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https://api.github.com/repos/huggingface/transformers/issues/11844 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11844/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11844/comments | https://api.github.com/repos/huggingface/transformers/issues/11844/events | https://github.com/huggingface/transformers/pull/11844 | 899,616,309 | MDExOlB1bGxSZXF1ZXN0NjUxMjkzNTg4 | 11,844 | Fix flos single node | {
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"Not sure why the CI is failing, is it related to the PR? Doesn't look so to me but I may be missing something",
"No, the CI is failing all the time those days, don't worry about it."
] | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | This PR fixes a bug typo where in single-node settings, flos in the Trainer would stay constant, and also updates the flo count in the trainer state at every log occasion (instead of every model-saving occasion) so that users that wish to use a flo-logging callback can access it more frequently. I feel like the first b... | {
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https://api.github.com/repos/huggingface/transformers/issues/11843 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11843/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11843/comments | https://api.github.com/repos/huggingface/transformers/issues/11843/events | https://github.com/huggingface/transformers/issues/11843 | 899,585,015 | MDU6SXNzdWU4OTk1ODUwMTU= | 11,843 | Issues loading finetuned BERT | {
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"It's advised to save models using the [`.save_pretrained()` method](https://huggingface.co/transformers/main_classes/model.html#transformers.PreTrainedModel.save_pretrained). You can then read it back in using the `.from_pretrained()` method. \r\n\r\nNote that you should specify the name of a directory, not the na... | 1,621 | 1,621 | 1,621 | NONE | null | Hello, I’m having issues loading a finetuned BERT model for binary classification. I have this class for the BERT model:
```
class BertClassifier(nn.Module):
def __init__(self, freeze_bert=False):
super(BertClassifier, self).__init__()
self.bert = BertModel.from_pretrained('bert-base-multilingual-uncased')
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11842 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11842/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11842/comments | https://api.github.com/repos/huggingface/transformers/issues/11842/events | https://github.com/huggingface/transformers/pull/11842 | 899,530,303 | MDExOlB1bGxSZXF1ZXN0NjUxMjE5NTg4 | 11,842 | Fix bug in Masked Language Modeling example scripts (#11840)) | {
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"The `line_by_line=False` argument is not supposed to be used for BERT-like pretraining objectives, it it there to do GPT-like pretraining. Maybe it does not make sense to have it in `run_mlm` at all.\r\nIn any case this fix will not necessarily work for all models supported by the script, as the special tokens may... | 1,621 | 1,625 | 1,625 | CONTRIBUTOR | null | # What does this PR do?
when `data_args.line_by_line == False`, the script firstly converts given examples into input_ids, token_type_ids, attention_mask and special_tokens_mask including cls_token, sep_token. Then it concatenates all tokenized outputs and generate chunks of max_seq_length. However, it will generate u... | {
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https://api.github.com/repos/huggingface/transformers/issues/11841 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11841/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11841/comments | https://api.github.com/repos/huggingface/transformers/issues/11841/events | https://github.com/huggingface/transformers/issues/11841 | 899,522,561 | MDU6SXNzdWU4OTk1MjI1NjE= | 11,841 | Generate Function call throughs error when "inputs_embeds" argument passed | {
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"Hey @abhikasd6523,\r\n\r\nI don't think that `generate()` currently supports `inputs_embeds` correctly. It would require quite some changes in `generate()` to make it work I'm afraid. Can you give me some more background on your use-case for passing `inputs_embeds` instead of `input_ids`. If it's a general enough ... | 1,621 | 1,626 | 1,626 | NONE | null | When using `inputs_embeds` as the argument instead of 'input_ids' while trying to generate text with GPT2 model, an error pops up about `input_ids`.
```
from transformers import GPT2Tokenizer, GPT2LMHeadModel, GPT2Config
import transformers
import torch
import torch.nn as nn
model = GPT2LMHeadModel.from_pr... | {
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https://api.github.com/repos/huggingface/transformers/issues/11840 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11840/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11840/comments | https://api.github.com/repos/huggingface/transformers/issues/11840/events | https://github.com/huggingface/transformers/issues/11840 | 899,495,487 | MDU6SXNzdWU4OTk0OTU0ODc= | 11,840 | Bug in MLM example scripts | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,625 | 1,625 | CONTRIBUTOR | null | when `data_args.line_by_line == False`, the script firstly converts given examples into input_ids, token_type_ids, attention_mask and special_tokens_mask **including cls_token, sep_token**. Then it concatenates all tokenized outputs and generate chunks of max_seq_length. However, it will generate unintended training e... | {
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https://api.github.com/repos/huggingface/transformers/issues/11839 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11839/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11839/comments | https://api.github.com/repos/huggingface/transformers/issues/11839/events | https://github.com/huggingface/transformers/pull/11839 | 899,489,700 | MDExOlB1bGxSZXF1ZXN0NjUxMTg0NTM4 | 11,839 | [Flax] Fix PyTorch import error | {
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11838 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11838/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11838/comments | https://api.github.com/repos/huggingface/transformers/issues/11838/events | https://github.com/huggingface/transformers/issues/11838 | 899,458,036 | MDU6SXNzdWU4OTk0NTgwMzY= | 11,838 | Is 10% in annotation different from 0.5 in code？ | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,625 | 1,625 | NONE | null | ERROR: type should be string, got "https://github.com/huggingface/transformers/blob/0cbddfb190ab9b05b6575fbf818aae17bad4d24a/src/transformers/data/data_collator.py#L387\r\n\r\n```python\r\n # 10% of the time, we replace masked input tokens with random word\r\n indices_random = torch.bernoulli(torch.full(labels.shape, 0.5)).bool() & masked_indices & ~indices_replaced\r\n random_words = torch.randint(len(self.tokenizer), labels.shape, dtype=torch.long)\r\n inputs[indices_random] = random_words[indices_random]\r\n```\r\n\r\n" | {
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https://api.github.com/repos/huggingface/transformers/issues/11837 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11837/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11837/comments | https://api.github.com/repos/huggingface/transformers/issues/11837/events | https://github.com/huggingface/transformers/issues/11837 | 899,317,558 | MDU6SXNzdWU4OTkzMTc1NTg= | 11,837 | Module torch has no attribute minimum for modeling_big_bird.py | {
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"`torch.minimum` was only added in August 2020 to PyTorch, so `torch.minimum` is probably only part of torch 1.7+. To work for previous versions, it should indeed be replaced by `torch.min`.\r\n\r\nThe README of this repository states that: \"This repository is tested on Python 3.6+, Flax 0.3.2+, PyTorch 1.3.1+ and... | 1,621 | 1,626 | 1,626 | NONE | null | Hello
I came across `module 'torch' has no attribute minimum` from the following two lines
1.https://github.com/huggingface/transformers/blob/73fde1defe9be259a47b9024525882f3ec420994/src/transformers/models/big_bird/modeling_big_bird.py#L662
2.https://github.com/huggingface/transformers/blob/73fde1defe9be259a... | {
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https://api.github.com/repos/huggingface/transformers/issues/11836 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11836/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11836/comments | https://api.github.com/repos/huggingface/transformers/issues/11836/events | https://github.com/huggingface/transformers/issues/11836 | 899,314,132 | MDU6SXNzdWU4OTkzMTQxMzI= | 11,836 | Not able to fine tune language model | {
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"Hey @ghoshmithun, \r\nWhen you are using the `examples/` / \"use sagemaker\" with custom data on s3 `huggingface_estimator.fit({'train':'s3://train-data-gpt/'})`. \r\nYou need to provide the hyperparameter `train_file` with the path to your file from s3. In your case, this would be `/opt/ml/input/data/train/my_tra... | 1,621 | 1,625 | 1,625 | NONE | null | I am trying to fine tune a language model using sagemaker huggingface API
I am using the code
```
import sagemaker
from sagemaker.huggingface import HuggingFace
# gets role for executing training job
role = sagemaker.get_execution_role()
hyperparameters = {
'model_name_or_path':'EleutherAI/gpt-neo-1... | {
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https://api.github.com/repos/huggingface/transformers/issues/11835 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11835/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11835/comments | https://api.github.com/repos/huggingface/transformers/issues/11835/events | https://github.com/huggingface/transformers/pull/11835 | 899,290,972 | MDExOlB1bGxSZXF1ZXN0NjUxMDA4NDc0 | 11,835 | Tiny fix in README.md of run_flax_mlm | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,625 | 1,625 | CONTRIBUTOR | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/11834 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11834/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11834/comments | https://api.github.com/repos/huggingface/transformers/issues/11834/events | https://github.com/huggingface/transformers/issues/11834 | 899,186,063 | MDU6SXNzdWU4OTkxODYwNjM= | 11,834 | convert_pytorch_checkpoint_to_tf2.py AttributeError: embeddings.word_embeddings.weight not found in PyTorch model | {
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"Are you trying to convert it a HuggingFace TensorFlow object? If so can you do the following?\r\n\r\n```\r\nfrom transformers import TFBertForPreTraining\r\n\r\nmodel = TFBertForPreTraining.from_pretrained(path_to_checkpoint, from_pt=True)\r\n```\r\n\r\nHow did you fine-tune your model? How did you save it? Did yo... | 1,621 | 1,626 | 1,626 | NONE | null | I am trying to convert a finetuned bert model to tensorflow. The model was finetuned using pytorch-pretrained-bert on bert-base-multilingual-cased. But I am getting the following error while trying to convert using the tuned checkpoint.
code:
```
from transformers import convert_pytorch_checkpoint_to_tf2
convert_... | {
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https://api.github.com/repos/huggingface/transformers/issues/11833 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11833/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11833/comments | https://api.github.com/repos/huggingface/transformers/issues/11833/events | https://github.com/huggingface/transformers/issues/11833 | 899,127,189 | MDU6SXNzdWU4OTkxMjcxODk= | 11,833 | [BUG] Trainer predict bug under DDP model. | {
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"Without seeing the whole stack trace, your version of Transformers used (please follow the issue template!) or the code you are using to build your dataset, there is little we can do to help.",
"> Without seeing the whole stack trace, your version of Transformers used (please follow the issue template!) or the ... | 1,621 | 1,625 | 1,625 | NONE | null | ### Background
The model is trained with DDP.
The error denotes that the batch is smaller than the model required.
However, the test file cannot use `droplast`.
How I can predict the test file with DDP or remove DDP?
### Code
```
training_args = TrainingArguments(
output_dir='./results', # out... | {
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https://api.github.com/repos/huggingface/transformers/issues/11832 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11832/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11832/comments | https://api.github.com/repos/huggingface/transformers/issues/11832/events | https://github.com/huggingface/transformers/issues/11832 | 899,047,240 | MDU6SXNzdWU4OTkwNDcyNDA= | 11,832 | Seq2seq-based model running slowly on TPU | {
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"I'm not sure if we ever tested whether those seq2seq models run correctly on TPU (@patil-suraj). It might be the case that a lot of the computations are dynamic and therefore are constantly re-compiled.",
"I realize that I haven't passed --pad_to_max_length to the script, which leads to our model running slowly.... | 1,621 | 1,622 | 1,621 | 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: v4.5.1 and newest version
- Platform: Colab
- Python version: 3.8
- PyTorch version (GPU?): 1.8.1
- TPU v2-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11831 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11831/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11831/comments | https://api.github.com/repos/huggingface/transformers/issues/11831/events | https://github.com/huggingface/transformers/issues/11831 | 898,941,236 | MDU6SXNzdWU4OTg5NDEyMzY= | 11,831 | [docs] XLnet reference link bug in description of past_index Parameter of TrainingArguments | {
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"Thanks for flagging! Should be fixed by the PR linked above!"
] | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | XLnet reference link bug in description of past_index Parameter of TrainingArguments
link to the doc: https://huggingface.co/transformers/main_classes/trainer.html#transformers.TrainingArguments
**current description:** Some models like TransformerXL or **:doc`XLNet <../model_doc/xlnet>`** can make use of the past... | {
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https://api.github.com/repos/huggingface/transformers/issues/11830 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11830/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11830/comments | https://api.github.com/repos/huggingface/transformers/issues/11830/events | https://github.com/huggingface/transformers/issues/11830 | 898,935,181 | MDU6SXNzdWU4OTg5MzUxODE= | 11,830 | Delete key or set to `None` in __getstate__ impl. | {
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"Hmmm - thinking about it - the value is also set to None by default in the constructor. I will close this..."
] | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | Hi,
there are some places that implement `__getstate__` because an object has a reference to an other object that is not pickable.
`__getstate__` then "deletes" the reference by setting it to `None`. Just a few examples:
https://github.com/huggingface/transformers/blob/73fde1defe9be259a47b9024525882f3ec420994/sr... | {
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https://api.github.com/repos/huggingface/transformers/issues/11829 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11829/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11829/comments | https://api.github.com/repos/huggingface/transformers/issues/11829/events | https://github.com/huggingface/transformers/issues/11829 | 898,918,722 | MDU6SXNzdWU4OTg5MTg3MjI= | 11,829 | [AutomaticSpeechRecognitionPipeline] CUDA support | {
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"Sure, feel free to open a PR! Thanks @francescorubbo "
] | 1,621 | 1,622 | 1,622 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.6.0
- Platform: Linux-4.15.0-106-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (True)
- Tensorflow version (GPU?): 2.3.1 (True)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?:... | {
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https://api.github.com/repos/huggingface/transformers/issues/11828 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11828/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11828/comments | https://api.github.com/repos/huggingface/transformers/issues/11828/events | https://github.com/huggingface/transformers/issues/11828 | 898,869,591 | MDU6SXNzdWU4OTg4Njk1OTE= | 11,828 | possible bug in `TokenizerFast` when setting `return_offset_mapping=True` | {
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"Indeed, the model does not accept the `offset_mapping`, and does not need them for anything; so when using the standard BERT model, make sure you don't feed this value to the model.\r\n\r\nIf you're making a custom BERT model that accepts offset mappings, then you should also update the signature to handle them!",... | 1,621 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1, 4.6.1
- `tokenizers` version 0.10.2
- Platform: Linux/Ubuntu 18.04
- Python version: 3.9.1
- PyTorch... | {
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https://api.github.com/repos/huggingface/transformers/issues/11827 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11827/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11827/comments | https://api.github.com/repos/huggingface/transformers/issues/11827/events | https://github.com/huggingface/transformers/issues/11827 | 898,843,738 | MDU6SXNzdWU4OTg4NDM3Mzg= | 11,827 | My modified `run_glue.py` works well with v4.1.1 but not good with v4.6.0 | {
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"You should upgrade to 4.6.1, I think this is related to a bug fixed by #11785. Let us know if this doesn't solve your problem!",
"@sgugger \r\nThank you for telling me the information!\r\nI upgraded to 4.6.1 and tried running the script again, and now got the expected (or even better) result! \r\n(I expected to ... | 1,621 | 1,621 | 1,621 | 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! -->
`The environment in which the script doesn't work well`
- `transformers` version: 4.6.0
- Platform: Linux-5.4.0-72-generic-x86_64-wit... | {
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https://api.github.com/repos/huggingface/transformers/issues/11826 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11826/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11826/comments | https://api.github.com/repos/huggingface/transformers/issues/11826/events | https://github.com/huggingface/transformers/pull/11826 | 898,753,876 | MDExOlB1bGxSZXF1ZXN0NjUwNTkwOTM4 | 11,826 | feat: add contributor over time graph to README | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,625 | 1,625 | NONE | null | Hi, community!
To better present how our community grows, we develop a tool to show contributors growing history on [https://github.com/api7/contributor-graph](https://github.com/api7/contributor-graph). Since we found it helpful, we think maybe if it could help some other community.
## WHAT IT IS
Basically, i... | {
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https://api.github.com/repos/huggingface/transformers/issues/11825 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11825/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11825/comments | https://api.github.com/repos/huggingface/transformers/issues/11825/events | https://github.com/huggingface/transformers/pull/11825 | 898,606,327 | MDExOlB1bGxSZXF1ZXN0NjUwNDY1NTE5 | 11,825 | Faster list concat for trainer_pt_utils.get_length_grouped_indices() | {
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"No problem, thank you for all your wonderful work!"
] | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | # What does this PR do?
substitutes faster list concatenation for get_length_grouped_indices() in LengthGroupedSampler and DistributedLengthGroupedSampler as prior sum(megabatches, []) is prohibitively slow for large number of megabatches (in test case takes hours for ~270k megabatches with 100 items each).
Fixes... | {
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https://api.github.com/repos/huggingface/transformers/issues/11824 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11824/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11824/comments | https://api.github.com/repos/huggingface/transformers/issues/11824/events | https://github.com/huggingface/transformers/pull/11824 | 898,600,709 | MDExOlB1bGxSZXF1ZXN0NjUwNDYwMTgz | 11,824 | Add flax text class colab | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11823 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11823/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11823/comments | https://api.github.com/repos/huggingface/transformers/issues/11823/events | https://github.com/huggingface/transformers/issues/11823 | 898,302,624 | MDU6SXNzdWU4OTgzMDI2MjQ= | 11,823 | Hugging Face model Bio_ClinicalBERT producing 404 error | {
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"Hi @NicoleJaneway ,\r\n\r\nI think this issue is similar to the following one in `ktrain` repo:\r\n\r\nhttps://github.com/amaiya/ktrain/issues/367\r\n\r\n\"Problem\" is, that there's no TensorFlow compatible model found on the hub (more precisely the `tf_model.h5` one). One good \"workaround\" would be if the mode... | 1,621 | 1,621 | 1,621 | NONE | null | I'm building a Named Entity Recognition (NER) model using the Hugging Face implementation of emilyalsentzer/Bio_ClinicalBERT. Up to today, I've had no issues with the model. Today it's not working as expected.
Question 1 - today, trying to train using:
MODEL_NAME = 'emilyalsentzer/Bio_ClinicalBERT'
model = tex... | {
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https://api.github.com/repos/huggingface/transformers/issues/11822 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11822/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11822/comments | https://api.github.com/repos/huggingface/transformers/issues/11822/events | https://github.com/huggingface/transformers/issues/11822 | 898,249,684 | MDU6SXNzdWU4OTgyNDk2ODQ= | 11,822 | Training Transformer XL from scratch | {
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"Hi! I believe you should be using `TransfoXLLMHeadModel` instead, as right now you're using the Transfo XL model without it's LM head.\r\n\r\nThe TransfoXL model is one of our older models which doesn't fit one-to-one with other models, unfortunately. I invite you to take a look at the signature here: https://hugg... | 1,621 | 1,698 | 1,625 | NONE | null | Hello, I am trying to recreate this notebook https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb for transformer XL
I made changes to the tokenizer as follows
```
%%time
from pathlib import Path
from tokenizers import Tokenizer
from tokenizers.models import WordL... | {
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https://api.github.com/repos/huggingface/transformers/issues/11821 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11821/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11821/comments | https://api.github.com/repos/huggingface/transformers/issues/11821/events | https://github.com/huggingface/transformers/pull/11821 | 898,187,907 | MDExOlB1bGxSZXF1ZXN0NjUwMDg5ODA2 | 11,821 | [run_clm.py] restore caching | {
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"No we can't just add the new argument without checking the version, as it's probably not going to work anymore for earlier versions of datasets (that's why it's bad to do breaking changes :-P).\r\nIt seems like it's the way the Datasets library wants to be used, so I would leave the default behavior here and you c... | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | `datasets==0.1.6` introduced in-memory datasets, which unfortunately has no caching which makes it very slow to develop with as the dataset gets reprocessed on every run. Supposedly this should make things faster overall, but at this huge cost to us developers.
It's also inconsistent where some datasets behave in on... | {
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https://api.github.com/repos/huggingface/transformers/issues/11820 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11820/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11820/comments | https://api.github.com/repos/huggingface/transformers/issues/11820/events | https://github.com/huggingface/transformers/pull/11820 | 898,166,775 | MDExOlB1bGxSZXF1ZXN0NjUwMDcwNTgx | 11,820 | [Flax] Small fixes in `run_flax_glue.py` | {
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<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11819 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11819/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11819/comments | https://api.github.com/repos/huggingface/transformers/issues/11819/events | https://github.com/huggingface/transformers/pull/11819 | 898,069,793 | MDExOlB1bGxSZXF1ZXN0NjQ5OTg2NTg1 | 11,819 | Add option to log only once in multinode training | {
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This PR adds the option to only log on one node when doing multinode training. This is controlled by the `is_local_process_zero` method, so I apply the switch there to avoid putting in multiple places.
Fixes #11796 | {
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https://api.github.com/repos/huggingface/transformers/issues/11818 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11818/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11818/comments | https://api.github.com/repos/huggingface/transformers/issues/11818/events | https://github.com/huggingface/transformers/pull/11818 | 898,063,723 | MDExOlB1bGxSZXF1ZXN0NjQ5OTgxNDkx | 11,818 | [Trainer] Report both steps and num samples per second | {
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As seen with @stas00, there is a bug in the current speed metrics reporting: training reports the number of training steps per second while evaluation and predict report the number of samples per second. After discussion we concluded that both are interesting, so this PR updates the Trainer t... | {
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https://api.github.com/repos/huggingface/transformers/issues/11817 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11817/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11817/comments | https://api.github.com/repos/huggingface/transformers/issues/11817/events | https://github.com/huggingface/transformers/issues/11817 | 898,026,822 | MDU6SXNzdWU4OTgwMjY4MjI= | 11,817 | same sentence different padding length result different embedding. | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,624 | 1,624 | NONE | null | I use nn.Softmax(dim=-1) to softmax. I find different outputs.
```
a = [-3.6180e-01, 6.6926e-01, 1.2248e+01, -9.5795e-01]
b = [-3.6180e-01, 6.6926e-01, 1.2248e+01, -9.5795e-01, -9.5795e-01]
```
softmax(a) = [3.3403e-06, 9.366**2**e-06, 9.999**9**e-01, 1.8402e-06]
softmax(b) =[3.3403e-06, 9.366**1**e-06, 9.999... | {
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https://api.github.com/repos/huggingface/transformers/issues/11816 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11816/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11816/comments | https://api.github.com/repos/huggingface/transformers/issues/11816/events | https://github.com/huggingface/transformers/issues/11816 | 898,019,574 | MDU6SXNzdWU4OTgwMTk1NzQ= | 11,816 | ValueError batch-size mismatch when redefining classifier layer on BertForSequenceClassification | {
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I am currently using BertForSequenceClassification for my project, to show some results regarding transfer performance on the GLUE Benchmark.
I wan't to do two things.
1. Add a seperate nn.Linear() head on top of the already fine-tuned BertForSequenceClassification model and train the entire model:
Input ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11815 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11815/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11815/comments | https://api.github.com/repos/huggingface/transformers/issues/11815/events | https://github.com/huggingface/transformers/issues/11815 | 897,971,221 | MDU6SXNzdWU4OTc5NzEyMjE= | 11,815 | How get sentenses embbedings from TFBertForMaskedLM | {
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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!",
"Resolved"
] | 1,621 | 1,622 | 1,622 | NONE | null | Good afternoon!
I am solving a text clustering problem by fine-tuning a trained BERT model. After seeing a number of articles on the subject, I decided to use the masking problem and the TFBertForMaskedLM model for fine-tuning. I was able to fine-tune the network on my set, and now I want to use the embbedings of th... | {
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https://api.github.com/repos/huggingface/transformers/issues/11814 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11814/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11814/comments | https://api.github.com/repos/huggingface/transformers/issues/11814/events | https://github.com/huggingface/transformers/issues/11814 | 897,970,634 | MDU6SXNzdWU4OTc5NzA2MzQ= | 11,814 | Permission error for cardiffnlp/twitter-roberta-base-emotion | {
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"Hey @StephenQuirolgico,\r\n\r\ncould you attach a code snippet that I can copy-paste to reproduce the error? :-)",
"@patrickvonplaten, Not exactly sure what the issue was but it's working now. Thanks!"
] | 1,621 | 1,622 | 1,622 | NONE | null | @patrickvonplaten,
I'm having issues accessing the `cardiffnlp/twitter-roberta-base-emotion` model using:
```
task='emotion'
MODEL = f"cardiffnlp/twitter-roberta-base-{task}"
tokenizer = AutoTokenizer.from_pretrained(MODEL)
```
When I substitute another task, such as `task='sentiment'`, it works fine. I have ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11813 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11813/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11813/comments | https://api.github.com/repos/huggingface/transformers/issues/11813/events | https://github.com/huggingface/transformers/pull/11813 | 897,961,450 | MDExOlB1bGxSZXF1ZXN0NjQ5ODk0MjU4 | 11,813 | fix roformer config doc | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/11812 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11812/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11812/comments | https://api.github.com/repos/huggingface/transformers/issues/11812/events | https://github.com/huggingface/transformers/pull/11812 | 897,907,026 | MDExOlB1bGxSZXF1ZXN0NjQ5ODQ3NTI0 | 11,812 | Patch recursive import | {
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This resulted in a cyclic dependency and a partially initialized module.
This PR fixes the issue by importing it only when necessary and additionally tests that the `PreTrainedTokenizerFast` can be loaded as a stan... | {
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https://api.github.com/repos/huggingface/transformers/issues/11811 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11811/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11811/comments | https://api.github.com/repos/huggingface/transformers/issues/11811/events | https://github.com/huggingface/transformers/issues/11811 | 897,876,078 | MDU6SXNzdWU4OTc4NzYwNzg= | 11,811 | GPT Neo for Sequence Classification | {
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"@patil-suraj this may be a good first issue? Feel free to open a PR!",
"Thanks @NielsRogge .\n\nHi @patil-suraj ,\n\nIs there any workaround to make it work in my local?",
"We could for sure add `GPTNeoForSequenceClassification`. \r\n\r\nIt would be as easy as \r\n- just copying the `GPT2ForSequenceClassificat... | 1,621 | 1,622 | 1,622 | NONE | null | Hi,
Is there a way to use GPT Neo for classification tasks like BoolQ ?
As 'OpenAI GPT2' integration of HF has 'GPT2ForSequenceClassification', is there a similar one for GPT Neo? | {
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https://api.github.com/repos/huggingface/transformers/issues/11810 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11810/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11810/comments | https://api.github.com/repos/huggingface/transformers/issues/11810/events | https://github.com/huggingface/transformers/pull/11810 | 897,864,385 | MDExOlB1bGxSZXF1ZXN0NjQ5ODEyMTAy | 11,810 | Feature to use the PreTrainedTokenizerFast class as a stand-alone tokenizer | {
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"Could this also be a fallback for `AutoTokenizer` when none of the children classes match?"
] | 1,621 | 1,623 | 1,623 | CONTRIBUTOR | null | # What does this PR do?
In this PR, I propose to add the features needed to use `PreTrainedTokenizerFast` as a standalone tokenizer. These features include:
1. The ability to save a `PreTrainedTokenizerFast` tokenizer. Until now, it was not possible to `save_pretrained` ( with default values in the method) a `Pre... | {
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https://api.github.com/repos/huggingface/transformers/issues/11809 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11809/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11809/comments | https://api.github.com/repos/huggingface/transformers/issues/11809/events | https://github.com/huggingface/transformers/issues/11809 | 897,857,159 | MDU6SXNzdWU4OTc4NTcxNTk= | 11,809 | Wrong LayerNorm weight names in "bert-base-uncased" checkpoint ? | {
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"Did you try with other models?\r\n\r\nSince 4.6, it gives a similar warning for every model i try to load. For example:\r\n\r\n```python\r\nimport transformers as tr\r\n\r\ntr.AutoModel.from_pretrained(\"xlm-roberta-base\")\r\n```\r\n```bash\r\nSome weights of the model checkpoint at xlm-roberta-base were not used... | 1,621 | 1,703 | 1,624 | NONE | null | ## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Linux-4.18.0-147.44.1.el8_1.x86_64-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?: No
- Using distributed or parallel set-up in script?... | {
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https://api.github.com/repos/huggingface/transformers/issues/11808 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11808/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11808/comments | https://api.github.com/repos/huggingface/transformers/issues/11808/events | https://github.com/huggingface/transformers/issues/11808 | 897,758,990 | MDU6SXNzdWU4OTc3NTg5OTA= | 11,808 | How to save and load model from local path in pipeline api ? | {
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"I don't think it's currently possible, you would have to specify the local path in `model` but it won't ping the custom `cache_dir`.\r\n\r\nWe would happily welcome a PR that enables that for pipelines, would you be interested in that?",
"> I don't think it's currently possible, you would have to specify the loc... | 1,621 | 1,621 | 1,621 | NONE | null | In `from_pretrained` api, the model can be loaded from local path by passing the `cache_dir`. However, I have not found any parameter when using `pipeline`
for example, `nlp = pipeline("fill-mask" , model = 'distilbert-base-uncased', device=0)`
how to save the downloaded model and load it next time from local path... | {
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https://api.github.com/repos/huggingface/transformers/issues/11807 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11807/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11807/comments | https://api.github.com/repos/huggingface/transformers/issues/11807/events | https://github.com/huggingface/transformers/issues/11807 | 897,745,208 | MDU6SXNzdWU4OTc3NDUyMDg= | 11,807 | version of T5 is not reported in HuggingFace models | {
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"Hi there,\r\n\r\nfor T5V1.1 models we explicitly mention it in the model name, for example see here \r\nhttps://huggingface.co/google/t5-v1_1-base\r\n\r\nthe model version is mentioned in the name as `v1_1`.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think... | 1,621 | 1,624 | 1,624 | NONE | null | Hi @patrickvonplaten, @patil-suraj,
Google T5 model has two checkpoints, of t5.0.0 and t5.1.0, the performance of the two models is very different, in huggingface mdoels it is not specified which version HuggingFace is using, could you kindly add the details?
thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/11806 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11806/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11806/comments | https://api.github.com/repos/huggingface/transformers/issues/11806/events | https://github.com/huggingface/transformers/pull/11806 | 897,670,195 | MDExOlB1bGxSZXF1ZXN0NjQ5NjQ3MDgz | 11,806 | updated the original RAG implementation to be compatible with latest Pytorch-Lightning | {
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"Hey @shamanez,\r\n\r\nCould you run `make style`? \r\n\r\n@lhoestq - could you take a look as well?",
"Hey @patrickvonplaten \r\n\r\nI did run the \"make style\" and it changed following files and working alright.\r\n",
"Thanks @patrickvonplaten :)"
] | 1,621 | 1,623 | 1,623 | CONTRIBUTOR | null | The original RAG version was not working with PL>=1.3, specially due to the fact that DDPAccelerator class has removed (Retriever Initialization of RAG). The new version of PL library advises us to use DDP pluggings as a replacement.
I also updated lightning_base.py regarding the new PL version. Now RAG works wit... | {
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https://api.github.com/repos/huggingface/transformers/issues/11805 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11805/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11805/comments | https://api.github.com/repos/huggingface/transformers/issues/11805/events | https://github.com/huggingface/transformers/pull/11805 | 897,657,860 | MDExOlB1bGxSZXF1ZXN0NjQ5NjM2NDMx | 11,805 | [Deepspeed] support `zero.Init` in `from_config` | {
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- adds missing support for `zero.Init` (zero3) for `from_config` (same as we have in `from_pretrained) - which allows a huge model to be loaded in small chunks per gpu at once.
- test
@sgugger
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https://api.github.com/repos/huggingface/transformers/issues/11804 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11804/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11804/comments | https://api.github.com/repos/huggingface/transformers/issues/11804/events | https://github.com/huggingface/transformers/issues/11804 | 897,652,406 | MDU6SXNzdWU4OTc2NTI0MDY= | 11,804 | Index out of range when doing manual testing for TFBertModel | {
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"Hi, you're quite right with your diagnosis. The problem is that by default, the tokenizer creates a dict of Python lists, not Tensors. Our models don't really understand those list inputs, and so you get errors. \r\n\r\nYou already found the solution of converting those lists to TF Tensors or Numpy arrays, but the... | 1,621 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0
- Platform: Windows 10
- Python version: 3.8.5
- PyTorch version (GPU?):
- Tensorflow version (GPU?):... | {
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https://api.github.com/repos/huggingface/transformers/issues/11803 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11803/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11803/comments | https://api.github.com/repos/huggingface/transformers/issues/11803/events | https://github.com/huggingface/transformers/issues/11803 | 897,650,375 | MDU6SXNzdWU4OTc2NTAzNzU= | 11,803 | bert model (bert-base-chinese) consumed too much memory | {
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"A batch size of 128 is a lot! Are you using batch size 128 with sequence length 128?",
"Most likely you have a large tensor size of 128 * 128 * 768 - and also depends on what type of tensor data you put int32 / float32 / float64? Try to reduce the batch size, even to 2.",
"> A batch size of 128 is a lot! Are y... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0
- Platform: Linux-4.19.117.bsk.5-amd64-x86_64-with-debian-10.7
- Python version: 3.7.3
- PyTorch versi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11802 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11802/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11802/comments | https://api.github.com/repos/huggingface/transformers/issues/11802/events | https://github.com/huggingface/transformers/issues/11802 | 897,636,064 | MDU6SXNzdWU4OTc2MzYwNjQ= | 11,802 | Text Generation, adding random words, weird linebreaks & symbols at random. | {
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"Hi! Could you provide more information, especially regarding which model and tokenizer you're using? Also, you might have more luck asking on the [forum](https://discusss.huggingface.co), as GitHub issues are for bugs/feature requests.\r\n\r\nThanks!",
"> Hi! Could you provide more information, especially regard... | 1,621 | 1,624 | 1,624 | NONE | null | Here's the code I'm using to generate text.
`sentence= tokenizer.encode(kw, return_tensors='pt')
output = model.generate(sentence,
max_length = 500,
no_repeat_ngram_size = 2,
do_sample=False)
text.append(tokenizer.decode(output[0], skip_special_tokens = True))`
The issue is that the output often comes lik... | {
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https://api.github.com/repos/huggingface/transformers/issues/11801 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11801/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11801/comments | https://api.github.com/repos/huggingface/transformers/issues/11801/events | https://github.com/huggingface/transformers/issues/11801 | 897,527,216 | MDU6SXNzdWU4OTc1MjcyMTY= | 11,801 | [examples] run_clm re-processes dataset on every run | {
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"The dataset caching is all relying on the datasets library, so the issue should probably be tracked here. Especially if this is a new change: since there was no change I'm aware of in `run_clm` recently it may be coming from a change there.",
"Thank you! I will ask on the `datasets` side.",
"you scooped me Syl... | 1,621 | 1,623 | 1,623 | CONTRIBUTOR | null | developing with `run_clm` is difficult since its startup is very slow - it rebuilds the dataset on each start.
@VictorSanh says it started to do that recently...
I think it's because it has to chunk the existing dataset into smaller pieces, it's a slow start everytime and it doesn't save these results.
So the or... | {
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https://api.github.com/repos/huggingface/transformers/issues/11800 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11800/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11800/comments | https://api.github.com/repos/huggingface/transformers/issues/11800/events | https://github.com/huggingface/transformers/issues/11800 | 897,444,281 | MDU6SXNzdWU4OTc0NDQyODE= | 11,800 | CamemBert Tokenizer AttributeError: 'NoneType' object has no attribute 'tokenize' | {
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"Hi! Could you try installing `sentencepiece` to see if that solves the problem?",
"I got an error when sentencepiece wasn't installed and after installing it returned None. Trying it again now I don't see the error anymore though so I'll close the issue 🙂",
"If this was on colab it's possible that you needed ... | 1,621 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.1+cpu (Fal... | {
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https://api.github.com/repos/huggingface/transformers/issues/11799 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11799/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11799/comments | https://api.github.com/repos/huggingface/transformers/issues/11799/events | https://github.com/huggingface/transformers/issues/11799 | 897,425,049 | MDU6SXNzdWU4OTc0MjUwNDk= | 11,799 | ImportError: tokenizers>=0.10.1,<0.11 is required for a normal functioning of this module, but found tokenizers==0.8.1rc1. | {
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"Hello, the error is pretty straightforward: your Python environment has the wrong `tokenizers` version.\r\n\r\nI would suggest you reinstall tokenizers *while making sure you are in the same environment as your python runtime*: `pip install -U tokenizers`",
"`pip install -U tokenizers` does not solve the problem... | 1,621 | 1,687 | 1,622 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.1
- Platform: Linux Mint Tricia 19.3 (ubuntu 18.04)
- Python version: 3.8.8
- PyTorch version (GPU?): 1.... | {
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https://api.github.com/repos/huggingface/transformers/issues/11798 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11798/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11798/comments | https://api.github.com/repos/huggingface/transformers/issues/11798/events | https://github.com/huggingface/transformers/pull/11798 | 897,409,860 | MDExOlB1bGxSZXF1ZXN0NjQ5NDIxNzEy | 11,798 | [Examples] create model with custom config on the fly | {
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"So now can we activate activation checkpointing with: `--config_overrides \"gradient_checkpointing=true,use_cache=False\"`\r\n\r\n1. Should we document this somewhere? maybe `examples/pytorch/README.md` once we port this to all other examples?\r\n\r\n2. But it's only available for non-pretrained model, should I ma... | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | This PR is addressing a need to:
1. be able to quickly whip up a model of any desired size for the big-science experiments.
2. be able to activate gradient checkpointing (later addition)
We already have the functionality to create a model instead of using a pretrained one, but there was no way to control its confi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11797 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11797/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11797/comments | https://api.github.com/repos/huggingface/transformers/issues/11797/events | https://github.com/huggingface/transformers/issues/11797 | 897,331,299 | MDU6SXNzdWU4OTczMzEyOTk= | 11,797 | [examples] add desc to `dataset.map` to improve tqdm bars | {
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Currently we get a bunch of bars that are absolutely meaningless and hard to understand what they do. See also: https://github.c... | {
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https://api.github.com/repos/huggingface/transformers/issues/11796 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11796/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11796/comments | https://api.github.com/repos/huggingface/transformers/issues/11796/events | https://github.com/huggingface/transformers/issues/11796 | 897,300,869 | MDU6SXNzdWU4OTczMDA4Njk= | 11,796 | [trainer] multi-node tweaks | {
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"Mmm I guess there should be some argument controlling this: when I'm using multi-node I launch the command on two separate machines and have two separate terminals, so having both output the logs is helpful to know where each is at.",
"Absolutely agree for a few nodes! This becomes an issue on 64+ nodes ;) \r\n\... | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | As I'm using Trainer in a multi-node setup, I will use this issue to post the things that could be improved for that type of env.
1. Repeated logging for non-rank-0 process rank-0 machine:
I gathered all these that get repeated 16 times on a 16 nodes machine:
```
[INFO|trainer.py:1145] 2021-05-20 20:16:39,037... | {
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https://api.github.com/repos/huggingface/transformers/issues/11795 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11795/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11795/comments | https://api.github.com/repos/huggingface/transformers/issues/11795/events | https://github.com/huggingface/transformers/issues/11795 | 897,244,805 | MDU6SXNzdWU4OTcyNDQ4MDU= | 11,795 | get_length_grouped_indices() uses slow list concat | {
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"Thanks a lot for looking at this optimization. It does look like a nice speedup! Do you want to open a PR with the suggested changes since you're the one who designed it?"
] | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | Hi,
get_length_grouped_indices() in LengthGroupedSampler and DistributedLengthGroupedSampler is prohibitively slow for large number of megabatches (in my case takes hours for ~270k megabatches with 100 items each) due to slow list concatenation with sum(megabatches, []).
Concatenating the lists with sum() may be... | {
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https://api.github.com/repos/huggingface/transformers/issues/11794 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11794/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11794/comments | https://api.github.com/repos/huggingface/transformers/issues/11794/events | https://github.com/huggingface/transformers/issues/11794 | 897,240,123 | MDU6SXNzdWU4OTcyNDAxMjM= | 11,794 | Bug in TokenClassificationPipeline | {
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"That is true. `len(word_ref) != len(word)` is a heuristic that will work on tokenizers that use BPE `continuing_subword_prefix` concept.\r\n \r\nThe reality is that there is no consistent notion of a \"word\" within arbitrary tokenizers.\r\nThe `continuing_subword_prefix` in BPE that *can* be used makes the concep... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-5.4.0-42-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- 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/11793 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11793/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11793/comments | https://api.github.com/repos/huggingface/transformers/issues/11793/events | https://github.com/huggingface/transformers/issues/11793 | 897,213,429 | MDU6SXNzdWU4OTcyMTM0Mjk= | 11,793 | [trainer] the noisy tensorflow loaded when asked explicitly not to load it | {
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"Indeed, the `import Trainer` seems to be importing TensorFlow again. Let me try to see if I can remove that.",
"I messed up my branch and pushed directly on master by mistake, but I don't think it needs reverting and doing a PR since it's a short fix.\r\nShort story is that I locally have no tensorflow import wi... | 1,621 | 1,623 | 1,623 | CONTRIBUTOR | null | Unrequested TF loading and its noisy disrespectful logging is back it seems:
```
USE_TF=0 python examples/pytorch/language-modeling/run_clm.py \
--model_name_or_path $MODEL \
--dataset_name $DATASET \
--output_dir output_dir \
--overwrite_output_dir \
--do_train \
--do_eval \
--m... | {
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https://api.github.com/repos/huggingface/transformers/issues/11792 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11792/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11792/comments | https://api.github.com/repos/huggingface/transformers/issues/11792/events | https://github.com/huggingface/transformers/issues/11792 | 897,118,325 | MDU6SXNzdWU4OTcxMTgzMjU= | 11,792 | T5EncoderModel slower in half-precision | {
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"@stas00 or @sgugger can chime in if I'm wrong, but I believe half-precision performance improvement is strongly tied to hardware: even hardware that handles half-precision like pascal GPUs may not see a speed increase with FP16 compared to FP32, and I believe it can have the opposite effect. Could you share your s... | 1,621 | 1,622 | 1,622 | NONE | null | Hi,
I am encountering troubles in understanding why the half-precision version of the T5Encoder infers slower than the full-precision one.
## To reproduce
Starting with the `half`-precision.
```python
import torch
from transformers import T5EncoderModel, T5Tokenizer
import time
device = torch.device('c... | {
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https://api.github.com/repos/huggingface/transformers/issues/11791 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11791/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11791/comments | https://api.github.com/repos/huggingface/transformers/issues/11791/events | https://github.com/huggingface/transformers/issues/11791 | 897,003,525 | MDU6SXNzdWU4OTcwMDM1MjU= | 11,791 | LongformerForSequenceClassification: global_attention_mask=None | {
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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 because it has not had recent activity. If you think this sti... | 1,621 | 1,624 | 1,624 | NONE | null | Hi, my question is, what happens if `global_attention_mask` in `LongformerForSequenceClassification` is not stated? Does it mean that only local attention works in this case? I haven't found anything about it in the docs. Thanks in advance! | {
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https://api.github.com/repos/huggingface/transformers/issues/11790 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11790/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11790/comments | https://api.github.com/repos/huggingface/transformers/issues/11790/events | https://github.com/huggingface/transformers/issues/11790 | 896,909,088 | MDU6SXNzdWU4OTY5MDkwODg= | 11,790 | facebook/mbart-large-50-one-to-many-mmt fails on Swahili | {
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"Hi @DCNemesis \r\n\r\nDoes this happen for this specific example or for all the examples that you tried?\r\n\r\nAnd this isn't really an issue with implementation. As the model is many-to-many is not trained in every single language pair this does happen in some cases. It's likey that there's far less data for X t... | 1,621 | 1,627 | 1,627 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0
- Platform: Linux-5.4.109+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11789 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11789/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11789/comments | https://api.github.com/repos/huggingface/transformers/issues/11789/events | https://github.com/huggingface/transformers/issues/11789 | 896,900,160 | MDU6SXNzdWU4OTY5MDAxNjA= | 11,789 | PegasusTokenizer returning None | {
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"Hey @akashe,\r\n\r\nThink this error is analogs to this one: https://github.com/huggingface/transformers/issues/8864. \r\n\r\nInstalling `sentencepiece` should solve the problem :-) \r\n\r\nhttps://github.com/huggingface/transformers/issues/8864",
"This issue has been automatically marked as stale because it has... | 1,621 | 1,674 | 1,625 | 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:
- Platform: Ubuntu 20.04
- Python version: Python 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101
- Tensorflow... | {
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https://api.github.com/repos/huggingface/transformers/issues/11788 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11788/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11788/comments | https://api.github.com/repos/huggingface/transformers/issues/11788/events | https://github.com/huggingface/transformers/issues/11788 | 896,860,928 | MDU6SXNzdWU4OTY4NjA5Mjg= | 11,788 | EncoderDecoder Cross Attention Generation Output Shape does not match Documentation | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1
- Platform: Linux-4.15.0-143-generic-x86_64-with-glibc2.27
- Python version: 3.9.4
- PyTorch version (... | {
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https://api.github.com/repos/huggingface/transformers/issues/11787 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11787/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11787/comments | https://api.github.com/repos/huggingface/transformers/issues/11787/events | https://github.com/huggingface/transformers/issues/11787 | 896,859,628 | MDU6SXNzdWU4OTY4NTk2Mjg= | 11,787 | GPT Neo past_key_values unexpected behaviour | {
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"I encountered a similar problem when trying to use GPT-Neo with PPLM (https://github.com/uber-research/PPLM). Seems that Neo's `past_key_values` is returning and consuming key-value tensors as well as (I'm guessing) feed-forward tensors:\r\n\r\n```python\r\ninputs = tokenizer(prompt, return_tensors='pt')\r\noutput... | 1,621 | 1,631 | 1,631 | NONE | null | I have been successfully using the GPT2LMHeadModel module for text generation for some time and I recently tried to reuse the code to generate with GPTNeoForCausalLM. Though the documentations appear identical, I get the error "ValueError: not enough values to unpack (expected 2, got 1)" for the line`output, past = se... | {
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https://api.github.com/repos/huggingface/transformers/issues/11786 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11786/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11786/comments | https://api.github.com/repos/huggingface/transformers/issues/11786/events | https://github.com/huggingface/transformers/pull/11786 | 896,845,411 | MDExOlB1bGxSZXF1ZXN0NjQ4OTA5OTcz | 11,786 | [RFC] Laying down building stone for more flexible ONNX export capabilities | {
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"Example of potential command line to export `bert-base-cased` => \r\n\r\n`python3 -m transformers.onnx -f pytorch --model=bert-base-cased --features=default --optimize --optimization-level=all onnx/bert-base-cased/`",
"See the contributed docs here https://235542-155220641-gh.circle-artifacts.com/0/docs/_build/... | 1,621 | 1,652 | 1,625 | MEMBER | null | This PR aims at reworking the way the ONNX export tool work by introducing a static, checked description format to provide ONNX exporters (pt almost done, TF will follow) all the required knobs.
More specifically this PR introduces the following concepts:
- `OnnxConfig` dataclass which enforces a model to be suppor... | {
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https://api.github.com/repos/huggingface/transformers/issues/11785 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11785/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11785/comments | https://api.github.com/repos/huggingface/transformers/issues/11785/events | https://github.com/huggingface/transformers/pull/11785 | 896,829,353 | MDExOlB1bGxSZXF1ZXN0NjQ4ODk1NjU2 | 11,785 | Fix regression in regression | {
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"Thank you for fixing the issue! "
] | 1,621 | 1,621 | 1,621 | COLLABORATOR | null | # What does this PR do?
This PR fixes the regression introduced in #11012 for regression problems with only one label (like STS-B), see discussion on #11780. I checked both `run_glue` and `run_glue_no_trainer` on this branch and get the proper results for this task now.
Fixes #11780
Fixes #11583 | {
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https://api.github.com/repos/huggingface/transformers/issues/11784 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11784/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11784/comments | https://api.github.com/repos/huggingface/transformers/issues/11784/events | https://github.com/huggingface/transformers/pull/11784 | 896,806,126 | MDExOlB1bGxSZXF1ZXN0NjQ4ODc0Njcy | 11,784 | Fix release utilpattern in conf.py | {
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When we applied black to the conf.py style, the line with the version changed but the pattern in our release util script was not updated. This PR fixes that. | {
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https://api.github.com/repos/huggingface/transformers/issues/11783 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11783/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11783/comments | https://api.github.com/repos/huggingface/transformers/issues/11783/events | https://github.com/huggingface/transformers/issues/11783 | 896,645,300 | MDU6SXNzdWU4OTY2NDUzMDA= | 11,783 | PyInstaller Transformers runtime import error | {
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"Hi, the error seems to originate from PyInstaller rather than `transformers`, right? Have you reported it to the PyInstaller team?",
"> Hi, the error seems to originate from PyInstaller rather than `transformers`, right? Have you reported it to the PyInstaller team?\r\n\r\nYes @LysandreJik, I posted the same que... | 1,621 | 1,624 | 1,624 | NONE | null | Hi,
I am getting the following error while creating executable with transformers using PyInstaller
**PyInstaller: 4.3
Transformers Version: 4.6.0
736 INFO: Python: 3.8.5 (conda)
751 INFO: Platform: macOS-10.15.5**
_413560 INFO: Packages required by datasets:
['dill', 'multiprocess', 'pandas', 'tqdm', 'tqdm... | {
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https://api.github.com/repos/huggingface/transformers/issues/11782 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11782/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11782/comments | https://api.github.com/repos/huggingface/transformers/issues/11782/events | https://github.com/huggingface/transformers/pull/11782 | 896,307,798 | MDExOlB1bGxSZXF1ZXN0NjQ4NDI5MDIy | 11,782 | [WIP] Expand `past_key_values` also during beam search in EncoderDecoder models | {
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"Changed to `WIP` because right now the PR does not account for cross attentions in `past_key_values` (indices 2 and 3). \r\n\r\nCould not be certain if cross-attention matrix for each layer in `past_key_values` is always a 4-tuple for all encoder-decoder models (maybe some model does not use cross-attention even t... | 1,621 | 1,622 | 1,622 | NONE | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/11781 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11781/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11781/comments | https://api.github.com/repos/huggingface/transformers/issues/11781/events | https://github.com/huggingface/transformers/issues/11781 | 896,305,367 | MDU6SXNzdWU4OTYzMDUzNjc= | 11,781 | `generate` with `num_beam` > 1 does not work in EncoderDecoder models when `past` is supplied. | {
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" Hey @seongminp,\r\n\r\nThanks for the issue report. It's a rather specific use-case to pass `past_key_values` to `generate()`. Could you give me some more detail when you need to do so? ",
"Hi @patrickvonplaten!\r\n\r\nMy use-case for passing `past_key_values` to `generate` is to manipulate the encoder hidden s... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.7.0.dev0
- Platform: Linux-5.4.0-72-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11780 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11780/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11780/comments | https://api.github.com/repos/huggingface/transformers/issues/11780/events | https://github.com/huggingface/transformers/issues/11780 | 896,038,212 | MDU6SXNzdWU4OTYwMzgyMTI= | 11,780 | Unintentional(?) interface change on loss function in models didn't work well for single-column regression | {
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"Yes the change was unintentional to enable multi-label regression. I think the old\r\n```\r\nloss = loss_fct(logits.view(-1), labels.view(-1))\r\n```\r\nwill work in the case of one or several labels but might not give a clear error message if we have multiple labels but a shape error (if we have 5 possible lables... | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | The recent PR #11012 changed the interface of forward function for `labels` in regression tasks as it skips `.view(-1)` in loss function like [this](https://github.com/huggingface/transformers/pull/11012/files#diff-a48ba7f6444ca4954a58f1ac3e66c7941a2bbc4615649d56b182aeac8cc36d9cL1523).
As shown below, that causes `U... | {
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https://api.github.com/repos/huggingface/transformers/issues/11779 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11779/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11779/comments | https://api.github.com/repos/huggingface/transformers/issues/11779/events | https://github.com/huggingface/transformers/pull/11779 | 895,797,186 | MDExOlB1bGxSZXF1ZXN0NjQ3OTczMjc2 | 11,779 | Deprecate commands from the transformers-cli that are in the hf-cli | {
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"my reason for removing (still keeping a descriptive error obviously) rather than deprecating is that I'd love to know if people actually use those (and if they do, do they use them in scripts or manually)\r\n\r\nBut I will defer to the great transformers-maintainers as the final decision 💖",
"sounds good to me!... | 1,621 | 1,621 | 1,621 | MEMBER | null | Commands that are both in the `transformers-cli` and in the `huggingface-cli` are deprecated here and will be quickly removed.
I'm voting for deprecating them and not removing them even though better ways exist as I suspect some users to use the `transformers-cli` in bash scripts to automatically upload models to th... | {
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https://api.github.com/repos/huggingface/transformers/issues/11778 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11778/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11778/comments | https://api.github.com/repos/huggingface/transformers/issues/11778/events | https://github.com/huggingface/transformers/pull/11778 | 895,699,977 | MDExOlB1bGxSZXF1ZXN0NjQ3ODg4NjEy | 11,778 | [Flax] Align GLUE training script with mlm training script | {
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"Ran the experiment again, but testing time stayed the same for me...think it's better though to have a consistent way of handling the random keys though - so merging"
] | 1,621 | 1,621 | 1,621 | MEMBER | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11776 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11776/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11776/comments | https://api.github.com/repos/huggingface/transformers/issues/11776/events | https://github.com/huggingface/transformers/pull/11776 | 895,691,040 | MDExOlB1bGxSZXF1ZXN0NjQ3ODgwNzIw | 11,776 | uplaod | {
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https://api.github.com/repos/huggingface/transformers/issues/11775 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11775/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11775/comments | https://api.github.com/repos/huggingface/transformers/issues/11775/events | https://github.com/huggingface/transformers/pull/11775 | 895,571,910 | MDExOlB1bGxSZXF1ZXN0NjQ3Nzc3NjM3 | 11,775 | Fix usage of head masks by TF encoder-decoder models' `generate()` function | {
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"Thanks for the addition @stancld ! \r\n\r\nI think once we fix the tests in led + T5 we can merge this one :-)",
"It also looks good to me!",
"Hey @patrickvonplaten, I haven't implemented head masking for the `generate` method for LED and T5 intentionally. The reason is that TF LED and T5 does not use head mas... | 1,621 | 1,622 | 1,622 | CONTRIBUTOR | null | TF counterpart to #11621
**Description:** It is necessary to fix head masking for LED and T5 models.
Edit: Fix for T5 - #11857
<hr>
**Reviewers:** @patrickvonplaten @Rocketknight1 | {
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https://api.github.com/repos/huggingface/transformers/issues/11774 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11774/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11774/comments | https://api.github.com/repos/huggingface/transformers/issues/11774/events | https://github.com/huggingface/transformers/issues/11774 | 895,520,414 | MDU6SXNzdWU4OTU1MjA0MTQ= | 11,774 | Finetune - Helsinki-NLP/opus-mt-fr-en | {
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"Could you share your code so that we may help?\r\n\r\nI believe this is covered in the quicktour! https://huggingface.co/transformers/quicktour.html",
"here is my code\r\n\r\n`python3 /marian/examples/transformers/examples/research_projects/seq2seq-distillation/finetune.py \\\r\n --learning_rate=3e-5 \\\r\n --fp... | 1,621 | 1,624 | 1,624 | NONE | null | Hi all
I am new to huggingface!
I am trying to finetune the Helsinki-NLP/opus-mt-fr-en but I am getting the error:
```
2021-05-19 14:20:33.882388: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dyn
amic library libcudart.so.11.0
Traceback (most recent call last):
File... | {
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https://api.github.com/repos/huggingface/transformers/issues/11773 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11773/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11773/comments | https://api.github.com/repos/huggingface/transformers/issues/11773/events | https://github.com/huggingface/transformers/pull/11773 | 895,320,478 | MDExOlB1bGxSZXF1ZXN0NjQ3NTU2NDQx | 11,773 | [Demo] Slow down in TPU training | {
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"Basically prior to this change you were running a single jitted function in each train step, and because of asynchronous dispatch it didn't have to wait until the previous step was complete until dispatching the program for the next step. But if you split an RNG in between, then JAX blocks until the previous step ... | 1,621 | 1,621 | 1,621 | MEMBER | null | @avital @marcvanzee - I wanted to align `run_mlm_flax.py` more with `run_glue_flax.py` and noticed that by doing the change as shown in this PR, training on TPU slows down very significantly by ca. ~40%.
Currently, [`run_glue_flax.py`](https://github.com/huggingface/transformers/blob/master/examples/flax/text-classi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11772 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11772/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11772/comments | https://api.github.com/repos/huggingface/transformers/issues/11772/events | https://github.com/huggingface/transformers/issues/11772 | 895,278,537 | MDU6SXNzdWU4OTUyNzg1Mzc= | 11,772 | Different performance when training different transformers version | {
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"We do not guarantee the exact reproducibility of training between versions, only with the same version (PyTorch does the same by the way). Are you using the Trainer API? If this is the case, I believe it's the work done to ensure full reproducibility for checkpoints (e.g. you get to the same results training from ... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
- `transformers` version: 4.6 and 4.5
- Platform:
- Python version: 3.7
- PyTorch version (GPU?): 1.8.0 GPU
- Tensorflow version (GPU?):
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
### Who can help
@LysandreJik @sgugger
Models: PhoBERT (RoBERTa ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11771 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11771/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11771/comments | https://api.github.com/repos/huggingface/transformers/issues/11771/events | https://github.com/huggingface/transformers/pull/11771 | 895,265,066 | MDExOlB1bGxSZXF1ZXN0NjQ3NTA3Njc1 | 11,771 | Add DOI badge to README | {
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Add DOI badge to README, as explained in https://guides.github.com/activities/citable-code/ | {
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https://api.github.com/repos/huggingface/transformers/issues/11770 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11770/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11770/comments | https://api.github.com/repos/huggingface/transformers/issues/11770/events | https://github.com/huggingface/transformers/pull/11770 | 895,191,182 | MDExOlB1bGxSZXF1ZXN0NjQ3NDQzNjA2 | 11,770 | [T5 failing CI] Fix generate test | {
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https://api.github.com/repos/huggingface/transformers/issues/11769 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11769/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11769/comments | https://api.github.com/repos/huggingface/transformers/issues/11769/events | https://github.com/huggingface/transformers/issues/11769 | 895,125,646 | MDU6SXNzdWU4OTUxMjU2NDY= | 11,769 | Trainer removes newer checkpoints, not older. | {
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"Please give us a command that reproduces the bug as your indications are too vague to reproduce. Also make sure you are using a source install as there was a bug recently fixed with the checkpoints (though it was with `load_best_model_at_end=True` which I have no idea if you're using).",
"I'm using load_best_mod... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0
- Platform:
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11768 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11768/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11768/comments | https://api.github.com/repos/huggingface/transformers/issues/11768/events | https://github.com/huggingface/transformers/issues/11768 | 895,115,179 | MDU6SXNzdWU4OTUxMTUxNzk= | 11,768 | DataCollatorForWholeWordMask only works for BERT, and nothing is said in the docstring. | {
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"Yes merging it was a mistake. It will be removed when we have something better in the future.",
"@sgugger Could you please tell me how could I adapt it for a general fast tokenizer? Or at least how would you do it for a ByteBPETokenizer like Roberta's or Deberta's?",
"I haven't dug into this, but it should pro... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform:
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in script... | {
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https://api.github.com/repos/huggingface/transformers/issues/11767 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11767/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11767/comments | https://api.github.com/repos/huggingface/transformers/issues/11767/events | https://github.com/huggingface/transformers/issues/11767 | 895,099,780 | MDU6SXNzdWU4OTUwOTk3ODA= | 11,767 | AttributeError when using EncoderDecoderModel.forward() with encoder_outputs and return_dict=True | {
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"Hey @aizawa-naoki,\r\n\r\nThanks for your bug report here. \r\n\r\nThe problem here is that the model expects the inputs and outputs to be of type `ModelOutput` by setting `return_dict=True`.\r\nHowever, `encoder_outputs` is passed as a tuple and not as a `ModelOutput` which leads to an error. You could fix your c... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.9.4
- PyTorch version (GPU?): 1.8.1 (F... | {
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https://api.github.com/repos/huggingface/transformers/issues/11766 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11766/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11766/comments | https://api.github.com/repos/huggingface/transformers/issues/11766/events | https://github.com/huggingface/transformers/issues/11766 | 895,074,347 | MDU6SXNzdWU4OTUwNzQzNDc= | 11,766 | Error when using IterableDataset as train_dataset for Trainer | {
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"Can you print the elements you get when iterating through your dataset (and their types)? It seems like there is something wrong here. I'm not familiar with parquet but your iter is only going to return the result of the first of `df.to_batches()`, is that expected?\r\n\r\nNote that the `__len__` should not be imp... | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | Hi, I'm using large train data (parquet format) and want to pass this as `IterableDataset` to `Trainer`.
I managed to make custom `IterableDataset`, but sadly it doesn't work.
```python
import torch
import pyarrow.parquet as pq
from transformers import BatchEncoding
class CustomIterableData(torch.utils.data.d... | {
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https://api.github.com/repos/huggingface/transformers/issues/11765 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11765/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11765/comments | https://api.github.com/repos/huggingface/transformers/issues/11765/events | https://github.com/huggingface/transformers/issues/11765 | 895,010,625 | MDU6SXNzdWU4OTUwMTA2MjU= | 11,765 | Unable to use fill-mask pipeline on gpt-neo model | {
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"Fill-mask is for encoder-only models like BERT and RoBERTa. The GPT-neo model is a decoder-only model that is capable of doing text generation. There's a `TextGenerationPipeline` available, so you might try that out. The documentation can be found [here](https://huggingface.co/transformers/main_classes/pipelines.h... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0
- Platform: googleColab
- Python version:3.7
Models: `GPT neo`
Code :
```
#Import Hugging Face... | {
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https://api.github.com/repos/huggingface/transformers/issues/11764 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11764/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11764/comments | https://api.github.com/repos/huggingface/transformers/issues/11764/events | https://github.com/huggingface/transformers/pull/11764 | 894,895,560 | MDExOlB1bGxSZXF1ZXN0NjQ3MTkyMDY1 | 11,764 | [Wav2Vec2] SpecAugment Fast | {
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"Noticed a small speed-up when training (1-2%) only though, and even slighly improved results. More importantly I think the code is much more readable now."
] | 1,621 | 1,621 | 1,621 | MEMBER | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11763 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11763/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11763/comments | https://api.github.com/repos/huggingface/transformers/issues/11763/events | https://github.com/huggingface/transformers/pull/11763 | 894,637,917 | MDExOlB1bGxSZXF1ZXN0NjQ2OTcxNTk2 | 11,763 | A cleaner and more scalable implementation of symbolic tracing | {
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"What do you think about `dtype` being hardcoded?\r\n\r\nWhile this is OK for now hardcoding dtype might be an issue down the road. For most NLP models inputs are int, but for example for wav2vec2 they are floats. \r\n\r\nAnd would this have an impact if the final usage is in fp16 for where you used `float`.\r\n\r\... | 1,621 | 1,621 | 1,621 | MEMBER | null | # What does this PR do?
This PR provides a much cleaner and less hacky implementation of symbolic tracing for models of the library.
It also provides support for more architectures:
- ALBERT
- DistilBERT
- MobileBERT
- MegatronBERT
- GPT2
- GPT Neo
| {
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https://api.github.com/repos/huggingface/transformers/issues/11762 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11762/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11762/comments | https://api.github.com/repos/huggingface/transformers/issues/11762/events | https://github.com/huggingface/transformers/pull/11762 | 894,627,834 | MDExOlB1bGxSZXF1ZXN0NjQ2OTYzMDU0 | 11,762 | Fix a bug in summarization example which did not load model from config properly | {
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Current example script does not load model when config is supplied, just a small bug fix.
## Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/11761 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11761/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11761/comments | https://api.github.com/repos/huggingface/transformers/issues/11761/events | https://github.com/huggingface/transformers/issues/11761 | 894,359,820 | MDU6SXNzdWU4OTQzNTk4MjA= | 11,761 | Add batching to pipelines | {
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"Hi! You may find the discussion on this PR useful: https://github.com/huggingface/transformers/pull/11251",
"Thanks for explaining this"
] | 1,621 | 1,621 | 1,621 | NONE | null | # Add batching to pipelines
Are there any plans to add a batching option to existing pipelines? Currently, the model tries to process all the input simultaneously, which sometimes (if the input is considerable) leads to memory errors. | {
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https://api.github.com/repos/huggingface/transformers/issues/11760 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11760/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11760/comments | https://api.github.com/repos/huggingface/transformers/issues/11760/events | https://github.com/huggingface/transformers/pull/11760 | 894,320,053 | MDExOlB1bGxSZXF1ZXN0NjQ2NzAxNTk1 | 11,760 | add `dataset_name` to data_args and added accuracy metric | {
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Added `dataset_name` and `dataset_config_name` to `DataTrainingArguments` to use a compatible dataset from the dataset hub. I tested it with `imdb`.
Additionally also resolved `TODO` and added `load_metrics('accuracy')` | {
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https://api.github.com/repos/huggingface/transformers/issues/11759 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11759/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11759/comments | https://api.github.com/repos/huggingface/transformers/issues/11759/events | https://github.com/huggingface/transformers/issues/11759 | 894,266,121 | MDU6SXNzdWU4OTQyNjYxMjE= | 11,759 | error in load of tokenizer with add_token | {
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"Hello! Could you provide the code that you used, library version, etc (everything asked in the issue template) thanks!",
"here is the code to add tokens to tokenizer and then train on the corpus as a pretrained model:\r\nafter training is finished when I want to load the tokenizer, I got Error.\r\ntransformers v... | 1,621 | 1,625 | 1,625 | NONE | null | Hi,
in term of adding tokens to the Bert tokenizer, I tried to add 10k new tokens to my BERT model tokenizer and I saved the tokenizer .
So when I want to load the tokenizer to use, I got this error:
AssertionError: Non-consecutive added token '#سلام' found. Should have index 100005 but has index 100006 in saved ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11758 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11758/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11758/comments | https://api.github.com/repos/huggingface/transformers/issues/11758/events | https://github.com/huggingface/transformers/pull/11758 | 894,243,969 | MDExOlB1bGxSZXF1ZXN0NjQ2NjM2NjI5 | 11,758 | Add more subsections to main doc | {
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This PR adds a subsection right before the list of supported models & the big table of supported frameworks for each model. Merging this PR would change the "welcome" doc page as follows:
![pic1](https://user-images.githubusercontent.com/23423619/118638456-c4edd900-b7ce-11eb-8191-aa9bfc622... | {
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I found that I broke the link by accidentally adding a newline (probably by my formatter) in #11650.
Here is a fix for that.
Sorry for any inconvenience.
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"Indeed, thanks for reporting. This is related to https://github.com/huggingface/tokenizers/issues/552",
"Thanks! Could you please indicate the time this could be fixed? I'll decide whether to align it locally haha..",
"This issue has been automatically marked as stale because it has not had recent activity. If... | 1,621 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.3
### Who can help
@LysandreJik
## Information
The `word_to_tokens` method of `XLNetTokenizerF... | {
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https://api.github.com/repos/huggingface/transformers/issues/11755 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11755/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11755/comments | https://api.github.com/repos/huggingface/transformers/issues/11755/events | https://github.com/huggingface/transformers/issues/11755 | 893,989,068 | MDU6SXNzdWU4OTM5ODkwNjg= | 11,755 | A problem of Ibert IntSoftmax | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,621 | 1,624 | 1,624 | NONE | null | ## 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:
- `transformers` version: 4.6.0.dev0
- Platform: Linux-4.15.0-122-generic-x86_64-with-glibc2.10
- Python ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/11754 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11754/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11754/comments | https://api.github.com/repos/huggingface/transformers/issues/11754/events | https://github.com/huggingface/transformers/issues/11754 | 893,784,795 | MDU6SXNzdWU4OTM3ODQ3OTU= | 11,754 | Trainer accumulates GPU usage at the beginning of each step | {
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"I've experienced the same issue. "
] | 1,621 | 1,621 | 1,621 | NONE | null | Hello,
My problem is that GPU usage gets increased at the beginning of each step. Although the usage gets decreased with the help of torch.cuda.empty_cache() and gc.collector() during training, OOM errors happened after a while.
## Environment info
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https://api.github.com/repos/huggingface/transformers/issues/11753 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11753/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11753/comments | https://api.github.com/repos/huggingface/transformers/issues/11753/events | https://github.com/huggingface/transformers/pull/11753 | 893,701,831 | MDExOlB1bGxSZXF1ZXN0NjQ2MTczOTIx | 11,753 | Add Flax Examples and Cloud TPU README | {
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"cc @patrickvonplaten "
] | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | # What does this PR do?
Adds a Flax examples README. Pretty bare for now, but will include a link to Cloud TPU instructions once they are up.
I hope my use of relative links works well, but looking for feedback. The main goal here is to have a canonical link we can point to. Perhaps later this should live on the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11752 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11752/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11752/comments | https://api.github.com/repos/huggingface/transformers/issues/11752/events | https://github.com/huggingface/transformers/pull/11752 | 893,641,850 | MDExOlB1bGxSZXF1ZXN0NjQ2MTIzODA0 | 11,752 | Fixed: Better names for nlp variables in pipelines' tests and docs. | {
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"Could you take care of the merge conflicts and we should be good to merge? Thanks!",
"Thanks a lot for this !"
] | 1,621 | 1,621 | 1,621 | CONTRIBUTOR | null | # What does this PR do?
Fixes #9455
## 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-contributing-pull-reques... | {
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https://api.github.com/repos/huggingface/transformers/issues/11751 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11751/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11751/comments | https://api.github.com/repos/huggingface/transformers/issues/11751/events | https://github.com/huggingface/transformers/issues/11751 | 893,599,150 | MDU6SXNzdWU4OTM1OTkxNTA= | 11,751 | parallelize and deparallelize method for GPT-Neo series model | {
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"This is answered in #11054.\r\n\r\n(I'm in a similar situation as you. I'm just going to go with the suggestion and use DeepSpeed instead of model parallelism.)",
"Thanks, didn't saw that. Parallelism notes are also awesome."
] | 1,621 | 1,621 | 1,621 | NONE | null | # 🚀 Feature request
Parallelize and deparallelize methods for distribution of attention modules across multiple GPUs.
## Motivation
Finetuning GPT Neo 2.7B model on 12 GB GPU gives out of memory error. Having a parallelize method would allow us to train that model by splitting attention modules across multiple ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11750 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11750/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11750/comments | https://api.github.com/repos/huggingface/transformers/issues/11750/events | https://github.com/huggingface/transformers/pull/11750 | 893,595,881 | MDExOlB1bGxSZXF1ZXN0NjQ2MDgzNzAw | 11,750 | Flax BERT fix token type init | {
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<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11749 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11749/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11749/comments | https://api.github.com/repos/huggingface/transformers/issues/11749/events | https://github.com/huggingface/transformers/issues/11749 | 893,524,955 | MDU6SXNzdWU4OTM1MjQ5NTU= | 11,749 | [deepspeed] supporting `--adafactor` | {
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https://api.github.com/repos/huggingface/transformers/issues/11748 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11748/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11748/comments | https://api.github.com/repos/huggingface/transformers/issues/11748/events | https://github.com/huggingface/transformers/pull/11748 | 893,495,320 | MDExOlB1bGxSZXF1ZXN0NjQ2MDAwNTU2 | 11,748 | Fix checkpoint deletion | {
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As pointed out on the [forums](https://discuss.huggingface.co/t/checkpoint-missing-optimizer-pt-how-to-resume/6138) there is a problem in the way checkpoints are deleted currently when `save_total_limit` is set and `load_best_model_at_end` is True. Since the best checkpoint is switched with t... | {
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https://api.github.com/repos/huggingface/transformers/issues/11747 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11747/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11747/comments | https://api.github.com/repos/huggingface/transformers/issues/11747/events | https://github.com/huggingface/transformers/issues/11747 | 893,415,968 | MDU6SXNzdWU4OTM0MTU5Njg= | 11,747 | mbart-large-cc25 tokenization_utils_fast.py TypeError | {
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"Hi @lysa-n,\r\nFor multilingual models you must define input language(src_lang) and target language(tgt_lang). Since you are using it for summarization for the Dutch language the src_lang and tgt_lang will be the same.\r\nThis should work:\r\n```python\r\nfrom transformers import AutoTokenizer, AutoModelForSeq2Seq... | 1,621 | 1,621 | 1,621 | NONE | null | ## Environment info
Hi, I am trying to fine-tune a dutch summarization algorithm. I used the [following ](https://github.com/huggingface/notebooks/blob/master/examples/summarization.ipynb) example notebook provided by huggingface.co.
To prepare the targets for the model, we need to tokenize them inside the as_targ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11746 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11746/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11746/comments | https://api.github.com/repos/huggingface/transformers/issues/11746/events | https://github.com/huggingface/transformers/pull/11746 | 893,360,318 | MDExOlB1bGxSZXF1ZXN0NjQ1ODg3NTA4 | 11,746 | Use new evaluation loop in TrainerQA | {
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When writing the new evaluation loop, the code of the special `Trainer` or question answering was not updated, this PR fixes that.
Fixes #11721 | {
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https://api.github.com/repos/huggingface/transformers/issues/11745 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11745/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11745/comments | https://api.github.com/repos/huggingface/transformers/issues/11745/events | https://github.com/huggingface/transformers/pull/11745 | 893,298,416 | MDExOlB1bGxSZXF1ZXN0NjQ1ODM1Njk1 | 11,745 | [Flax MLM] Refactor run mlm with optax | {
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<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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