358,243 | MDU6SXNzdWU3ODQzNTgyNDM= | 9,542 | Is the GPT-2 forward too different from Bert or RoBerta? | {
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"the `IndexError` is from the padding token being added. GPT2 doesn't have a padding token. You should be able to manually set that input_id to 0 (or any other valid input id) and then rely on the attention mask to ignore those positions. ",
"> the `IndexError` is from the padding token being added. GPT2 doesn't ... | 1,610 | 1,614 | 1,614 | NONE | null | I am using some Transformers (Bert, RoBerta, etc.) in my project.
When including the `GPT-2` as shown below:
```python
from transformers import GPT2Tokenizer, GPT2Model
import torch
# inits model and tokenizer
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
tokenizer.add_special_tokens({'pad_token': '[PAD]... | {
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https://api.github.com/repos/huggingface/transformers/issues/9541 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9541/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9541/comments | https://api.github.com/repos/huggingface/transformers/issues/9541/events | https://github.com/huggingface/transformers/pull/9541 | 784,357,016 | MDExOlB1bGxSZXF1ZXN0NTUzNTYxODcx | 9,541 | Fix fill mask pipeline slow test using deprecated argument | {
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https://api.github.com/repos/huggingface/transformers/issues/9540 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9540/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9540/comments | https://api.github.com/repos/huggingface/transformers/issues/9540/events | https://github.com/huggingface/transformers/issues/9540 | 784,323,657 | MDU6SXNzdWU3ODQzMjM2NTc= | 9,540 | bounding by compute, retraining from the time the model is killed | {
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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."
] | 1,610 | 1,614 | 1,614 | NONE | null | Hi
I have limited access to GPUs, with limited hours, I am using finetune_trainer.py is there a way I can retrain the models from the time it is killed? could you assist me and give me some hints?
thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/9539 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9539/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9539/comments | https://api.github.com/repos/huggingface/transformers/issues/9539/events | https://github.com/huggingface/transformers/pull/9539 | 784,299,047 | MDExOlB1bGxSZXF1ZXN0NTUzNTEyNzUy | 9,539 | LayoutLM Config | {
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This was failing the `test_parents_and_children_in_mappings` test as it was placed after the `BertConfig` in the `AutoModelForSequenceClassification` test. | {
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https://api.github.com/repos/huggingface/transformers/issues/9538 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9538/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9538/comments | https://api.github.com/repos/huggingface/transformers/issues/9538/events | https://github.com/huggingface/transformers/pull/9538 | 784,288,024 | MDExOlB1bGxSZXF1ZXN0NTUzNTAzNDA4 | 9,538 | fix BlenderbotSmallTokenizer | {
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`BlenderbotSmallTokenizer` returns `token_type_ids` but those are not needed by the model. This PR fixes the tokniezer to not return `token_type_ids` | {
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https://api.github.com/repos/huggingface/transformers/issues/9537 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9537/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9537/comments | https://api.github.com/repos/huggingface/transformers/issues/9537/events | https://github.com/huggingface/transformers/issues/9537 | 784,243,952 | MDU6SXNzdWU3ODQyNDM5NTI= | 9,537 | BertForTokenClassificiation save | {
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"You can save a model using the `.save_pretrained()` method. So given that your model is called `model`, you can save it as follows:\r\n\r\n`model.save_pretrained(path_to_directory) `",
"Thank you for your reply. I already tried it. But got an error like this.\r\n\r\n```\r\n'BertForTokenClassification' object ha... | 1,610 | 1,610 | 1,610 | NONE | null | How can I save the BertForTokenClassificiation model?
| {
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https://api.github.com/repos/huggingface/transformers/issues/9536 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9536/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9536/comments | https://api.github.com/repos/huggingface/transformers/issues/9536/events | https://github.com/huggingface/transformers/pull/9536 | 784,242,526 | MDExOlB1bGxSZXF1ZXN0NTUzNDY0NjU4 | 9,536 | [WIP][EncoderDecoder] Fix label behavior | {
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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."
] | 1,610 | 1,615 | 1,614 | MEMBER | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/9535 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9535/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9535/comments | https://api.github.com/repos/huggingface/transformers/issues/9535/events | https://github.com/huggingface/transformers/issues/9535 | 784,237,274 | MDU6SXNzdWU3ODQyMzcyNzQ= | 9,535 | strange output of fast/slow tokenizers | {
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"@chiapas , We will review this issue and propose code changes soon.",
"@chiapas , I executed the same code in GoogleColab. I am getting the same tokens for both of them. Here is the output.\r\n\r\n\r\n`{'input_ids': [[0, 2203, 23708, 441, 9, 7, 653, 39, 19437, 7, 7, 7, 347, 4526, 34837, 38, 981, 58, 238, 10060, ... | 1,610 | 1,610 | 1,610 | COLLABORATOR | 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: 4.1.1
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.6.6
- PyTorch version (GPU?): 1.5.0+cpu (Fal... | {
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https://api.github.com/repos/huggingface/transformers/issues/9534 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9534/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9534/comments | https://api.github.com/repos/huggingface/transformers/issues/9534/events | https://github.com/huggingface/transformers/issues/9534 | 784,141,444 | MDU6SXNzdWU3ODQxNDE0NDQ= | 9,534 | Need clarification in /examples/research_projects/rag/use_own_knowledge_dataset.py | {
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"Indeed, the models have no model card. Maybe @lhoestq can help you out! ",
"Hi !\r\n- 'facebook/dpr-ctx_encoder-single-nq-base' is the DPR context encoder model trained on NQ alone\r\n- 'facebook/dpr-ctx_encoder-multiset-base' is the DPR context encoder model trained on the multiset/hybrid dataset defined in the... | 1,610 | 1,610 | 1,610 | CONTRIBUTOR | null | Please explain the difference between:
'facebook/dpr-ctx_encoder-single-nq-base' and 'facebook/dpr-ctx_encoder-multiset-base'
Which datasets are the 2 models trained on? | {
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https://api.github.com/repos/huggingface/transformers/issues/9533 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9533/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9533/comments | https://api.github.com/repos/huggingface/transformers/issues/9533/events | https://github.com/huggingface/transformers/issues/9533 | 784,124,443 | MDU6SXNzdWU3ODQxMjQ0NDM= | 9,533 | xla_spawn.py crashes when training on TPU V3-32 | {
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"Hmmm this may be because a TPU v3-32 regroups several TPU chips, as the error here seems to imply:\r\n```\r\nInternal: Invalid system configuration: 2x2 host topology with 0 missing hosts, but 1 hosts in total.\r\n```\r\n\r\n@sgugger can you confirm this is the source of the issue? Do you know the status of the Tr... | 1,610 | 1,673 | 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: 4.0.1
- Platform: Google Cloud debian-9-torch-xla-v20201215
- Python version: 3.7
- PyTorch version (GPU?): ... | {
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https://api.github.com/repos/huggingface/transformers/issues/9532 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9532/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9532/comments | https://api.github.com/repos/huggingface/transformers/issues/9532/events | https://github.com/huggingface/transformers/pull/9532 | 784,113,267 | MDExOlB1bGxSZXF1ZXN0NTUzMzU2MzYz | 9,532 | [Blenderbot] Fix Links | {
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"Ok now's really the time to remove those hard-coded links once and for all, i think",
"Indeed! It's on my todo for the week."
] | 1,610 | 1,610 | 1,610 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/9531 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/9531/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/9531/comments | https://api.github.com/repos/huggingface/transformers/issues/9531/events | https://github.com/huggingface/transformers/issues/9531 | 784,106,141 | MDU6SXNzdWU3ODQxMDYxNDE= | 9,531 | Seq2Seq include custom glossary/dictionary | {
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"Hi @codingnoobneedshelp \r\n\r\nNot sure what exactly this means,\r\n\r\nWhat do you mean by\r\n\r\n> custom glossary/dictionary\r\n\r\nand \r\n> ensure that specific words are always translated as they are in the glossary/dictionary.",
"Thanks for the answer. Let me try to clarify this. \r\nFrom Google: A glos... | 1,610 | 1,614 | 1,614 | NONE | null | Hello,
Is it possible to include a custom glossary/dictionary while fine-tuning the Seq2Seq model for a specific domain?
So I basically want to ensure that specific words are always translated as they are in the glossary/dictionary.
Thanks for helping out.
coodingnoobneedshelp | {
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