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https://api.github.com/repos/huggingface/transformers/issues/11644 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11644/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11644/comments | https://api.github.com/repos/huggingface/transformers/issues/11644/events | https://github.com/huggingface/transformers/issues/11644 | 880,749,324 | MDU6SXNzdWU4ODA3NDkzMjQ= | 11,644 | Cannot load studio-ousia/luke-base for AutoModelForTokenClassification | {
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"cc @NielsRogge",
"LUKE does not have a `*ForTokenClassification` model, so it's not available in the token classification auto model. The following three models are available: `LukeForEntityClassification`, `LukeForEntityPairClassification`, `LukeForEntitySpanClassification`",
"Yes, I explicitly did not includ... | 1,620 | 1,629 | 1,626 | 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 (pulled from repo)
- Platform: 3
- Python version: 3.7.10
- PyTorch version (GPU?): 1.7.0 (no)
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11643 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11643/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11643/comments | https://api.github.com/repos/huggingface/transformers/issues/11643/events | https://github.com/huggingface/transformers/issues/11643 | 880,682,416 | MDU6SXNzdWU4ODA2ODI0MTY= | 11,643 | How to train TFBertForTokenClassification without padding mechanism | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this sti... | 1,620 | 1,623 | 1,623 | NONE | null | I have a situation that input are variable-length, and I want to train sentence one by one. I do not want to use padding and train on batch.
In my study, Keras support fit-generator, but this mechanism deprecated on TF2
Is there any suggestion, I have no idea and need help | {
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https://api.github.com/repos/huggingface/transformers/issues/11642 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11642/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11642/comments | https://api.github.com/repos/huggingface/transformers/issues/11642/events | https://github.com/huggingface/transformers/issues/11642 | 880,534,547 | MDU6SXNzdWU4ODA1MzQ1NDc= | 11,642 | IDE cannot correctly navigate to references, It will navigate all object to `transformers/utils/dummy_pt_objects.py`. | {
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"In PyCharm, you can select all `dummy*` files, right-click and select \"Mark as Plain Text\". This should prevent the IDE from navigating to the dummy files.\r\nI have never used VSCode with `Pylance` however.",
"need some help from vscode user, does anyone found the same issue?",
"I'm also having this issue w... | 1,620 | 1,648 | 1,627 | NONE | null | # Enviornment
- `transformers` version: 4.5.1
- Platform: macOS-11.1-arm64-arm-64bit
- Python version: 3.9.1
- PyTorch version (GPU?): 1.8.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>
# Issues
When... | {
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https://api.github.com/repos/huggingface/transformers/issues/11641 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11641/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11641/comments | https://api.github.com/repos/huggingface/transformers/issues/11641/events | https://github.com/huggingface/transformers/issues/11641 | 880,402,467 | MDU6SXNzdWU4ODA0MDI0Njc= | 11,641 | How to change training epochs when using run_summarization.py | {
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"Hi there,\r\n\r\n`run_summarization.py` uses `Trainer`, you can pass the `--num_train_epochs` to control the number of epochs. Please find the docs [here](https://huggingface.co/transformers/main_classes/trainer.html).\r\n\r\nAlso please use the [forum](https://discuss.huggingface.co/) to ask such questions, issu... | 1,620 | 1,623 | 1,623 | NONE | null | ### Who can help
<!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
Please tag fewer than 3 people.!-->
Models:
- bart, t5: @patrickvonplaten, @pati... | {
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https://api.github.com/repos/huggingface/transformers/issues/11640 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11640/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11640/comments | https://api.github.com/repos/huggingface/transformers/issues/11640/events | https://github.com/huggingface/transformers/issues/11640 | 880,174,093 | MDU6SXNzdWU4ODAxNzQwOTM= | 11,640 | Multilingual MobileBERT | {
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] | closed | false | null | [] | [] | 1,620 | 1,621 | 1,621 | CONTRIBUTOR | null | # 🌟 New model addition
## Model description
Recently Google released multilingual MobileBERT on [tensorflow/models](https://github.com/tensorflow/models/blob/master/official/nlp/projects/mobilebert/README.md)
> In addition, we also provide new multiple-lingual MobileBERT checkpoint trained using multi-lingual... | {
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https://api.github.com/repos/huggingface/transformers/issues/11639 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11639/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11639/comments | https://api.github.com/repos/huggingface/transformers/issues/11639/events | https://github.com/huggingface/transformers/issues/11639 | 879,938,069 | MDU6SXNzdWU4Nzk5MzgwNjk= | 11,639 | I-BERT tokenizer not loading; example code not working. | {
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"Hi @carolmanderson ,\r\n\r\nSome tokenizer files were missing from the model repo. I've uploaded them, it should now work.",
"Hi,\r\n\r\nI want to test IBERT's speedup, and I have done exactly what is said in https://huggingface.co/kssteven/ibert-roberta-base. For the quantization part, when I set quant_mode to ... | 1,620 | 1,630 | 1,620 | NONE | null | Following the example [here](https://huggingface.co/transformers/model_doc/ibert.html), I'm trying to load the 'kssteven/ibert-roberta-base' tokenizer:
```
from transformers import RobertaTokenizer
tokenizer = RobertaTokenizer.from_pretrained('kssteven/ibert-roberta-base')
```
It errors out as follows:
```... | {
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https://api.github.com/repos/huggingface/transformers/issues/11638 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11638/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11638/comments | https://api.github.com/repos/huggingface/transformers/issues/11638/events | https://github.com/huggingface/transformers/pull/11638 | 879,855,751 | MDExOlB1bGxSZXF1ZXN0NjMzNTQ2Mjg1 | 11,638 | [Deepspeed Wav2vec2] integration | {
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"Also link: #11452 here",
"Also while working on this I came up with a fused version of `Conv1d` + `WeightNorm` which is simpler to understand and work with as compared to the original `weight_norm` which uses a pre-forward hook, but I'm not sure how to test its correctness - I only tested it in my head.\r\n\r\n... | 1,620 | 1,623 | 1,623 | CONTRIBUTOR | null | Addressing the need in https://github.com/huggingface/transformers/issues/11446, this PR is working on making wav2vec2 work under deepspeed.
This PR:
* changes Trainer to automatically convert inputs to the correct dtype if it's not int64 - we didn't need this for nlp models because embeddings took care of this - t... | {
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Thank you!
@sgugger or @LysandreJik
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"That can't work since `conftest` now believes the module \"tensorflow\" is the folder in the examples with the same name, which is the reason why I moved it.\r\n\r\nPath in conftest need to be adapted instead.",
"ah, OK, then I will make copies of it. But you can't move it since sys.path was relying on it being ... | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | the pt/tf reshuffle broke the examples tests setup. This PR fixes it, by
* fixing `sys.path` setting now that it's one level down
@sgugger | {
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probably the most natural place to put it, @gary149 @LysandreJik | {
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I added it to the requirements.txt of the rag example | {
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"Can I help with this, @patrickvonplaten ?",
"Hey @mrm8488,\r\n\r\nIt would be amazing if you're interested in adding this model. It looks like a difficult one, but I'd definitely try to help you as much as I can if you want to add it :-)",
"Looking forward ! ",
"@ArthurZucker @younesbelkada (the ML engineers... | 1,620 | 1,689 | null | MEMBER | null | # 🌟 New model addition
## Model description
New model released by [google](https://github.com/google-research/google-research/tree/master/felix)
## Open source status
* [x] the model implementation is available: https://github.com/google-research/google-research/tree/master/felix
* [x] the model weights a... | {
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Fixes a small typo in the code example of `LukeForEntitySpanClassification`.
Fixes #11629
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"I just found an issue with use_cache. Will fix it later.\r\n\r\nEdit: Fixed.",
"unstale",
"I have used this version of the code quite extensively without issues and have found no difference in performance when doing evaluations. I have also just fixed the so far present warning about the local attention layer ... | 1,620 | 1,631 | 1,631 | NONE | null | # What does this PR do?
The current local self attention implementation for gpt-neo follows the implementation in mtf, which makes it hard to understand. This pull request implements local self attention by changing the bias mask in global attention. Local self attention is a sliding window where each token can only... | {
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"Yes, it should be updated, because `LukeForEntitySpanClassification` classifies each possible entity span independently, so it should instead become this:\r\n\r\n```\r\npredicted_class_indices = logits.argmax(-1).squeeze().tolist()\r\nfor span, predicted_class_idx in zip(entity_spans, predicted_class_indices):\r\n... | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0.dev0
- Platform: Linux-5.10.25-linuxkit-x86_64-with-debian-10.1
- Python version: 3.7.4
- PyTorch vers... | {
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https://api.github.com/repos/huggingface/transformers/issues/11628 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11628/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11628/comments | https://api.github.com/repos/huggingface/transformers/issues/11628/events | https://github.com/huggingface/transformers/pull/11628 | 878,736,795 | MDExOlB1bGxSZXF1ZXN0NjMyNTIwMzY4 | 11,628 | Fixes NoneType exception when topk is larger than one coupled with a small context in the Question-Answering pipeline | {
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"Great, thanks! Could you fix the quality issues in your code? You can do so with the following:\r\n\r\n```\r\npip install -e .[quality]\r\nmake fixup\r\n```",
"> Great, thanks! Could you fix the quality issues in your code? You can do so with the following:\r\n> \r\n> ```\r\n> pip install -e .[quality]\r\n> make... | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
This PR fixes a bug while using the QA pipeline where if `topk` > 1 (e.g., 20) and the context of a Question-Context pair is short, the pipeline will propose non-context words as candidates for the answer span. This will generate a `NoneType` error down the line.
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"Hi there, would you mind opening this issue in `nn_pruning` repo? Thanks.",
"This was bypassed in nn_pruning then fixed in transformers in https://github.com/huggingface/transformers/pull/12026 ."
] | 1,620 | 1,623 | 1,620 | NONE | null | Hi!
I am trying to run the launch_qa_sparse_single.py file from the question answering example from your nn_pruning library (https://github.com/huggingface/nn_pruning). I haven't changed anything from the original code and I get this error:
You should probably TRAIN this model on a down-stream task to be able to ... | {
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.3
- Platform: Ubuntu 18.04.5 LTS (x86_64)
- Python version: 3.8 (64-bit runtime)
- PyTorch version (GPU?... | {
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Fix comment in run_clm_no_trainer.py
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"It's just a matter of data: a lot of the words are labelled with \"not entity\" so the model has a tendency to learn to spit that label for each word, in the absence of more data."
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0.dev0
- Platform: windows 7
- Python version: 3.8.8
- PyTorch version (GPU?):
- Tensorflow version (G... | {
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https://api.github.com/repos/huggingface/transformers/issues/11622 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11622/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11622/comments | https://api.github.com/repos/huggingface/transformers/issues/11622/events | https://github.com/huggingface/transformers/pull/11622 | 878,294,204 | MDExOlB1bGxSZXF1ZXN0NjMyMTQxMDI0 | 11,622 | [TokenClassification] Label realignment for subword aggregation | {
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"@sgugger the failed test (`test_gpt2_model_past_large_inputs`) seems unrelated to the changes in this PR. Any thought on what might be going on and how to resolve?",
"No, it's just flaky, don't worry!",
"Hey @francescorubbo, @Narsil pointed out a few issues with the current implementation that we'll take a loo... | 1,620 | 1,622 | 1,622 | CONTRIBUTOR | null | # What does this PR do?
Fixes #10263, #10763
See also #10568
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-c... | {
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https://api.github.com/repos/huggingface/transformers/issues/11621 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11621/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11621/comments | https://api.github.com/repos/huggingface/transformers/issues/11621/events | https://github.com/huggingface/transformers/pull/11621 | 878,081,507 | MDExOlB1bGxSZXF1ZXN0NjMxOTQ3ODM2 | 11,621 | Fix usage of head masks by PT encoder-decoder models' `generate()` function | {
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"Hey @stancld,\r\n\r\nThanks a lot for this contribution! Could we add one test to verify that generation works with head_mask for all encoder-decoder models? \r\n\r\nI think it could be added to `test_generation_utils.py` ",
"Hey @patrickvonplaten, I've added one test. At this moment, there are two little issues... | 1,620 | 1,621 | 1,621 | CONTRIBUTOR | null | This PR adds missing arguments `head_mask`, `decoder_head_mask` and `cross_attn_head_mask` into `prepare_inputs_for_generation` function of **PyTorch encoder-decoder models** so that these args will be used during the generation when `generate()` function is called.
EDIT: Need to fix the new test for ProphetNet
<hr... | {
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https://api.github.com/repos/huggingface/transformers/issues/11620 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11620/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11620/comments | https://api.github.com/repos/huggingface/transformers/issues/11620/events | https://github.com/huggingface/transformers/pull/11620 | 878,016,309 | MDExOlB1bGxSZXF1ZXN0NjMxODg5NzU2 | 11,620 | Fix RNG saves in distributed mode. | {
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The newly introduced RNG saves in the Trainer checkpoints can yield to an error when one of the process of local_rank != 0 arrives to the end of the function faster then the process local_rank=0 arrived at the beginning: in this case the subfolder "checkpoint-xxx" is not created yet, so tryin... | {
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https://api.github.com/repos/huggingface/transformers/issues/11619 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11619/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11619/comments | https://api.github.com/repos/huggingface/transformers/issues/11619/events | https://github.com/huggingface/transformers/pull/11619 | 877,957,146 | MDExOlB1bGxSZXF1ZXN0NjMxODM2OTE4 | 11,619 | [cuda ext tests] fixing tests | {
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One failure I couldn't reproduce locally, posted about it here https://github.com/huggingface/transformers/issues/11618
@LysandreJik or @sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/11618 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11618/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11618/comments | https://api.github.com/repos/huggingface/transformers/issues/11618/events | https://github.com/huggingface/transformers/issues/11618 | 877,954,126 | MDU6SXNzdWU4Nzc5NTQxMjY= | 11,618 | [fairscale] rng states saving fails in an extended multi-gpu test | {
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"Found the root: the \"checkpoint-1\" folder is only created by process 0 when calling \"model.save_pretrained\", so if process 1 is faster and arrives at `_save_checkpoint` first, it will not see this folder (there is almost no saving on process 1, so it goes through this method quickly).\r\n\r\nWill send a fix sh... | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | @sgugger, following up on the RNG states PR
```
RUN_SLOW=1 pytest tests/extended/test_trainer_ext.py::TestTrainerExt::test_run_seq2seq_fully_sharded_ddp_fp16 -sv
```
fails on multi-gpu scheduled CI:
```
File "/__w/transformers/transformers/examples/pytorch/translation/run_translation.py", line 589, in <module>
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11617 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11617/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11617/comments | https://api.github.com/repos/huggingface/transformers/issues/11617/events | https://github.com/huggingface/transformers/pull/11617 | 877,952,696 | MDExOlB1bGxSZXF1ZXN0NjMxODMyOTQx | 11,617 | Adding TFWav2Vec2Model | {
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"Hi @will-rice, just an FYI, there's a CookieCutter template that allows you to automatically create a lot of files (modeling files, test files, documentation pages) for you. You can then edit those files. \r\n\r\nSee [here](https://github.com/huggingface/transformers/tree/master/templates/adding_a_new_model) for m... | 1,620 | 1,675 | 1,623 | CONTRIBUTOR | null | Adds a TensorFlow version of Wav2Vec2
https://github.com/huggingface/transformers/issues/11603
# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/11616 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11616/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11616/comments | https://api.github.com/repos/huggingface/transformers/issues/11616/events | https://github.com/huggingface/transformers/issues/11616 | 877,903,814 | MDU6SXNzdWU4Nzc5MDM4MTQ= | 11,616 | wrong default value of argument "ignore_index" in CrossEntropyLoss for loss calculation in models forward method | {
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"@LysandreJik @sgugger - we could add a warning that fires if one hasn't set `-100` in the labels, but has padding tokens instead - what do you think? ",
"Would it not hurt performance to do the check at each forward?",
"My opinion on this is that the documentation explicitly states how the `labels` should be c... | 1,620 | 1,623 | 1,623 | NONE | null | Hi guys!
You calculate loss in models forward() methods as follows:
`loss_fct = CrossEntropyLoss()`
for example:
[BertForMaskedLM::forward](https://github.com/huggingface/transformers/blob/master/src/transformers/models/bert/modeling_bert.py#L1328)
[BartForConditionalGeneration:forward](https://github.com/huggin... | {
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https://api.github.com/repos/huggingface/transformers/issues/11615 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11615/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11615/comments | https://api.github.com/repos/huggingface/transformers/issues/11615/events | https://github.com/huggingface/transformers/pull/11615 | 877,813,030 | MDExOlB1bGxSZXF1ZXN0NjMxNzA3NTQz | 11,615 | [Lazy init] Fix edge cases | {
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Luckily, the test caught those edge cases ;-) | {
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https://api.github.com/repos/huggingface/transformers/issues/11614 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11614/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11614/comments | https://api.github.com/repos/huggingface/transformers/issues/11614/events | https://github.com/huggingface/transformers/pull/11614 | 877,584,116 | MDExOlB1bGxSZXF1ZXN0NjMxNTEwNjEy | 11,614 | Vectorized Numpy to Torch based Functions for SpecAugment | {
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"Following are the average test results for the `_compute_mask_indices` function when ran 100 times. Each X.1 subtest case is calculated with `attention_mask = None` and each X.2 subtest case is calculated with `attention_mask` calculated with the following code:\r\n```\r\nattention_mask = torch.ones((batch_size, s... | 1,620 | 1,621 | 1,621 | CONTRIBUTOR | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11613 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11613/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11613/comments | https://api.github.com/repos/huggingface/transformers/issues/11613/events | https://github.com/huggingface/transformers/pull/11613 | 877,556,987 | MDExOlB1bGxSZXF1ZXN0NjMxNDg4ODQw | 11,613 | Re-styling in seq2seq attention | {
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"Tests should be fixed now as well: https://github.com/huggingface/transformers/pull/11615"
] | 1,620 | 1,620 | 1,620 | COLLABORATOR | null | # What does this PR do?
After commenting the same things on multiple new models, I looked around and found everyone was copying this code I don't like from `BartAttention`. So fixing the source to avoid seeing it in the future :-) | {
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https://api.github.com/repos/huggingface/transformers/issues/11612 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11612/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11612/comments | https://api.github.com/repos/huggingface/transformers/issues/11612/events | https://github.com/huggingface/transformers/issues/11612 | 877,410,269 | MDU6SXNzdWU4Nzc0MTAyNjk= | 11,612 | Error when using Adafactor without learn rate | {
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"This was added by @jsrozner and @stas00 in #10526, so pinging them here.",
"Thank you @sgugger for the feedback. I install the latest transformers version from source using: \r\n```pip install git+https://github.com/huggingface/transformers```\r\n\r\nand set the recommended parameters from the patch:\r\n\r\nopti... | 1,620 | 1,623 | 1,623 | CONTRIBUTOR | null | Hi,
I get these strange errors when I use the Adafactor. This code will result in this (expected) error:
```
optimizer = Adafactor(model.parameters(), scale_parameter=True, relative_step=True, warmup_init=True, lr=1e-4)
```
> ValueError: Cannot combine manual `lr` and `relative_step=True` options
however, if... | {
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https://api.github.com/repos/huggingface/transformers/issues/11611 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11611/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11611/comments | https://api.github.com/repos/huggingface/transformers/issues/11611/events | https://github.com/huggingface/transformers/pull/11611 | 877,388,312 | MDExOlB1bGxSZXF1ZXN0NjMxMzUzMTI1 | 11,611 | Fix typo in docstring | {
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## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests),
Pull R... | {
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https://api.github.com/repos/huggingface/transformers/issues/11610 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11610/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11610/comments | https://api.github.com/repos/huggingface/transformers/issues/11610/events | https://github.com/huggingface/transformers/issues/11610 | 877,322,706 | MDU6SXNzdWU4NzczMjI3MDY= | 11,610 | In "Question Answering" separate context from question | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,664 | 1,626 | NONE | null | # 🚀 Feature request
## Motivation
Often one may have many questions on the same content. In the current implementation, the function will be called multiple times with the same context but with different questions causing a lot of computational time.
## Idea
I was wondering if there's a way to speed up runtim... | {
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https://api.github.com/repos/huggingface/transformers/issues/11609 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11609/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11609/comments | https://api.github.com/repos/huggingface/transformers/issues/11609/events | https://github.com/huggingface/transformers/issues/11609 | 877,319,861 | MDU6SXNzdWU4NzczMTk4NjE= | 11,609 | [RAG] ModuleNotFoundError: No module named 'git' when finetuning the model | {
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"Indeed you need to install `pip install GitPython` to make it work\r\nI created a PR to add it to the requirements.txt of the RAG example",
"Thanks @lhoestq . I confirm that it works after installing GitPython."
] | 1,620 | 1,620 | 1,620 | NONE | null | ## Environment info
- `transformers` version: 4.6.0.dev0
- Platform: Linux-3.10.0-1127.10.1.el7.x86_64-x86_64-with-debian-buster-sid
- Python version: 3.6.13
- PyTorch version (GPU?): 1.8.1+cu102 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: no
- Using distributed or parallel set-up ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11608 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11608/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11608/comments | https://api.github.com/repos/huggingface/transformers/issues/11608/events | https://github.com/huggingface/transformers/issues/11608 | 877,184,880 | MDU6SXNzdWU4NzcxODQ4ODA= | 11,608 | Is it correct to load weights from task A to train task B | {
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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!",
"Thanks for your reply @LysandreJik Ly\r\n"
] | 1,620 | 1,620 | 1,620 | NONE | null | > I want to use 2 tasks of modelling including (a) Causal language modelling &
> (b) Mask language modelling for training my new added tokens
My pseudo-code is below
```
##add new tokenizer
model_name = "vinai/phobert-large"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.... | {
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https://api.github.com/repos/huggingface/transformers/issues/11606 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11606/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11606/comments | https://api.github.com/repos/huggingface/transformers/issues/11606/events | https://github.com/huggingface/transformers/pull/11606 | 877,121,837 | MDExOlB1bGxSZXF1ZXN0NjMxMTM1MDU3 | 11,606 | Added Feature: Prefix decoding for wav2vec2 models | {
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"- [x] Currently the code supports prefix decoding without LM. I am still working to integrate the kenlm version.\r\n\r\nProblem faced currently: I created a custom kenlm and tried to run the code, but it stops without throwing any error at line `results = self.decoder.decode(emissions_ptr, T, N)` I am currently t... | 1,620 | 1,636 | 1,631 | NONE | null | # What does this PR do?
Added the code for prefix decoding for wav2vec2 based models.
<!--
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... | {
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https://api.github.com/repos/huggingface/transformers/issues/11605 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11605/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11605/comments | https://api.github.com/repos/huggingface/transformers/issues/11605/events | https://github.com/huggingface/transformers/pull/11605 | 877,062,124 | MDExOlB1bGxSZXF1ZXN0NjMxMDg2MjY2 | 11,605 | fix typo in command | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11604 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11604/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11604/comments | https://api.github.com/repos/huggingface/transformers/issues/11604/events | https://github.com/huggingface/transformers/issues/11604 | 877,041,951 | MDU6SXNzdWU4NzcwNDE5NTE= | 11,604 | Model type to AutoModelForQuestionAnswering incorrect | {
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"`AutoModelForQuestionAnswering` expects a model with a span classification head on top, GPT2 is an auto-regressive language model and does not have `ForQuestionAnswering` class defined for it. So it can't be used with `AutoModelForQuestionAnswering`",
"This issue has been automatically marked as stale because it... | 1,620 | 1,623 | 1,623 | NONE | null | `model = AutoModelForQuestionAnswering.from_pretrained("dbmdz/german-gpt2")
ValueError: Unrecognized configuration class <class 'transformers.models.gpt2.configuration_gpt2.GPT2Config'> for this kind of AutoModel: AutoModelForQuestionAnswering.
Model type should be one of BigBirdConfig, ConvBertConfig, LEDConfig, D... | {
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https://api.github.com/repos/huggingface/transformers/issues/11603 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11603/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11603/comments | https://api.github.com/repos/huggingface/transformers/issues/11603/events | https://github.com/huggingface/transformers/issues/11603 | 876,989,725 | MDU6SXNzdWU4NzY5ODk3MjU= | 11,603 | TFWav2Vec2Model | {
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"Sure, there's a [general conversion script](https://github.com/huggingface/transformers/blob/master/src/transformers/convert_pytorch_checkpoint_to_tf2.py) that allows you to convert the weights from a PyTorch model to its TF counterpart. You only need to make sure that all the attributes of the TF model correspond... | 1,620 | 1,623 | 1,623 | CONTRIBUTOR | null | # 🌟 New model addition
I want a Tensorflow version of Wav2Vec2 and it's something I'm willing to work on. I just wanted to make sure no one else was working on it. I looked at the issues, PR's, and source code. The only mention of TFWav2Vec2Model is in the current docs so just wanted to double-check no one was workin... | {
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"Could you please post the full error?\r\nFrom what I can see here, the dataset should return tensors, not NumPy arrays. This could be the issue."
] | 1,620 | 1,621 | 1,621 | NONE | null |
## Information
<!-- Important information -->
Model I am using Bert2Bert, training using Seq2SeqTrainer on Google Colab.
## Details
I am trying to use a Bert2Bert model on multiple-choice qa dataset using Seq2SeqTrainer. My whole code is given in the [following]( https://colab.research.google.com/drive/1bq... | {
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https://api.github.com/repos/huggingface/transformers/issues/11601 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11601/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11601/comments | https://api.github.com/repos/huggingface/transformers/issues/11601/events | https://github.com/huggingface/transformers/issues/11601 | 876,955,830 | MDU6SXNzdWU4NzY5NTU4MzA= | 11,601 | Using `TFGPT2LMHeadModel.generate` with tf.distribute.TPUStrategy and tf.function | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,623 | 1,623 | NONE | null | ## High-level description
I was wondering what were the steps that one is supposed to use to be able to do call `strategy.run` on `model.generate` with tf.distribute.TPUStrategy.
Right now, I get an error message telling me that TPUStrategy doesn't support pure eager functions, so I tried to put `model.__call__` and ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11600 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11600/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11600/comments | https://api.github.com/repos/huggingface/transformers/issues/11600/events | https://github.com/huggingface/transformers/issues/11600 | 876,766,700 | MDU6SXNzdWU4NzY3NjY3MDA= | 11,600 | [consistent use] `F` vs. `nn.functional` | {
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"I personally vote for 4, and if there is any risk of ambiguity, doing\r\n```\r\nfrom torch.nn.functional import foo as torch_foo\r\n```\r\n",
"2 or 4 for me, but I don't have strong feeling about this issue",
"2 looks good to me but no strong feelings either",
"I further analyzed the codebase and it looks li... | 1,620 | 1,623 | 1,623 | CONTRIBUTOR | null | We use 3 different ways of doing the same:
1. `F.foo()`
2. `nn.functional.foo()`
3. `torch.nn.functional.foo()`
and these could also be imported:
4. `from torch.nn.functional import foo; foo()`
Asking others it appears that `F` is not quite liked, so it's 2, 3 or 4.
2 and 3 often lead to longer lines whi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11599 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11599/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11599/comments | https://api.github.com/repos/huggingface/transformers/issues/11599/events | https://github.com/huggingface/transformers/pull/11599 | 876,752,099 | MDExOlB1bGxSZXF1ZXN0NjMwODM0MDM5 | 11,599 | Auto modelcard | {
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This PR adds functionality in the Trainer to auto-generate model cards and some utilities to do the same without the Trainer if people are not using it. In passing, the old `ModelCard` class is deprecated (to be removed in v5).
As an example [here](https://huggingface.co/sgugger/test-glue-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11598 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11598/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11598/comments | https://api.github.com/repos/huggingface/transformers/issues/11598/events | https://github.com/huggingface/transformers/pull/11598 | 876,730,391 | MDExOlB1bGxSZXF1ZXN0NjMwODE2NTEx | 11,598 | Add the ImageClassificationPipeline | {
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"LGTM, thank you for adding this.",
"I should have addressed all comments. \r\n\r\n@Narsil, if you could review once again when you have time, would love your feedback on the updated tests and on the updated `__init__` method."
] | 1,620 | 1,620 | 1,620 | MEMBER | null | This PR adds the `ImageClassificationPipeline`. It is tested on DeiT and ViT and should enable the inference API for these models.
Since I encountered an issue with the `AutoExtractor`, I fixed it as seen with @sgugger (namely switched it from using names such as `"deit"` to using the configuration class as a key, s... | {
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https://api.github.com/repos/huggingface/transformers/issues/11597 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11597/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11597/comments | https://api.github.com/repos/huggingface/transformers/issues/11597/events | https://github.com/huggingface/transformers/issues/11597 | 876,415,382 | MDU6SXNzdWU4NzY0MTUzODI= | 11,597 | Is the "dummy inputs and standard lengths" implication, when using tracing for exporting a model, still true? | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,623 | 1,623 | NONE | null | Hi,
We're experimenting with exporting a CamemBERT model via tracing. We used a relatively short sentence as sample input. Then we used the resulting traced model for inference of a sentence with greater length than the sample input's. According to https://huggingface.co/transformers/serialization.html#dummy-inputs-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11596 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11596/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11596/comments | https://api.github.com/repos/huggingface/transformers/issues/11596/events | https://github.com/huggingface/transformers/pull/11596 | 876,413,557 | MDExOlB1bGxSZXF1ZXN0NjMwNTY0MTQ4 | 11,596 | fix head_mask for albert encoder part(`AlbertTransformer`) | {
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"Great, thanks for the fix @baeseongsu ! Could you run the code quality tool to ensure the PR fits the quality requirements?\r\n\r\n```\r\npip install -U -e .[quality]\r\nmake fixup\r\n```",
"@LysandreJik Sure 👍 "
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11595 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11595/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11595/comments | https://api.github.com/repos/huggingface/transformers/issues/11595/events | https://github.com/huggingface/transformers/pull/11595 | 876,409,221 | MDExOlB1bGxSZXF1ZXN0NjMwNTYwNzI2 | 11,595 | Accept tensorflow-rocm package when checking TF availability | {
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At least ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11594 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11594/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11594/comments | https://api.github.com/repos/huggingface/transformers/issues/11594/events | https://github.com/huggingface/transformers/issues/11594 | 876,272,716 | MDU6SXNzdWU4NzYyNzI3MTY= | 11,594 | Distil BART for text simplification | {
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"Can you provide a link to a paper, implementation and optional weights, if possible?",
"Hello NeilsRogge, I am building the model on basis of DistilBERT. I am still in the initial phase, but if you want to read/know more about it please go through this link\r\nhttps://huggingface.co/transformers/_modules/transfo... | 1,620 | 1,620 | null | NONE | null | # 🌟 New model addition
## Model description
Not completed yet. I will notify very soon when it is done.
If anyone has any leads regarding the same issue, please share. It would be great help. | {
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https://api.github.com/repos/huggingface/transformers/issues/11593 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11593/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11593/comments | https://api.github.com/repos/huggingface/transformers/issues/11593/events | https://github.com/huggingface/transformers/pull/11593 | 876,268,604 | MDExOlB1bGxSZXF1ZXN0NjMwNDQ4ODA4 | 11,593 | [WIP] HF style example flax version | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,623 | 1,623 | MEMBER | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/11592 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11592/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11592/comments | https://api.github.com/repos/huggingface/transformers/issues/11592/events | https://github.com/huggingface/transformers/issues/11592 | 876,263,481 | MDU6SXNzdWU4NzYyNjM0ODE= | 11,592 | Cannot use multiple GPUs to finetune RAG using sample code with customized knowledge | {
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"Hi ! Is there an error message ? Is there any CPU activity when it gets stuck (maybe the index is just being loaded) ?",
"I'm not getting any error message, and yes is there is CPU activity. But given the fact that my dataset is quite small(check test.csv), would it really that much time(>5mins) to load it? And ... | 1,620 | 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: 4.5.1
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): torch1.8.1with cuda10.2
- Using GPU... | {
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https://api.github.com/repos/huggingface/transformers/issues/11591 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11591/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11591/comments | https://api.github.com/repos/huggingface/transformers/issues/11591/events | https://github.com/huggingface/transformers/pull/11591 | 876,118,029 | MDExOlB1bGxSZXF1ZXN0NjMwMzI2NTM4 | 11,591 | add importlib_metadata and huggingface_hub as dependency in the conda recipe | {
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"Thanks @LysandreJik. "
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
<!--
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"Hi, TF maintainer here! We're currently in the process of rewriting the examples. We're deprecating TFTrainer and using more native Keras. Rewriting our GLUE examples is coming up very soon on my to-do list.\r\n\r\nThat said, the `run_text_classification.py` script is updated to our new standards - feel free to tr... | 1,620 | 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: 4.5.1
- Platform: ubuntu 18.04
- Python version: 3.6.9
- PyTorch version (GPU?):
- Tensorflow version (GPU?... | {
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"Hey @Lynx1820,\r\n\r\nThanks a lot for the PR! Could you run `make style` to make the tests pass? :-)"
] | 1,620 | 1,621 | 1,621 | CONTRIBUTOR | null | - test_tokenization_wav2vec2.py failure on Windows - fixed by changing directory separator when running on Windows.
- tests/test_utils_check_copies.py failure on Windows due to splitting text with "\n" on Windows, instead of "\r\n" - fixed by using universal newlines.
- tests/extended/test_trainer_ext.py failure on... | {
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- documents what awesomeness @sgugger added in https://github.com/huggingface/transformers/pull/11582
- plus what to do if one wants full determinism
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/11587 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11587/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11587/comments | https://api.github.com/repos/huggingface/transformers/issues/11587/events | https://github.com/huggingface/transformers/pull/11587 | 875,665,705 | MDExOlB1bGxSZXF1ZXN0NjI5OTYyMzE0 | 11,587 | Removes SageMakerTrainer code but keeps class as wrapper | {
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This PRs removes the `SageMakerTrainer` specific code since it has been merged into Trainer #10975. We had issues and bugs in `SageMakerTrainer` but not in `Trainer` since this class is already deprecated and will be removed in v5 of Transformers I removed the code for the next release.
`Sa... | {
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"The tests are not run on Windows, so there is absolutely no guarantee any of them passes there.",
"> The tests are not run on Windows, so there is absolutely no guarantee any of them passes there.\r\n\r\nIsn't Windows a supported platform? If so, would it be helpful to run HF tests on Windows as well? ",
"This... | 1,620 | 1,623 | 1,623 | CONTRIBUTOR | null | There are some errors that I encounter when running tests on Windows.
**tests\test_benchmark.py**
```
obj = <MemoryMeasureProcess(MemoryMeasureProcess-8, initial)>
file = <_io.BufferedWriter name=10>, protocol = None
def dump(obj, file, protocol=None):
'''Replacement for pickle.dump() using ForkingPic... | {
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https://api.github.com/repos/huggingface/transformers/issues/11585 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11585/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11585/comments | https://api.github.com/repos/huggingface/transformers/issues/11585/events | https://github.com/huggingface/transformers/pull/11585 | 875,645,400 | MDExOlB1bGxSZXF1ZXN0NjI5OTQ2Njg2 | 11,585 | [template runner CI] copies need to be fixed too | {
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Also it's unclear what purpose serves: `git fetch origin master:master` ... | {
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"Hey @krrishdholakia,\r\n\r\nWav2Vec2 was fine-tuned mostly on Librispeech which does not contain any punctuation so it'll be very difficult for the model to predict punctuation. You could take a pre-trained Wav2Vec2 model and fine-tune it on a downstream task that contains punctuation. This should then just work f... | 1,620 | 1,623 | 1,623 | NONE | null | Playing around with Wav2Vec2, and some of the sentences contain punctuation (like apostrophes, etc.) but i don't see any periods, question marks, commas etc. in my output.
I'm not sure if this a new feature, or just a way of handling the processing, but would it be possible to get punctuation in the Wav2Vec2 output... | {
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https://api.github.com/repos/huggingface/transformers/issues/11583 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11583/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11583/comments | https://api.github.com/repos/huggingface/transformers/issues/11583/events | https://github.com/huggingface/transformers/issues/11583 | 875,591,705 | MDU6SXNzdWU4NzU1OTE3MDU= | 11,583 | Wrong results for GLUE task STS-B | {
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"Are you sure you don't have any bad checkpoints in where your `output_dir` points to? Just executed the command and it works perfectly fine on my end. You can add `--overwrite_output_dir` to your command to make sure to overwrite what is there.",
"> Are you sure you don't have any bad checkpoints in where your `... | 1,620 | 1,621 | 1,621 | NONE | null | ## Environment info
- `transformers` version: 4.6.0.dev0
- Platform: Linux-4.13.0-26-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: True
- Using distributed or parallel set-up in script?: False
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11582 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11582/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11582/comments | https://api.github.com/repos/huggingface/transformers/issues/11582/events | https://github.com/huggingface/transformers/pull/11582 | 875,549,564 | MDExOlB1bGxSZXF1ZXN0NjI5ODY5OTY1 | 11,582 | Reproducible checkpoint | {
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"@stas00 Could you double check the last changes are all good with you? They include loading/saving all RNGs state (and separately in distributed training) as you suggested.",
"Everything looks great, @sgugger.\r\n\r\nGiven the fragile nature of this added feature it'd be relatively easily to break it, so may I s... | 1,620 | 1,646 | 1,620 | COLLABORATOR | null | # What does this PR do?
This PR fixes reproducibility when resuming training from a checkpoint for PyTorch >= 1.6 and non-TPU trainings. The current implementation in the Trainer had two flaws:
First when going over the data at the beginning (skipping epochs and batches), the first shuffling was the same in the o... | {
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"You should use the `save_pretrained` method to save the models.",
"when i was trying to save model model.save_pretrained(\"./model/\").\r\nI got error\r\nAttributeError: 'Functional' object has no attribute 'save_pretrained'",
"This issue has been automatically marked as stale because it has not had recent act... | 1,620 | 1,623 | 1,623 | NONE | null | Hi Team,
I was trying to save model but i got error.
model.save("model1.h5")
but it didn't work.
I tried different method like model.save("model1") so it will save as .pb file. But when i was trying to load I am getting below error.
please let me know how to solved it. how can save model after using distil-bert w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11580 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11580/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11580/comments | https://api.github.com/repos/huggingface/transformers/issues/11580/events | https://github.com/huggingface/transformers/issues/11580 | 875,412,527 | MDU6SXNzdWU4NzU0MTI1Mjc= | 11,580 | ValueError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length | {
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"@Kamilbentounes Were you able to resolve this error? If so, how did you do it? I'm also having the same error.",
"I am having the same error again in the following notebook. It occurs on cell # 3\r\nhttps://colab.research.google.com/github/huggingface/notebooks/blob/master/course/chapter7/section5_pt.ipynb",
"... | 1,620 | 1,692 | 1,620 | NONE | null | ## Environment info
- `transformers` version: 4.4.0
- Ubuntu 18.04
- Python version: 3.7.4
- PyTorch version: 1.8.1
- Using Colab
@Nithin-Holla @LysandreJik
Models: Wav2vec 2.0
## Information
Model I am using : Wav2vec 2.0
The problem arises when using:
* [Theses steps](https://colab.research.g... | {
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"For reference, pandas leverages `s3fs` and `gcsfs`. A generic implementation is available through `fsspec.open()` (see [docs](https://filesystem-spec.readthedocs.io/en/latest/usage.html#higher-level)). Would the maintainers be open to that? I would be happy to contribute.",
"This issue has been automatically mar... | 1,620 | 1,637 | 1,624 | CONTRIBUTOR | null | # 🚀 Feature request
Support saving and loading models to and from remote buckets, e.g. Google Cloud Storage and Amazon S3.
## Motivation
Currently this is not supported, making it more difficult to train in AWS/GCP.
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"Hi there,\r\n\r\nCould you post the full stack trace ?\r\n\r\nAlso, does the `encoder`s forward has this argument? Because if you see here, the extra `kwargs` are passed to the encoder as well\r\n\r\nhttps://github.com/huggingface/transformers/blob/09b0bcfea98eb9e863248fd29566b6d1caf9a0ea/src/transformers/generati... | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | Hi, I'm working on custom `BartForConditionalGeneration` model and it has additional parameters as following.
parameter with `'pos_' `prefix is the parameter I added personally.
```
class SynSemBartForConditionalGeneration(BartPretrainedModel):
...
def forward(
self,
input_ids=... | {
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https://api.github.com/repos/huggingface/transformers/issues/11577 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11577/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11577/comments | https://api.github.com/repos/huggingface/transformers/issues/11577/events | https://github.com/huggingface/transformers/issues/11577 | 875,314,983 | MDU6SXNzdWU4NzUzMTQ5ODM= | 11,577 | potential mismatch between `save_pretrained` and `from_pretrained` for `AutoTokenizer` | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,685 | 1,680 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-4.15.0-48-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.3
- PyTorch version (GPU?): 1.6.0+cu101 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?... | {
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https://api.github.com/repos/huggingface/transformers/issues/11576 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11576/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11576/comments | https://api.github.com/repos/huggingface/transformers/issues/11576/events | https://github.com/huggingface/transformers/issues/11576 | 875,300,473 | MDU6SXNzdWU4NzUzMDA0NzM= | 11,576 | no connection error | {
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"Please put the code you used that led to this error.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github... | 1,620 | 1,623 | 1,623 | NONE | null |
- `transformers` version: 4.5.0
- Platform: linux
- Python version: 3.8
- PyTorch version (GPU?): 1.7.1
- Tensorflow version (GPU?):
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?:
Models: mbart and mt5
@patrickvonplaten, @patil-suraj
output: ValueError: Connection... | {
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https://api.github.com/repos/huggingface/transformers/issues/11575 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11575/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11575/comments | https://api.github.com/repos/huggingface/transformers/issues/11575/events | https://github.com/huggingface/transformers/issues/11575 | 875,153,849 | MDU6SXNzdWU4NzUxNTM4NDk= | 11,575 | longform | {
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform:
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in script... | {
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https://api.github.com/repos/huggingface/transformers/issues/11574 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11574/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11574/comments | https://api.github.com/repos/huggingface/transformers/issues/11574/events | https://github.com/huggingface/transformers/issues/11574 | 875,085,179 | MDU6SXNzdWU4NzUwODUxNzk= | 11,574 | Number of BART layers is confusing in the Pretrained models page | {
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"Hi @mnskim \r\n\r\nUsually, we specify the total number of layers in a model instead of an individual components layer (i.e encoder or decoder). And seq2seq models like BART, T5 usually use the same number of layers in both encoder-decoder i.e 6-6 or 12-12. We could specify the encoder layer and decoder layer if t... | 1,620 | 1,648 | 1,623 | NONE | null | In the [Pretrained models](https://huggingface.co/transformers/pretrained_models.html) page, facebook/bart-large is described as 24-layer, 1024-hidden, 16-heads, 406M parameters, and facebook/bart-base as 12-layer, 768-hidden, 16-heads, 139M parameters.
I think this is a little confusing because bart-base consists o... | {
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https://api.github.com/repos/huggingface/transformers/issues/11573 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11573/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11573/comments | https://api.github.com/repos/huggingface/transformers/issues/11573/events | https://github.com/huggingface/transformers/pull/11573 | 874,999,544 | MDExOlB1bGxSZXF1ZXN0NjI5NDM3NjQ2 | 11,573 | Make quality scripts work when one backend is missing. | {
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"The CI will have all backends installed.\r\n\r\nThis takes care of contributors that cannot install one backend for one reason or another (for instance if jax/flax was not available on Windows which wouldn't surprise me).",
"> The CI will have all backends installed.\r\n\r\nAll is good then.\r\n\r\nI totally agr... | 1,620 | 1,620 | 1,620 | COLLABORATOR | null | # What does this PR do?
This PR makes the quality scripts issue a warning instead of erroring when one backend is missing (which shouldn't be the case since the contributing guide says to run `pip install -e .[dev]` but we never know). It's also fine since a user is unlikely to make changes to a specific backend of ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11572 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11572/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11572/comments | https://api.github.com/repos/huggingface/transformers/issues/11572/events | https://github.com/huggingface/transformers/pull/11572 | 874,835,303 | MDExOlB1bGxSZXF1ZXN0NjI5MzA2ODE3 | 11,572 | [Deepspeed] fix resize_token_embeddings | {
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uncovered a bug in Deepspeed integration.
We have to create the new resized embedd... | {
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https://api.github.com/repos/huggingface/transformers/issues/11571 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11571/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11571/comments | https://api.github.com/repos/huggingface/transformers/issues/11571/events | https://github.com/huggingface/transformers/issues/11571 | 874,789,280 | MDU6SXNzdWU4NzQ3ODkyODA= | 11,571 | reformer-enwik8 Fine-tuning | {
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"Hi, you could use [this ](https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/PyTorch_Reformer.ipynb) notebook as a reference, it shows how to train reformer on the crime-and-punishment data. \r\n\r\nYou could usually find such examples in the community notebooks section [here](https://... | 1,620 | 1,623 | 1,623 | NONE | null | Could you pls provide a demo for training and Fine-tuning the model of 'reformer-enwik8'? @patrickvonplaten | {
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https://api.github.com/repos/huggingface/transformers/issues/11570 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11570/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11570/comments | https://api.github.com/repos/huggingface/transformers/issues/11570/events | https://github.com/huggingface/transformers/issues/11570 | 874,734,958 | MDU6SXNzdWU4NzQ3MzQ5NTg= | 11,570 | [fixup/style] requires TF but doesn't say that cleanly | {
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"The same thing happens with flax.",
"This should take care of all the deps:\r\n```\r\npip install -e .[dev]\r\n```\r\nPlease let us know if it didn't.",
"I don't think we need a new script for that. Maybe add the check inside the script that fails (`check_all_models_are_auto_configured`) and issue a warning if... | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | It looks like `make fixup` et al, require tf (and pt), but fail in unexpected way when the requirements are missing:
```
python utils/check_repo.py
Checking all models are properly tested.
Checking all objects are properly documented.
Checking all models are in at least one auto class.
Traceback (most recent ca... | {
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https://api.github.com/repos/huggingface/transformers/issues/11569 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11569/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11569/comments | https://api.github.com/repos/huggingface/transformers/issues/11569/events | https://github.com/huggingface/transformers/pull/11569 | 874,670,195 | MDExOlB1bGxSZXF1ZXN0NjI5MTc4NTcz | 11,569 | Fix metric computation in `run_glue_no_trainer` | {
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There is a problem in the metric computation in `run_glue_no_trainer`, which always takes the argmax regardless of the task: when the problem is a regression problem it should not be the case.
Fixes #11555 | {
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"You're sending this to your tokenizer: `[(example.text_a, example.text_b) for example in examples]`\r\n\r\nBut this is: `[('Ututu goes public.', None), ('This moon is huge.', None)]`.\r\n\r\nA tokenizer cannot handle `None`, only text.",
"This issue has been automatically marked as stale because it has not had r... | 1,620 | 1,623 | 1,623 | NONE | null | ### Bug
On version 4.5.1, trying to use fast tokenizer for Roberta, and got the above error. Weirdly, saw `transformers/models/gpt2/tokenization_gpt2_fast.py` in the traceback even no `gpt2` models are involved.
**Script to reproduce**
```
from transformers import AutoTokenizer
from transformers.data.proces... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,623 | 1,623 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.9.4
- PyTorch version (GPU?): 1.8.1+cpu (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
## Information
Model... | {
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https://api.github.com/repos/huggingface/transformers/issues/11566 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11566/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11566/comments | https://api.github.com/repos/huggingface/transformers/issues/11566/events | https://github.com/huggingface/transformers/pull/11566 | 874,540,550 | MDExOlB1bGxSZXF1ZXN0NjI5MDc3MjA0 | 11,566 | Fixes a useless warning in `generate`. | {
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"Sorry about that ! \r\n\r\nI'll wait for @patrickvonplaten before merging."
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
We removed `max_length` as a necessary parameter for `greedy`/`sample`/`beam_search`/`group_beam_search`.
Unfortunately a extra warnings made its way in the PR which is unwarranted for.
Fixes #11371
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"Looks like using --dataset_name parameters prevents other tasks from working, causing the same error. But using custom datasets with --train_file and --validation_file passing csv/json paths seems to work. However, this doesn't happen for NER dataset. I'm getting an error for --dataset_name conll2003 or using cust... | 1,620 | 1,626 | 1,626 | 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-4.15.0-142-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (... | {
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https://api.github.com/repos/huggingface/transformers/issues/11564 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11564/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11564/comments | https://api.github.com/repos/huggingface/transformers/issues/11564/events | https://github.com/huggingface/transformers/pull/11564 | 874,471,914 | MDExOlB1bGxSZXF1ZXN0NjI5MDI1NTAy | 11,564 | Adds Flax BERT finetuning example on GLUE | {
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"Changes were done according to discussion [here](https://github.com/huggingface/transformers/pull/11593)",
"Test failures are unrelated"
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
Adds Flax BERT finetuning example which finetunes on one of the GLUE tasks.
I evaluated all tasks 5 times and added the average runs, the best run. and stdev in a table in the README. I used the seed of the best run as the default.
I also ran all experiments on three devices: 8 Cloud TP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11562 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11562/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11562/comments | https://api.github.com/repos/huggingface/transformers/issues/11562/events | https://github.com/huggingface/transformers/pull/11562 | 874,409,418 | MDExOlB1bGxSZXF1ZXN0NjI4OTc0NjQx | 11,562 | [Wav2Vec2] Fix convert | {
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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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"You don't have the latest master installed and the examples are synced with it. The easiest way is probably to do:\r\n```\r\npip uninstall transformers\r\npip install git+https://github.com/huggingface/transformers\r\n```\r\nto upgrade to the latest!\r\n\r\nOtherwise you can do an [editable install](https://huggin... | 1,620 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
`transformers` version: 4.6.0.dev0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.9
- PyTorch version (GPU?): 1.8.1+cpu ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11560 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11560/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11560/comments | https://api.github.com/repos/huggingface/transformers/issues/11560/events | https://github.com/huggingface/transformers/issues/11560 | 874,350,318 | MDU6SXNzdWU4NzQzNTAzMTg= | 11,560 | Error In Fine-Tuning Transformer XL ValueError: The two structures don't have the same sequence length. Input structure has length 3, while shallow structure has length 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)... | 1,620 | 1,633 | 1,626 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
###... | {
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https://api.github.com/repos/huggingface/transformers/issues/11559 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11559/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11559/comments | https://api.github.com/repos/huggingface/transformers/issues/11559/events | https://github.com/huggingface/transformers/pull/11559 | 874,325,930 | MDExOlB1bGxSZXF1ZXN0NjI4OTA5OTUx | 11,559 | fix the mlm longformer example by changing [MASK] to <mask> | {
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"Is there any way to look at the \"new\" docs locally? Because I don't know how to test my change if it's docs related",
"Yes! You can run `make docs` at the root of your clone. You can also run `make html` in the `docs` folder :)",
"You'll need to do `pip install .[docs]` beforehand to have all the appropriate... | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | This PR fixes an official Huggingface example in the Longformer model
## Before submitting
- [x ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
@Rocketknight1 this PR is to address https://github.com/huggingface/transformers/issues/11488#issuecomment-830065245
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"nit question: Any reason why we are accepting `bias_init` as a parameter while in all other modules we just use directly in `setup`\r\nhttps://github.com/huggingface/transformers/blob/a5d2967bd8a5ed2456c593fa9eb5d9c0d726ae7a/src/transformers/models/bert/modeling_flax_bert.py#L480-L483"
] | 1,620 | 1,620 | 1,620 | MEMBER | null | # What does this PR do?
This PR fixes a few docs in Flax models. | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,620 | 1,623 | 1,623 | NONE | null | # 🚀 Feature request
Dense Passage Retrieval should work with any language model as encoder, in particular also with ELECTRA models.
However, the current implementation of the class `DPREncoder` seems to be limited to BERT models:
https://github.com/huggingface/transformers/blob/a5d2967bd8a5ed2456c593fa9eb5d9c0d... | {
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https://api.github.com/repos/huggingface/transformers/issues/11556 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11556/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11556/comments | https://api.github.com/repos/huggingface/transformers/issues/11556/events | https://github.com/huggingface/transformers/pull/11556 | 874,223,918 | MDExOlB1bGxSZXF1ZXN0NjI4ODI2Njc0 | 11,556 | FlaxGPT2 | {
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"@LysandreJik @sgugger - this PR is blocking a couple of other things. Let me know if you guys aren't really ok with some of those things"
] | 1,620 | 1,621 | 1,621 | MEMBER | null | # What does this PR do?
[From Patrick:]
This PR adds GPT2 for Flax and lays the groundwork for `generation` in Flax.
The model is a straightforward translation from PyTorch with two exceptions:
1.) the `past_key_values/caching` is more complex since `generation` has to compile to be usable on TPU with Flax/J... | {
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https://api.github.com/repos/huggingface/transformers/issues/11555 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11555/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11555/comments | https://api.github.com/repos/huggingface/transformers/issues/11555/events | https://github.com/huggingface/transformers/issues/11555 | 874,222,625 | MDU6SXNzdWU4NzQyMjI2MjU= | 11,555 | NaN Person/Spearman corr. when fine-tuning BERT with example code and commands | {
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"Oh yes, we forgot to add special case for sts-b (which is a regression task) in this script. Will send a fix later this morning! Thanks for flagging!",
"Thank you @sgugger for the prompt fix!"
] | 1,620 | 1,620 | 1,620 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1
- Platform: Google COLAB and Ubuntu 18 LTS (tested both)
- Python version: 3.7 and 3.6
- PyTorch versi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11549 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11549/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11549/comments | https://api.github.com/repos/huggingface/transformers/issues/11549/events | https://github.com/huggingface/transformers/issues/11549 | 874,153,615 | MDU6SXNzdWU4NzQxNTM2MTU= | 11,549 | Bugs when trying to train a T5model from scratch in the run_summarization.py script | {
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"Hi there,\r\n\r\nThis is because you are using `T5Model`. When using `T5Model`, `decoder_input_ids` should be directly passed, but the examples pass `lables` which `T5Model` doesn't accept.\r\n\r\nAlso, for this task `T5ForConditionalGenerations` should be used instead of `T5Model`, it will take `lables` and prepa... | 1,620 | 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
- Platform: Macbook
- Python version: 3.7
- PyTorch version (GPU?):GPU
- Using GPU in script?:yes
#... | {
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https://api.github.com/repos/huggingface/transformers/issues/11548 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11548/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11548/comments | https://api.github.com/repos/huggingface/transformers/issues/11548/events | https://github.com/huggingface/transformers/issues/11548 | 874,013,440 | MDU6SXNzdWU4NzQwMTM0NDA= | 11,548 | why run_translation.py automatically is running on cpu? | {
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"Could you please post the command that you used?",
"I run the command for telugu to telugu\r\n\r\n\r\n python examples/pytorch/translation/run_translation.py --model_name_or_path facebook/mbart-large-50 --do_train --do_eval --do_predict --source_lang te_IN --target_lang te_IN --test_... | 1,619 | 1,623 | 1,623 | NONE | null |
-`transformers` version: 4.5.0
- Platform: linux
- Python version: 3.8
- PyTorch version (GPU?): 1.7.1
- Tensorflow version (GPU?):
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?:yes
@patrickvonplaten, @patil-suraj
Models: mbart-large-50
| {
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https://api.github.com/repos/huggingface/transformers/issues/11547 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11547/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11547/comments | https://api.github.com/repos/huggingface/transformers/issues/11547/events | https://github.com/huggingface/transformers/issues/11547 | 873,944,063 | MDU6SXNzdWU4NzM5NDQwNjM= | 11,547 | tokenizer not padding input_ids | {
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"Hello! I believe this comes from the fact that you're not passing `input_ids` as a `model_input_names` value. The tokenizer is unaware it should pad this value, so it doesn't.\r\n\r\nIf this code sample was working in previous versions, it's because of a bug that ignored the `input_ids` and always padded them whet... | 1,619 | 1,620 | 1,620 | NONE | null | ### Tokenizer Bug
Tested on RoBERTa and BERT tokenizer of version `4.5.1`, when calling `tokenizer()` with parameter set to pad sequence to `max_length`, the return value does not pad `input_ids`, only `token_type_ids` and `attention_masks`. This result in a downstream error in model `forward` step, where it complai... | {
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https://api.github.com/repos/huggingface/transformers/issues/11546 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11546/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11546/comments | https://api.github.com/repos/huggingface/transformers/issues/11546/events | https://github.com/huggingface/transformers/issues/11546 | 873,879,049 | MDU6SXNzdWU4NzM4NzkwNDk= | 11,546 | T5 fp16 crashes on the CPU (but works on CUDA) | {
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"AFAIK there is no possibility to run half-precision (fp16) on CPU in general (cc @stas00)",
"Last I looked pytorch didn't support that: https://github.com/pytorch/pytorch/issues/48245\r\n\r\nBut there is a design discussion going here: https://github.com/pytorch/pytorch/issues/55374 which discusses AMP for bf16 ... | 1,619 | 1,625 | 1,625 | CONTRIBUTOR | null | ## Environment info
* transformers version: 4.5.1
* Platform: Linux-4.15.0-126-generic-x86_64-with-glibc2.10 (ubuntu 18.04)
* Python version: 3.8.0
* PyTorch version (GPU?): 1.7.1 (True)
* Tensorflow version (GPU?): not installed (NA)
* Using GPU in script?: Nvidia Quadro RTX 8000
* Using ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11545 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11545/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11545/comments | https://api.github.com/repos/huggingface/transformers/issues/11545/events | https://github.com/huggingface/transformers/issues/11545 | 873,863,340 | MDU6SXNzdWU4NzM4NjMzNDA= | 11,545 | Strugle to change `num_labels` of roberta-large-mnli | {
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"Please have a look at [link](https://stackoverflow.com/questions/67158554/fine-tuning-models-classifier-layer-with-new-label/67187807#67187807). You can not resize a pre-trained model via config. You need to do it by yourself.",
"@cronoik , Thank you very for your response!\r\n\r\nI've changed the code to the fo... | 1,619 | 1,623 | 1,623 | NONE | null | - `transformers` version: 4.4.0
- Platform: Linux-5.8.0-45-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.7.10
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
I am trying to bui... | {
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https://api.github.com/repos/huggingface/transformers/issues/11544 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11544/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11544/comments | https://api.github.com/repos/huggingface/transformers/issues/11544/events | https://github.com/huggingface/transformers/issues/11544 | 873,812,482 | MDU6SXNzdWU4NzM4MTI0ODI= | 11,544 | 'return_dict_in_generate' and 'output_scores' argument in BartForConditionalGeneration.generate() | {
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"hi @ktr0921 \r\n\r\nPlease use the [forum](https://discuss.huggingface.co/) to ask such question, [this](https://discuss.huggingface.co/t/generation-probabilities-how-to-compute-probabilities-of-output-scores-for-gpt2/3175) thread might help"
] | 1,619 | 1,620 | 1,620 | NONE | null | Dear all
I was wondering if I can ask you some questions about how to use `.generate()` for BART or other pre-trained models. The example code is,
```
from transformers import BartTokenizer, BartForConditionalGeneration, BartConfig
path = 'facebook/bart-large'\
model = BartForConditionalGeneration.from_pretraine... | {
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https://api.github.com/repos/huggingface/transformers/issues/11543 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11543/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11543/comments | https://api.github.com/repos/huggingface/transformers/issues/11543/events | https://github.com/huggingface/transformers/issues/11543 | 873,800,792 | MDU6SXNzdWU4NzM4MDA3OTI= | 11,543 | Error when trying to use GPTNeo model | {
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"I cannot reproduce the error. `GPTNeoForCausalLM` clearly has a `from_pretrained(...)` method",
"Not sure what I'm doing wrong then. I'll post another snippet. \r\n\r\n```\r\nfrom transformers import GPT2Tokenizer, GPTNeoForCausalLM, pipeline\r\nimport tensorflowjs\r\n\r\ntokenizer = GPT2Tokenizer.from_pretraine... | 1,619 | 1,677 | 1,620 | NONE | null | ## Environment info
- `transformers` version: 4.6.0.dev0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.7
- PyTorch version (GPU?): not installed (NA)
- Tensorflow version (GPU?): 2.4.0 (False)
- Using GPU in script?: Not yet
- Using distributed or parallel set-up in script?: yes
### Who can he... | {
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https://api.github.com/repos/huggingface/transformers/issues/11541 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11541/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11541/comments | https://api.github.com/repos/huggingface/transformers/issues/11541/events | https://github.com/huggingface/transformers/issues/11541 | 873,773,939 | MDU6SXNzdWU4NzM3NzM5Mzk= | 11,541 | Pegasus tokenizer does not have bos token, cannot pretrain | {
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"Hi there,\r\n\r\nyes, PEGASUS has no BOS token, instead it uses `pad_token_id` as the `decoder_start_token_id`. Also, you won't need to pass `deocder_input_ids`, if you pass the `labels` the model prepares the `decoder_input_ids` by shifting the `labels` and setting the first token to pad token.",
"Hi @patil-su... | 1,619 | 1,639 | 1,625 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform: Ubuntu 18.04
- Python version: 3.8
- PyTorch version (GPU?): 1.7.1 with GPU (CUDA 10.1)
- Tenso... | {
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https://api.github.com/repos/huggingface/transformers/issues/11540 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11540/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11540/comments | https://api.github.com/repos/huggingface/transformers/issues/11540/events | https://github.com/huggingface/transformers/pull/11540 | 873,759,132 | MDExOlB1bGxSZXF1ZXN0NjI4NDg4MDYz | 11,540 | Fix examples in M2M100 docstrings | {
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Replaces `tok` with `tokenizer` so examples can run with copy-paste
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers... | {
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https://api.github.com/repos/huggingface/transformers/issues/11539 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11539/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11539/comments | https://api.github.com/repos/huggingface/transformers/issues/11539/events | https://github.com/huggingface/transformers/issues/11539 | 873,753,020 | MDU6SXNzdWU4NzM3NTMwMjA= | 11,539 | Unable to load DistilBertModel during training | {
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"Does removing the space between `--` and `n_gpu` help?",
"Yes @LysandreJik I was trying to use gpu device 1 , later made device changes from code .Thanks "
] | 1,619 | 1,620 | 1,620 | NONE | null | I'm following the example to train a DistilBert model from scratch from: examples/distillation/README.md
[https://github.com/huggingface/transformers/blob/1ab8dc44b3d84ed1894f5b6a6fab58fb39298fc7/examples/distillation/README.md](url)
during preparation of data converted my json training data to text and generated... | {
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