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https://api.github.com/repos/huggingface/transformers/issues/11135 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11135/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11135/comments | https://api.github.com/repos/huggingface/transformers/issues/11135/events | https://github.com/huggingface/transformers/pull/11135 | 853,163,982 | MDExOlB1bGxSZXF1ZXN0NjExMjk2NTk4 | 11,135 | Adding FastSpeech2 | {
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"Hey @ontocord,\r\n\r\nThanks a lot for opening this pull request :-) \r\n\r\nWe are very much open to adding FastSpeech2 to `transformers`! One thing that is quite important to us is that we stick as much as possible to the original implementation of the model. \r\n\r\nIMO, the easiest way to approach this would b... | 1,617 | 1,641 | 1,619 | NONE | null | # What does this PR do?
This is a draft PR for Fastspeech2 which includes melgan and a custom g2p pythorch module. See https://huggingface.co/ontocord/fastspeech2-en
## Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors which may... | {
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https://api.github.com/repos/huggingface/transformers/issues/11134 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11134/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11134/comments | https://api.github.com/repos/huggingface/transformers/issues/11134/events | https://github.com/huggingface/transformers/issues/11134 | 853,135,648 | MDU6SXNzdWU4NTMxMzU2NDg= | 11,134 | Problem with data download | {
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"@chatzich your question seems similar to this - #2323. ",
"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://git... | 1,617 | 1,621 | 1,621 | NONE | null | Hello can I ask which is the directory that the downloaded stuff is stored? I am trying to bundle these data into a docker image and every time the image is built transformers is downloading the 440M data from the beggining | {
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https://api.github.com/repos/huggingface/transformers/issues/11133 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11133/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11133/comments | https://api.github.com/repos/huggingface/transformers/issues/11133/events | https://github.com/huggingface/transformers/pull/11133 | 853,071,777 | MDExOlB1bGxSZXF1ZXN0NjExMjE5Mjgw | 11,133 | Typo fix of the name of BertLMHeadModel in BERT doc | {
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Typo fix in BERT doc.
I was confused that I couldn't find the implementation and discussion log of `BertModelLMHeadModel,` and found that `BertLMHeadModel` is the correct name.
It was titled `BertModelLMHeadModel` in the BERT doc, and it seems `BertLMHeadModel` is the intended name.
## ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11132 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11132/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11132/comments | https://api.github.com/repos/huggingface/transformers/issues/11132/events | https://github.com/huggingface/transformers/issues/11132 | 852,981,758 | MDU6SXNzdWU4NTI5ODE3NTg= | 11,132 | Clear add labels to token classification example | {
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"Have you looked at the [run_ner](https://github.com/huggingface/transformers/blob/master/examples/token-classification/run_ner.py) example and its corresponding [notebook](https://github.com/huggingface/notebooks/blob/master/examples/token_classification.ipynb)?",
"Thanks for getting back to me so quickly @sgugg... | 1,617 | 1,621 | 1,621 | NONE | null | I have spent a lot of time looking for a clear example on how to add labels to an existing model. For example, I would like to train Bert to recognize addresses in addition to the B-PER, B-ORG, etc. labels. So I think I would do the following
1. Add B-ADDRESS, B-CITY, B-STATE, etc. to a portion of a data set (like t... | {
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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)... | 1,617 | 1,621 | 1,621 | NONE | null | # What does this PR do?
fix a typo in tutorial
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https://api.github.com/repos/huggingface/transformers/issues/11130 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11130/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11130/comments | https://api.github.com/repos/huggingface/transformers/issues/11130/events | https://github.com/huggingface/transformers/pull/11130 | 852,965,558 | MDExOlB1bGxSZXF1ZXN0NjExMTM5MDMz | 11,130 | Fix LogitsProcessor documentation | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
When training or fine tuning models, data collator provided in huggingface isn't enough.
For example, if we want to further pretrain `mBART... | {
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https://api.github.com/repos/huggingface/transformers/issues/11128 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11128/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11128/comments | https://api.github.com/repos/huggingface/transformers/issues/11128/events | https://github.com/huggingface/transformers/pull/11128 | 852,823,550 | MDExOlB1bGxSZXF1ZXN0NjExMDE2MTk3 | 11,128 | Run mlm pad to multiple for fp16 | {
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This PR uses padding to a multiple of 8 in the run_mlm.py language modeling example, when fp16 is used. Since the DataCollatorForLanguageModeling did not initially accept the pad_to_multiple_of option, that functionality was added.
Fixes #10627
## Before submitting
- [X] Did you write any... | {
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This PR fixes issues that a user may have with `make quality`/`make fixup` when all backends are not installed: in that case `requires_backends` is imported in the main init on top of the dummy objects and the script complains it's not documented.
The PR also refactors the white-list for t... | {
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https://api.github.com/repos/huggingface/transformers/issues/11126 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11126/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11126/comments | https://api.github.com/repos/huggingface/transformers/issues/11126/events | https://github.com/huggingface/transformers/issues/11126 | 852,707,235 | MDU6SXNzdWU4NTI3MDcyMzU= | 11,126 | Create embeddings vectors for the context parameter of QuestionAnsweringPipeline for reusability. | {
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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)... | 1,617 | 1,621 | 1,621 | NONE | null | Create embeddings vectors for the context parameter of QuestionAnsweringPipeline for reusability.
**Scinario**
For each time we pass question and context to QuestionAnsweringPipeline, the context vector is created. Is there a way to create this context for once and just pass the question to save time and make inferen... | {
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"The text you are providing is probably too long for the model. Most Transformer models accept a sequence length of 512 tokens.\r\n\r\nWhich model did you use?",
"I just used the general q-a pipeline:\r\nfrom google.colab import files\r\nuploaded = files.upload() \r\nfilename = \"New_Spark_Questions.txt\"\r\nnew_... | 1,617 | 1,621 | 1,621 | NONE | null | When I try to feed in this context from a long txt file lets say below:
[New_Spark_Questions.txt](https://github.com/huggingface/transformers/files/6273496/New_Spark_Questions.txt)
and I feed in a question from that txt file: Would police or the FBI ever be able to access DNA or other information collected?
it is no... | {
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https://api.github.com/repos/huggingface/transformers/issues/11124 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11124/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11124/comments | https://api.github.com/repos/huggingface/transformers/issues/11124/events | https://github.com/huggingface/transformers/issues/11124 | 852,636,637 | MDU6SXNzdWU4NTI2MzY2Mzc= | 11,124 | ALBERT pretrained tokenizer loading failed on Google Colab | {
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"Have you installed the [sentencepiece](https://github.com/google/sentencepiece) library?",
"> Have you installed the [sentencepiece](https://github.com/google/sentencepiece) library?\r\n\r\nYes.\r\n\r\n```\r\n!pip install transformers\r\n!pip install sentencepiece\r\n```\r\n\r\n```\r\nRequirement already satisfi... | 1,617 | 1,617 | 1,617 | NONE | null | I tried the example code for ALBERT model on Google Colab:
```
from transformers import AlbertTokenizer, AlbertModel
import torch
tokenizer = AlbertTokenizer.from_pretrained('albert-base-v2')
model = AlbertModel.from_pretrained('albert-base-v2')
inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11123 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11123/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11123/comments | https://api.github.com/repos/huggingface/transformers/issues/11123/events | https://github.com/huggingface/transformers/pull/11123 | 852,568,686 | MDExOlB1bGxSZXF1ZXN0NjEwNzk3NTc5 | 11,123 | Adds use_auth_token with pipelines | {
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This PR adds `use_auth_token` as a named parameter to the `pipeline`. Also fixed `AutoConfig.from_pretrained` adding the `model_kwargs` as `**kwargs` to load private model with `use_auth_token`.
**Possible Usage for `pipeline` with `use_auth_token`:**
with model_kwargs
```python
hf_pip... | {
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https://api.github.com/repos/huggingface/transformers/issues/11122 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11122/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11122/comments | https://api.github.com/repos/huggingface/transformers/issues/11122/events | https://github.com/huggingface/transformers/pull/11122 | 852,483,434 | MDExOlB1bGxSZXF1ZXN0NjEwNzI4MDcx | 11,122 | fixed max_length in beam_search() and group_beam_search() to use beam… | {
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"hi @GeetDsa \r\n\r\nThanks a lot for the PR. I understand the issue and IMO what should be done here is to make sure to pass the same `max_length` to the `BeamScorer` and `beam_search` instead of changing the method.\r\n\r\nThis is because the overall philosophy of `generate` is that whenever some argument is `Non... | 1,617 | 1,622 | 1,622 | CONTRIBUTOR | null | …_scorer.max_length
# What does this PR do?
Fixes the issue #11040
`beam_search()` and `group_beam_search()` uses `beam_scorer.max_length` if `max_length` is not explicitly passed.
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"Maybe of interest to @Narsil ",
"@DeveloperInProgress .\r\nSorry, there is no exhaustive list of those as of yet (as a number of them are actual exceptions raised by transformers itself)\r\n\r\nWhat I can say, is that Environment and ValueError are simply displayed as is and treated as user error (usually proble... | 1,617 | 1,617 | 1,617 | NONE | null | I understand that the inference API returns a json with "error" field if an error occurs. Where can I find the list of such possible errors? | {
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https://api.github.com/repos/huggingface/transformers/issues/11120 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11120/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11120/comments | https://api.github.com/repos/huggingface/transformers/issues/11120/events | https://github.com/huggingface/transformers/pull/11120 | 852,413,510 | MDExOlB1bGxSZXF1ZXN0NjEwNjcwMjU0 | 11,120 | Adds a note to resize the token embedding matrix when adding special … | {
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This was added to the `add_tokens` method, but was forgotten on the `add_special_tokens` method.
See the updated docs: https://191874-155220641-gh.circle-artifacts.com/0/docs/_build/html/internal/tokenization_utils.html?highlight=add_special_tokens#transformers.tokenization_utils_base.SpecialTokensMixin.a... | {
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https://api.github.com/repos/huggingface/transformers/issues/11119 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11119/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11119/comments | https://api.github.com/repos/huggingface/transformers/issues/11119/events | https://github.com/huggingface/transformers/pull/11119 | 852,397,579 | MDExOlB1bGxSZXF1ZXN0NjEwNjU2NzMw | 11,119 | updated user permissions based on umask | {
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"Thank you, @bhavitvyamalik. This is excellent\r\n\r\nLet's first review what we are trying to correct.\r\n\r\nLooking under `~/.cache/huggingface/transformers/` I see:\r\n```\r\n-rw------- 1 stas stas 1.1K Oct 16 13:27 00209bab0f0b1af5ef50d4d8a2f8fb0589ec747d29d975f496d377312fc50ea7.688a102406298bdd2190bac9e0c6da... | 1,617 | 1,623 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
Fixes [#2065](https://github.com/huggingface/datasets/issues/2065) where cached model's permissions change depending on running user's umask.
## Who can review?
@thomwolf @stas00 please let me know if any other changes are required in this.
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This PR removes the custom styling of the progress bar, because the default one is actually prettier and it can cause some lag on some browsers (like Safari) to recompute the style at each update of the progress bar.
It also removes the timing metrics which do not make much sense form the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11117 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11117/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11117/comments | https://api.github.com/repos/huggingface/transformers/issues/11117/events | https://github.com/huggingface/transformers/pull/11117 | 852,364,374 | MDExOlB1bGxSZXF1ZXN0NjEwNjI5MzQ5 | 11,117 | Add an error message for Reformer w/ .backward() | {
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"@forest1988 thank you for your PR! Patrick is off for a couple of weeks, but will review once he's back. Thank you for your patience!",
"@LysandreJik \r\nThank you for letting me know about that! That's totally fine!\r\n"
] | 1,617 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
Add an error message that fires when Reformer is not in training mode, but one runs .backward().
Fixes #10370
## 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](ht... | {
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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)... | 1,617 | 1,621 | 1,621 | NONE | null | I have a pre-trained model that i have cached locally and i am passing model_name_or_path.
When i pass do_train, it results in the following code executing causing a second model reload. Unfortunately, this codepath ignores the config causing default num_labels to be passed leading to pytorch assert.
If last_chec... | {
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https://api.github.com/repos/huggingface/transformers/issues/11115 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11115/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11115/comments | https://api.github.com/repos/huggingface/transformers/issues/11115/events | https://github.com/huggingface/transformers/issues/11115 | 852,255,198 | MDU6SXNzdWU4NTIyNTUxOTg= | 11,115 | Nested MLflow logging with cross-validation | {
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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)... | 1,617 | 1,621 | 1,621 | NONE | null | First of all: I apologize for not using the bug/feature request templates, I believe I'm having more of a general question here.
I was wondering if there is any way in which the `MLflowCallback` can be **used in conjunction with a cross-validation training procedure**?
In each split, I am initializing a new mode... | {
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https://api.github.com/repos/huggingface/transformers/issues/11114 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11114/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11114/comments | https://api.github.com/repos/huggingface/transformers/issues/11114/events | https://github.com/huggingface/transformers/issues/11114 | 852,198,560 | MDU6SXNzdWU4NTIxOTg1NjA= | 11,114 | Add CodeTrans, a model for source code generation, documentation generation and similar subtasks. | {
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"Hi @tanmaylaud ,\r\n\r\nThanks for creating this issue and your interest.\r\n\r\nWe already integrated our models into hugging face :)\r\nYou can find all of them here:\r\n[https://huggingface.co/models?search=code_trans_](https://huggingface.co/models?search=code_trans_)\r\n\r\n@patrickvonplaten : FYI, we have re... | 1,617 | 1,631 | 1,631 | CONTRIBUTOR | null | # 🌟 New model addition
Paper: https://arxiv.org/abs/2104.02443
<!-- Important information -->
## Open source status
* [ ] the model implementation is available: https://github.com/agemagician/CodeTrans
* [ ] the model weights are available:
https://github.com/agemagician/CodeTrans
Currently tensorflow.
* [ ] who ... | {
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"Hi @DapangLiu \r\n\r\nThe `resume_from_checkpoint` should work for any `PreTrainedModel` class. Even though `EncoderDecoder` model is initialized using two sepearte models when save it using `save_pretarined` it's saved as a single model and can be loaded using `from_pretrained`.\r\n\r\nMake sure that your checkpo... | 1,617 | 1,621 | 1,618 | NONE | null | Hi transformers developers:
First thanks to your great work!
I noticed there was a resume from checkpoint method for the Seq2SeqTrainer when the LM was BART-like out-of-the-box Seq2Seq LMs, like this:
https://github.com/huggingface/transformers/blob/fd338abdeba25cb40b27650ba2203ac6789d2776/examples/seq2seq/run... | {
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https://api.github.com/repos/huggingface/transformers/issues/11112 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11112/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11112/comments | https://api.github.com/repos/huggingface/transformers/issues/11112/events | https://github.com/huggingface/transformers/issues/11112 | 852,108,599 | MDU6SXNzdWU4NTIxMDg1OTk= | 11,112 | XLNET tokenization changes after saving and loading | {
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"Wow, that was quick, I just saw @stefan-it recent comment in our failing PR: https://github.com/deepset-ai/FARM/pull/727#issuecomment-814641885\r\n\r\nSo loading the XLNet Tokenizer in slow mode with\r\n```python\r\ntokenizer_orig = AutoTokenizer.from_pretrained(\"xlnet-base-cased\", use_fast=True, from_slow=True)... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | ## Environment info
- Fresh Colab env with !pip install transformers[sentencepiece]
- `transformers` version: 4.5.0
- Behavior also observed in previous Transformers versions >= 4.3.0
### Who can help
xlnet tokenization: @patrickvonplaten
## Information
Our CI reported different tokenization when saving and... | {
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https://api.github.com/repos/huggingface/transformers/issues/11111 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11111/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11111/comments | https://api.github.com/repos/huggingface/transformers/issues/11111/events | https://github.com/huggingface/transformers/issues/11111 | 852,068,514 | MDU6SXNzdWU4NTIwNjg1MTQ= | 11,111 | Where to add truncation=True for warning Truncation was not explicitely activated but max_length is provided a specific value, please use truncation=True to explicitely truncate examples to max length. Defaulting to 'longest_first' truncation strategy. If you encode pairs of sequences (GLUE-style) with the tokenizer yo... | {
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"> encoding = tokenizer.encode_plus(\r\n> sample_txt,\r\n> max_length=32,\r\n> add_special_tokens=True, # Add '[CLS]' and '[SEP]'\r\n> return_token_type_ids=False,\r\n> pad_to_max_length=True,\r\n> return_attention_mask=True,\r\n> return_tensors='pt', # Return PyTorch tensors\r\n> )\r\... | 1,617 | 1,621 | 1,621 | NONE | null | Don't know where to change the code for sentiment analysis. I just wanted to add truncation=True. I'm getting warning tokenizer started throwing this warning,
**Truncation was not explicitly activated but max_length is provided with a specific value, please use truncation=True to explicitly truncate examples to max... | {
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https://api.github.com/repos/huggingface/transformers/issues/11110 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11110/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11110/comments | https://api.github.com/repos/huggingface/transformers/issues/11110/events | https://github.com/huggingface/transformers/pull/11110 | 852,068,159 | MDExOlB1bGxSZXF1ZXN0NjEwMzgxNDkz | 11,110 | [versions] handle version requirement ranges | {
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I don't know if it fixes the problem reported in https://github.com/huggingface/transformers/issues/11107 as I can't reproduce it.
One odd thin... | {
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https://api.github.com/repos/huggingface/transformers/issues/11109 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11109/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11109/comments | https://api.github.com/repos/huggingface/transformers/issues/11109/events | https://github.com/huggingface/transformers/pull/11109 | 852,055,897 | MDExOlB1bGxSZXF1ZXN0NjEwMzcxMDQ0 | 11,109 | [BigBird] fix bigbird slow tests | {
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This PR will fix bigbird's slow tests as per our discussion @LysandreJik.
<!--
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 ref... | {
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https://api.github.com/repos/huggingface/transformers/issues/11108 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11108/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11108/comments | https://api.github.com/repos/huggingface/transformers/issues/11108/events | https://github.com/huggingface/transformers/issues/11108 | 852,027,718 | MDU6SXNzdWU4NTIwMjc3MTg= | 11,108 | [run_clm] handling large inputs | {
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"We don't care since we are not feeding those inputs to the model, they are split afterwards: the preprocessing has two stages, first tokenize everything then create the blocks of size `block_size`. We can't truncate large inputs because then the special tokens would be added weirdly and there is no way I know of o... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | This could probably use a bit of sorting out:
> [WARNING|tokenization_utils_base.py:3138] 2021-04-06 21:29:29,790 >> Token indices sequence length is longer than the specified maximum sequence length for this model (1462828 > 1024). Running this sequence through the model will result in indexing errors
This doesn... | {
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https://api.github.com/repos/huggingface/transformers/issues/11107 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11107/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11107/comments | https://api.github.com/repos/huggingface/transformers/issues/11107/events | https://github.com/huggingface/transformers/issues/11107 | 852,022,593 | MDU6SXNzdWU4NTIwMjI1OTM= | 11,107 | Dependency version check fails for tokenizers | {
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"Thank you for this report, @guyrosin \r\n\r\nAny idea how we could reproduce this problem? This works for me:\r\n```\r\n$ python -c \"from importlib.metadata import version; print(version('tokenizers'))\"\r\n0.10.1\r\n```\r\n\r\nI do see a different problem though. I see we now have: `\"tokenizers>=0.10.1,<0.11\"`... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.5.0
- Platform: Linux-4.15.0-134-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.1 (False)
- Tensorflow version (GPU?): 2.4.0 (False)
- Using GPU in script?: N/A
- Using distributed or parallel set-up in script?: N/A
- `tokeni... | {
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https://api.github.com/repos/huggingface/transformers/issues/11106 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11106/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11106/comments | https://api.github.com/repos/huggingface/transformers/issues/11106/events | https://github.com/huggingface/transformers/issues/11106 | 852,019,622 | MDU6SXNzdWU4NTIwMTk2MjI= | 11,106 | lr scheduler before optimizer step warning | {
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"I think that's because of the dynamic loss scaling in FP16, which skips some optimizer steps at the beginning of training if the gradients overflowed (while it's trying to find the best loss scale). Not sure of the best way to treat this:\r\n\r\n- If we somehow manage to catch those skipped optimizer steps and del... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | for a really long time now we have this warning being spewed up on startup:
> torch/optim/lr_scheduler.py:132: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`. Failu... | {
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https://api.github.com/repos/huggingface/transformers/issues/11105 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11105/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11105/comments | https://api.github.com/repos/huggingface/transformers/issues/11105/events | https://github.com/huggingface/transformers/pull/11105 | 851,996,427 | MDExOlB1bGxSZXF1ZXN0NjEwMzIwODc0 | 11,105 | fix: The 'warn' method is deprecated | {
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examples/language-modeling/run_clm.py:340: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
logger.warn(
```
This PR is fixing many dozes of those with:
```
find . -type d -name ".git" -prune -o -type f -exec perl -pi -e 's|logger.warn\(|logger.warning(|g' {} \;
```
@LysandreJi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11104 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11104/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11104/comments | https://api.github.com/repos/huggingface/transformers/issues/11104/events | https://github.com/huggingface/transformers/issues/11104 | 851,991,701 | MDU6SXNzdWU4NTE5OTE3MDE= | 11,104 | Model config is logged twice on startup | {
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"Yes, this is known and on the roadmap for the tokenizers: the goal is for them to use their specific config instead of the model config. Hoping to get to that in the next month or so!"
] | 1,617 | 1,620 | null | CONTRIBUTOR | null | Currently, the model config is logged twice during startup:
1. via `AutoConfig.from_pretrained`
2. via `AutoTokenizer.from_pretrained` -> `AutoConfig.from_pretrained`
Should there be a state variable that prevents the logging of the same config twice?
This happens for example with all example scripts:
Exam... | {
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https://api.github.com/repos/huggingface/transformers/issues/11103 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11103/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11103/comments | https://api.github.com/repos/huggingface/transformers/issues/11103/events | https://github.com/huggingface/transformers/pull/11103 | 851,985,535 | MDExOlB1bGxSZXF1ZXN0NjEwMzExODI1 | 11,103 | dead link fixed | {
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Fixes a dead link of the documentation.
## Before submitting
- [X] 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#sta... | {
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"Hi @MoonshotQuest, this is because you haven't resized your token embedding matrix after adding new tokens to your vocabulary. The tokenizer can therefore generate new tokens, but the model doesn't know how to handle them. The `add_tokens` method has a [note for that](https://huggingface.co/transformers/internal/t... | 1,617 | 1,617 | 1,617 | NONE | null | Hi all, I need your help as I'm stuck on an issue IndexError trying to finetune GPT2 using **run_clm.py** while adding special tokens. The error is trigger at this line of **functional.py**:
`return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)`
**run_clm.py** has been "barely" modified j... | {
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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)... | 1,617 | 1,621 | 1,621 | NONE | null | Like you mention below: I am doing a question answering task I was using BERT originally so can
I convert from BERT to this?
To download and use any of the pretrained models on your given task, you just need to use those three lines of codes (PyTorch version):
>>> from transformers import AutoTokenizer, AutoModel
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https://api.github.com/repos/huggingface/transformers/issues/11100 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11100/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11100/comments | https://api.github.com/repos/huggingface/transformers/issues/11100/events | https://github.com/huggingface/transformers/pull/11100 | 851,877,449 | MDExOlB1bGxSZXF1ZXN0NjEwMjI1NDY0 | 11,100 | Dummies multi backend | {
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We now have several objects that requires two of the backends and not just one. This PR adds support for dummies that require two backends.
To achieve that the various `requires_xxx` function used internally are refactored in one `requires_backends` function that takes one or a list of bac... | {
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@LysandreJik | {
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@LysandreJik
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https://api.github.com/repos/huggingface/transformers/issues/11097 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11097/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11097/comments | https://api.github.com/repos/huggingface/transformers/issues/11097/events | https://github.com/huggingface/transformers/pull/11097 | 851,774,508 | MDExOlB1bGxSZXF1ZXN0NjEwMTM5NjQ1 | 11,097 | Auto feature extractor | {
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"Really awesome! Thanks a lot Sylvain!"
] | 1,617 | 1,617 | 1,617 | COLLABORATOR | null | # What does this PR do?
This PR does a few things that are all tangled together to bring a new `AutoFeatureExtractor` API.
First it removes the check at init for `Speech2TextFeatureExtractor` to only import this object when the `speech` dep is installed and add a dummy class if it's not, so it's easier to add spe... | {
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"Hi @sboparen \r\n\r\nRight now the caching is implemented such that when `past_key_values` are passed current token length must be 1.\r\nThis is due to the local attention layer which uses dynamic block length. This is a known limitation and I'm working on it at the moment.",
"This issue has been automatically m... | 1,617 | 1,623 | 1,623 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0.dev0
- Platform: Linux-5.11.11-arch1-1-x86_64-with-glibc2.33
- Python version: 3.9.2
- PyTorch version... | {
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https://api.github.com/repos/huggingface/transformers/issues/11095 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11095/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11095/comments | https://api.github.com/repos/huggingface/transformers/issues/11095/events | https://github.com/huggingface/transformers/issues/11095 | 851,662,971 | MDU6SXNzdWU4NTE2NjI5NzE= | 11,095 | XLMRobertaTokenizerFast gives incorrect offset mappings when loaded from disk | {
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"This does not appear to occur with `BertTokenizerFast`, `GPT2TokenizerFast`, or `RobertaTokenizerFast`.",
"This bug was introduced in `4.3.0`, I do not encounter this issue when running with `transformers==4.2.2` ",
"Hi @johnmccain! This is unfortunately a known issue, and an issue on which we're working. It's... | 1,617 | 1,617 | 1,617 | NONE | null | ## Environment info
- `transformers` version: 4.5.0
- Platform: Windows 10 (replicated on Ubuntu 18.04 as well)
- Python version: 3.6.8
- PyTorch version (GPU?): n/a
- Tensorflow version (GPU?): n/a
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
Full package list:
```
cer... | {
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https://api.github.com/repos/huggingface/transformers/issues/11094 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11094/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11094/comments | https://api.github.com/repos/huggingface/transformers/issues/11094/events | https://github.com/huggingface/transformers/issues/11094 | 851,606,494 | MDU6SXNzdWU4NTE2MDY0OTQ= | 11,094 | Using BERTModel for learning a siamese encoder | {
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"Hi,\r\n\r\nCan you please ask this question on the [forum](https://discuss.huggingface.co/) rather than here? For example, [this comment](https://discuss.huggingface.co/t/what-are-some-recommended-pretrained-models-for-extracting-semantic-feature-on-single-sentence/2698/3?) might help you already.\r\n\r\nThe autho... | 1,617 | 1,617 | 1,617 | NONE | null | Hi! This is more of a question than a bug report. Can I use BERTModel without any modifications to train a BERT-based siamese encoder?
(Not sure if this really is a BERT-specific question, but I will tag @LysandreJik just in case)
This is how my training step looks like:
```
optimizer.zero_grad()
outputs_a... | {
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https://api.github.com/repos/huggingface/transformers/issues/11093 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11093/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11093/comments | https://api.github.com/repos/huggingface/transformers/issues/11093/events | https://github.com/huggingface/transformers/issues/11093 | 851,573,042 | MDU6SXNzdWU4NTE1NzMwNDI= | 11,093 | Cannot get test logits after training for TFSequenceClassifier on TF 2 | {
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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)... | 1,617 | 1,621 | 1,621 | NONE | null | - `transformers` version: 4.4.2
- Platform: Linux-5.4.17-2036.102.0.2.el7uek.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.0 (True)
- Tensorflow version (GPU?): 2.4.1 (True)
- Using GPU in script?: (True)
- Using distributed or parallel set-up in script?: (True)
After fitti... | {
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https://api.github.com/repos/huggingface/transformers/issues/11092 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11092/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11092/comments | https://api.github.com/repos/huggingface/transformers/issues/11092/events | https://github.com/huggingface/transformers/issues/11092 | 851,439,069 | MDU6SXNzdWU4NTE0MzkwNjk= | 11,092 | [question/help] T5 cross-attention shows inconsistent results | {
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"Hi @dupuisIRT \r\n\r\nI'm not sure if this qualifies as an issue with the model, I think you should post this on the [forum](https://discuss.huggingface.co/) instead. I am not sure if I can help with this.",
"Thanks @patil-suraj, you are right, I will do it.\r\n"
] | 1,617 | 1,618 | 1,618 | NONE | null | # :question: Questions & Help
## Environment info
```
Python version: 3.7.10
PyTorch version (GPU?): '1.7.1+cu110' (True)
Transformer version: '4.5.0.dev0'
```
## Who can help
TextGeneration: @TevenLeScao
Text Generation: @patrickvonplaten
examples/seq2seq: @patil-suraj
## Details
I am trying to us... | {
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https://api.github.com/repos/huggingface/transformers/issues/11091 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11091/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11091/comments | https://api.github.com/repos/huggingface/transformers/issues/11091/events | https://github.com/huggingface/transformers/pull/11091 | 851,402,347 | MDExOlB1bGxSZXF1ZXN0NjA5ODMyMjYy | 11,091 | accelerate question answering examples with no trainer | {
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"Thankyou @sgugger for guiding me at every step. ",
"Thank *you* for all your work on this :-)",
"One last step: could you make a PR to update the README of this folder to explain how to use the new scripts you added (you can take inspiration in the other folders).",
"> One last step: could you make a PR to u... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11090 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11090/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11090/comments | https://api.github.com/repos/huggingface/transformers/issues/11090/events | https://github.com/huggingface/transformers/pull/11090 | 851,398,152 | MDExOlB1bGxSZXF1ZXN0NjA5ODI4ODky | 11,090 | added new merged Trainer test | {
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This PR adds a an additional test for `model-parallelism` using the merged `Trainer` and the `examples/` `run_glue.py` . Already tested ✅ | {
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https://api.github.com/repos/huggingface/transformers/issues/11089 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11089/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11089/comments | https://api.github.com/repos/huggingface/transformers/issues/11089/events | https://github.com/huggingface/transformers/issues/11089 | 851,369,995 | MDU6SXNzdWU4NTEzNjk5OTU= | 11,089 | [Possible Bug] Getting IndexError: list index out of range when fine-tuning custom LM model | {
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"Save problem with #10947 but it is still unsolved. Can anyone of HuggingFace's authors please help us out on this issue?\r\n",
"The issue you are mentioning concerns TensorFlow models which you are not using so there is no link. In your case, tehre is a problem with your dataset (this is where the error arises f... | 1,617 | 1,621 | 1,621 | NONE | null | ## Environment info
`transformers` version: 4.3.3
Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
Python version: 3.7.10
PyTorch version (GPU?): 1.7.1+cu101 (False)
Tensorflow version (GPU?): 2.4.1 (False)
Using GPU in script?: True/False
Using distributed or parallel set-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11088 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11088/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11088/comments | https://api.github.com/repos/huggingface/transformers/issues/11088/events | https://github.com/huggingface/transformers/issues/11088 | 851,317,255 | MDU6SXNzdWU4NTEzMTcyNTU= | 11,088 | CTRL model can not work | {
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"I also try to git pull the updated codes and run the official command:\r\n`python run_generation.py --model_type ctrl --model_name ctrl --temperature 0 --repetition 1.2`\r\n\r\nERROR:\r\n\r\n> 04/07/2021 10:22:08 - WARNING - main - device: cpu, n_gpu: 0, 16-bits training: False\r\n> 04/07/2021 10:23:25 - INFO - ma... | 1,617 | 1,621 | 1,621 | NONE | null | torch ver: 1.8.1+cu102
transformers ver: 4.4.2
I adopt the example codes from https://github.com/huggingface/transformers/blob/master/examples/text-generation/run_generation.py
to generate text by using ctrl.
here is the head part of my codes:
```
import torch
from transformers import CTRLTokenizer, CTRLLMHe... | {
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https://api.github.com/repos/huggingface/transformers/issues/11087 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11087/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11087/comments | https://api.github.com/repos/huggingface/transformers/issues/11087/events | https://github.com/huggingface/transformers/issues/11087 | 851,227,715 | MDU6SXNzdWU4NTEyMjc3MTU= | 11,087 | using RAG with local documents | {
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"duplicated"
] | 1,617 | 1,617 | 1,617 | NONE | null | Hi,
I have a requirement that model should search for relevant documents before answering the query. I found RAG from Facebook AI which perfectly aligns with my requirement . Also saw [this](https://huggingface.co/blog/ray-rag) blog from HF and came to know that HF implemented RAG which is awesome!
My doubt is whet... | {
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https://api.github.com/repos/huggingface/transformers/issues/11086 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11086/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11086/comments | https://api.github.com/repos/huggingface/transformers/issues/11086/events | https://github.com/huggingface/transformers/issues/11086 | 851,221,553 | MDU6SXNzdWU4NTEyMjE1NTM= | 11,086 | using RAG with local documents | {
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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!",
"ok. Created [issue](https://discuss.huggingface.co/t/using-rag-with-local-documents/5326) in [forum](https://di... | 1,617 | 1,617 | 1,617 | NONE | null | Hi,
I have a requirement that model should search for relevant documents to answer the query and I found [RAG](https://arxiv.org/pdf/2005.11401.pdf) from [Facebook AI](https://ai.facebook.com/) which perfectly fits my usecase. I also found [this](https://huggingface.co/blog/ray-rag) post in which HuggingFace explains ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11085 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11085/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11085/comments | https://api.github.com/repos/huggingface/transformers/issues/11085/events | https://github.com/huggingface/transformers/pull/11085 | 851,211,087 | MDExOlB1bGxSZXF1ZXN0NjA5NjczNTc4 | 11,085 | Add DistilBertForCausalLM | {
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"Hey @patil-suraj, I've worked on your very helpful comments in #8387 and implemented them in this PR. Apart from a few formatting changes which I still need to work on the main test that is still failing is `python3 -m pytest tests/test_modeling_distilbert.py::DistilBertModelTest::test_for_causal_lm_decoder`. \r\n... | 1,617 | 1,648 | null | CONTRIBUTOR | null | # What does this PR do?
Similar to the `BertLMHeadModel` this PR aims to add a `DistilBertForCausalLM` model in `modeling_distilbert.py`.
Fixes #7397
Replaces #8387
## Who can review?
@patil-suraj | {
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"Are you sure it's properly installed? This code should indeed work if `tensoboard` is installed in the environment in which you execute it. You can try to force the `TensorBoard` integration by adding `report_to=[\"tensorboard\"]` in your `TrainingArguments`.",
"@sgugger My bad, somehow missed tensorboard instal... | 1,617 | 1,617 | 1,617 | NONE | null | From the docs, TrainingArguments has a 'logging_dir' parameter that defaults to 'runs/'. Also, Trainer uses a default callback called TensorBoardCallback that should log to a tensorboard by default.
I use:
```
training_args = TrainingArguments(
output_dir=".",
group_by_length=True,
per_device_train_... | {
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https://api.github.com/repos/huggingface/transformers/issues/11083 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11083/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11083/comments | https://api.github.com/repos/huggingface/transformers/issues/11083/events | https://github.com/huggingface/transformers/pull/11083 | 851,201,221 | MDExOlB1bGxSZXF1ZXN0NjA5NjY1MzIw | 11,083 | added social thumbnail for docs | {
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"Will do it tomorrow. Wanted to add it to `transformers` to be included in the next release"
] | 1,617 | 1,617 | 1,617 | MEMBER | null | # What does this PR do?
I added OpenGraph/ Twitter Card support to the docs to create nice social thumbnails.
To be able to add these I needed to install `sphinxext-op... | {
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"Hi,\r\n\r\nCan you ask this question on the [forum](https://discuss.huggingface.co/) instead of here? There are plenty of people active there, and will help you with this question.\r\n\r\nGithub issues are more for bugs/feature requests, not training-related questions.\r\n\r\nThanks! ",
"This issue has been auto... | 1,617 | 1,621 | 1,621 | NONE | null | ### the model originally use glove and kazuma embedding
```
embeddings = [GloveEmbedding(), KazumaCharEmbedding()]
E = []
for w in tqdm(vocab._index2word):
e = []
for emb in embeddings:
e += emb.emb(w, default='zero')
E.append(e)
with ... | {
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This PR proposes to replace 🤗 with "HuggingFace" for an exception message.
@LysandreJik
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https://api.github.com/repos/huggingface/transformers/issues/11080 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11080/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11080/comments | https://api.github.com/repos/huggingface/transformers/issues/11080/events | https://github.com/huggingface/transformers/issues/11080 | 850,981,033 | MDU6SXNzdWU4NTA5ODEwMzM= | 11,080 | 'BertTokenizer' object has no attribute 'decode' | {
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"@merleyc Instead of using pytorch_pretrained_bert try using transformers:- `from transformers import BertTokenizer`.",
"Thanks a lot, @frankhart2018! It works."
] | 1,617 | 1,617 | 1,617 | NONE | null | ## Environment info
- `transformers` version: 4.4.2 and 3.5.0
- Platform: Linux-3.10.0-957.el7.x86_64-x86_64-with-centos-7.6.1810-Core (centos 7)
- Python version: 3.7.7
- PyTorch version (GPU?): CPU torch=1.6.0
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or par... | {
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https://api.github.com/repos/huggingface/transformers/issues/11079 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11079/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11079/comments | https://api.github.com/repos/huggingface/transformers/issues/11079/events | https://github.com/huggingface/transformers/pull/11079 | 850,969,980 | MDExOlB1bGxSZXF1ZXN0NjA5NDU4NjQw | 11,079 | GPTNeo: handle padded wte (#11078) | {
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Fixes #11078
## Who can review?
@LysandreJik | {
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https://api.github.com/repos/huggingface/transformers/issues/11078 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11078/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11078/comments | https://api.github.com/repos/huggingface/transformers/issues/11078/events | https://github.com/huggingface/transformers/issues/11078 | 850,956,600 | MDU6SXNzdWU4NTA5NTY2MDA= | 11,078 | GPTNeo: importing model with padded vocab size should truncate wte | {
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: latest from `master`
### Who can help
@LysandreJik
## Information
Model I am using (Bert, XLNet .... | {
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https://api.github.com/repos/huggingface/transformers/issues/11077 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11077/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11077/comments | https://api.github.com/repos/huggingface/transformers/issues/11077/events | https://github.com/huggingface/transformers/issues/11077 | 850,912,718 | MDU6SXNzdWU4NTA5MTI3MTg= | 11,077 | bug in quantization on albert | {
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"I fix the quantization bug through changing the matrix multiply process as below\r\nthe old version\r\n```python\r\ncontext_layer = context_layer.permute(0, 2, 1, 3).contiguous()\r\n\r\n# Should find a better way to do this\r\nw = (\r\n self.dense.weight.t()\r\n .view(self.num_attention_heads, self.attention... | 1,617 | 1,617 | 1,617 | NONE | null | The Linear op in albert attention module use the .weight.t() to transpose the weight,but the DynamicQuantizedLinear in forward() do not have the transpose function t()
```python
context_layer = context_layer.permute(0, 2, 1, 3).contiguous()
# Should find a better way to do this
w = (
self.dense.weight.t()
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11076 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11076/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11076/comments | https://api.github.com/repos/huggingface/transformers/issues/11076/events | https://github.com/huggingface/transformers/issues/11076 | 850,896,989 | MDU6SXNzdWU4NTA4OTY5ODk= | 11,076 | FP16 overflow with GPT-Neo when using sequence lengths of 2048. | {
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"Thank you for the report, @LouisCastricato \r\n\r\nI think it's pretty safe to take DeepSpeed out of the equation for now, since as you're saying the problem is due to mixed precision, so let's deal with AMP first.\r\n\r\nHow was GPT-Neo pre-trained?\r\n\r\nIs it by chance the case that GPT-Neo was pre-trained wit... | 1,617 | 1,644 | 1,622 | NONE | null | ## Environment info
- `transformers` version: 4.5.0.dev0
- Platform: Linux-5.4.0-54-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.0+cu111
- Tensorflow version (GPU?): N/A
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No
### Who can help
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11075 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11075/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11075/comments | https://api.github.com/repos/huggingface/transformers/issues/11075/events | https://github.com/huggingface/transformers/pull/11075 | 850,774,450 | MDExOlB1bGxSZXF1ZXN0NjA5Mjk5MDk5 | 11,075 | Big Bird Fast Tokenizer implementation | {
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"> This is great, it's a very clean implementation! However, there are a few things remaining:\r\n> \r\n> * It should be in the BigBird `__init__.py` file\r\n> * It should be in the main `__init__.py` file\r\n> * It should be in the `AutoTokenizer` mapping\r\n> * It should be tested!\r\n\r\nYes, this was just to ge... | 1,617 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
Fixes #11052
## Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors which may be interested in your PR.
@LysandreJik
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This PR adds a base init to `FeatureExtractionMixin` so that high up in the hierarchy, remaining kwargs are set as attributes. Without this, adding new fields to the config of a feature extractor inheriting directly from `FeatureExtractionMixin`, like `ViTFeatureExtractor`, will fail so we wo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11073 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11073/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11073/comments | https://api.github.com/repos/huggingface/transformers/issues/11073/events | https://github.com/huggingface/transformers/pull/11073 | 850,669,245 | MDExOlB1bGxSZXF1ZXN0NjA5MjAyNTcw | 11,073 | Add Readme for language modeling scripts with custom training loop and accelerate | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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"@sgugger I fixed an edge case in the `_collate_batch` method and added tests for that, but if it's ok I'd like to close this PR and open a fresh one.",
"Closing in favor of #11128"
] | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
This PR uses padding to a multiple of 8 in the run_mlm.py language modeling example, when fp16 is used. Since the DataCollatorForLanguageModeling did not initially accept the pad_to_multiple_of option, that functionality was added.
Fixes #10627
## Before submitting
- [x] Did you write an... | {
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Currently, the `DistributedTensorGatherer` responsible for gathering all predictions fails if the arrays to gather are a tuple of tensors, one of which has fixed dimensions (apart form the batch dimensions) and another varying sequence lengths. This is the case if the model has `output_hidden... | {
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https://api.github.com/repos/huggingface/transformers/issues/11070 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11070/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11070/comments | https://api.github.com/repos/huggingface/transformers/issues/11070/events | https://github.com/huggingface/transformers/pull/11070 | 850,573,196 | MDExOlB1bGxSZXF1ZXN0NjA5MTI0MzI0 | 11,070 | Document common config attributes | {
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This PR adds documentation for the common attributes in all model configs, such as `hidden_size`. It also formats the class attributes to be consistent with the rest of the parameters. | {
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"@stas00 can I try this?",
"Yes, please!\r\n\r\nYou run `make docs` to build the docs and then the build ends up under `docs/_build/html/`.\r\n\r\nYou will need to run `pip install -e .[docs,all]` first to get all the packages installed.",
"@stas00 can I work on this?",
"I don't know where @frankhart2018 is w... | 1,617 | 1,622 | 1,622 | CONTRIBUTOR | null | # 🚀 Feature request
`T5ForConditionalGeneration` inherits `generate` from `PreTrainedModel` via `GenerationMixin`.
Currently in our docs if we write:
```
for more info see :meth:`transformers.T5ForConditionalGeneration.generate`
```
it doesn't get resolved in the html docs (it doesn't get a xref link, but le... | {
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https://api.github.com/repos/huggingface/transformers/issues/11068 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11068/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11068/comments | https://api.github.com/repos/huggingface/transformers/issues/11068/events | https://github.com/huggingface/transformers/pull/11068 | 850,552,472 | MDExOlB1bGxSZXF1ZXN0NjA5MTA3MjEy | 11,068 | Add a special tokenizer for CPM model | {
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"The CI error looks irrelevant",
"Sure! Thanks for the guidance.",
"@LysandreJik ping😅",
"Done @LysandreJik ",
"> Great, thanks a lot for adding this! Could you also add the model to the main README since it has a doc page? After doing so run `make fix-copies` so the table in the index is also updated.\n\n... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | Added a special tokenizer (pre-tokenization) for CPM model: https://huggingface.co/TsinghuaAI/CPM-Generate | {
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https://api.github.com/repos/huggingface/transformers/issues/11067 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11067/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11067/comments | https://api.github.com/repos/huggingface/transformers/issues/11067/events | https://github.com/huggingface/transformers/issues/11067 | 850,528,967 | MDU6SXNzdWU4NTA1Mjg5Njc= | 11,067 | Inconsistent ProphetNet Tokenization | {
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"> I would expect the tokenizer to always return the same sequence of tokens. I am not too familiar with how the tokenizers work, so I might be wrong in this assumption. Is this behavior expected and should I just try to avoid re-tokenizing whenever possible?\r\n\r\nWhy should the tokenizer do that? You give him so... | 1,617 | 1,621 | 1,621 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.4.2
- Platform: Linux-5.4.0-1041-aws-x86_64-with-debian-buster-sid
- Python version: 3.7.10
- 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?: no
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11066 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11066/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11066/comments | https://api.github.com/repos/huggingface/transformers/issues/11066/events | https://github.com/huggingface/transformers/pull/11066 | 850,495,476 | MDExOlB1bGxSZXF1ZXN0NjA5MDU5NTkw | 11,066 | Add center_crop to ImageFeatureExtractionMixin | {
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This PR adds the center crop operation to `ImageFeatureExtractionMixin`. It works on PIL Images, NumPy arrays or torch tensors and behaves the same way as torchvision.transforms.CenterCrop: if the image is smaller than the desired size on a given dimension, it will be padded in that dimension... | {
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https://api.github.com/repos/huggingface/transformers/issues/11065 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11065/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11065/comments | https://api.github.com/repos/huggingface/transformers/issues/11065/events | https://github.com/huggingface/transformers/issues/11065 | 850,412,462 | MDU6SXNzdWU4NTA0MTI0NjI= | 11,065 | Token indices sequence length is longer than the specified maximum sequence length for this model (651 > 512) with Hugging face sentiment classifier | {
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"Could you specify `truncation=True` when calling the pipeline with your data?\r\n\r\nReplacing `classifier(\"My name is mark\")` by `classifier(\"My name is mark\", truncation=True)`",
"> Could you specify `truncation=True` when calling the pipeline with your data?\r\n> \r\n> Replacing `classifier(\"My name is m... | 1,617 | 1,655 | 1,620 | NONE | null | I'm trying to get the sentiments for comments with the help of hugging face sentiment analysis pretrained model. It's returning error like **Token indices sequence length is longer than the specified maximum sequence length for this model (651 > 512) with Hugging face sentiment classifier.**
Below I'm attaching the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11064 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11064/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11064/comments | https://api.github.com/repos/huggingface/transformers/issues/11064/events | https://github.com/huggingface/transformers/pull/11064 | 850,370,302 | MDExOlB1bGxSZXF1ZXN0NjA4OTU1NDM3 | 11,064 | Some models have no tokenizers | {
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:warning: this means that we're missing a check to ensure that all tokenizers have an AutoTokenizer. As seen with @sgugger, this will be handled in a script from now on. | {
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https://api.github.com/repos/huggingface/transformers/issues/11063 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11063/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11063/comments | https://api.github.com/repos/huggingface/transformers/issues/11063/events | https://github.com/huggingface/transformers/issues/11063 | 850,365,450 | MDU6SXNzdWU4NTAzNjU0NTA= | 11,063 | save_strategy="no" but checkpoints are created after each evaulation | {
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"Is that a bug or something is wrong with my config?\r\n",
"I wonder if that could be because of load_best_model_at_end? In that case, how can I remove all remaining checkpoints after training is done?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this... | 1,617 | 1,621 | 1,621 | NONE | null | I have set the save_strategy to no in my TrainingArguments, yet, checkpoints are being created every 100 steps, here is how I configured TA:
<img width="790" alt="image" src="https://user-images.githubusercontent.com/13952413/113585244-faad7880-95f9-11eb-90f5-069a1a688723.png">
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https://api.github.com/repos/huggingface/transformers/issues/11062 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11062/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11062/comments | https://api.github.com/repos/huggingface/transformers/issues/11062/events | https://github.com/huggingface/transformers/pull/11062 | 850,362,654 | MDExOlB1bGxSZXF1ZXN0NjA4OTQ5MDk3 | 11,062 | Pin docutils | {
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https://api.github.com/repos/huggingface/transformers/issues/11061 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11061/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11061/comments | https://api.github.com/repos/huggingface/transformers/issues/11061/events | https://github.com/huggingface/transformers/pull/11061 | 850,356,226 | MDExOlB1bGxSZXF1ZXN0NjA4OTQzNzUx | 11,061 | Replace pkg_resources with importlib_metadata | {
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"This is odd, CI is not being triggered 2nd time in a row!\r\n\r\nI pushed an empty commit and now it started the CI. "
] | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
Fixes #10964. The other reason for this change is that pkg_resources has been [deprecated](https://github.com/pypa/setuptools/commit/8fe85c22cee7fde5e6af571b30f864bad156a010) in favor of importlib_metadata.
`ImportError` looked like the best replacement for `pkg_resources.VersionConflict` ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11060 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11060/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11060/comments | https://api.github.com/repos/huggingface/transformers/issues/11060/events | https://github.com/huggingface/transformers/pull/11060 | 850,351,148 | MDExOlB1bGxSZXF1ZXN0NjA4OTM5NDIw | 11,060 | Remove unnecessary space | {
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closes https://github.com/huggingface/transformers/issues/11034#issuecomment-812628691 | {
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https://api.github.com/repos/huggingface/transformers/issues/11059 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11059/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11059/comments | https://api.github.com/repos/huggingface/transformers/issues/11059/events | https://github.com/huggingface/transformers/issues/11059 | 850,305,827 | MDU6SXNzdWU4NTAzMDU4Mjc= | 11,059 | run_summarization: fine tuning Pegasus large, CUDA out of memory error | {
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"@patil-suraj : Any thoughts or suggestions? ",
"Hi @karrtikiyer \r\n\r\n`pegasus-large ` is quite a bid model (for a 16GB GPU), so I won't be surprised if it OOMs. I would really recommend you to try using `deepspeed` or `fairscale`, which will definitely help you to fine-tune this model more efficiently. To gi... | 1,617 | 1,621 | 1,621 | NONE | null | ## Environment info
- `transformers` version: 4.5.0.dev0
- Platform: Linux-4.14.225-121.362.amzn1.x86_64-x86_64-with-glibc2.9
- Python version: 3.6.13
- PyTorch version (GPU?): 1.8.1+cu102 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Directly running the example script `run_summa... | {
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https://api.github.com/repos/huggingface/transformers/issues/11058 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11058/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11058/comments | https://api.github.com/repos/huggingface/transformers/issues/11058/events | https://github.com/huggingface/transformers/issues/11058 | 850,284,580 | MDU6SXNzdWU4NTAyODQ1ODA= | 11,058 | MemoryError when computing metrics on Wav2Vec2 | {
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"To properly compute the metrics, the evaluation loop stores all the prediction in a NumPy array. It looks like your evaluation dataset is very large, so you should use evaluate/predict on smaller subsets then save those predictions to disk.",
"Thank you. I think I will make my own evaluation loop to compute metr... | 1,617 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Linux-5.8.0-48-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11057 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11057/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11057/comments | https://api.github.com/repos/huggingface/transformers/issues/11057/events | https://github.com/huggingface/transformers/issues/11057 | 850,271,550 | MDU6SXNzdWU4NTAyNzE1NTA= | 11,057 | Difference in tokenizer output depending on where `add_prefix_space` is set. | {
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"@sai-prasanna This is because RobertaTokenizer is subclassed from GPT2Tokenizer (methods from this class are shared for tokenization) and the params are passed to the parent class only when you instantiate RobertaTokenizer. So, when you change the value of add_prefix_space to True after instantiating RobertaTokeni... | 1,617 | 1,623 | 1,623 | 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: 4.4.2
- Platform: Linux-4.19.112+-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/11056 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11056/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11056/comments | https://api.github.com/repos/huggingface/transformers/issues/11056/events | https://github.com/huggingface/transformers/pull/11056 | 850,245,242 | MDExOlB1bGxSZXF1ZXN0NjA4ODQ5MjAz | 11,056 | Add DeiT (PyTorch) | {
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"Thanks for the review, I've addressed your comments.\r\n\r\nHowever, I'm getting the following error when running `make quality`:\r\n```\r\nException: Found the following copy inconsistencies:\r\n- src/transformers\\models\\deit\\modeling_deit.py: copy does not match models.vit.modeling_vit.ViTSelfOutput at line 1... | 1,617 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
This PR adds [DeiT (Data-efficient Image Transformers)](https://ai.facebook.com/blog/data-efficient-image-transformers-a-promising-new-technique-for-image-classification/) by Facebook AI.
It's a near-copy of ViT, with only some slight changes:
- DeiT add a distillation token, besides th... | {
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https://api.github.com/repos/huggingface/transformers/issues/11055 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11055/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11055/comments | https://api.github.com/repos/huggingface/transformers/issues/11055/events | https://github.com/huggingface/transformers/issues/11055 | 850,132,857 | MDU6SXNzdWU4NTAxMzI4NTc= | 11,055 | Got ValueError when `output_hidden_states=True` with `eval_accumulation_steps` | {
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"@jungwhank Can you change permission to colab notebook? Not able to view it.",
"@frankhart2018 Sorry I changed the link",
"I can reproduce and see where this is coming from. The fix is not particularly easy, will try to have something ready by the end of the week.\r\n\r\nThanks for flagging this and for the ni... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Colab
- Python version: 3.7
- PyTorch version (GPU?): 1.8.1+cu101
- Tensorflow version (G... | {
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https://api.github.com/repos/huggingface/transformers/issues/11054 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11054/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11054/comments | https://api.github.com/repos/huggingface/transformers/issues/11054/events | https://github.com/huggingface/transformers/issues/11054 | 849,980,817 | MDU6SXNzdWU4NDk5ODA4MTc= | 11,054 | Add parallelize method to GPT-neo models | {
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"Hi @anamtamais,\r\n\r\nWe decided that it's not worth investing time into porting the naive MP solution to other models beyond t5+gpt2 since this solution doesn't scale well resource-wise. And given the 2 existing implementations of ZeRO (fairscale and DeepSpeed) this is by far more scalable solution, in particula... | 1,617 | 1,620 | 1,620 | NONE | null | # 🚀 Feature request
Add `parallelize` method to GPT-neo models, so we can finetune them using model parallelism using less expensive GPUs.
## Motivation
I want to finetune a GPT-neo model using model parallelism in order to do it using less expensive GPUs. It is not yet implemented, and, as higher-end GPUs ar... | {
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https://api.github.com/repos/huggingface/transformers/issues/11053 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11053/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11053/comments | https://api.github.com/repos/huggingface/transformers/issues/11053/events | https://github.com/huggingface/transformers/pull/11053 | 849,956,936 | MDExOlB1bGxSZXF1ZXN0NjA4NjA4MDQ0 | 11,053 | [doc] fix code-block rendering | {
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# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/11052 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11052/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11052/comments | https://api.github.com/repos/huggingface/transformers/issues/11052/events | https://github.com/huggingface/transformers/issues/11052 | 849,943,915 | MDU6SXNzdWU4NDk5NDM5MTU= | 11,052 | Implement fast tokenizer for Big Bird models | {
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"The way I would approach is to start from a copy-paste of a very similar fast tokenizer (it's based on SentencePiece, so ALBERT is an example of these), and adapt to Big Bird.\r\n\r\nFeel free to open a PR in early stages and let us know if you run in any issues!",
"This issue has been automatically marked as st... | 1,617 | 1,620 | 1,620 | CONTRIBUTOR | null | This issue is similar to #10498
## Your contribution
I can help with the implementation. Can someone provide me the high-level steps ?
@stefan-it
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https://api.github.com/repos/huggingface/transformers/issues/11051 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11051/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11051/comments | https://api.github.com/repos/huggingface/transformers/issues/11051/events | https://github.com/huggingface/transformers/issues/11051 | 849,907,517 | MDU6SXNzdWU4NDk5MDc1MTc= | 11,051 | Training mask language model using multiple files | {
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"@lindan1128 the same code can be used for multiple files too, check this cell:-\r\n\r\n```\r\n%%time \r\nfrom pathlib import Path\r\n\r\nfrom tokenizers import ByteLevelBPETokenizer\r\n\r\npaths = [str(x) for x in Path(\".\").glob(\"**/*.txt\")]\r\n\r\n# Initialize a tokenizer\r\ntokenizer = ByteLevelBPETokenizer(... | 1,617 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:4.5
- Platform:Linux
- Python version:3.7
- PyTorch version (GPU?):1.7.1
- Tensorflow version (GPU?):
- Usi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11050 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11050/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11050/comments | https://api.github.com/repos/huggingface/transformers/issues/11050/events | https://github.com/huggingface/transformers/pull/11050 | 849,866,711 | MDExOlB1bGxSZXF1ZXN0NjA4NTM5Nzgw | 11,050 | accelerate scripts for question answering with no trainer | {
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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/11049 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11049/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11049/comments | https://api.github.com/repos/huggingface/transformers/issues/11049/events | https://github.com/huggingface/transformers/pull/11049 | 849,737,172 | MDExOlB1bGxSZXF1ZXN0NjA4NDQyMTM1 | 11,049 | [docs] fix xref to `PreTrainedModel.generate` | {
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"Would it be a good idea to make an Good second Issue for someone to research whether sphinx could be configured to resolve inherited and mixin methods when it does cross-referencing? It'd be much more intuitive for doc writing if we could have the sub-classed method named and also not needing to hide the sub-class... | 1,617 | 1,622 | 1,622 | CONTRIBUTOR | null | This PR partially resolves the issue raised in https://github.com/huggingface/transformers/issues/9202
I spent quite some time to try to figure out how to get sphinx to figure out the inheritance so that it could cross-reference inherited methods, but it can't even handle mixins it seems. i.e. it can't resolve: `tra... | {
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https://api.github.com/repos/huggingface/transformers/issues/11048 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11048/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11048/comments | https://api.github.com/repos/huggingface/transformers/issues/11048/events | https://github.com/huggingface/transformers/pull/11048 | 849,734,674 | MDExOlB1bGxSZXF1ZXN0NjA4NDQwMjYz | 11,048 | fix incorrect case for s|Pretrained|PreTrained| | {
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```
git-replace PretrainedTokenizer PreTrainedTokenizer
git-replace transformers.PretrainedModel transformers.PreTrainedModel
```
there might be other cases to fix, but these stood out.
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/11047 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11047/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11047/comments | https://api.github.com/repos/huggingface/transformers/issues/11047/events | https://github.com/huggingface/transformers/issues/11047 | 849,604,791 | MDU6SXNzdWU4NDk2MDQ3OTE= | 11,047 | Use Bert model without pretrained weights | {
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"If you want to train it from scratch you can use `BertConfig`, something like this:-\r\n\r\n```python\r\nfrom transformers import BertConfig, BertForSequenceClassification\r\n\r\nconfig = BertConfig() # You can also change the architecture using this config class\r\n\r\nmodel = BertForSequenceClassification(config... | 1,617 | 1,617 | 1,617 | NONE | null | Hi,
I wanted to train a Bert classifier from scratch without any pretrained weights. It has to be randomly initialized and trained.
Example:
```
bert_base_model = BertForSequenceClassification()
trainer = Trainer(model=bert_base_model,
args=training_args,
train_dataset=tra... | {
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https://api.github.com/repos/huggingface/transformers/issues/11046 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11046/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11046/comments | https://api.github.com/repos/huggingface/transformers/issues/11046/events | https://github.com/huggingface/transformers/issues/11046 | 849,568,459 | MDU6SXNzdWU4NDk1Njg0NTk= | 11,046 | Potential incorrect application of layer norm in BlenderbotSmallDecoder | {
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"cc @patrickvonplaten @patil-suraj ",
"Great catch @sougata-ub! This indeed seems like a bug. Will check the original implementation and fix this.",
"Hey @sougata-ub - did you try to change the order in the `BlenderbotSmallDecoder` manually and run a couple of examples to see whether the model performs better? ... | 1,617 | 1,622 | 1,622 | NONE | null | In BlenderbotSmallDecoder, layer norm is applied only on the token embeddings, and not on the hidden_states, whereas in the BlenderbotSmallEncoder, layer norm is applied after adding the input_embeds and positional embeds
BlenderbotSmallEncoder:
`hidden_states = inputs_embeds + embed_pos`
`hidden_states = self.la... | {
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https://api.github.com/repos/huggingface/transformers/issues/11045 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11045/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11045/comments | https://api.github.com/repos/huggingface/transformers/issues/11045/events | https://github.com/huggingface/transformers/issues/11045 | 849,544,374 | MDU6SXNzdWU4NDk1NDQzNzQ= | 11,045 | Multi-GPU seq2seq example evaluation significantly slower than legacy example evaluation | {
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"You should compare apple to apple: if you're not launching the script with `torch.distributed.launch` you're not comparing the same kinds of distributed training (not using the launcher uses `DataParallel` behind the scenes whereas the launcher uses `DistributedDataParallel`).",
"Ah, thanks -- it's my issue then... | 1,617 | 1,620 | 1,620 | NONE | null |
### Who can help
@patil-suraj @sgugger
Models:
T5
## Information
I've been doing multi-GPU evaluation for some weeks using a Transformers pull from Feb 12th, just using the example scripts for training/evaluating custom datasets (specifically `run_distributed_eval.py` , though that seq2seq example is now ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11044 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11044/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11044/comments | https://api.github.com/repos/huggingface/transformers/issues/11044/events | https://github.com/huggingface/transformers/issues/11044 | 849,529,761 | MDU6SXNzdWU4NDk1Mjk3NjE= | 11,044 | [DeepSpeed] ZeRO stage 3 integration: getting started and issues | {
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"Superceded by https://github.com/huggingface/transformers/issues/11464",
"Hi @stas00,\r\n\r\nThank you for working on this amazing library. I looked into the deepspeed documentation for optimizers at https://deepspeed.readthedocs.io/en/latest/optimizers.html and there're a bunch of optimizers, but `adafactor` is... | 1,617 | 1,669 | 1,619 | CONTRIBUTOR | null | # Why would you want ZeRO-3
In a few words, while ZeRO-2 was very limited scability-wise - if `model.half()` couldn't fit onto a single gpu, adding more gpus won't have helped so if you had a 24GB GPU you couldn't train a model larger than about 5B params.
Since with ZeRO-3 the model weights are partitioned acro... | {
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https://api.github.com/repos/huggingface/transformers/issues/11043 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11043/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11043/comments | https://api.github.com/repos/huggingface/transformers/issues/11043/events | https://github.com/huggingface/transformers/issues/11043 | 849,499,734 | MDU6SXNzdWU4NDk0OTk3MzQ= | 11,043 | Can't load model estimater after training | {
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"@philschmid I know you are an expert on the Sagemaker side of the product. Can you point me in the right direction for this?\r\n",
"Hey @gwc4github,\r\n\r\nI have to tell you that using `Estimator.deploy()` is currently not possible yet. Currently, the easiest way to test your model is to upload it to the Hub a... | 1,617 | 1,626 | 1,623 | NONE | null | I was trying to follow the Sagemaker instructions [here](https://docs.aws.amazon.com/sagemaker/latest/dg/deploy-model.html) to load the model I just trained and test an estimation. I get the error message:
NotImplementedError: Creating model with HuggingFace training job is not supported.
Can someone share some s... | {
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https://api.github.com/repos/huggingface/transformers/issues/11042 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11042/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11042/comments | https://api.github.com/repos/huggingface/transformers/issues/11042/events | https://github.com/huggingface/transformers/issues/11042 | 849,274,362 | MDU6SXNzdWU4NDkyNzQzNjI= | 11,042 | [LXMERT] Unclear what img_tensorize does with color spaces | {
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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)... | 1,617 | 1,620 | 1,620 | NONE | null | ## Environment info
- `transformers` version: Not using transformers directly, I'm loading a model "unc-nlp/frcnn-vg-finetuned"
- Platform: MacOS
- Python version: 3.8
- PyTorch version (GPU?): 1.6.0, no GPU
- Tensorflow version (GPU?): don't have
- Using GPU in script?: no
- Using distributed or parallel set-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11041 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11041/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11041/comments | https://api.github.com/repos/huggingface/transformers/issues/11041/events | https://github.com/huggingface/transformers/pull/11041 | 849,269,684 | MDExOlB1bGxSZXF1ZXN0NjA4MDcxNjc1 | 11,041 | wav2vec2 converter: create the proper vocab.json while converting fairseq wav2vec2 finetuned model | {
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"Thanks for opening a PR @cceyda! I'll let Patrick review this one, but he's off for a couple of weeks. \r\n\r\nMaybe @patil-suraj can give it a look in the meantime, but we'll probably have to wait for Patrick to review as he has the most extensive experience with w2v2!",
"@LysandreJik Merging this PR. The chan... | 1,617 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
While converting a finetuned wav2vec2 model we also need to convert the related dictionary `dict.ltr.txt` to hugging face `vocab.json` format.
If a `dict_path` is specified:
- Creates&saves the necessary vocab.json file
- Modifies config file special token ids and vocab size accordin... | {
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https://api.github.com/repos/huggingface/transformers/issues/11040 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11040/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11040/comments | https://api.github.com/repos/huggingface/transformers/issues/11040/events | https://github.com/huggingface/transformers/issues/11040 | 849,265,615 | MDU6SXNzdWU4NDkyNjU2MTU= | 11,040 | max_length in beam_search() and group_beam_search() does not consider beam_scorer.max_length | {
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"follo... | [] | 1,617 | 1,619 | 1,619 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform: 4.3.2
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.0
- Using GPU in script?: No
- Us... | {
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https://api.github.com/repos/huggingface/transformers/issues/11039 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11039/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11039/comments | https://api.github.com/repos/huggingface/transformers/issues/11039/events | https://github.com/huggingface/transformers/issues/11039 | 849,244,819 | MDU6SXNzdWU4NDkyNDQ4MTk= | 11,039 | Trainer not logging into Tensorboard | {
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"Could you check if the bug persists with a [source install](https://huggingface.co/transformers/installation.html#installing-from-source)? I'm trying to reproduce but I have proper logs on my side.",
"@sgugger It only happened when I use `torch.distributed.launch`.\r\nWhat might cause this problem?",
"I'm stil... | 1,617 | 1,617 | 1,617 | 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.dev0
- Platform: Ubuntu 18.04.5 LTS (x86_64)
- Python version: 3.7.0
- PyTorch version (GPU?): 1.7.1+c... | {
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https://api.github.com/repos/huggingface/transformers/issues/11038 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11038/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11038/comments | https://api.github.com/repos/huggingface/transformers/issues/11038/events | https://github.com/huggingface/transformers/issues/11038 | 849,180,384 | MDU6SXNzdWU4NDkxODAzODQ= | 11,038 | DeBERTa xlarge v2 throwing runtime error | {
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"@roshan-k-patel this model has been trained using DebertaV2 and not Deberta, hence the size mismatch. Use DebertaV2ForSequenceClassification instead of DebertaForSequenceClassification 😃 .",
"Hi @frankhart2018, do you mean the [mnli variant](https://huggingface.co/microsoft/deberta-xlarge-mnli)?",
"No, @rosha... | 1,617 | 1,620 | 1,620 | NONE | null | - `transformers` version: 4.4.2
- Platform: Linux-3.10.0-1127.el7.x86_64-x86_64-with-redhat-7.8-Maipo
- Python version: 3.6.13
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script: yes
```
RuntimeError: Error(s) in loading state_dict for DebertaForSequenc... | {
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https://api.github.com/repos/huggingface/transformers/issues/11037 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11037/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11037/comments | https://api.github.com/repos/huggingface/transformers/issues/11037/events | https://github.com/huggingface/transformers/issues/11037 | 849,111,037 | MDU6SXNzdWU4NDkxMTEwMzc= | 11,037 | Was bert-large-uncased-whole-word-masking-finetuned-squad fine tuned or not. | {
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"@CaoZhongZ which version are you using? I tried loading this model and it didn't throw any warning. ",
"Thanks for the hint! Might installed some spurious packages. A clean installation of transformers have no issue."
] | 1,617 | 1,617 | 1,617 | NONE | null | In the description of repo 'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad', it states: "After pre-training, this model was fine-tuned on the SQuAD dataset with one of our fine-tuning scripts. See below for more information regarding this fine-tuning."
However I receive error messages w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11036 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11036/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11036/comments | https://api.github.com/repos/huggingface/transformers/issues/11036/events | https://github.com/huggingface/transformers/issues/11036 | 848,996,240 | MDU6SXNzdWU4NDg5OTYyNDA= | 11,036 | BertForTokenClassification class ignores long tokens when making predictions | {
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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)... | 1,617 | 1,620 | 1,620 | NONE | null | # Goal
I am trying to run the adapted version of `run_ner.py` hosted [here](https://github.com/huggingface/transformers/tree/master/examples/token-classification) (see MWE session for my code) on my custom dataset.
The dataset I am using has some extra-long tokens (mainly URLs). When I obtained the predictions af... | {
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