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"No, it shouldn't!",
"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/... | 1,614 | 1,619 | 1,619 | NONE | null | Hi!
I just want to know whether or not the speed is slower in model forward function like roberta or bert when return_dict=True. | {
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https://api.github.com/repos/huggingface/transformers/issues/10432 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10432/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10432/comments | https://api.github.com/repos/huggingface/transformers/issues/10432/events | https://github.com/huggingface/transformers/issues/10432 | 817,804,871 | MDU6SXNzdWU4MTc4MDQ4NzE= | 10,432 | Adding Longformer Encoder Decoder support for T5 | {
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"So it looks like using sliding chunk mult is not the way to go. I can't figure out what's happening to the attn_scores and how it is shaped to be able to apply the position bias to it.\r\n\r\n\r\n```\r\n # POSITION_BIAS here: stack 2*one_sided_attn_window_size+1 worth of bias in the last dimension\r\n ... | 1,614 | 1,619 | 1,619 | NONE | null | # 🚀 Adding Longformer Encoder Decoder support for T5
LED is great for doing long form encoder decoder of documents, but it is based only on BART. T5 has certain advantages, such as being designed for multi tasks (QA, summarization, etc.) and having relative positioning.
T5 uses relative positioning which maps w... | {
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https://api.github.com/repos/huggingface/transformers/issues/10430 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10430/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10430/comments | https://api.github.com/repos/huggingface/transformers/issues/10430/events | https://github.com/huggingface/transformers/issues/10430 | 817,699,483 | MDU6SXNzdWU4MTc2OTk0ODM= | 10,430 | Inference with Finetuned BERT Model outputting odd results | {
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"Hi,\r\n\r\nis it possible to ask this question on the [forum](https://discuss.huggingface.co/) rather than here? Since this question is a perfect use case for that.\r\n\r\nThank you. ",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be ... | 1,614 | 1,619 | 1,619 | 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: 3.5.1
- Platform: Linux-4.14.203-116.332.amzn1.x86_64-x86_64-with-glibc2.10
- Python version: 3.7.6
- PyTorc... | {
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https://api.github.com/repos/huggingface/transformers/issues/10429 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10429/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10429/comments | https://api.github.com/repos/huggingface/transformers/issues/10429/events | https://github.com/huggingface/transformers/issues/10429 | 817,694,937 | MDU6SXNzdWU4MTc2OTQ5Mzc= | 10,429 | Trainer's load_best_model_at_end argument results in error with DistributedDataParallel | {
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"Could you explain a bit more the code you are running as well as the exact command you are using for launch? We can't help if we can't reproduce your bug and running:\r\n```\r\npython -m torch.distributed.launch --nproc_per_node 2 examples/text-classification/run_glue.py \\\r\n --model_name_or_path bert-base-unca... | 1,614 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.0
- Platform: Linux
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1 (CUDA Version: 11.2)
- Tens... | {
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https://api.github.com/repos/huggingface/transformers/issues/10428 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10428/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10428/comments | https://api.github.com/repos/huggingface/transformers/issues/10428/events | https://github.com/huggingface/transformers/pull/10428 | 817,692,475 | MDExOlB1bGxSZXF1ZXN0NTgxMTQyOTIw | 10,428 | [run_seq2seq.py] restore functionality: saving to test_generations.txt | {
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"Ah, I re-read it closer, you're correct. I just remembered the part about the `test_generations.txt` but didn't bother to check out the full story. My bad. I will study it and follow up once I understand it better. ",
"I went back to `finetune_trainer.py` from December and checked that it was just saving `test_g... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | This PR restores the original functionality that for some reason was modified.
Fixes: https://github.com/huggingface/transformers/issues/10381
@sgugger
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https://api.github.com/repos/huggingface/transformers/issues/10427 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10427/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10427/comments | https://api.github.com/repos/huggingface/transformers/issues/10427/events | https://github.com/huggingface/transformers/pull/10427 | 817,677,097 | MDExOlB1bGxSZXF1ZXN0NTgxMTI5MDgz | 10,427 | [examples] better model example | {
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* [x] makes the helper methods work for rank0 internally - simplifying the caller
* [x] abstracts t... | {
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https://api.github.com/repos/huggingface/transformers/issues/10426 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10426/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10426/comments | https://api.github.com/repos/huggingface/transformers/issues/10426/events | https://github.com/huggingface/transformers/pull/10426 | 817,675,353 | MDExOlB1bGxSZXF1ZXN0NTgxMTI3NjQ2 | 10,426 | [WIP] CLIP | {
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"Awesome effort. Is the current version already compatible with (now merged) #10594 ?",
"Thanks @dribnet \r\n\r\nI haven't added a feature extractor class for CLIP yet. We first need to finish the `ImageFeatureExtractor` (#01608)\r\nThen the `ClipFeatureExtractor` can inherit from that. This PR will be ready to m... | 1,614 | 1,619 | 1,619 | MEMBER | null | # What does this PR do?
This PR adds OpenAI's CLIP model.
original repo: https://github.com/openai/CLIP
initial demo: https://colab.research.google.com/drive/1hwiCuKvw7hwSlE8yv7J1dh280PlYgPef?usp=sharing | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,614 | 1,614 | 1,614 | NONE | null | I pretrained a rag model using the "finetune_rag.py" script and it generates pretty good results for my (knowledge intensive) use case, certainly better than the straight finetuned BART model i was using before. I am using my own custom datasource generated from use_own_knowledge_dataset.py. One curious thing that is h... | {
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https://api.github.com/repos/huggingface/transformers/issues/10424 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10424/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10424/comments | https://api.github.com/repos/huggingface/transformers/issues/10424/events | https://github.com/huggingface/transformers/pull/10424 | 817,569,644 | MDExOlB1bGxSZXF1ZXN0NTgxMDQwNzM2 | 10,424 | Refactor checkpoint name in BERT and MobileBERT | {
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Linked to #10193, this PR gives an example on how to refactor the checkpoint names in one private constant and use the `# Copied from` syntax to make the task-specific models that are copies of each other properly watched by our tooling.
It adds the option in check-copies to:
- put multip... | {
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"Hi @stas00,\r\nCan I work on this?",
"Yes please! Thank you, @bhadreshpsavani ",
"I was just thinking about this and why do we not have this functionality in the Trainer in first place? then perhaps none of this will be needed.\r\n\r\nI'm asking here: https://github.com/huggingface/transformers/issues/10437\r\... | 1,614 | 1,615 | 1,615 | CONTRIBUTOR | null | As a part of an effort to make all examples have the same look and feel this issue requests to sync the support for these 3 cl args in `run_seq2seq.py`:
```
--max_train_samples 5 --max_val_samples 5 --max_test_samples 5
```
into:
1. all other `examples/*/run_*.py`
2. `templates/adding_a_new_example_script`
Par... | {
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https://api.github.com/repos/huggingface/transformers/issues/10422 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10422/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10422/comments | https://api.github.com/repos/huggingface/transformers/issues/10422/events | https://github.com/huggingface/transformers/pull/10422 | 817,522,054 | MDExOlB1bGxSZXF1ZXN0NTgxMDAxMTcw | 10,422 | Layoutlm tf | {
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"Very nice! Can you let us know when you want us to review/give feedback/help? Thanks!",
"> Very nice! Can you let us know when you want us to review/give feedback/help? Thanks!\r\n\r\nthanks! I need to upload the TF model file to the hub and run another check to make sure it gives the same results as the PT vers... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/10421 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10421/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10421/comments | https://api.github.com/repos/huggingface/transformers/issues/10421/events | https://github.com/huggingface/transformers/pull/10421 | 817,514,809 | MDExOlB1bGxSZXF1ZXN0NTgwOTk1MjI4 | 10,421 | updated metrics saving and logging | {
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"I want to mention one thing here while testing the file I found that,\r\nFor files `run_clm.py, run_mlm.py, run_plm.py, run_ner.py, run glue.py`\r\nThe logs are as expected like this\r\n```\r\n02/26/2021 20:31:22 - INFO - __main__ - ***** eval metrics *****\r\n02/26/2021 20:31:22 - INFO - __main__ - HasAns_e... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | # What does this PR do?
I have updated redundant code for saving and logging metrics in the example scripts
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https://api.github.com/repos/huggingface/transformers/issues/10420 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10420/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10420/comments | https://api.github.com/repos/huggingface/transformers/issues/10420/events | https://github.com/huggingface/transformers/issues/10420 | 817,405,736 | MDU6SXNzdWU4MTc0MDU3MzY= | 10,420 | Unable to convert Facebook/mbart-many-to-many model to onxx | {
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"I do not think mBART can be converted to ONNX as of now.",
"Hi Thanks for the information.\r\nFacebook/many-to-many takes 9s seconds for translation on cpu , is there a way to reduce the inference time ?",
"Hi @sankarsiva123, have you tried HF's API inference ?\r\n\r\n9s per inference seems a bit off: https://... | 1,614 | 1,619 | 1,619 | NONE | null | When I tried to convert Facebook/mbart-many-to-many model . I am unable to convert I am getting issue.
Pls help me to convert this model to ONXX | {
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https://api.github.com/repos/huggingface/transformers/issues/10419 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10419/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10419/comments | https://api.github.com/repos/huggingface/transformers/issues/10419/events | https://github.com/huggingface/transformers/pull/10419 | 817,402,457 | MDExOlB1bGxSZXF1ZXN0NTgwOTAxMjM1 | 10,419 | [LED] Correct Docs | {
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https://api.github.com/repos/huggingface/transformers/issues/10418 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10418/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10418/comments | https://api.github.com/repos/huggingface/transformers/issues/10418/events | https://github.com/huggingface/transformers/issues/10418 | 817,396,368 | MDU6SXNzdWU4MTczOTYzNjg= | 10,418 | Slow evaluation using Trainer with TPUs in Colab | {
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"The notebook won't execute on TPU, you need to spawn a function on multiple processes for this (`xm.spawn(train_function)`). That function should contain all the training code including the `Trainer`, but `Trainer.train` by itself won't spawn multiple processes.\r\n\r\nThe recommended way to train on TPU is to fol... | 1,614 | 1,618 | 1,614 | NONE | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.9.0a0+7a178a8 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: TPU
- Using distributed or parallel set-up in script?: NO
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10417 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10417/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10417/comments | https://api.github.com/repos/huggingface/transformers/issues/10417/events | https://github.com/huggingface/transformers/pull/10417 | 817,384,747 | MDExOlB1bGxSZXF1ZXN0NTgwODg2NTIy | 10,417 | Dont use sigmoid when num_labels==1 | {
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"Sorry, I don't really understand this - could give a bit more context?",
"@patrickvonplaten Please see this https://github.com/huggingface/transformers/blob/master/src/transformers/models/bert/modeling_bert.py#L1515\r\nor any `XForSequenceClassification` model",
"This is a very big breaking change. What do you... | 1,614 | 1,651 | 1,619 | MEMBER | null | It seems like we use MSELoss when num_labels==1 in config, i.e. a single column regression problem. But in text_classification pipeline, this is considered as a classification problem and uses sigmoid. This PR fixes that issue. | {
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https://api.github.com/repos/huggingface/transformers/issues/10416 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10416/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10416/comments | https://api.github.com/repos/huggingface/transformers/issues/10416/events | https://github.com/huggingface/transformers/pull/10416 | 817,344,217 | MDExOlB1bGxSZXF1ZXN0NTgwODUyNjA4 | 10,416 | Add BERTForMultiLabel Classification or Regression | {
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"moving to new pr"
] | 1,614 | 1,651 | 1,617 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/10415 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10415/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10415/comments | https://api.github.com/repos/huggingface/transformers/issues/10415/events | https://github.com/huggingface/transformers/issues/10415 | 817,291,312 | MDU6SXNzdWU4MTcyOTEzMTI= | 10,415 | Bug when combining grouped beam search and constrained prefix decoding | {
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"Hey @mnschmit,\r\n\r\nthanks for your bug report! Yes, you're right -> I think we should indeed replace `num_beams` by `num_beams // num_beam_groups`. Do you want to open a PR to fix it? :-) Otherwise, I can do it as well"
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Linux-5.8.0-38-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyTorch version (GPU?): 1.5.1+cu101 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
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https://api.github.com/repos/huggingface/transformers/issues/10414 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10414/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10414/comments | https://api.github.com/repos/huggingface/transformers/issues/10414/events | https://github.com/huggingface/transformers/pull/10414 | 817,284,602 | MDExOlB1bGxSZXF1ZXN0NTgwODAyMjUw | 10,414 | Add Ray Tune hyperparameter search integration test | {
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"Oh, that makes sense. Does this happen in the repo? Is this something I can help with, or do you have to configure it?",
"I'm currently working on these scheduled tests, I'll enable these while I do so. Thanks!"
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | # What does this PR do?
Currently, only Optuna HP search is tested in integration tests. This PR duplicates and adjusts the test for the Ray backend.
## 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 gu... | {
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https://api.github.com/repos/huggingface/transformers/issues/10413 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10413/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10413/comments | https://api.github.com/repos/huggingface/transformers/issues/10413/events | https://github.com/huggingface/transformers/pull/10413 | 817,255,751 | MDExOlB1bGxSZXF1ZXN0NTgwNzc4MTkz | 10,413 | Update run_mlm.py | {
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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)... | 1,614 | 1,619 | 1,619 | NONE | null | # What does this PR do?
<!--
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"I think this would a very welcome change indeed, so please work on that if you have time and if it's something you'd like to do!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note... | 1,614 | 1,619 | 1,619 | CONTRIBUTOR | null | # 🚀 Feature request
An enhancement of `best_model_checkpoint` for more robustness.
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
Currently `Trainer.state.best_model_checkpoint` holds absolute path to the best checkpoint when `... | {
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https://api.github.com/repos/huggingface/transformers/issues/10411 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10411/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10411/comments | https://api.github.com/repos/huggingface/transformers/issues/10411/events | https://github.com/huggingface/transformers/issues/10411 | 817,235,401 | MDU6SXNzdWU4MTcyMzU0MDE= | 10,411 | Problem using add_special_tokens | {
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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)... | 1,614 | 1,619 | 1,619 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:3.4.0
- Platform:windows
- Python version:3.7.0
- PyTorch version (GPU?):1.7.0
- Tensorflow version (GPU?):2... | {
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https://api.github.com/repos/huggingface/transformers/issues/10410 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10410/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10410/comments | https://api.github.com/repos/huggingface/transformers/issues/10410/events | https://github.com/huggingface/transformers/pull/10410 | 817,200,481 | MDExOlB1bGxSZXF1ZXN0NTgwNzMyMzYx | 10,410 | [WIP] RAG end-to-end retriever training (with ray workers) | {
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"@lhoestq @patrickvonplaten \r\n\r\nI have already started doing the above changes you have mentioned. Apart from that, I changed the following elements of the codebase. \r\n\r\n1. I used a dedicated RAY worker to compute embeddings for the dataset with an updated ctx encoder in this version. However, the proces... | 1,614 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
As mentioned in this [issue](https://github.com/huggingface/transformers/issues/9646), this PR adds the fine-tuning ability the Retriever in the original RAG implementation.
This PR first updates the ctx_encoder and then initializes the index using RAY workers.
@lhoestq
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https://api.github.com/repos/huggingface/transformers/issues/10409 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10409/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10409/comments | https://api.github.com/repos/huggingface/transformers/issues/10409/events | https://github.com/huggingface/transformers/pull/10409 | 817,161,253 | MDExOlB1bGxSZXF1ZXN0NTgwNzAwMjY0 | 10,409 | [ci, flax] non-existing models are unlikely to pass tests | {
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https://api.github.com/repos/huggingface/transformers/issues/10408 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10408/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10408/comments | https://api.github.com/repos/huggingface/transformers/issues/10408/events | https://github.com/huggingface/transformers/issues/10408 | 817,109,555 | MDU6SXNzdWU4MTcxMDk1NTU= | 10,408 | Question about the `decoder_input_ids` in `LEDForConditionalGeneration` forward method | {
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"Hey @yww211, \r\n\r\nactually there was a bug in the docstring, that I found thanks to you :-) The attached PR corrects this mistake.\r\n\r\nTo answer your question, you should not shift the `decoder_input_ids` explicitly by one when passing them & in fact you have to pass the `decoder_input_ids` if you want to us... | 1,614 | 1,614 | 1,614 | NONE | null | https://github.com/huggingface/transformers/blob/17b6e0d474b797cdddf5225b0f51bf0e928091b9/src/transformers/models/led/modeling_led.py#L2337
Hi,
I have a question about the `LEDForConditionalGeneration` forward args.
The `decoder_input_ids` has a comment that `decoder_input_ids (torch.LongTensor of shape (batch_... | {
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https://api.github.com/repos/huggingface/transformers/issues/10407 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10407/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10407/comments | https://api.github.com/repos/huggingface/transformers/issues/10407/events | https://github.com/huggingface/transformers/pull/10407 | 816,981,680 | MDExOlB1bGxSZXF1ZXN0NTgwNTUwODc5 | 10,407 | offline mode for firewalled envs | {
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"> The constant should be documented in the install page, in the section about caching models I think (https://huggingface.co/transformers/installation.html#caching-models).\r\n\r\nGreat idea, @sgugger. Please kindly check the doc I added is good when you get a chance.\r\n\r\nAnd also the kind of test I had to add ... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | This PR implements the proposal from https://github.com/huggingface/transformers/issues/10379 to enable transformers to cache everything it needs and then run in the offline mode - e.g. in a firewalled environment.
This PR:
* [x] adds `is_offline_mode()` helper function that returns `True` when env var `TRANSFORM... | {
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https://api.github.com/repos/huggingface/transformers/issues/10406 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10406/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10406/comments | https://api.github.com/repos/huggingface/transformers/issues/10406/events | https://github.com/huggingface/transformers/pull/10406 | 816,936,839 | MDExOlB1bGxSZXF1ZXN0NTgwNTE0MDE4 | 10,406 | Ray Tune Integration Bug Fixes | {
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"@amogkam There is an `s` missing in line 202 in `src/transformers/integrations.py` in `{kwargs['keep_checkpoint_num']}` which should be `{kwargs['keep_checkpoints_num']}`, which is causing the logger to crash instead of just a warning. Thanks for the fixes btw!\r\n"
] | 1,614 | 1,615 | 1,614 | COLLABORATOR | null | # What does this PR do?
Fixes resource allocation and checkpointing bugs with the Ray Tune `hyperparameter_search` integration.
@sgugger @richardliaw @krfricke | {
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https://api.github.com/repos/huggingface/transformers/issues/10405 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10405/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10405/comments | https://api.github.com/repos/huggingface/transformers/issues/10405/events | https://github.com/huggingface/transformers/issues/10405 | 816,852,408 | MDU6SXNzdWU4MTY4NTI0MDg= | 10,405 | Problem running T5 (configuration) with text classification | {
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"Hey, \r\n\r\neven though T5 can be used very well for text-classification it remains a text-to-text only model. So you can only load the model via\r\n\r\n```python\r\nfrom transformers import AutoModelForConditionalGeneration\r\nmodel = AutoModelForConditionalGeneration.from_pretrained(\"t5-small\")\r\n```",
"Go... | 1,614 | 1,645 | 1,614 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.2
- Platform: Linux-4.18.0-193.el8.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyTorch versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/10404 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10404/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10404/comments | https://api.github.com/repos/huggingface/transformers/issues/10404/events | https://github.com/huggingface/transformers/issues/10404 | 816,817,899 | MDU6SXNzdWU4MTY4MTc4OTk= | 10,404 | Model Hub: Search by model size | {
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"Definitely a good idea",
"And since I started talking about model cards... :) I think it would be cool if you guys actually imposed some format. I think the original paper/idea had a format. Now \"model cards\" stands for \"whatever the researcher had time to fill in that day\" :) A few fields of interest: model... | 1,614 | 1,619 | 1,619 | NONE | null | # 🚀 Feature request
It would be great if the model cards for models would include the model size (i.e., the number of parameters) and then the model hub will allow searching for models by size.
## Motivation
Depending on the task/problem/context, smaller or larger models are more beneficial. It's hard to keep u... | {
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https://api.github.com/repos/huggingface/transformers/issues/10403 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10403/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10403/comments | https://api.github.com/repos/huggingface/transformers/issues/10403/events | https://github.com/huggingface/transformers/pull/10403 | 816,806,207 | MDExOlB1bGxSZXF1ZXN0NTgwNDA1OTQ1 | 10,403 | Sagemaker Model Parallel tensoboard writing fix | {
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<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/10402 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10402/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10402/comments | https://api.github.com/repos/huggingface/transformers/issues/10402/events | https://github.com/huggingface/transformers/issues/10402 | 816,750,677 | MDU6SXNzdWU4MTY3NTA2Nzc= | 10,402 | SageMaker Model Parallel: cluttered tensorboard plots | {
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"Hello! Thank you for opening an issue and for offering a code sample!\r\n\r\nCould you open a PR with your code changes?\r\n\r\nThank you!",
"@LysandreJik Please find the PR here: https://github.com/huggingface/transformers/pull/10403/files ",
"Cool, thanks for fixing! Just merged the PR."
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: master
- Platform: SageMaker
- Python version: 3.6
- PyTorch version (GPU?): 1.6
- Using GPU in script?: Y
- Using distributed or parallel set-up in script?: Y
### Who can help
Models:All
Library:SageMaker Model parallel
## Information
The prob... | {
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https://api.github.com/repos/huggingface/transformers/issues/10401 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10401/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10401/comments | https://api.github.com/repos/huggingface/transformers/issues/10401/events | https://github.com/huggingface/transformers/pull/10401 | 816,710,607 | MDExOlB1bGxSZXF1ZXN0NTgwMzI0Mzcy | 10,401 | Fix run_glue evaluation when model has a label correspondence | {
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The `run_glue` script uses the correspondence id to label stored in a given model but when using
```
AutoModelForSequenceClassication.from_pretrained(xxx, num_labels=x)
```
that correspondence is reset. This PR fixes that, along with a few other bugs in the script. To confirm MNLI evaluat... | {
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https://api.github.com/repos/huggingface/transformers/issues/10400 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10400/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10400/comments | https://api.github.com/repos/huggingface/transformers/issues/10400/events | https://github.com/huggingface/transformers/issues/10400 | 816,694,608 | MDU6SXNzdWU4MTY2OTQ2MDg= | 10,400 | [Deepspeed] getting multiple prints of: Avoid using `tokenizers` before the fork if possible | {
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"@chrissyjsartt, you probably accidentally subscribed/set to \"Watching\" the transformers repository which will now send you every comment on every Issue or PR. \r\n\r\nSo urgently go to https://github.com/watching and \"Unwatch\" this or any other repositories you may have set to Watch. Then you will stop getting... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | on master when running with DeepSpeed I started getting multiple dumps of:
```
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork... | {
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https://api.github.com/repos/huggingface/transformers/issues/10399 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10399/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10399/comments | https://api.github.com/repos/huggingface/transformers/issues/10399/events | https://github.com/huggingface/transformers/pull/10399 | 816,582,416 | MDExOlB1bGxSZXF1ZXN0NTgwMjE5NDI2 | 10,399 | Make Barthez tokenizer tests a bit faster | {
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Currently, CI is pretty slow because of this:
```
93.44s call tests/test_tokenization_barthez.py::BarthezTokenizationTest::test_add_special_tokens
77.20s call tests/test_tokenization_barthez.py::BarthezTokenizationTest::test_pretokenized_inputs
77.00s call tests/test_tokenizat... | {
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https://api.github.com/repos/huggingface/transformers/issues/10398 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10398/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10398/comments | https://api.github.com/repos/huggingface/transformers/issues/10398/events | https://github.com/huggingface/transformers/issues/10398 | 816,552,299 | MDU6SXNzdWU4MTY1NTIyOTk= | 10,398 | Does the synonym replacement tasks need Transformer? | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,614 | 1,614 | 1,614 | NONE | null | Or traditional language processing toolkit (like WordNet) is enough? | {
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https://api.github.com/repos/huggingface/transformers/issues/10397 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10397/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10397/comments | https://api.github.com/repos/huggingface/transformers/issues/10397/events | https://github.com/huggingface/transformers/pull/10397 | 816,513,248 | MDExOlB1bGxSZXF1ZXN0NTgwMTYxNjU1 | 10,397 | Ignore unexpected weights from PT conversion | {
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To see for yourself, the following code throws a warning before the PR:
```py
from transformers import BertForPreTraining, BertConfig, TFBertForPreTraining
pt = BertForPreTraining(BertCon... | {
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https://api.github.com/repos/huggingface/transformers/issues/10396 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10396/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10396/comments | https://api.github.com/repos/huggingface/transformers/issues/10396/events | https://github.com/huggingface/transformers/issues/10396 | 816,490,214 | MDU6SXNzdWU4MTY0OTAyMTQ= | 10,396 | how to freeze specific layers of TFbert model and just train a classifier? | {
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"I googled it, this should be working:\r\n\r\nhttps://colab.research.google.com/drive/1EAVhQGdVvXbCu8gGq0lZ9dOnN4jJtvAj?usp=sharing",
"@NielsRogge thanks for the help! ",
"> I googled it, this should be working:\r\n> \r\n> https://colab.research.google.com/drive/1EAVhQGdVvXbCu8gGq0lZ9dOnN4jJtvAj?usp=sharing\r\n... | 1,614 | 1,635 | 1,614 | NONE | null | Could someone help me to freeze say first 3 layers of transformers.TFDistilBertModel.from_pretrained('distilbert-base-multilingual-cased'). I've tried recommendations for TF model from [#400](https://github.com/huggingface/transformers/issues/400) but it seems to freeze all layers at once.
Thanks in advance! | {
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https://api.github.com/repos/huggingface/transformers/issues/10395 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10395/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10395/comments | https://api.github.com/repos/huggingface/transformers/issues/10395/events | https://github.com/huggingface/transformers/issues/10395 | 816,437,271 | MDU6SXNzdWU4MTY0MzcyNzE= | 10,395 | RobertaTokenizerFast does not add special tokens | {
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"Hi, thanks for opening an issue. Indeed, I can reproduce. The conversion to IDs happens in the `encode_batch` method in `tokenizers` directly, which doesn't return the special tokens even though it correctly receives `add_special_tokens=True`. The tokenizer object in transformers also seems to have the correct `sp... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | I'm not sure whether this should be a part of tokenizers or transformers, because it uses both. Classes that don't work are from `transformers` so I'm posting it here.
## Environment info
- `transformers` version: 4.3.3
- Platform: Colab
- PyTorch version (GPU?): n/a
- Tensorflow version (GPU?): n/a
- Using... | {
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https://api.github.com/repos/huggingface/transformers/issues/10394 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10394/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10394/comments | https://api.github.com/repos/huggingface/transformers/issues/10394/events | https://github.com/huggingface/transformers/issues/10394 | 816,430,079 | MDU6SXNzdWU4MTY0MzAwNzk= | 10,394 | DeepSpeedEngine object has no attribute 'no_sync' | {
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"Thank you for your report. This issue has already been fixed in `transformers` master."
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.0
- Platform: Linux-4.14.209-160.339.amzn2.x86_64-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.8
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: yes
- Using distributed or parallel set-up i... | {
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https://api.github.com/repos/huggingface/transformers/issues/10393 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10393/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10393/comments | https://api.github.com/repos/huggingface/transformers/issues/10393/events | https://github.com/huggingface/transformers/issues/10393 | 816,340,853 | MDU6SXNzdWU4MTYzNDA4NTM= | 10,393 | NER Pipeline not working | {
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"Hello! The fix for this was merged a few days ago: https://github.com/huggingface/transformers/pull/10184\r\n\r\nI recommend you install from source while no new version is available for Transformers (a new version should be out in ~2 weeks). Sorry for the inconvenience.",
"Ok thank you for the fast response. I ... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null |
I just followed the token classification notebook and created a pipeline from the model I trained there. Here you can see the full notebook: https://colab.research.google.com/drive/1OzfFTgZwjxdIikbQ8lVJbA2SRF3IeJ5F?usp=sharing
The only thing that I changed (apart from creating the pipeline and calling it) s the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10392 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10392/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10392/comments | https://api.github.com/repos/huggingface/transformers/issues/10392/events | https://github.com/huggingface/transformers/pull/10392 | 816,320,566 | MDExOlB1bGxSZXF1ZXN0NTgwMDAxMzE3 | 10,392 | Remove unused variable in example for Q&A | {
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"Thanks a lot for the fix!",
"What is this all about why am I attached can someone help me\n\n\nOn Thu, Feb 25, 2021, 8:19 AM Lysandre Debut <notifications@github.com>\nwrote:\n\n> Merged #10392 <https://github.com/huggingface/transformers/pull/10392>\n> into master.\n>\n> —\n> You are receiving this because you ... | 1,614 | 1,614 | 1,614 | MEMBER | null | This PR removed unsed `text_tokens = tokenizer.convert_ids_to_tokens(input_ids)` from pytorch and tensorflow examples of Question Answering: https://huggingface.co/transformers/usage.html#extractive-question-answering | {
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https://api.github.com/repos/huggingface/transformers/issues/10391 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10391/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10391/comments | https://api.github.com/repos/huggingface/transformers/issues/10391/events | https://github.com/huggingface/transformers/issues/10391 | 816,281,773 | MDU6SXNzdWU4MTYyODE3NzM= | 10,391 | some bugs about mbart50 for spanish | {
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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)... | 1,614 | 1,619 | 1,619 | NONE | null | ```
from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
article_en = "Hello World"
encoded_en =... | {
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"Hi! We do not maintain the conda-forge versions of transformers and tokenizers. We maintain the versions that are on the `huggingface` channel.\r\n\r\nI just tried with the `huggingface` channel and I get no such errors:\r\n\r\n```\r\nconda create --name=env1 python=3.8 jupyter transformers tokenizers -y -c huggin... | 1,614 | 1,621 | 1,621 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.2
- Platform: Ubuntu 16.04.6 LTS
- Python version: 3.8.8
### Who can help
- tokenizers: @n1t0, @LysandreJik
## Information
To reproduce:
```
conda create --name=env1 python=3.8 jupyter transformers tokenizers -y -c conda-forge
conda activate env1... | {
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https://api.github.com/repos/huggingface/transformers/issues/10387 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10387/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10387/comments | https://api.github.com/repos/huggingface/transformers/issues/10387/events | https://github.com/huggingface/transformers/issues/10387 | 815,913,391 | MDU6SXNzdWU4MTU5MTMzOTE= | 10,387 | loss.backward() TypeError seed issue for pretrained reformer model | {
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"duplicate of https://github.com/huggingface/transformers/issues/10370 more or less. Just need to do the same fixes as in the answer of #10370 "
] | 1,614 | 1,614 | 1,614 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.2
- Platform: Google Colab
- Python version: 3.7.10
- PyTorch version (GPU?): 1.7.0+cu101
- Using GPU ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10386 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10386/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10386/comments | https://api.github.com/repos/huggingface/transformers/issues/10386/events | https://github.com/huggingface/transformers/issues/10386 | 815,889,277 | MDU6SXNzdWU4MTU4ODkyNzc= | 10,386 | MNLI evaluation on pretrained models | {
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"Hello! This may be because of labels being switched around for the MNLI task. See this thread https://github.com/huggingface/transformers/pull/10203 for more context.",
"Hello, \r\nMany thanks for your response. Yes, that seems to be the source of my issue, and now I can get the accuracy. \r\nThanks!\r\n",
"I ... | 1,614 | 1,645 | 1,614 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.dev / 4.3.3 / 4.3.2
- Platform: Ubuntu 18.04/ Windows 10
- Python version: 3.6.2
- PyTorch version (GPU... | {
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https://api.github.com/repos/huggingface/transformers/issues/10385 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10385/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10385/comments | https://api.github.com/repos/huggingface/transformers/issues/10385/events | https://github.com/huggingface/transformers/issues/10385 | 815,857,133 | MDU6SXNzdWU4MTU4NTcxMzM= | 10,385 | DDP performing slightly worse in terms of loss and metrics than DP | {
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"Hi! This thread https://github.com/huggingface/transformers/issues/10223 might be useful, it sheds light over the issue you mention.",
"Hi thank you for linking, it is actually worse in terms of loss, not speed. DDP is significantly faster than DP, which I believe it is supposed to be.",
"Oh, sorry about that,... | 1,614 | 1,615 | 1,615 | NONE | null | Hi,
I am running Transformers 4.3.2 and am testing DistributedDataParallel vs DataParallel. The Huggingface Trainer in both instances have been untouched and slight modifications were made to run_clm.py to fit my specific use case.
This is using GPT-2 model trained from scratch.
I am consistently seeing much fas... | {
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https://api.github.com/repos/huggingface/transformers/issues/10384 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10384/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10384/comments | https://api.github.com/repos/huggingface/transformers/issues/10384/events | https://github.com/huggingface/transformers/issues/10384 | 815,836,682 | MDU6SXNzdWU4MTU4MzY2ODI= | 10,384 | Fine-tune pretrained Wav2Vec2 on a small custom dataset | {
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"Patrick is working on it, see #10145 ",
"I am also searching for fine-tuning of this model.",
"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... | 1,614 | 1,619 | 1,619 | NONE | null | I am wondering how to **fine-tune** a pre-trained model on a small speech/audio dataset. I have 10 hours of audio with their transcript.
I would like to fine-tune a model and then use it as described here:
[](https://huggingface.co/facebook/wav2vec2-large-960h)
Thanks! | {
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https://api.github.com/repos/huggingface/transformers/issues/10383 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10383/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10383/comments | https://api.github.com/repos/huggingface/transformers/issues/10383/events | https://github.com/huggingface/transformers/pull/10383 | 815,836,127 | MDExOlB1bGxSZXF1ZXN0NTc5NTk5Nzk2 | 10,383 | Run GA on every push even on forks | {
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Fixes https://github.com/huggingface/transformers/issues/10065 | {
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https://api.github.com/repos/huggingface/transformers/issues/10382 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10382/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10382/comments | https://api.github.com/repos/huggingface/transformers/issues/10382/events | https://github.com/huggingface/transformers/pull/10382 | 815,832,063 | MDExOlB1bGxSZXF1ZXN0NTc5NTk2NTE4 | 10,382 | Run GA on forks (Attempt #2) | {
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https://api.github.com/repos/huggingface/transformers/issues/10381 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10381/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10381/comments | https://api.github.com/repos/huggingface/transformers/issues/10381/events | https://github.com/huggingface/transformers/issues/10381 | 815,737,788 | MDU6SXNzdWU4MTU3Mzc3ODg= | 10,381 | Option to output "test predictions" text file with each checkpoint in run_seq2seq.py | {
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"May be of interest to @patil-suraj @stas00 @sgugger ",
"Yes, as I replied in the forums, this functionality was dropped - not sure why it was done, as I wasn't part part of the planning discussion.\r\n\r\nI think it was not intentional, the devs were probably unaware it was used and given that the example tests ... | 1,614 | 1,614 | 1,614 | NONE | null | Further to this discussion:
https://discuss.huggingface.co/t/how-to-output-test-generations-txt-with-run-seq2seq-py/3825
The prior incarnation of this script would output test generations at each checkpoint, which was very useful for understanding the progress of model training.
The current script...
https:... | {
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https://api.github.com/repos/huggingface/transformers/issues/10380 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10380/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10380/comments | https://api.github.com/repos/huggingface/transformers/issues/10380/events | https://github.com/huggingface/transformers/issues/10380 | 815,709,748 | MDU6SXNzdWU4MTU3MDk3NDg= | 10,380 | Trainer.train() gets stuck when executed on K8 pods | {
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"Hi there. Unless you tell us what script you are using and how you are launching it, there is nothing we can do to help.",
"@sgugger i'm trying to execute this example script\r\nhttps://github.com/huggingface/notebooks/blob/master/examples/text_classification.ipynb\r\n\r\nThis notebook works fine in a docker con... | 1,614 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.3.2
- Platform: Linux-4.15.0-76-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.10
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in scrip... | {
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https://api.github.com/repos/huggingface/transformers/issues/10379 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10379/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10379/comments | https://api.github.com/repos/huggingface/transformers/issues/10379/events | https://github.com/huggingface/transformers/issues/10379 | 815,688,966 | MDU6SXNzdWU4MTU2ODg5NjY= | 10,379 | [firewalled env] OFFLINE mode | {
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"This is done."
] | 1,614 | 1,615 | 1,615 | CONTRIBUTOR | null | This is done - we now have:
* `HF_DATASETS_OFFLINE=1`
* `TRANSFORMERS_OFFLINE=1`
Documented: [here](https://huggingface.co/transformers/master/installation.html#offline-mode)
The transformers-specific issue is here:
-------------------
Similar to `datasets` https://github.com/huggingface/datasets/issue... | {
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https://api.github.com/repos/huggingface/transformers/issues/10378 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10378/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10378/comments | https://api.github.com/repos/huggingface/transformers/issues/10378/events | https://github.com/huggingface/transformers/issues/10378 | 815,578,400 | MDU6SXNzdWU4MTU1Nzg0MDA= | 10,378 | AttributeError: 'QAModel' object has no attribute 'automatic_optimization' | {
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"Hello! This issue seems to be with PyTorch Lightning rather than with Transformers.",
"> Hello! This issue seems to be with PyTorch Lightning rather than with Transformers.\r\n\r\nWell, I've tried to pass MT5ForConditionalGeneration directly to fit() function, but got following error:\r\n\r\nModuleAttributeError... | 1,614 | 1,614 | 1,614 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.2
- Platform: google colab
- `pytorch-lightning` version (GPU?): 1.2.0
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https://api.github.com/repos/huggingface/transformers/issues/10377 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10377/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10377/comments | https://api.github.com/repos/huggingface/transformers/issues/10377/events | https://github.com/huggingface/transformers/issues/10377 | 815,555,962 | MDU6SXNzdWU4MTU1NTU5NjI= | 10,377 | Training LongformerForQuestionAnswering on TriviaQA | {
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"Pinging @ibeltagy and @patrickvonplaten who would know better.",
"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](http... | 1,614 | 1,619 | 1,619 | NONE | null | Hello,
Could you please give a short explanation on how to retrain `LongformerForQuestionAnswering` in order to receive these weights: `allenai/longformer-large-4096-finetuned-triviaqa` (https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/tree/main).
Thank you,
Sapir | {
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https://api.github.com/repos/huggingface/transformers/issues/10376 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10376/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10376/comments | https://api.github.com/repos/huggingface/transformers/issues/10376/events | https://github.com/huggingface/transformers/issues/10376 | 815,534,852 | MDU6SXNzdWU4MTU1MzQ4NTI= | 10,376 | UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 64: invalid start byte | {
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"You're using `AutoModelForTokenClassification` but you're specifying a `ckpt` file. It needs a folder with a `config.json`, and a state dict. Here it's expecting a PyTorch state dict named `pytorch_model.bin` since you're using the PyTorch version.\r\n\r\nIf you've retrieved your checkpoint from the original BERT ... | 1,614 | 1,614 | 1,614 | NONE | null | ## Description
I have fine tunned a transformers model ('bert-base') and saved the checkpoint. Now I want to use somewhere with the checkpoints I saved. But If I still use bert-base on my new env it will not retrieve my checkpoints, so I want to know the proper way to make my model (Pytorch Lightning model) understand... | {
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https://api.github.com/repos/huggingface/transformers/issues/10375 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10375/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10375/comments | https://api.github.com/repos/huggingface/transformers/issues/10375/events | https://github.com/huggingface/transformers/issues/10375 | 815,490,718 | MDU6SXNzdWU4MTU0OTA3MTg= | 10,375 | DPR decode_best_spans include spans from title | {
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"Yes that's totally true. Good catch !\r\nCould you open a PR to fix that please ?\r\n\r\nMaybe this could have affected the performance of the DPR Reader a bit, but probably not significantly though since the logits of the tokens in the title have very low values. The model was trained to return answers from the p... | 1,614 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.1.1
### Who can help
@lhoestq, @LysandreJik
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https://api.github.com/repos/huggingface/transformers/issues/10374 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10374/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10374/comments | https://api.github.com/repos/huggingface/transformers/issues/10374/events | https://github.com/huggingface/transformers/pull/10374 | 815,485,446 | MDExOlB1bGxSZXF1ZXN0NTc5MzA3NDI3 | 10,374 | Fix None in add_token_positions - issue #10210 | {
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"Hello @joeddav,\r\nYes the proposed change works!\r\n\r\nI have updated the commit.\r\n\r\nThank you for the attention,\r\nAndrea"
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | Related to the issue #10210
I fix the error in that way, can you confirm is right?
@joeddav @sgugger
Kind regards,
Andrea | {
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https://api.github.com/repos/huggingface/transformers/issues/10373 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10373/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10373/comments | https://api.github.com/repos/huggingface/transformers/issues/10373/events | https://github.com/huggingface/transformers/issues/10373 | 815,482,878 | MDU6SXNzdWU4MTU0ODI4Nzg= | 10,373 | [Documentation issue] Sequence to sequence models | {
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"Option 1) seems the way to go for me as well here!",
"Said the same in private but realized I didn't put it here. So option 1 it is!",
"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\nPleas... | 1,614 | 1,621 | 1,621 | MEMBER | null | Most models have their example docstrings appended using the `add_code_sample_docstrings` method. This method checks the name of the architecture, and according to its suffix, adds the corresponding sequence.
However, this isn't perfect with the difference between sequence-to-sequence and enc/dec only models, which ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10372 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10372/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10372/comments | https://api.github.com/repos/huggingface/transformers/issues/10372/events | https://github.com/huggingface/transformers/issues/10372 | 815,357,615 | MDU6SXNzdWU4MTUzNTc2MTU= | 10,372 | deprecated reference `tokenizer.max_len` in glue.py (PR #10220) | {
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"Thanks for opening a PR which fixes the issue! I just merged it.\r\n\r\n"
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | There is a deprecated reference to `tokenizer.max_len` with `tokenizer.model_max_length` - similar to [issue 8739](https://github.com/huggingface/transformers/issues/8739) and [PR 8604](https://github.com/huggingface/transformers/pull/8604).
See error example [in Colab here](https://colab.research.google.com/gist/poe... | {
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https://api.github.com/repos/huggingface/transformers/issues/10371 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10371/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10371/comments | https://api.github.com/repos/huggingface/transformers/issues/10371/events | https://github.com/huggingface/transformers/issues/10371 | 815,308,742 | MDU6SXNzdWU4MTUzMDg3NDI= | 10,371 | Load pretrained model except the head layer for a specific downstream task | {
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"for now, how can I load pretrained models that have different prediction heads? thanks!",
"For now you can discard the head by passing through a base model:\r\n\r\n```py\r\nfrom transformers import AutoModelForSequenceClassification, AutoModel\r\n\r\npretrained_with_head = AutoModelForSequenceClassification.from... | 1,614 | 1,630 | null | CONTRIBUTOR | null | # 🚀 Feature request
It would be nice to have a flag for `from_pretrained` method that indicates whether to load last layer or not. This feature is needed for transfer learning.
## Motivation
I have trained a model with a specific dataset for a downstream task. Now, I need to train another model that needs to ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10370 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10370/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10370/comments | https://api.github.com/repos/huggingface/transformers/issues/10370/events | https://github.com/huggingface/transformers/issues/10370 | 815,246,120 | MDU6SXNzdWU4MTUyNDYxMjA= | 10,370 | ReformerForQuestionAnswering : int() argument must be a string, a bytes-like object or a number, not 'NoneType' | {
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"Hey @harikc456,\r\n\r\nThe problem is that the model is not put into training mode. If you run the following code:\r\n\r\n```python\r\nfrom transformers import ReformerTokenizer, ReformerForQuestionAnswering\r\nfrom transformers.models.reformer.modeling_reformer import PositionEmbeddings\r\nimport torch\r\n\r\ntok... | 1,614 | 1,618 | 1,618 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform:
- Python version: 3.7.10
- PyTorch version (GPU?): 1.7
- Using GPU in script?: Yes
- Using di... | {
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https://api.github.com/repos/huggingface/transformers/issues/10369 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10369/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10369/comments | https://api.github.com/repos/huggingface/transformers/issues/10369/events | https://github.com/huggingface/transformers/issues/10369 | 815,238,477 | MDU6SXNzdWU4MTUyMzg0Nzc= | 10,369 | Why should `attn_weights` be reshaped twice in BartAttention ? | {
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"@patrickvonplaten excuse me, could you share any idea please",
"See this PR for more information: https://github.com/huggingface/transformers/pull/8747",
"> See this PR for more information: #8747\r\n\r\nAlmost understand, although it's still weird. As #8747 explained,\r\n```\r\nThis ensures that the returned ... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | Can anybody help to understand that? https://github.com/huggingface/transformers/blob/3437d12134893dd7b45737e422e105e511341297/src/transformers/models/bart/modeling_bart.py#L238-L244
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https://api.github.com/repos/huggingface/transformers/issues/10368 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10368/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10368/comments | https://api.github.com/repos/huggingface/transformers/issues/10368/events | https://github.com/huggingface/transformers/issues/10368 | 815,227,400 | MDU6SXNzdWU4MTUyMjc0MDA= | 10,368 | TFMarianModel from_pretrained can't load weights | {
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"Thanks for the issue! \r\n\r\nI uploaded the TF weights https://huggingface.co/Helsinki-NLP/opus-mt-en-de/commit/1a8c2263da11e68e50938f97e10cd57820bd504c. Should be fixed now - could you try again?",
"Thanks, this method working now. Please upload a model 'Helsinki-NLP/opus-mt-ru-en'. And I think other models ar... | 1,614 | 1,630 | 1,630 | NONE | null | ## Environment info
- `transformers` version: 4.3.2
- Platform: Windows-7-6.1.7601-SP1
- Python version: 3.6.6
- PyTorch version (GPU?): 1.5.1+cpu (False)
- Tensorflow version (GPU?): 2.3.0 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### Who can help
@patrickvonpl... | {
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https://api.github.com/repos/huggingface/transformers/issues/10367 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10367/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10367/comments | https://api.github.com/repos/huggingface/transformers/issues/10367/events | https://github.com/huggingface/transformers/issues/10367 | 815,177,536 | MDU6SXNzdWU4MTUxNzc1MzY= | 10,367 | device-side assert triggered Error while doing inference on Distilbert and Bert | {
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"If you have a CUDA device-side error, it is advised to run your code on CPU, because then you will receive a more informative error message.",
"Hi @NielsRogge,\r\nIn CPU its working fine, Error is coming while using GPU only\r\n",
"Hi @bhadreshpsavani, this can't work on CPU. You're sending a sequence that is ... | 1,614 | 1,614 | 1,614 | 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: 3.4.0
- Platform: Colab
- Python version: 3.8
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- U... | {
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https://api.github.com/repos/huggingface/transformers/issues/10366 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10366/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10366/comments | https://api.github.com/repos/huggingface/transformers/issues/10366/events | https://github.com/huggingface/transformers/issues/10366 | 815,176,328 | MDU6SXNzdWU4MTUxNzYzMjg= | 10,366 | can't allocate memory error with wav2vec2 | {
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"Hi! You seem to be passing all of the file at once to the model. This can be extremely expensive from a memory point of view, as the number of samples (and therefore your batch size) can be very big.\r\n\r\nI would advocate for you to do a custom batching here, by only passing some of the values in yout `input_val... | 1,614 | 1,619 | 1,619 | NONE | null | I am trying out the wav2vec2 model for ASR from the huggingface library. Here, I am passing a 7 min(~15 MB file) long wav file having a conversation(english) to the wav2vec2 model. I am getting "can't allocate memory" error. I found that the model uses all 64 GB of the available RAM. Can anyone help with this.
- `... | {
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<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
The original Blenderbot [paper](https://arxiv.org/pdf/2004.13637.pdf) considered three transformer based models (Retrieval, Generator and RetNRef), however f... | {
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https://api.github.com/repos/huggingface/transformers/issues/10364 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10364/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10364/comments | https://api.github.com/repos/huggingface/transformers/issues/10364/events | https://github.com/huggingface/transformers/issues/10364 | 815,032,134 | MDU6SXNzdWU4MTUwMzIxMzQ= | 10,364 | Loading mBART Large 50 MMT (many-to-many) is slow | {
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"Related: https://github.com/huggingface/transformers/issues/9205",
"Thanks. I'll rerun the benchmarks once patrick makes the changes.",
"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\nPlea... | 1,614 | 1,621 | 1,621 | CONTRIBUTOR | null | ## Environment info
I'm installing the library directly from `master` and running it in a kaggle notebook.
<!-- 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: 4.4.0.dev0
- Platf... | {
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https://api.github.com/repos/huggingface/transformers/issues/10363 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10363/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10363/comments | https://api.github.com/repos/huggingface/transformers/issues/10363/events | https://github.com/huggingface/transformers/pull/10363 | 815,004,637 | MDExOlB1bGxSZXF1ZXN0NTc4OTAzMzUz | 10,363 | [trainer] move secondary methods into a separate file | {
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https://api.github.com/repos/huggingface/transformers/issues/10362 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10362/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10362/comments | https://api.github.com/repos/huggingface/transformers/issues/10362/events | https://github.com/huggingface/transformers/pull/10362 | 814,827,713 | MDExOlB1bGxSZXF1ZXN0NTc4NzUyMTc4 | 10,362 | [Trainer/Deepspeed] handle get_last_lr() before first step() | {
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"Yes, that's a good idea. I'm just not clear on whether you suggest to make a function just for the deepspeed segment of the branch or wrap up the whole getting lr function?\r\n\r\nPlus, the code needs the `trainer` object, so I'm not sure how to put it in utils. \r\n\r\n\r\nI propose to put it as a separate Traine... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | with deepspeed's fp16 and dynamic loss scale enabled the optimizer/scheduler steps may not run for the first few dozens steps while loss is overflowing, so `get_last_lr` will fail if called during that warm up stage, so this PR tries to catch that special warm situation and handle it by returning a fake LR=0, which is ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10361 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10361/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10361/comments | https://api.github.com/repos/huggingface/transformers/issues/10361/events | https://github.com/huggingface/transformers/issues/10361 | 814,826,760 | MDU6SXNzdWU4MTQ4MjY3NjA= | 10,361 | denoising objective for pretraining | {
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"@patil-suraj @patrickvonplaten please help. thanks ",
"Hey @dorooddorood606,\r\n\r\ncould you please make use of the forum: https://discuss.huggingface.co/ for such questions. Thanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to ... | 1,614 | 1,619 | 1,619 | NONE | null | Hi
Denoising objective is used in T5 and BART models, could you please add it in pretraining language models?
For now, if you could I appreciate sharing some advice how I can implement it. is there a piece of codes in huggingface I could start from?
thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/10360 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10360/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10360/comments | https://api.github.com/repos/huggingface/transformers/issues/10360/events | https://github.com/huggingface/transformers/issues/10360 | 814,801,374 | MDU6SXNzdWU4MTQ4MDEzNzQ= | 10,360 | Rag Use Your Knowledge dataset | {
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"Hi ! It looks like you `embed` functions expects a batch of documents as input.\r\nCan you try to set `batched=True` in your call to `dataset.map` ?",
"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 th... | 1,614 | 1,619 | 1,619 | 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: Colab
- Python version: 3.7.10
- PyTorch version (CPU): 1.7.0
### Who can help
Models:
ra... | {
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https://api.github.com/repos/huggingface/transformers/issues/10359 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10359/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10359/comments | https://api.github.com/repos/huggingface/transformers/issues/10359/events | https://github.com/huggingface/transformers/issues/10359 | 814,796,764 | MDU6SXNzdWU4MTQ3OTY3NjQ= | 10,359 | Security Bug found - looking for contact for responsible disclosure | {
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"Hi – can you send an email to `tech at huggingface.co`? Thanks.",
"I did send it.",
"closing as will handle over email. Thanks!"
] | 1,614 | 1,614 | 1,614 | NONE | null | Hi,
I found a security bug on software related to you.
Can you please tell me how to contact you for a responsible disclosure?
Thanks. | {
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https://api.github.com/repos/huggingface/transformers/issues/10358 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10358/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10358/comments | https://api.github.com/repos/huggingface/transformers/issues/10358/events | https://github.com/huggingface/transformers/issues/10358 | 814,737,100 | MDU6SXNzdWU4MTQ3MzcxMDA= | 10,358 | BART Summarization : Torchscript Export / Inference Triton Server | {
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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)... | 1,614 | 1,683 | 1,621 | NONE | null | # 📚 Migration
@sshleifer maybe you can help ?? (thanks for all your work bud!)
## Information
**Objective** : Performance gain, clocking 1-1.5 sec per transaction at the moment, target : under 100 ms. It seems exporting model via TorchScript & running on Triton Server may be plausible solution.
I am export... | {
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https://api.github.com/repos/huggingface/transformers/issues/10357 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10357/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10357/comments | https://api.github.com/repos/huggingface/transformers/issues/10357/events | https://github.com/huggingface/transformers/pull/10357 | 814,701,451 | MDExOlB1bGxSZXF1ZXN0NTc4NjQ2Mzg1 | 10,357 | tokenization_marian.py: use current_spm for decoding | {
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"Hi @patil-suraj! \r\nThanks for your review. As you suggested, I started updating the code and docs where `decode` or `batch_decode` is used.\r\nDoing so, I noticed RAG model also has the same issue: in `decode` and `batch_decode`, `generator` is used instead of `current_tokenizer`. Do you want me to also update t... | 1,614 | 1,615 | 1,615 | 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/10356 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10356/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10356/comments | https://api.github.com/repos/huggingface/transformers/issues/10356/events | https://github.com/huggingface/transformers/issues/10356 | 814,656,314 | MDU6SXNzdWU4MTQ2NTYzMTQ= | 10,356 | Fine-tuning bart-base on XSum and got 34.0 as ROUGE1 (40.61 with higher lr) | {
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"Just an update, I increased lr and got ROUGE-F(1/2/l): 40.61/17.48/32.62",
"Maybe @patrickvonplaten or @patil-suraj have an idea",
"Hi @XinnuoXu \r\n\r\nThat model was trained a while ago, and there were some bugs in BART related to `decoder_start_token_id` at that time, see https://discuss.huggingface.co/t/ba... | 1,614 | 1,620 | 1,620 | NONE | null | Hi, I'm wondering whether there are any benchmarks for fine-turning bart-base on XSum. I found this one [https://huggingface.co/VictorSanh/bart-base-finetuned-xsum/tree/main](url) which also shows the R1 is 35 -ish. Does it suppose to be this low? | {
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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)... | 1,614 | 1,622 | 1,622 | CONTRIBUTOR | null | I am having an issue finetuning a ProphetNet model for question generation. The current error I am running into is an indexing issue when getting the `position_embeddings, position_ids`. In the below line of code, we call the `ProphetNetPositionalEmbeddings` module to get the embeddings
https://github.com/huggingfac... | {
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https://api.github.com/repos/huggingface/transformers/issues/10354 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10354/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10354/comments | https://api.github.com/repos/huggingface/transformers/issues/10354/events | https://github.com/huggingface/transformers/pull/10354 | 814,629,849 | MDExOlB1bGxSZXF1ZXN0NTc4NTg3NTAz | 10,354 | Add support for ZeRO-2/3 and ZeRO-offload in fairscale | {
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"> Other values supported are: `zero2`, `zero2_offload`, `zero3` and `zero3_offload`. To fully take advantage of the `zero3`/`zero3_offload` the model passed to the `Trainer` will need to have its internal layers wrapped inside the `FullyShardedDataParallel`, but this out of scope for this particular PR.\r\n\r\nDo ... | 1,614 | 1,614 | 1,614 | COLLABORATOR | null | # What does this PR do?
This PR adds support for the new `FullyShardedDataParallel` introduced in fairscale. See [this PR](https://github.com/facebookresearch/fairscale/pull/413) for more details.
The PR changes a tiny bit the behavior of the `--sharded_ddp` flag/training argument to support a list of options. Yo... | {
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https://api.github.com/repos/huggingface/transformers/issues/10353 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10353/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10353/comments | https://api.github.com/repos/huggingface/transformers/issues/10353/events | https://github.com/huggingface/transformers/pull/10353 | 814,591,506 | MDExOlB1bGxSZXF1ZXN0NTc4NTU1Njg0 | 10,353 | [bert-base-german-cased] use model repo, not external bucket | {
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https://api.github.com/repos/huggingface/transformers/issues/10351 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10351/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10351/comments | https://api.github.com/repos/huggingface/transformers/issues/10351/events | https://github.com/huggingface/transformers/issues/10351 | 814,511,016 | MDU6SXNzdWU4MTQ1MTEwMTY= | 10,351 | Can every line in the input CSV file contain more than one sentence when pertraining BERT for MLM Loss? | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead? You'll get more answers over there, as questions like these are the point of the forum :)\r\n\r\nThanks!"
] | 1,614 | 1,614 | 1,614 | NONE | null | Hello HF Team,
I am familiar with how to pretrain BERT and I have a Dataloader that reads an input CSV file line by line and every time it reads a line, it tokenizes it and sends back the tokens for training to the training code. My question is whether is it ok for this input CSV file to contain more than one sent... | {
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https://api.github.com/repos/huggingface/transformers/issues/10350 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10350/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10350/comments | https://api.github.com/repos/huggingface/transformers/issues/10350/events | https://github.com/huggingface/transformers/issues/10350 | 814,475,652 | MDU6SXNzdWU4MTQ0NzU2NTI= | 10,350 | Got "RuntimeError: CUDA error: device-side assert triggered" with Seq2SeqTrainer | {
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"Hi there. Could you please post the code you are using? The steps you are defining are too vague for us to efficiently reproduce the issue and help.",
"Hi @sgugger \r\nIt was my fault when I update the max_encoder_length and re-run on the updated blocks.\r\nThe issue will not happen when I restart the kernel on ... | 1,614 | 1,614 | 1,614 | NONE | null | ## Environment info
- `transformers` version: 4.3.2
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101 (True)
- Tensorflow version (GPU?): 2.4.1 (True)
- Using GPU in script?: YES
- Using distributed or parallel set-up in script?: NO
### W... | {
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https://api.github.com/repos/huggingface/transformers/issues/10349 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10349/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10349/comments | https://api.github.com/repos/huggingface/transformers/issues/10349/events | https://github.com/huggingface/transformers/issues/10349 | 814,434,106 | MDU6SXNzdWU4MTQ0MzQxMDY= | 10,349 | Padding of bbox input in LayoutLM | {
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"Hi! This is a fair request, indeed. The `bbox` values should definitely be padded/truncated by the tokenizer.\r\n\r\nI think here we would welcome a PR adding this functionality for the LayoutLM tokenizer, and then think of a way to upstream it to be handled by the tokenizer directly, for LayoutLM but also for any... | 1,614 | 1,620 | 1,620 | CONTRIBUTOR | null | I've been working with LayoutLM and had some issues with different lengths of samples in a batch.
```
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.
```
It turns out that `transformer... | {
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https://api.github.com/repos/huggingface/transformers/issues/10348 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10348/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10348/comments | https://api.github.com/repos/huggingface/transformers/issues/10348/events | https://github.com/huggingface/transformers/issues/10348 | 814,424,293 | MDU6SXNzdWU4MTQ0MjQyOTM= | 10,348 | BertForMaskedLM cannot be initialized from BERT checkpoints | {
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"Note that the way to load TF weights in a PyTorhc model while using the hub is just to do:\r\n```\r\nmodel = BertForMaskedLM.from_pretrained(\"SZTAKI-HLT/hubert-base-cc\", from_tf=True)\r\n```\r\nIt does look like this model has some weights missing (I still get a warning but with a few less weights than you) but ... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | When I try to load a BERT model from a TF checkpoint (via `transformers-cli convert`) into a `BertForMaskedLM`, I get the following warning:
```
Some weights of BertForMaskedLM were not initialized from the model checkpoint at `SZTAKI-HLT/hubert-base-cc` and are newly initialized:
['cls.predictions.bias', 'cls.predi... | {
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https://api.github.com/repos/huggingface/transformers/issues/10347 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10347/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10347/comments | https://api.github.com/repos/huggingface/transformers/issues/10347/events | https://github.com/huggingface/transformers/issues/10347 | 814,405,254 | MDU6SXNzdWU4MTQ0MDUyNTQ= | 10,347 | [Benchmark] | {
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## Benchmark
Which part of `transformers` did you benchmark?
## Set-up
What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization did you use?
## Results
Put your results here! | {
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https://api.github.com/repos/huggingface/transformers/issues/10346 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10346/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10346/comments | https://api.github.com/repos/huggingface/transformers/issues/10346/events | https://github.com/huggingface/transformers/issues/10346 | 814,403,227 | MDU6SXNzdWU4MTQ0MDMyMjc= | 10,346 | Custom tokenizer with run_mlm script | {
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"Hi! The issue here is that the `AutoTokenizer` has no idea what is the type of your tokenizer: it's looking for the `model_type` specified in the `config.json`, but it seems it cannot find it.\r\n\r\nCould you show us the results of `ls ../Data/tokenizer/`, and if the file `config.json` is in it, could you show us... | 1,614 | 1,625 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.2
- Platform: Linux-5.9.16-1-MANJARO-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/10345 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10345/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10345/comments | https://api.github.com/repos/huggingface/transformers/issues/10345/events | https://github.com/huggingface/transformers/issues/10345 | 814,371,963 | MDU6SXNzdWU4MTQzNzE5NjM= | 10,345 | MarianMT - ONNX only accepts fixed input despite setting dynamic axes | {
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"pinging @mfuntowicz, our `onnx` expert.",
"Any lead on the solution? @mfuntowicz, @patrickvonplaten, @patil-suraj ",
"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... | 1,614 | 1,619 | 1,619 | 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: 3.1.0
- Platform: Linux-5.8.0-43-generic-x86_64-with-glibc2.29 (Ubuntu 20.04.2)
- Python version: 3.8.3
- Py... | {
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https://api.github.com/repos/huggingface/transformers/issues/10344 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10344/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10344/comments | https://api.github.com/repos/huggingface/transformers/issues/10344/events | https://github.com/huggingface/transformers/pull/10344 | 814,351,512 | MDExOlB1bGxSZXF1ZXN0NTc4MzUzNDc5 | 10,344 | Fix broken examples/seq2seq/README.md markdown | {
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This PR fix broken markdown in examples/seq2seq/README.md
<!--
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/10343 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10343/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10343/comments | https://api.github.com/repos/huggingface/transformers/issues/10343/events | https://github.com/huggingface/transformers/issues/10343 | 814,164,977 | MDU6SXNzdWU4MTQxNjQ5Nzc= | 10,343 | Where can we find the `RAG` implementation? | {
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"The implementation can be found [here](https://github.com/huggingface/transformers/tree/master/src/transformers/models/rag).",
"@NielsRogge Thanks! That's it."
] | 1,614 | 1,614 | 1,614 | NONE | null | I noticed that `transformers` included the implementation for `DPR`. But for `RAG`, I only find a [demo](https://huggingface.co/rag/). Is there a source code for `RAG`? Or do you know where is Facebook's source code for `RAG`? Thanks | {
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"Hi! This change may have originated from the move to the git-based repos. @patrickvonplaten and I have just modified the DialoGPT tokenizer configuration to have 1024 as model max length, you shouldn't have to do anything but re-run your script to see it updated.",
"@LysandreJik Don't hesitate to reference the u... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.2
- Platform: Darwin-19.3.0-x86_64-i386-64bit
- Python version: 3.6.5
- PyTorch version (GPU?): 1.6.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### Who can help
M... | {
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https://api.github.com/repos/huggingface/transformers/issues/10341 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10341/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10341/comments | https://api.github.com/repos/huggingface/transformers/issues/10341/events | https://github.com/huggingface/transformers/issues/10341 | 814,113,801 | MDU6SXNzdWU4MTQxMTM4MDE= | 10,341 | Translate English into Japanese using mbart | {
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"Hi @DUT-Tjy \r\n\r\n`facebook/mbart-large-cc25` is not fine-tuned for translation, it's a pretrained model, which should be fine-tuned if you want to use it for translation. You could use the `mbart-large-50-one-to-many-mmt` or `mbart-large-50-many-to-many-mmt` model for `en-ja` translation, these are fine-tuned m... | 1,614 | 1,622 | 1,619 | NONE | null | Transformers version: 4.4.0.dev0
Hello, I am trying to translate English into Japanese(en-ja). I confirm that there is no error in my target content and source content. However, when I try to translate, the result of predict is always English. What should I do?
I only changed config.json as shown below:
"task_spec... | {
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https://api.github.com/repos/huggingface/transformers/issues/10340 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10340/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10340/comments | https://api.github.com/repos/huggingface/transformers/issues/10340/events | https://github.com/huggingface/transformers/issues/10340 | 814,015,617 | MDU6SXNzdWU4MTQwMTU2MTc= | 10,340 | tokenizer.Tokenizer compatibility with Inference API or Auto* classes | {
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] | open | false | null | [] | [] | 1,614 | 1,614 | null | NONE | null | # 🚀 Feature request
Make tokenizers created with the tokenizers library compatible with the Inference API or Auto classes
## Motivation
I have trained a model on a specific domain by modeling a sequence generation problem as a language modeling problem to predict the next token in the set. The tokenizer associa... | {
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https://api.github.com/repos/huggingface/transformers/issues/10339 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10339/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10339/comments | https://api.github.com/repos/huggingface/transformers/issues/10339/events | https://github.com/huggingface/transformers/issues/10339 | 813,922,912 | MDU6SXNzdWU4MTM5MjI5MTI= | 10,339 | Problem with GPT2/DistilGPT2 prediction - dimension mismatch | {
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"Maybe @sgugger has seen that error previously?",
"Yes, and it has been fixed... but only in the more recent versions of Transformers.",
"Excellent, thank you guys, I'll work on upgrading tomorrow.",
"If it can help you, we have a [migration guide from versions v3 to v4](https://huggingface.co/transformers/mi... | 1,614 | 1,614 | 1,614 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.4.0
- Platform: Linux-4.18.0-193.el8.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyTorch versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/10338 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10338/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10338/comments | https://api.github.com/repos/huggingface/transformers/issues/10338/events | https://github.com/huggingface/transformers/pull/10338 | 813,868,908 | MDExOlB1bGxSZXF1ZXN0NTc3OTQzOTEx | 10,338 | Fix evaluation with label smoothing in Trainer | {
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There was a bug in Trainer when using label smoothing: the `compute_loss` function pops the labels out of the inputs so they couldn't be gathered. This PR fixes that.
Fixes #10309 | {
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https://api.github.com/repos/huggingface/transformers/issues/10337 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10337/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10337/comments | https://api.github.com/repos/huggingface/transformers/issues/10337/events | https://github.com/huggingface/transformers/issues/10337 | 813,868,378 | MDU6SXNzdWU4MTM4NjgzNzg= | 10,337 | [trainer] port metrics logging and saving methods to all example scripts | {
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"Can I work on this issue?",
"Yes, please and thank you!",
"Hi @stas00,\r\nSometimes it is saving it as txt file instead of a JSON file like the below code\r\n```python\r\noutput_train_file = os.path.join(training_args.output_dir, \"train_results.txt\")\r\nif trainer.is_world_process_zero():\r\n with open(ou... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | In an effort to make the examples easier to read, in https://github.com/huggingface/transformers/pull/10266 we added new trainer methods:
* `trainer.log_metrics` - to perform consistent formatting for logged metrics
* `trainer.save_metrics` - to save the metrics into a corresponding json file.
and deployed them ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10336 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10336/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10336/comments | https://api.github.com/repos/huggingface/transformers/issues/10336/events | https://github.com/huggingface/transformers/issues/10336 | 813,781,072 | MDU6SXNzdWU4MTM3ODEwNzI= | 10,336 | [Benchmark] Converting a QA distilbert model to onnx - the f1 score plummet | {
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"After further investigating, I found this useful repo: https://github.com/airKlizz/benchmark-for-transformers\r\nWorking on adding squad to this"
] | 1,614 | 1,614 | 1,614 | NONE | null | # 🖥 Benchmarking onnx QA `transformers`
## Issue
Poor benchmark result (squadv2) of converted onnx QA model using run_squad_onnx benchmark.
## Context
As part of my day job, my goal is to convert our QA model to onnx to make them available in production in Java.
My teammate generated a distilbert model t... | {
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https://api.github.com/repos/huggingface/transformers/issues/10335 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10335/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10335/comments | https://api.github.com/repos/huggingface/transformers/issues/10335/events | https://github.com/huggingface/transformers/issues/10335 | 813,773,781 | MDU6SXNzdWU4MTM3NzM3ODE= | 10,335 | Return cross-attention weights in generation function | {
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"Hi @patrickvonplaten!\r\nPlease let me know what you think about the feature. I can send a PR for it once you confirm.",
"Yes, this would be a nice addition indeed :-)",
"Happy to help you in your PR!"
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
With v4.2.0 release, generation can now return encoder and decoder self-attention weights but it still doesn't return cross-attention weights. These weights ... | {
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"Raised changes. 1 reply to your review comment. \r\nDo let me know if any other change required. \r\n\r\nThanks.",
"Thanks a lot for your contribution!"
] | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | Enhance resume_from_checkpoint argument of Trainer.train to accept
bool type. If True given, last saved checkpoint in self.args.output_dir
will be loaded. (#10280)
# What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/10333 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10333/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10333/comments | https://api.github.com/repos/huggingface/transformers/issues/10333/events | https://github.com/huggingface/transformers/pull/10333 | 813,582,263 | MDExOlB1bGxSZXF1ZXN0NTc3NzA2ODAz | 10,333 | Clean TF ConvBert | {
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"I don't understand this PR, I disagree with your proposal of adding keyword names when they're not required and don't help readability.\r\n\r\nMentioned here https://github.com/huggingface/transformers/pull/9788#discussion_r564365003 and here https://github.com/huggingface/transformers/pull/9788#discussion_r564373... | 1,614 | 1,614 | 1,614 | CONTRIBUTOR | null | # What does this PR do?
This PR aims to clean TF ConvBert by adding explicit keyword arguments, typing and update the documentation in the model implementation to make it easier to understand and read.
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