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https://api.github.com/repos/huggingface/transformers/issues/14960 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14960/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14960/comments | https://api.github.com/repos/huggingface/transformers/issues/14960/events | https://github.com/huggingface/transformers/issues/14960 | 1,089,761,967 | I_kwDOCUB6oc5A9HKv | 14,960 | Missing parameters when iterating over `module.parameters()` | {
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"Hey @jankrepl,\r\n\r\n`self.lm_head` is identical to `self.transformer.wte` since those weights are tied (input and output word embeddings are the same for a lot of Transformer models) which is why `self.lm_head` doesn't show up here I think ",
"```python\r\nfrom transformers import AutoModelForCausalLM\r\n\r\n\... | 1,640 | 1,640 | 1,640 | 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: `4.15.0`
- Python
- Implementation: CPython
- Version : 3.8.12
- Platform
- OS : Darw... | {
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https://api.github.com/repos/huggingface/transformers/issues/14959 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14959/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14959/comments | https://api.github.com/repos/huggingface/transformers/issues/14959/events | https://github.com/huggingface/transformers/pull/14959 | 1,089,742,203 | PR_kwDOCUB6oc4wVDRq | 14,959 | [Wav2Vec2] Rename model's feature extractor to feature encoder | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/14958 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14958/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14958/comments | https://api.github.com/repos/huggingface/transformers/issues/14958/events | https://github.com/huggingface/transformers/pull/14958 | 1,089,740,306 | PR_kwDOCUB6oc4wVC4v | 14,958 | [WavLM] give model more precision tolerance in tests | {
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"cc @sgugger "
] | 1,640 | 1,640 | 1,640 | MEMBER | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/14956 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14956/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14956/comments | https://api.github.com/repos/huggingface/transformers/issues/14956/events | https://github.com/huggingface/transformers/pull/14956 | 1,089,624,034 | PR_kwDOCUB6oc4wUq3u | 14,956 | [megatron convert] PYTHONPATH requirements | {
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Since one can't install Megatron-LM as a package we can't make the script require it, so documenting it h... | {
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https://api.github.com/repos/huggingface/transformers/issues/14955 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14955/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14955/comments | https://api.github.com/repos/huggingface/transformers/issues/14955/events | https://github.com/huggingface/transformers/pull/14955 | 1,089,528,179 | PR_kwDOCUB6oc4wUX9v | 14,955 | [doc] :class: hunt | {
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- `:meth:`, `:func` - all is good
- `:class:`
```
find . -type d -name ".git" -prune -o -type f -exec perl -pi -e 's#:class: ?`([^`]+)`#[`$1`]#g' {} \;
find . -type d -name ".git" -prune -o -type f -exec perl -pi -e 's#:c... | {
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https://api.github.com/repos/huggingface/transformers/issues/14954 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14954/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14954/comments | https://api.github.com/repos/huggingface/transformers/issues/14954/events | https://github.com/huggingface/transformers/pull/14954 | 1,089,515,152 | PR_kwDOCUB6oc4wUVWG | 14,954 | [doc] :obj: hunt | {
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"Redone w/o examples and utils"
] | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | I think it'd be easier to review if we focus on one type at a time. So this PR is about `obj`:
it catches all the invalid `:obj:` versions, reformats the next field as if they were normal and then removes them all.
```
find . -type d -name ".git" -prune -o -type f -exec perl -pi -e 's#:?obj: ?\*([^\*]+)\*#`$1`#g... | {
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https://api.github.com/repos/huggingface/transformers/issues/14953 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14953/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14953/comments | https://api.github.com/repos/huggingface/transformers/issues/14953/events | https://github.com/huggingface/transformers/pull/14953 | 1,089,506,736 | PR_kwDOCUB6oc4wUToG | 14,953 | Doc styler examples | {
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"Cool! Good to merge for me once all tests pass"
] | 1,640 | 1,640 | 1,640 | COLLABORATOR | null | # What does this PR do?
Last bit of the new style-doc script, blackify all code examples which:
- insures they don't have bacis Python errors
- are on par with our usual code format
This PR fixes a few code examples mistakes (see first commit for the docstrings and [this commit](https://github.com/huggingface/t... | {
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For some reason we forgot the `auto.rst` doc file in the mass conversion. This PR fixes that problem. | {
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"Done"
] | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | This PR sets True/False/None default format in a consistent manner of backticks.
```
find . -type d -name ".git" -prune -o -type f -exec perl -pi -e 's#\*(True|False|None)\*#`$1`#g' {} \;
```
Fixes: https://github.com/huggingface/transformers/issues/14949
@sgugger
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https://api.github.com/repos/huggingface/transformers/issues/14950 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14950/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14950/comments | https://api.github.com/repos/huggingface/transformers/issues/14950/events | https://github.com/huggingface/transformers/pull/14950 | 1,089,468,429 | PR_kwDOCUB6oc4wULs8 | 14,950 | Doc styler v2 | {
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This PR rewrites the doc-styler to work with the Markdown docstrings and re-enables the checks.
Merging and inspecting the doc is alright as the diff is... consequent :-) | {
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"It's not the conversion fault, those were inconsistent before. Meaning some were properly set with an :obj: marker or double backticks while other had simple backticks and were thus converted in italics.\r\n\r\nBy all means, if you want to do a batch conversion, the proper format is \\`False\\` (or \\`True\\`)",
... | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | After the conversion we ended up with inconsistent values for `defaults to` - sometimes it's `formatted`, other times it's *italics*, with former being the prevailing form. Example:
```
src/transformers/generation_tf_utils.py: use_cache: (`bool`, *optional*, defaults to `True`):
src/transformers/generatio... | {
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"So the idea is that `deepspeed.save_fp16_model()` will return True if the weights have already been saved at the given path in which case there is no need to call `deepspeed.save_checkpoint()`?",
"That's right. I just want to make sure that someone won't lose their work in case they misconfigured their DS setup.... | 1,640 | 1,643 | 1,643 | CONTRIBUTOR | null | `_save_checkpoint` saves the deepspeed checkpoint, but this path:
```
push_to_hub => save_model => questionable outcome
```
for z3 if `stage3_gather_fp16_weights_on_model_save=false` will not save the model, so this PR adds a fallback to saving the full checkpoint instead from which weights can be recovered.
... | {
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"> Thanks for working on this. I don't think you have properly put Niels as Co-author, there needs to be a special syntax Co-authored-by xxx in a commit description for GitHub to recognize it.\r\n\r\nThe email I used was wrong, I had to dive into other git commits to find the proper email."
] | 1,640 | 1,641 | 1,641 | CONTRIBUTOR | null | # What does this PR do?
Largely taken from #859, but redone in order to avoid documentation issues since the
switch to MD. @NielsRogge you are co-authored, since it's mainly your PR.
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"sorry, didn't realize that the 2 PRs were the same, just different source branch. ok, let's work on this one.\r\n\r\nSo indeed there is a duplication as you discovered https://github.com/huggingface/transformers/pull/14652/files#diff-ed55888e6665791fe92cc8fc0c499da54f4ace6738551cd9a2591881cda076deR1986\r\n\r\nSo i... | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | # What does this PR do?
Drop duplicate call to deepspeed.save_checkpoint(), the trainer.save_model() function already handles that case.
Following this change: https://github.com/huggingface/transformers/pull/14652/files#diff-ed55888e6665791fe92cc8fc0c499da54f4ace6738551cd9a2591881cda076deR1986
The call to save_... | {
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"Could you update your Transformers to the last version? I think this was fixed recently.",
"I updated Transformers to the latest (master) version and I can see total_flos now. Thank you for your help."
] | 1,640 | 1,640 | 1,640 | 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: 4.14.1
- Platform: Ubuntu 20.04.1
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.0 (True)
- Tensorfl... | {
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https://api.github.com/repos/huggingface/transformers/issues/14944 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14944/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14944/comments | https://api.github.com/repos/huggingface/transformers/issues/14944/events | https://github.com/huggingface/transformers/pull/14944 | 1,089,345,363 | PR_kwDOCUB6oc4wTyKs | 14,944 | Map model_type and doc pages names | {
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"very neat!",
"Sounds good to me. Will resolve conflicts and merge."
] | 1,640 | 1,641 | 1,641 | COLLABORATOR | null | # What does this PR do?
As discussed on [moon-landing](https://github.com/huggingface/moon-landing/pull/1692#discussion_r774957604), it's not possible to automatically generate the link to the documentation from the configuration of a model, due to multiple inconsistencies between model type and doc page name.
Th... | {
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"I'm not entirely sure the result section is up to date, so it may have been with slightly different hyperparameters (like a batch size of 8 which is the default). It might also be an error in the base checkpoint used, as I may have used the `bert-base-cased` checkpoint to get those results.\r\n\r\nFor your second ... | 1,640 | 1,643 | 1,643 | NONE | null | ## Environment info
- `transformers` version: 4.10.0
- Platform: Linux-4.15.0-142-generic-x86_64-with-debian-stretch-sid
- Python version: 3.7.11
- PyTorch version (GPU?): 1.10.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not instal... | {
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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)... | 1,640 | 1,643 | 1,643 | NONE | null | I found that these args are not really useful, actually I can not run the code when use the arg—— "model_name"
the origin code is like this, which I find it not work:
` model = BertModel.from_pretrained(
pretrained_model_name_or_path=args.model_name,
state_dict=torch.load(args.pytorch_model_path... | {
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`tokenizers==0.11` is now available on all distributions locations (conda included)
and will enable truncating left on tokenizers that require it.
<!--
Congratulations! You've made it this far! You're not quite done yet though.
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"Closed PR as it was created from the wrong branch",
"continued in https://github.com/huggingface/transformers/pull/14946"
] | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | # What does this PR do?
Drop duplicate call to deepspeed.save_checkpoint(), the trainer.save_model() function already handles that case.
Following this change: https://github.com/huggingface/transformers/pull/14652/files#diff-ed55888e6665791fe92cc8fc0c499da54f4ace6738551cd9a2591881cda076deR1986
The call to save_... | {
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"It's because your custom checkpoint includes a module namespace visible during training (and embedded in the checkpoint) but not at the conversion time.\r\n\r\nThe official checkpoint converts w/o errors:\r\n\r\n```\r\ngit clone https://github.com/huggingface/transformers/\r\ncd transformers\r\nmkdir megatron_lm_3... | 1,640 | 1,641 | 1,641 | 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: 4.11.2
- Platform: Linux-5.4.0-91-generic-x86_64-with-glibc2.10
- Python version: 3.8.10
- PyTorch version (... | {
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"Hey @Captainr22,\r\n\r\nThanks for reporting this issue here. I now know how you create the model. Could you also provide the code to run this model with the Trainer? A bash command is enough in case you are using one of the official examples :-)",
"Hi @patrickvonplaten ,\r\n\r\nHere is my code to run my model. ... | 1,640 | 1,641 | 1,641 | NONE | null | Hi.
An error occurred when I used Trainer to train and save EncoderDecoderModel.
```python
File "/home/jwli/ljw/study/hotpotqa/roberta_seq2seq/roberta_for_seq2seq.py", line 482, in <module>
run(model_args, data_args, training_args)
File "/home/jwli/ljw/study/hotpotqa/roberta_seq2seq/roberta_for_seq2seq.p... | {
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https://api.github.com/repos/huggingface/transformers/issues/14937 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14937/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14937/comments | https://api.github.com/repos/huggingface/transformers/issues/14937/events | https://github.com/huggingface/transformers/issues/14937 | 1,088,938,349 | I_kwDOCUB6oc5A5-Ft | 14,937 | Cannot instantiate model under dopamine | {
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"Hey @kovkev,\r\n\r\nCould you please provide an easily reproducible code snippet? I don't really know what `mytest.py` is",
"Do clone github.com/kovkev/dopamine , where I patch dopamine with my code snippet",
"Hi @patrickvonplaten , quick Github question - do you get notified if I make a comment that does not ... | 1,640 | 1,644 | 1,644 | NONE | null | ## Environment info
- `transformers` version: 4.13.0.dev0
- Platform: Linux-5.11.0-43-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyTorch version (GPU?): not installed (NA)
- Tensorflow version (GPU?): 2.7.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- J... | {
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https://api.github.com/repos/huggingface/transformers/issues/14936 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14936/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14936/comments | https://api.github.com/repos/huggingface/transformers/issues/14936/events | https://github.com/huggingface/transformers/issues/14936 | 1,088,931,444 | I_kwDOCUB6oc5A58Z0 | 14,936 | A warning is raised when using DistributedDataParallel of PyTorch | {
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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)... | 1,640 | 1,643 | 1,643 | NONE | null | When I train huggingface-transformers model in multi-cards and multi-machines using DistributedDataParallel (DDP) of PyTorch, a warning is always output at each epoch:
```
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...... | {
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https://api.github.com/repos/huggingface/transformers/issues/14935 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14935/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14935/comments | https://api.github.com/repos/huggingface/transformers/issues/14935/events | https://github.com/huggingface/transformers/pull/14935 | 1,088,922,505 | PR_kwDOCUB6oc4wSawG | 14,935 | [performance doc] Power and Cooling | {
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- Power and Cooling
- Grad accumulation
- links to various benchmarks I recently created
- a direct link to the scalabilty doc
@LysandreJik, @sgugger
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,640 | 1,649 | 1,649 | CONTRIBUTOR | null | This PR adds a benchmarking tool for HF Trainer args - e.g. compare --fp16 vs --bf16 performance, but can do that for multiple dimensions and it prints automatic tables suitable for instant pasting in Issues, including relative performance. e.g.:
| Variation | Train<br>samples<br>per<br>s... | {
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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)... | 1,640 | 1,643 | 1,643 | CONTRIBUTOR | null | # What does this PR do?
Added few parameters to be able to create custom backbone models for different use cases (partially explained in mentioned issue)
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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)... | 1,640 | 1,646 | 1,646 | MEMBER | null | # What does this PR do?
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"It seems like this issue also occur with other AutoClass like `AutoFeatureExtractor`.",
"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 [contri... | 1,640 | 1,674 | 1,647 | NONE | null | ## Environment info
- `transformers` version: 4.15.0
- Platform: Linux-5.4.0-91-generic-x86_64-with-glibc2.27
- Python version: 3.9.7
- PyTorch version (GPU?): 1.10.1+cu113 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/14930 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14930/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14930/comments | https://api.github.com/repos/huggingface/transformers/issues/14930/events | https://github.com/huggingface/transformers/pull/14930 | 1,088,745,252 | PR_kwDOCUB6oc4wR5R5 | 14,930 | fix to issue #14833 in data_collator - consider no labels | {
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Fixing `DataCollatorForSeq2Seq.__call__` to not preparing decoder_input_ids when `labels` is None.
Fixes # (issue)
#14833
## 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 guid... | {
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"I tried the LXMERT and VisualBERT demos from [here](https://github.com/huggingface/transformers/blob/master/examples/research_projects/lxmert/demo.ipynb) and [here](https://github.com/huggingface/transformers/blob/master/examples/research_projects/visual_bert/demo.ipynb) \n\nThere seems to be dependency issues and... | 1,640 | 1,641 | 1,641 | NONE | null | There are a bunch of models fine tuned for VQA and NLVR tasks based on LXMERT, ViLT and Visual BERT, CLIP vision BERT and so on. Is there a resource to see how to run inferences on them ? (and possibly benchmark them ) | {
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https://api.github.com/repos/huggingface/transformers/issues/14928 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14928/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14928/comments | https://api.github.com/repos/huggingface/transformers/issues/14928/events | https://github.com/huggingface/transformers/pull/14928 | 1,088,678,124 | PR_kwDOCUB6oc4wRtY6 | 14,928 | [WIP] Fast tokenizer for debertaV2 | {
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"I noticed that while I was working on my PR, another was submitted for the same purpose: #14923. ",
"Hey @alcinos ,\r\n\r\nthanks for adding it!\r\n\r\nI'm currently running comparisons between slow and fast tokenizer. Here are some mismatches between fast and slow.\r\n\r\nI just run tokenization tests on `READM... | 1,640 | 1,650 | 1,650 | CONTRIBUTOR | null | # What does this PR do?
Implements a fast tokenizer for deberta v2. Loosely based on #11387
Fixes #11529
Fixes #14712
This is a draft as there are some failing tests (not super clear to me why atm, will have to investigate)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can d... | {
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"I figured out my mistake the config file hadn't been generated \r\nFixed that now"
] | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | I've been trying to run the code present here on new data - https://github.com/machelreid/lewis
In one of the steps there are the following lines of codes -
```
classifier = (
RobertaForSequenceClassification.from_pretrained(
f"{args.hf_dump}/pytorch_model.bin",
config=f"{... | {
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https://api.github.com/repos/huggingface/transformers/issues/14923 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14923/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14923/comments | https://api.github.com/repos/huggingface/transformers/issues/14923/events | https://github.com/huggingface/transformers/pull/14923 | 1,088,545,726 | PR_kwDOCUB6oc4wRWZH | 14,923 | [WIP] DeBERTav2 Fast Tokenizer - fixes #14712 | {
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"Merry xmas! Currently using the Converter to instantize the Fast DebertaV2 Tokenizer from a PreTrainedTokenizerFast serves as a workaround for now, but I'm finding it difficult to write up the DebertaV2TokenizerFast class \r\n for `tokenization_deberta_v2_fast.py` such that it wraps the SPMTokenizer class. \r\n\r\... | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | # What does this PR do?
Added DeBERTav2Converter for tokenizer of
- DeBERTav2
- DeBERTav3
- mDeBERTav3
Wish to add a DeBERTav2TokenizerFast classes and test but require guidance on this, thanks!
Fixes # (issue)
#14712
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss... | {
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https://api.github.com/repos/huggingface/transformers/issues/14922 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14922/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14922/comments | https://api.github.com/repos/huggingface/transformers/issues/14922/events | https://github.com/huggingface/transformers/issues/14922 | 1,088,526,619 | I_kwDOCUB6oc5A4Zkb | 14,922 | Using Huggingface Trainer in Colab -> Disk Full | {
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"I guess I found the reason, \r\non deleting the previous checkpoint, it goes to the google drive bin and the bin does not delete it then (deletes after 30 days) and this results in occupied space. \r\nOne way to solve this will be overriding the `_rotate_checkpoint` method of the `Trainer` to also clean the drive ... | 1,640 | 1,664 | 1,643 | NONE | null | https://discuss.huggingface.co/t/using-huggingface-trainer-in-colab-disk-full/5951/2
I faced the same issue mentioned in this discussion. Please give it a look.
[## Environment info
- `transformers` version: 4.15.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyTorch ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14921 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14921/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14921/comments | https://api.github.com/repos/huggingface/transformers/issues/14921/events | https://github.com/huggingface/transformers/issues/14921 | 1,088,471,843 | I_kwDOCUB6oc5A4MMj | 14,921 | Inference API: return token scores for text-generation models | {
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"cc @Narsil ",
"Hi @rodrigonogueira4 ,\r\n\r\nThis is an interesting feature. May I ask what the end goal would be ?\r\nIs it to potentially discard results which are deemed too low ?\r\nIs it to show some kind of confidence (color or otherwise) to your user ?\r\nAny other usage ?\r\n\r\nI think clarifying the en... | 1,640 | 1,693 | 1,644 | NONE | null | # 🚀 Feature request
It would be useful if the Accelerated Inference API returned token scores assigned by Text-generation and Text2text-generation models, similar to what is returned by "Fill mask" models. E.g.:
```
output = {
"sequence": "the answer to the universe is no.",
"score": 0.... | {
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https://api.github.com/repos/huggingface/transformers/issues/14920 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14920/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14920/comments | https://api.github.com/repos/huggingface/transformers/issues/14920/events | https://github.com/huggingface/transformers/pull/14920 | 1,088,449,603 | PR_kwDOCUB6oc4wRElB | 14,920 | Use tqdm.auto in Pipeline docs | {
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"Thanks again!"
] | 1,640 | 1,641 | 1,641 | CONTRIBUTOR | null | It's better for e.g. notebook. | {
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https://api.github.com/repos/huggingface/transformers/issues/14919 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14919/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14919/comments | https://api.github.com/repos/huggingface/transformers/issues/14919/events | https://github.com/huggingface/transformers/issues/14919 | 1,088,308,482 | I_kwDOCUB6oc5A3kUC | 14,919 | Multiprocessing for pipeline | {
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"same problem! @sharejing any insight so far? \r\n\r\nI was trying to do something like\r\n```\r\n# this is required otherwise it will complain \"AssertionError: daemonic processes are not allowed to have children\"\r\nclass NoDaemonProcess(multiprocessing.Process):\r\n @property\r\n def daemon(self):\r\n ... | 1,640 | 1,644 | 1,644 | NONE | null | I am using the question-answering pipeline provided by huggingface. I am trying to perform multiprocessing to parallelize the question answering, but it stucks!!! Eexcution does not end.
from transformers import pipeline
from torch.multiprocessing import Pool, Process, set_start_method
set_start_method('spawn', f... | {
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https://api.github.com/repos/huggingface/transformers/issues/14918 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14918/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14918/comments | https://api.github.com/repos/huggingface/transformers/issues/14918/events | https://github.com/huggingface/transformers/issues/14918 | 1,088,222,312 | I_kwDOCUB6oc5A3PRo | 14,918 | Why I met Type 'seq(tensor(int64))' of operator (MemcpyFromHost) is invalid when using onnxruntime.InferenceSession() in GPU, and How to resolve it? On emergency hold，thanks! | {
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"Hi @yuanhuachao thanks for raising this issue! Can you please provide the exact command you used to export the model with? You might also be interested in a related issue #14882 about running this example script on a GPU.",
"Hi @lewtun ,i run the run_onnx_exporter.py with command 'python run_onnx_exporter.py --m... | 1,640 | 1,643 | 1,643 | NONE | null | ## Environment info
when I run exported onnx model of transformers (BARTBeamSearchGenerator model example) on GPU. I met this. Who knows how can resolve it?
<img width="1392" alt="截屏2021-12-24 下午3 32 55" src="https://user-images.githubusercontent.com/13781668/147331435-f518d5c7-b6fd-4550-9de9-940a9ec87003.png">
- ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14917 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14917/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14917/comments | https://api.github.com/repos/huggingface/transformers/issues/14917/events | https://github.com/huggingface/transformers/pull/14917 | 1,088,212,611 | PR_kwDOCUB6oc4wQUxa | 14,917 | Fix Perceiver docs | {
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https://api.github.com/repos/huggingface/transformers/issues/14916 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14916/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14916/comments | https://api.github.com/repos/huggingface/transformers/issues/14916/events | https://github.com/huggingface/transformers/issues/14916 | 1,088,209,581 | I_kwDOCUB6oc5A3MKt | 14,916 | Add Deepspeed Transformer kernel, but encounter error IndexError: tuple index out of range | {
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"By the way, does Huggingface support similar XLA or kernel fusion capabilities?",
"Ok, problem solved, it's because the origin huggingface bert will return a tuple and choose the first element while deepspeed return the element",
"you can enable return_tuple in DeepSpeedTransformerConfig\r\n"
] | 1,640 | 1,658 | 1,640 | CONTRIBUTOR | null | I have compare the Bert-base pretraining performance between [Nvidia Tensorflow ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/BERT) and huggingface + Deepspeed.
My environment:
cuda: 11.2
torch: 1.10
deepspeed: 0.5.8
transformers: 4.13.0.dev0
machine: single node with 8 ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14915 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14915/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14915/comments | https://api.github.com/repos/huggingface/transformers/issues/14915/events | https://github.com/huggingface/transformers/issues/14915 | 1,088,138,980 | I_kwDOCUB6oc5A267k | 14,915 | ConnectionError | {
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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)... | 1,640 | 1,643 | 1,643 | NONE | null | I encounterd the issue:ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.16.1/datasets/common_voice/common_voice.py when run run_speech_recognition_ctc.py. How can I solve this problem?
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https://api.github.com/repos/huggingface/transformers/issues/14914 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14914/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14914/comments | https://api.github.com/repos/huggingface/transformers/issues/14914/events | https://github.com/huggingface/transformers/issues/14914 | 1,088,128,893 | I_kwDOCUB6oc5A24d9 | 14,914 | How to update config after model inited? | {
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"Hi,\r\n\r\nTo turn off dropout, you should put your model in evaluation mode: `model.eval()`. ",
" > To turn off dropout, you should put your model in evaluation mode: `model.eval()`.\r\n\r\nthanks for reply, due to certain needs, what I want is to change `drop prob` during training. Can this be achieved?\r\n",
... | 1,640 | 1,643 | 1,643 | NONE | null | Hello everyone, I want to **change** the config [such as `dropout probability`] after bert inited, what should I do in transformers?
```python
# fixed seed
random.seed(args.seed)
torch.manual_seed(args.seed)
cudnn.deterministic = True
# init bert
config = AutoConfig.from_pretrained(model_name, hidden_dropout... | {
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https://api.github.com/repos/huggingface/transformers/issues/14913 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14913/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14913/comments | https://api.github.com/repos/huggingface/transformers/issues/14913/events | https://github.com/huggingface/transformers/issues/14913 | 1,087,998,248 | I_kwDOCUB6oc5A2Yko | 14,913 | [Benchmark] Deepspeed +fp16/bf16 on a 8xA100 node | {
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"oh, and tagging @stas00 because is a `deepspeed` \"issue\".",
"Information about the cards:\r\n```\r\n+-----------------------------------------------------------------------------+\r\n| NVIDIA-SMI 495.29.05 Driver Version: 495.29.05 CUDA Version: 11.5 |\r\n|-------------------------------+------------... | 1,640 | 1,643 | 1,643 | NONE | null | # 🖥 Benchmarking `transformers`
## Benchmark
Which part of `transformers` did you benchmark?
`Deepspeed` with template `Zero 1, 2 and 3` configurations using fp16 and bf16.
- I am by no means an expert on this, I'm trying to find the fastest configuration for my setup. So if you see better ways to do this, p... | {
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https://api.github.com/repos/huggingface/transformers/issues/14912 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14912/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14912/comments | https://api.github.com/repos/huggingface/transformers/issues/14912/events | https://github.com/huggingface/transformers/pull/14912 | 1,087,979,803 | PR_kwDOCUB6oc4wPlkB | 14,912 | [doc] install - add link to jax installation | {
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Note: Flax install page only covers cpu jax installation info.
@sgugger
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https://api.github.com/repos/huggingface/transformers/issues/14911 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14911/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14911/comments | https://api.github.com/repos/huggingface/transformers/issues/14911/events | https://github.com/huggingface/transformers/issues/14911 | 1,087,953,936 | I_kwDOCUB6oc5A2NwQ | 14,911 | How to generate output using custom embeddings? | {
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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)... | 1,640 | 1,643 | 1,643 | NONE | null | My code is kinda like
```python
model = BartForConditionalGeneration.from_pretrained('facebook/bart-large')
token_embeds, pos_embeds = custom_embeds()
output = model(inputs_embeds=token_embeds + pos_embeds, decoder_input_ids=torch.tensor([[tokenizer.bos_token_id]]))
```
How do I generate text output from this out... | {
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https://api.github.com/repos/huggingface/transformers/issues/14910 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14910/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14910/comments | https://api.github.com/repos/huggingface/transformers/issues/14910/events | https://github.com/huggingface/transformers/pull/14910 | 1,087,948,770 | PR_kwDOCUB6oc4wPfBT | 14,910 | [WavLM] fix wavlm docs | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/14909 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14909/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14909/comments | https://api.github.com/repos/huggingface/transformers/issues/14909/events | https://github.com/huggingface/transformers/pull/14909 | 1,087,925,966 | PR_kwDOCUB6oc4wPaO9 | 14,909 | remove absl workaround as it's no longer needed | {
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"actually, that fix was in `abseil` - I may have misread the situation - let me just run some checks on whether the logging works.\r\n\r\nOK, here it says that `absl` was fixed as well: https://github.com/tensorflow/tensorflow/issues/26691#issuecomment-525519742\r\n",
"Hard to leave a reasonable opinion here for ... | 1,640 | 1,642 | 1,640 | CONTRIBUTOR | null | the `absl` workaround hasn't been needed since 2019-04 https://github.com/abseil/abseil-py/issues/99 so it should be safe to remove it.
Otherwise it's complaining about not finding TPUs, when there are no TPUs to be found when some of our libs load jax and not needing jax: https://github.com/huggingface/transformers... | {
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https://api.github.com/repos/huggingface/transformers/issues/14908 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14908/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14908/comments | https://api.github.com/repos/huggingface/transformers/issues/14908/events | https://github.com/huggingface/transformers/issues/14908 | 1,087,908,250 | I_kwDOCUB6oc5A2Cma | 14,908 | Can't load tokenizer for 'microsoft/wavlm-base' when using Wav2Vec2Processor as in docs | {
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"Hey @pszemraj,\r\n\r\nI'm sorry the documentation is really bad here :-/ I'll fix this asap. \r\n\r\n`wavlm-base` is just the pretrained model of wavlm. It has no character predicition (CTC) head and therefore it also cannot have a tokenizer. \r\n\r\nIf you want to try out a fine-tuned wavlm checkpoint you could t... | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | # overview
Thanks for adding `WavLM` guys! I wanted to try it out and ran into some issues which I am reporting (hopefully clearly) here.
the transformers docs say to use `Wav2Vec2Processor` as the processor/tokenizer for `WavLM`. Transformers 4.15.0 tells me it can't find a suitable tokenizer when running the fo... | {
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https://api.github.com/repos/huggingface/transformers/issues/14907 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14907/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14907/comments | https://api.github.com/repos/huggingface/transformers/issues/14907/events | https://github.com/huggingface/transformers/issues/14907 | 1,087,901,749 | I_kwDOCUB6oc5A2BA1 | 14,907 | [jax] absl issues | {
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"So this is one of the triggers:\r\n```\r\npython -c \"import jax; jax.default_backend()\"\r\n```\r\n\r\nand it is looking for TPUs:\r\n```\r\nTF_CPP_MIN_LOG_LEVEL=0 python -c \"import jax; jax.default_backend()\"\r\n2021-12-23 10:06:40.249749: I external/org_tensorflow/tensorflow/core/tpu/tpu_initializer_helper.cc... | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | update:
So the problem was that `jax` wasn't detecting a GPU when there was one.
**The solution is to install `jax` correctly for cuda and it is:**
```
pip install --upgrade "jax[cuda]" -f https://storage.googleapis.com/jax-releases/jax_releases.html
```
more details: https://github.com/huggingface/transf... | {
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https://api.github.com/repos/huggingface/transformers/issues/14906 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14906/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14906/comments | https://api.github.com/repos/huggingface/transformers/issues/14906/events | https://github.com/huggingface/transformers/pull/14906 | 1,087,887,769 | PR_kwDOCUB6oc4wPSM1 | 14,906 | Better logic for getting tokenizer config in AutoTokenizer | {
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"Thanks!"
] | 1,640 | 1,640 | 1,640 | COLLABORATOR | null | # What does this PR do?
In this PR, we make the logic in `AutoTokenizer` a little bit better by checking the tokenizer config is in the list of files of the repo when trying to get it, instead of bluntly trying to load it. This makes the function fail early with a clear error message if the repo name passed contains... | {
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https://api.github.com/repos/huggingface/transformers/issues/14905 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14905/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14905/comments | https://api.github.com/repos/huggingface/transformers/issues/14905/events | https://github.com/huggingface/transformers/issues/14905 | 1,087,881,699 | I_kwDOCUB6oc5A18Hj | 14,905 | Generate does not take into account config.decoder.eos_token_id | {
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"Hmm, yeah I think I'm fine with adding some `if - statements` to the `generate()` method",
"Do you want to open a PR for it? :-)",
"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 no... | 1,640 | 1,665 | 1,665 | CONTRIBUTOR | null | As reported by some people (see https://github.com/NielsRogge/Transformers-Tutorials/issues/53 and on the [forum](https://discuss.huggingface.co/t/trocr-repeated-generation/12361)), the `generate()` method currently does not take into account `config.decoder.eos_token_id`, only` config.eos_token_id` to properly stop ge... | {
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https://api.github.com/repos/huggingface/transformers/issues/14904 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14904/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14904/comments | https://api.github.com/repos/huggingface/transformers/issues/14904/events | https://github.com/huggingface/transformers/pull/14904 | 1,087,881,405 | PR_kwDOCUB6oc4wPQ2f | 14,904 | Update ONNX docs | {
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"This is great, thanks for working on it @lewtun! Pinging @stevhliu and @sgugger for knowledge.",
"Thank you for the feedback @sgugger 🙏 !\r\n\r\nI've now added the doctest `>>>` syntax to all the Python code blocks and removed the permalinks to the class references. OK to merge once the CI tests pass?"
] | 1,640 | 1,641 | 1,641 | MEMBER | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/14903 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14903/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14903/comments | https://api.github.com/repos/huggingface/transformers/issues/14903/events | https://github.com/huggingface/transformers/pull/14903 | 1,087,872,573 | PR_kwDOCUB6oc4wPO9i | 14,903 | Fix failing GPU trainer tests | {
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As discussed, this PR skips the fairscale tests until we update the container running them, and fixes the multiGPU failing test in the Trainer. | {
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"`FAILED examples/pytorch/test_examples.py::ExamplesTests::test_run_image_classification` is unrelated, merging..."
] | 1,640 | 1,640 | 1,640 | MEMBER | null | # What does this PR do?
Turns out the difference in `nn.GroupNorm` between torch `1.9` and `1.10` (https://github.com/pytorch/pytorch/issues/67907) is more noticeable than I initially expected. This PR updates the tolerances on some newer tests where the reference values were obtained on `1.10`. When we update the C... | {
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https://api.github.com/repos/huggingface/transformers/issues/14901 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14901/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14901/comments | https://api.github.com/repos/huggingface/transformers/issues/14901/events | https://github.com/huggingface/transformers/issues/14901 | 1,087,843,724 | I_kwDOCUB6oc5A1y2M | 14,901 | Adding tokens to pretrained model "Helsinki-NLP/opus-tatoeba-en-ja" using tokens from vietnamese not working | {
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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)... | 1,640 | 1,643 | 1,643 | NONE | null | Hello,
I am working on a code of the paper regarding multilingual model with multistage finetuning, I am using trainer API of huggingface for the finetuning of pretrained model from english to japanese with dataset containing vietnamese sentences, but before I want to modify the pretrained tokenizer adding tokens from... | {
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https://api.github.com/repos/huggingface/transformers/issues/14900 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14900/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14900/comments | https://api.github.com/repos/huggingface/transformers/issues/14900/events | https://github.com/huggingface/transformers/pull/14900 | 1,087,842,005 | PR_kwDOCUB6oc4wPIfC | 14,900 | [AutoTokenizer] Fix incorrect from pretrained | {
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"> Thanks for the hot fix! Will make a nicer one in a couple of hours.\r\n\r\nPerfect"
] | 1,640 | 1,640 | 1,640 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14899 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14899/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14899/comments | https://api.github.com/repos/huggingface/transformers/issues/14899/events | https://github.com/huggingface/transformers/issues/14899 | 1,087,832,443 | I_kwDOCUB6oc5A1wF7 | 14,899 | GPT-J: Implement Memory Efficient Attention | {
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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)... | 1,640 | 1,643 | 1,643 | CONTRIBUTOR | null | Just a note that it would be great to add memory efficient attention ( https://github.com/AminRezaei0x443/memory-efficient-attention ) for larger models. It might be nice to add an option to reuse the memory of input hidden states, too, if the user doesn't need them. | {
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https://api.github.com/repos/huggingface/transformers/issues/14898 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14898/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14898/comments | https://api.github.com/repos/huggingface/transformers/issues/14898/events | https://github.com/huggingface/transformers/pull/14898 | 1,087,743,267 | PR_kwDOCUB6oc4wOzdP | 14,898 | Add 3D attention_mask input support | {
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"This code will be copied to RemBERT and RoBERTa as well, because those inherit the same `call()` method. I think we can accept the PR with just a BERT test, though I'm not sure - @sgugger WDYT?",
"I think it's important to also have parity for the rest of the TF models - can all models accept the 3D attention ma... | 1,640 | 1,644 | 1,644 | NONE | null | Add 3D attention_mask input support. (The PyTorch version support, but TF cant.)
Sometimes we need to input custom 3D attention_mask.
```python
import tensorflow as tf
from transformers import TFBertModel
plm_name = "bert-base-chinese"
plm = TFBertModel.from_pretrained(plm_name, return_dict=False)
i = tf.ones(... | {
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https://api.github.com/repos/huggingface/transformers/issues/14897 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14897/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14897/comments | https://api.github.com/repos/huggingface/transformers/issues/14897/events | https://github.com/huggingface/transformers/pull/14897 | 1,087,702,708 | PR_kwDOCUB6oc4wOq69 | 14,897 | add custom stopping criteria to human eval script | {
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"Human eval crashes for me, and I believe this PR is to blame. Here's the stack:\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"human_eval.py\", line 126, in <module>\r\n main()\r\n File \"human_eval.py\", line 106, in main\r\n task_generations.extend(complete_code(pipe, prompt, num_completions... | 1,640 | 1,643 | 1,640 | MEMBER | null | This PR adds the new custom `stopping_criteria` feature in `generate` (#14779) to the code evaluation script at `scripts/human_eval.py`.
In HumanEval the task is to complete a function and with this feature the generation is stopped once the function body is complete. To do this a set of keywords, named end-of-funct... | {
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https://api.github.com/repos/huggingface/transformers/issues/14896 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14896/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14896/comments | https://api.github.com/repos/huggingface/transformers/issues/14896/events | https://github.com/huggingface/transformers/pull/14896 | 1,087,681,094 | PR_kwDOCUB6oc4wOmZh | 14,896 | Large audio chunking for the existing ASR pipeline | {
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"@Narsil sorry, I only now remembered about the work in [#14225](https://github.com/huggingface/transformers/pull/14225)!\r\nIndeed, the `ChunkPipeline` API is much cleaner and I can adapt this PR to work with it.\r\n\r\nRe: 2-4) totally agree, these points should be refactored as you suggest!\r\nRe: 5) If I unders... | 1,640 | 1,641 | 1,641 | MEMBER | null | # What does this PR do?
This adds audio chunking with fixed-sized chunks as a first step to enabling audio streaming in ASR pipelines (ref: https://github.com/huggingface/transformers/pull/14250)
In this iteration there's no ffmpeg streaming or VAD, just simple slicing of inputs with padding, so that we can revi... | {
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https://api.github.com/repos/huggingface/transformers/issues/14895 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14895/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14895/comments | https://api.github.com/repos/huggingface/transformers/issues/14895/events | https://github.com/huggingface/transformers/pull/14895 | 1,087,617,270 | PR_kwDOCUB6oc4wOYuk | 14,895 | Add ViLT | {
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"I'd like the PR to be green (or mostly green) before reviewing.",
"@sgugger should be mostly green now.",
"Note: with the new build dev job merged, you can preview the doc [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_14895/en/model_doc/vilt) :-) ",
"Great job merging this PR! the documenta... | 1,640 | 1,642 | 1,642 | CONTRIBUTOR | null | # What does this PR do?
This PR adds [ViLT](https://arxiv.org/abs/2102.03334) (Vision and Language Transformer).
It's a very nice, minimal multi-modal model, as it only adds a text embedding layer to an existing ViT.
I've defined the following head models:
* `ViltForMaskedLM`
* `ViltForVisualQuestionAnswer... | {
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https://api.github.com/repos/huggingface/transformers/issues/14894 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14894/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14894/comments | https://api.github.com/repos/huggingface/transformers/issues/14894/events | https://github.com/huggingface/transformers/pull/14894 | 1,087,534,907 | PR_kwDOCUB6oc4wOHRE | 14,894 | Set `run_name` in MLflowCallback | {
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Currently, when using `mlflow` integration to track experiments, runs are being logged as nameless. E.g. see below (image from #8519). This PR is a simple one-line fix of passing `args.run_name` (which is currently used for `wandb`) to `mlflow.start_run`. It also updates the doc of `args.run_... | {
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https://api.github.com/repos/huggingface/transformers/issues/14893 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14893/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14893/comments | https://api.github.com/repos/huggingface/transformers/issues/14893/events | https://github.com/huggingface/transformers/pull/14893 | 1,087,459,580 | PR_kwDOCUB6oc4wN3fA | 14,893 | support the trocr small models | {
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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/14892 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14892/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14892/comments | https://api.github.com/repos/huggingface/transformers/issues/14892/events | https://github.com/huggingface/transformers/issues/14892 | 1,087,358,810 | I_kwDOCUB6oc5Az8da | 14,892 | [doc] bug in docstring conversion | {
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"It seems to be happening every time we have a list in a parameter description. Filing an [issue](https://github.com/huggingface/doc-builder/issues/70) on `doc-builder` for this, Mishig will have a look when he's back from vacation :-)\r\n\r\nClosing on this side as there is nothing to do in Transformers. The gener... | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | There is an issue of rendering items in a docstring (in some places)
Here is an example:
https://huggingface.co/docs/transformers/main_classes/logging#transformers.utils.logging.set_verbosity
has a lose `<`
but I'm not sure where this one is coming from
It appears to be a messed up `<ul>` block:
```
Log... | {
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https://api.github.com/repos/huggingface/transformers/issues/14891 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14891/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14891/comments | https://api.github.com/repos/huggingface/transformers/issues/14891/events | https://github.com/huggingface/transformers/issues/14891 | 1,087,353,761 | I_kwDOCUB6oc5Az7Oh | 14,891 | Turn of do_sample for T0pp in Inference API | {
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"cc @Narsil ",
"Hi @feyzaakyurek ,\r\n\r\nThanks. Currently (and in the short term) this won't be available.\r\n\r\n`bigscience/T0pp` is a very large model (40Go) meaning we deploy it in a very specific way. Here we used `flax` and it's deployed on a TPU for instance. This enables quite fast inference speed but i... | 1,640 | 1,640 | 1,640 | NONE | null | Hi,
I'm trying to use the Inference API with T0pp. I would like to set `do_sample=False` but it doesn't let me specify `parameters` as in the example [here](https://api-inference.huggingface.co/docs/python/html/detailed_parameters.html#summarization-task).
Code:
API_URL = "https://api-inference.huggingface... | {
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https://api.github.com/repos/huggingface/transformers/issues/14890 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14890/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14890/comments | https://api.github.com/repos/huggingface/transformers/issues/14890/events | https://github.com/huggingface/transformers/pull/14890 | 1,087,350,748 | PR_kwDOCUB6oc4wNg2q | 14,890 | [doc] post-porting | {
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See:
https://huggingface.co/docs/transformers/main_classes/logging#transformers.utils.logging.enable_explicit_format
converted it into a formatted section
@sgugger | {
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"Hey @stas00, thanks for raising an issue! I think the `WARNING` level is probably too low, I'd expect to see some tqdm bars at this level. I think even in `ERROR` we would expect some tqdm bars?\r\n\r\nI believe that the `datasets` team uses a specific logging command to turn tqdm bars off:\r\nhttps://github.com/h... | 1,640 | 1,642 | 1,642 | CONTRIBUTOR | null | I'm writing a program in a notebook where I'm printing a results table for multiple models and I can't figure out how to turn off tqdm here as it downloads new models since its output breaks the table and adds a ton of unnecessary noise to the notebook's outputs.
So here is where the control is:
https://github.co... | {
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"Merging and lookin if the docs are alright :-) ",
"Fantastic, thanks for taking care of the rest @sgugger!"
] | 1,640 | 1,640 | 1,640 | COLLABORATOR | null | # What does this PR do?
This PR converts all remaining rst files to mdx and adapts the templates as well as the add_new_model command. The script for checking the table in the serialization page also needs a slight update. | {
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https://api.github.com/repos/huggingface/transformers/issues/14887 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14887/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14887/comments | https://api.github.com/repos/huggingface/transformers/issues/14887/events | https://github.com/huggingface/transformers/pull/14887 | 1,087,036,116 | PR_kwDOCUB6oc4wMfku | 14,887 | Properly indent return block | {
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This fixes the indentation for some return blocks. A check in the `doc-builder` will soon error for bad blocks like this. | {
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"Hi there!\r\n\r\nAs mentioned in the README, examples are just examples. We can't show every single usecase everyone will want, so it's up to you to adapt them to your needs :-). If you need help, you can reach out on the [forums](https://discuss.huggingface.co/) or our Discord.",
"This issue has been automatica... | 1,640 | 1,643 | 1,643 | NONE | null | # 🚀 Feature request
BERT pretraining with not line_by_line big dataset.
## Motivation
I'm trying to pretrain a BERT model with the classic masking task (without NSP), using examples/pytorch/language_modeling/run_mlm.py script. As with the original BERT, I would not like to construct each example of the batch us... | {
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https://api.github.com/repos/huggingface/transformers/issues/14885 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14885/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14885/comments | https://api.github.com/repos/huggingface/transformers/issues/14885/events | https://github.com/huggingface/transformers/pull/14885 | 1,086,991,531 | PR_kwDOCUB6oc4wMWZh | 14,885 | Fix installation instructions for BART ONNX example | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/14884 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14884/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14884/comments | https://api.github.com/repos/huggingface/transformers/issues/14884/events | https://github.com/huggingface/transformers/issues/14884 | 1,086,886,013 | I_kwDOCUB6oc5AyJB9 | 14,884 | TrOCR processor cannot be loaded from AutoProcessor | {
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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)... | 1,640 | 1,663 | 1,655 | MEMBER | null | The following works on current `master`:
```py
>>> from transformers import TrOCRProcessor
>>> processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")
Downloading: 100%|██████████| 878k/878k [00:00<00:00, 1.61MB/s]
Downloading: 100%|██████████| 446k/446k [00:00<00:00, 1.03MB/s]
Downloading: 1... | {
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https://api.github.com/repos/huggingface/transformers/issues/14883 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14883/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14883/comments | https://api.github.com/repos/huggingface/transformers/issues/14883/events | https://github.com/huggingface/transformers/pull/14883 | 1,086,825,827 | PR_kwDOCUB6oc4wLzN- | 14,883 | Fix pytorch image classification example | {
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"Hi @lonelydancer thank you for raising this issue!\r\n\r\nIf I understand correctly, you changed [this line](https://github.com/huggingface/transformers/blob/13504dcbea231d2cae701d1ffdeb0810d62aff81/examples/onnx/pytorch/summarization/run_onnx_exporter.py#L147) in the `run_onnx_exporter.py` script as follows:\r\n\... | 1,640 | 1,645 | 1,645 | NONE | null | Hi,
when i use the scrips in https://github.com/huggingface/transformers/tree/master/examples/onnx/pytorch/summarization/run_onnx_exporter.py;
i change the code
ort_sess = onnxruntime.InferenceSession(new_onnx_file_path, providers=['CUDAExecutionProvider'])
i get core dumps.
![image](https://user-images.github... | {
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"Error is unrelated",
"> Before being able to merge this PR, you will need to rebase and fix the docstrings. If we go with it that is.\r\n> \r\n> I have a general issue with feature extractors and processors sharing the same config file. It implies every processor will always have a feature extractor but differen... | 1,640 | 1,640 | 1,640 | MEMBER | null | … class.
This PR makes sure that all preprocessors, when saved automatically save the corresponding class to `preprocessing_config.json` so that they can always be loaded from `AutoProcessor` afterward. E.g. the following should always be possible:
```python
auto_processor.save_pretrained("./")
processor = Auto... | {
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"Hi there, thanks a lot for you PR! It will be great to be able to fully use LUKE and mLUKE for token classification!\r\n\r\nNow the issue is that we try to keep each example pretty simple so that users can easily tweak and customize them. Adding this in the `run_ner_no_trainer` example adds a lot of complexity so ... | 1,640 | 1,686 | 1,643 | CONTRIBUTOR | null | # What does this PR do?
This PR adds the possibility to train the (M)Luke model for a Token Classification task with the accelerate package. It also adds a tiny update to give the possibility to train over multiple datasets configuration, for example being able to concatenate multiple languages of the XTREME PAN-X d... | {
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This PR fixes the code example of the multimodal Perceiver model.
Fixes #14870 | {
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"This may be of interest to @stas00 as I believe he has quite a bit of experience with this kind of setups.",
"I haven't encountered this specific issue, so first let's try to understand what is going on here.\r\n\r\n> Note: I had to switch the backend to gloo because got nccl errors.\r\n\r\nand did you test that... | 1,640 | 1,640 | 1,640 | NONE | null | Hello,
I am attempting to train a model on 32 A100s split into 4 nodes. The queueing system is SLURM. When training on a single node, I can use all 8 GPUs with a batch size of 8:
`python -m torch.distributed.launch --nproc_per_node=8 ./script.py --model_name_or_path gpt2-large --train_file sample.txt --tokenize... | {
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https://api.github.com/repos/huggingface/transformers/issues/14877 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14877/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14877/comments | https://api.github.com/repos/huggingface/transformers/issues/14877/events | https://github.com/huggingface/transformers/issues/14877 | 1,086,422,080 | I_kwDOCUB6oc5AwXxA | 14,877 | dataset of Helsinki-NLP/opus-mt-en-zh | {
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"The README here mentions `eng-zho`, if I'm not mistaken: https://huggingface.co/Helsinki-NLP/opus-mt-en-zh",
"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 n... | 1,640 | 1,643 | 1,643 | NONE | null | Hi, thanks for your model. I have two questions of the train datasets of opus-mt-en-zh.
https://github.com/Helsinki-NLP/Tatoeba-Challenge/blob/master/data/README-v2021-08-07.md
English - Chinese eng-zho 10390 | 43075 | 129323178
Middle English (1100-1500) - Chinese enm-zho
In this website, there are two dataset... | {
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https://api.github.com/repos/huggingface/transformers/issues/14876 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14876/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14876/comments | https://api.github.com/repos/huggingface/transformers/issues/14876/events | https://github.com/huggingface/transformers/pull/14876 | 1,086,380,846 | PR_kwDOCUB6oc4wKVii | 14,876 | Add XGLM models | {
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This PR adds the XGLM model: [code](https://github.com/pytorch/fairseq/tree/main/examples/xglm), [paper](https://arxiv.org/abs/2112.10668) | {
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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)... | 1,640 | 1,661 | 1,645 | 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. -->
Add `in_chans` parameter to `DetrConfig` and corresponding models
## Motivation
I find myself wanting to test DETR on data that have only one channel (it c... | {
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https://api.github.com/repos/huggingface/transformers/issues/14874 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14874/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14874/comments | https://api.github.com/repos/huggingface/transformers/issues/14874/events | https://github.com/huggingface/transformers/pull/14874 | 1,086,311,081 | PR_kwDOCUB6oc4wKG_- | 14,874 | Fix doc mistakes | {
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Fix last issues to have the doc compile again:
- double return blocks in VisualBert, TFTapas and Perceiver
- some weird special characters in LXMert and an empty return block
Merging right now to unlock the doc building. | {
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"Thanks a lot!"
] | 1,640 | 1,640 | 1,640 | COLLABORATOR | null | # What does this PR do?
Completes #14872 and fixes `FlaxMarianMTModel`
cc @patrickvonplaten | {
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Fixes a few issues in the docstring for the Marian model. | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/14870 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14870/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14870/comments | https://api.github.com/repos/huggingface/transformers/issues/14870/events | https://github.com/huggingface/transformers/issues/14870 | 1,086,225,992 | I_kwDOCUB6oc5Avn5I | 14,870 | Error while reproducing example for PerceiverForMultimodalAutoencoding | {
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- `transformers` version: 4.14.1
- Platform: Linux-5.8.0-63-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.7.6
- PyTorch version (GPU?): 1.9.0+cu111 (True)
- Tensorflow version (GPU?): 2.5.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
... | {
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https://api.github.com/repos/huggingface/transformers/issues/14869 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14869/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14869/comments | https://api.github.com/repos/huggingface/transformers/issues/14869/events | https://github.com/huggingface/transformers/issues/14869 | 1,086,173,179 | I_kwDOCUB6oc5Ava_7 | 14,869 | Fine-tuning Wav2Vec2: Concern that pretrained weights are being reinitialized | {
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"Hey @rcoulter13,\r\n\r\nThis issue is quite difficult to debug for us since it's not an obvious bug but deals with the model having problems with continual learning. It's quite a common phenomena that fine-tuned models have catastrophic forgetting when they are re-finetuned on out of distribution data",
"There a... | 1,640 | 1,641 | 1,641 | NONE | null | ## Environment info
- OS Type: Google Colab
- 'transformers' version: 4.14.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyTorch version (GPU?): 1.10.0+cu111 (True)
- Tensorflow version (GPU?): 2.7.0 (True)
### Who can help
Anyone with knowledge of fine-tuning Wav2V... | {
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"Hey @MaximovaIrina we recently switched all of our documentation from RST to MDX, so you can rebase on `master` to eliminate the conflict with `docs/source/serialization.rst`",
"Checking slow tests for ibert \r\n![image](https://user-images.githubusercontent.com/36035908/147254715-5affc916-e2c8-4984-acdb-67c5732... | 1,640 | 1,641 | 1,641 | CONTRIBUTOR | null | Adds IBERT to models exportable with ONNX | {
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"I feel like it makes sense to test on three notebooks. (could be overkill so you decide)\r\n- Token classification\r\n- Translation\r\n- Masked language modeling\r\nIf you approve I’ll test for these ones. I wonder how it would look like with multiple metrics so in one of those I could test with multiple metrics (... | 1,640 | 1,640 | 1,640 | MEMBER | null | Hey, here's the unfinished Keras metric PR, co-authored with @merveenoyan!
Still to do:
1) The outputs from predict/generate are not being concatenated properly, this will be quick to fix! (Edit: Done)
2) I haven't tested prediction with generate at all. `generate()` is still very slow, but that's a separate PR ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14866 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14866/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14866/comments | https://api.github.com/repos/huggingface/transformers/issues/14866/events | https://github.com/huggingface/transformers/pull/14866 | 1,086,038,755 | PR_kwDOCUB6oc4wJMiA | 14,866 | Mass conversion of documentation from rst to Markdown | {
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"As seen with @LysandreJik, merging and inspecting the result in the doc. Failure is unrelated."
] | 1,640 | 1,640 | 1,640 | COLLABORATOR | null | # What does this PR do?
This PR treats a lot of docstrings and converts them from rst to Markdown. All of the remaining one.
It also includes a new repo consistency check that will detect someone does not add back some rst docstrings behind my back. 😈 | {
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https://api.github.com/repos/huggingface/transformers/issues/14865 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14865/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14865/comments | https://api.github.com/repos/huggingface/transformers/issues/14865/events | https://github.com/huggingface/transformers/pull/14865 | 1,086,033,556 | PR_kwDOCUB6oc4wJLbK | 14,865 | Convert model files from rst to mdx | {
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https://api.github.com/repos/huggingface/transformers/issues/14864 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14864/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14864/comments | https://api.github.com/repos/huggingface/transformers/issues/14864/events | https://github.com/huggingface/transformers/pull/14864 | 1,086,027,531 | PR_kwDOCUB6oc4wJKIh | 14,864 | Add Flax image captioning example | {
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"@patil-suraj , @sgugger \r\n\r\nThank you for the comments. I will make the example much simpler by only supporting loading pre-trained vision encoder and text models.\r\n\r\nAbout casting jax array to np arrary, there is a significant slow down (at least, in image examples) when using jax array as indices for acc... | 1,640 | 1,651 | 1,641 | COLLABORATOR | null | # What does this PR do?
Add `run_image_captioning_flax.py` (modified from `run_summarization_flax.py`).
## Who can review
Examples: @patil-suraj + cc @patrickvonplaten @NielsRogge @sgugger for info
| {
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https://api.github.com/repos/huggingface/transformers/issues/14863 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14863/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14863/comments | https://api.github.com/repos/huggingface/transformers/issues/14863/events | https://github.com/huggingface/transformers/issues/14863 | 1,085,987,088 | I_kwDOCUB6oc5AutkQ | 14,863 | Open discussion for design decisions. | {
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"Hi @pafi-code, regarding your first question: the loss calculation is coupled with the forward but it is opt-in. The models only perform the loss calculation when you pass the `labels`, which is not a requirement. You're perfectly free to retrieve the logits and compute your loss yourself, outside of the model.\r\... | 1,640 | 1,640 | 1,640 | NONE | null | # 🚀 Feature request
Hi all,
I'd like to ask some questions about design decisions that were made generally for this library.
**First one:**
Why did you couple the forward directly with the loss calculation? I don't really see any benefits doing this, rather downsides for example when you want to extend the `... | {
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https://api.github.com/repos/huggingface/transformers/issues/14862 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14862/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14862/comments | https://api.github.com/repos/huggingface/transformers/issues/14862/events | https://github.com/huggingface/transformers/issues/14862 | 1,085,873,504 | I_kwDOCUB6oc5AuR1g | 14,862 | Cache the files in get_fast_tokenizer_file() | {
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"Hello! This does cache the file, but you're unfortunately hitting an error on our side when checking that the file exists and its sha (cc @julien-c, @n1t0). If this happens, I recommend leveraging `local_files_only` as a parameter to `from_pretrained`, as this will only use local files.\r\n\r\nSorry for the inconv... | 1,640 | 1,648 | 1,645 | NONE | null | # 🚀 Feature request
`transformers.BertTokenizer.from_pretrained()` calls `get_fast_tokenizer_file()` which downloads a file from the HuggingFace server but never adds it to the cache.
Would be useful to cache that file (in the same folder as the models) to make CI runs more robust.
## Motivation
Try to avo... | {
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https://api.github.com/repos/huggingface/transformers/issues/14861 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14861/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14861/comments | https://api.github.com/repos/huggingface/transformers/issues/14861/events | https://github.com/huggingface/transformers/issues/14861 | 1,085,519,570 | I_kwDOCUB6oc5As7bS | 14,861 | [Wav2vec2] RuntimeError: CUDA error: an illegal memory access was encountered | {
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"Hey @flozi00, \r\n\r\nThis looks like a difficult error. Can we try to debug it step-by-step? \r\n\r\n1. Does it work **without** ` --sharded_ddp simple` and in a single-GPU environment (without `python -m torch.distributed.launch` - just `python run_speech_recognition_ctc.py`\r\n2. If yes, does it work **without*... | 1,640 | 1,640 | 1,640 | 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: master
- Platform: ubuntu
- Python version: 3.8
- PyTorch version (GPU?): 1.10
- Tensorflow version (GPU?):... | {
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https://api.github.com/repos/huggingface/transformers/issues/14860 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14860/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14860/comments | https://api.github.com/repos/huggingface/transformers/issues/14860/events | https://github.com/huggingface/transformers/issues/14860 | 1,085,426,792 | I_kwDOCUB6oc5Askxo | 14,860 | Huggingface Transformers fastTokenizer for DeBERTa v3 | {
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"Found #14712 for the same request",
"Let's centralize the discussion on #14712 if you don't mind :)",
"i have same problem"
] | 1,640 | 1,683 | 1,640 | NONE | 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. -->
I want to try NER for custom dataset using huggingface transformers DeBERTa v3 xsmall.
I need to use fastTokenizer, but it is not available.
I need to use ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14859 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14859/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14859/comments | https://api.github.com/repos/huggingface/transformers/issues/14859/events | https://github.com/huggingface/transformers/issues/14859 | 1,085,409,029 | I_kwDOCUB6oc5AsgcF | 14,859 | A potential bug in ModuleUtilsMixin.get_extended_attention_mask | {
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"I understand that the choice of 1e-4 may be suboptimal and that the masking may not be enough. I believe we've had this conversation before but I can't find it anywhere, I'm open to revisiting it.\r\n\r\nWDYT @patrickvonplaten @sgugger @patil-suraj @stas00 ",
"I agree 1e-4 might not be the best choice for every ... | 1,640 | 1,683 | 1,656 | 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: 4.13.0
- Platform:
- Python version: 3.8.5
- PyTorch version (GPU?): 1.10.0+cu102
- Tensorflow version (GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/14858 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14858/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14858/comments | https://api.github.com/repos/huggingface/transformers/issues/14858/events | https://github.com/huggingface/transformers/pull/14858 | 1,085,381,214 | PR_kwDOCUB6oc4wHBBj | 14,858 | [doc porting] several docs | {
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"Amazing that you noticed all those issues, @sgugger - I missed all of those.\r\n\r\nIt looks like we need to be careful with suggestions that include \"```\", it looks like github is buggy there, ate the \"````\" you added since it's also part of suggestion - had to switch to 4 backticks suggestion."
] | 1,640 | 1,640 | 1,640 | CONTRIBUTOR | null | Ported to mdx:
```
docs/source/debugging.rst
docs/source/testing.rst
docs/source/main_classes/deepspeed.rst
```
fixed a few small code block breakages in the first one.
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/14857 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14857/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14857/comments | https://api.github.com/repos/huggingface/transformers/issues/14857/events | https://github.com/huggingface/transformers/pull/14857 | 1,085,380,515 | PR_kwDOCUB6oc4wHA4c | 14,857 | Only create the model card on process 0 | {
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"Thank you @sgugger and Merry X'mas :)"
] | 1,640 | 1,640 | 1,640 | COLLABORATOR | null | # What does this PR do?
This PR makes sure the model card is only created and saved on process 0.
Fixes #14840 | {
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