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https://api.github.com/repos/huggingface/transformers/issues/11235 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11235/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11235/comments | https://api.github.com/repos/huggingface/transformers/issues/11235/events | https://github.com/huggingface/transformers/pull/11235 | 857,274,892 | MDExOlB1bGxSZXF1ZXN0NjE0NzIyMjU2 | 11,235 | [Deepspeed] zero3 tests band aid | {
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This PR is just a temporary band-aid to restore the state on the test level - and I nee... | {
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https://api.github.com/repos/huggingface/transformers/issues/11234 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11234/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11234/comments | https://api.github.com/repos/huggingface/transformers/issues/11234/events | https://github.com/huggingface/transformers/pull/11234 | 857,244,741 | MDExOlB1bGxSZXF1ZXN0NjE0Njk2Nzg0 | 11,234 | Tokenizer fast save | {
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This PR changes the behavior of `save_pretrained` to have the fast tokenizer unified json file being saved as well as the files of the "slow" tokenizer. The default of `legacy_format` is changed to None with the following behavior:
- unset -> a fast tokenizer is saved with both formats (toke... | {
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https://api.github.com/repos/huggingface/transformers/issues/11233 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11233/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11233/comments | https://api.github.com/repos/huggingface/transformers/issues/11233/events | https://github.com/huggingface/transformers/pull/11233 | 857,191,059 | MDExOlB1bGxSZXF1ZXN0NjE0NjUyNzQy | 11,233 | Indent code block in the documentation | {
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This is a new version of #11227 starting from a fresh master and following the remarks of Stas.
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https://api.github.com/repos/huggingface/transformers/issues/11232 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11232/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11232/comments | https://api.github.com/repos/huggingface/transformers/issues/11232/events | https://github.com/huggingface/transformers/issues/11232 | 857,177,391 | MDU6SXNzdWU4NTcxNzczOTE= | 11,232 | BigBird Causal Attention | {
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"Pinging @vasudevgupta7 and @patrickvonplaten ",
"There are several issues, we will have to keep in mind before we decide to implement bigbird block sparse attention in decoder.\r\n\r\n1) Initial number of tokens in decoder side must be > `5 x block_size + 2 x num_random_blocks x block_size` (for bigbird block sp... | 1,618 | 1,622 | 1,622 | CONTRIBUTOR | null | # 🚀 Feature request
I'd like to use bigbird sparse attention in a decoder. Isn't that feasible if we apply a causal mask [here](https://github.com/huggingface/transformers/blob/master/src/transformers/models/big_bird/modeling_big_bird.py#L665)?
So long as we know which entries correspond to (i, j) entries where... | {
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https://api.github.com/repos/huggingface/transformers/issues/11231 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11231/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11231/comments | https://api.github.com/repos/huggingface/transformers/issues/11231/events | https://github.com/huggingface/transformers/issues/11231 | 857,175,102 | MDU6SXNzdWU4NTcxNzUxMDI= | 11,231 | "Connection error, and we cannot find the requested files in the cached path." ValueError: Connection error, and we cannot find the requested files in the cached path. Please try again or make sure your Internet connection is on. | {
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"Pinging @stas00 since I see in your stack trace you are working on jean-zay and I know Stas has some experience with it.",
"@keloemma, please have a look at the special offline mode https://huggingface.co/transformers/installation.html#offline-mode - if your gpu instance is firewalled (which is the case on JZ) i... | 1,618 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11230 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11230/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11230/comments | https://api.github.com/repos/huggingface/transformers/issues/11230/events | https://github.com/huggingface/transformers/issues/11230 | 857,167,372 | MDU6SXNzdWU4NTcxNjczNzI= | 11,230 | run_qa.py fails evaluating on Squad2 | {
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"You need to pass along `--version_2_with_negative` when using this script with a dataset that has samples with no answers (like squad v2).",
"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\nP... | 1,618 | 1,621 | 1,621 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0.dev0
- Platform: Linux-5.4.0-66-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.7.10
- PyT... | {
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https://api.github.com/repos/huggingface/transformers/issues/11229 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11229/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11229/comments | https://api.github.com/repos/huggingface/transformers/issues/11229/events | https://github.com/huggingface/transformers/pull/11229 | 857,150,251 | MDExOlB1bGxSZXF1ZXN0NjE0NjE4NzM5 | 11,229 | Avoid using no_sync on SageMaker DP | {
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As reported on the [forums](https://discuss.huggingface.co/t/distributeddataparallel-object-has-no-attribute-no-sync/5469), SageMaker DP is incompatible with gradient accumulation for now. This PR fixes that. | {
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https://api.github.com/repos/huggingface/transformers/issues/11228 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11228/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11228/comments | https://api.github.com/repos/huggingface/transformers/issues/11228/events | https://github.com/huggingface/transformers/pull/11228 | 857,128,006 | MDExOlB1bGxSZXF1ZXN0NjE0NjAwMjc1 | 11,228 | Make "embeddings" plural in warning message within tokenization_utils_base | {
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Makes the word "embeddings" plural within the warning message in `tokenization_utils_base.py`.
## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline](https://github.com/hug... | {
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https://api.github.com/repos/huggingface/transformers/issues/11227 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11227/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11227/comments | https://api.github.com/repos/huggingface/transformers/issues/11227/events | https://github.com/huggingface/transformers/pull/11227 | 857,050,904 | MDExOlB1bGxSZXF1ZXN0NjE0NTM1MDky | 11,227 | Make sure code blocks are indented with four spaces | {
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"Ah, I don't match the `.. code-block:: xxx`, thanks for pointing that out!",
"OK, the next problem is the one I was concerned about in the first place (which is why i didn't offer a perl one liner). Your fixing code isn't shifting the whole block, but only the outside lines. so it now results in broken python co... | 1,618 | 1,618 | 1,618 | COLLABORATOR | null | # What does this PR do?
In the documentation, many code blocks are indented with two or three spaces instead of 4. This PR enforces the use of 4 by:
- replacing indents of less than 4 by 4 in `make style`/`make fixup`
- checking there is no indent less than 4 in code blocks during `make quality`
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https://api.github.com/repos/huggingface/transformers/issues/11226 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11226/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11226/comments | https://api.github.com/repos/huggingface/transformers/issues/11226/events | https://github.com/huggingface/transformers/pull/11226 | 857,039,433 | MDExOlB1bGxSZXF1ZXN0NjE0NTI1MzU2 | 11,226 | Add prefix to examples in model_doc rst | {
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"Hi @forest1988, thanks a lot for your PR! In parallel I've merged another PR that enforces proper indentation for those examples so now yours is conflicting. Could you rebase on master and solve the conflicts, or open a new PR from a fresh master, whichever is easier?\r\nThanks",
"Hi @sgugger,\r\nThank you for t... | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
In my previous PR #11219, I was advised that the example should follow the syntax
```
>>> code_line_1
>>> code_line_2
result
```
I found some `model_doc` rst files that have code blocks without the prefix.
This PR intends to add `>>>` to those examples.
## Before submitting
- [... | {
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https://api.github.com/repos/huggingface/transformers/issues/11225 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11225/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11225/comments | https://api.github.com/repos/huggingface/transformers/issues/11225/events | https://github.com/huggingface/transformers/pull/11225 | 857,031,803 | MDExOlB1bGxSZXF1ZXN0NjE0NTE4ODUy | 11,225 | Refactor GPT2 | {
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This PR refactors GPT2 model to make it more consistent with the rest of the models in the lib. These are mostly cosmetic changes and uses better names instead of those `nx, n_state` etc.
This does not cause any performance regression and I've verified that all slow tests are passing.
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https://api.github.com/repos/huggingface/transformers/issues/11224 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11224/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11224/comments | https://api.github.com/repos/huggingface/transformers/issues/11224/events | https://github.com/huggingface/transformers/pull/11224 | 856,995,000 | MDExOlB1bGxSZXF1ZXN0NjE0NDg3NzAz | 11,224 | Doc check: a bit of clean up | {
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This PR removes the data collator and BertForJapaneseTokenizer from the while list in the check that all public objects are documented. It also cleans up a bit the data collator page. | {
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https://api.github.com/repos/huggingface/transformers/issues/11223 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11223/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11223/comments | https://api.github.com/repos/huggingface/transformers/issues/11223/events | https://github.com/huggingface/transformers/pull/11223 | 856,960,182 | MDExOlB1bGxSZXF1ZXN0NjE0NDU4MjM5 | 11,223 | Add LUKE | {
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"@LysandreJik @sgugger all comments are addressed, CI is green! Incredible work by the original author. ",
"Thanks, addressed your comments.\r\n\r\nAdded LUKE to the README, and added 3 community notebooks. ",
"Thanks again for all your work on this!"
] | 1,618 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
It adds [LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention](https://arxiv.org/abs/2010.01057) by Yamada et al. [EMNLP 2020].
LUKE is similar to RoBERTa, but it adds an entity embedding matrix (500k Wikipedia entities!) and an entity-aware self-attention mech... | {
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https://api.github.com/repos/huggingface/transformers/issues/11222 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11222/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11222/comments | https://api.github.com/repos/huggingface/transformers/issues/11222/events | https://github.com/huggingface/transformers/issues/11222 | 856,843,168 | MDU6SXNzdWU4NTY4NDMxNjg= | 11,222 | Weird issue with OOM on exported save_pretrained models | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,618 | 1,621 | 1,621 | NONE | null | Having a weird issue with DialoGPT Large model deployment. From PyTorch 1.8.0 and Transformers 4.3.3 using model.save_pretrained and tokenizer.save_pretrained, the exported pytorch_model.bin is almost twice the size of the model card repo and results in OOM on a reasonably equipped machine that when using the standard ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11221 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11221/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11221/comments | https://api.github.com/repos/huggingface/transformers/issues/11221/events | https://github.com/huggingface/transformers/pull/11221 | 856,791,508 | MDExOlB1bGxSZXF1ZXN0NjE0MzE1Mzg3 | 11,221 | fix docs for decoder_input_ids | {
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This PR fixes the docs for `decoder_input_ids` and `decoder_attention_mask` arguments. | {
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https://api.github.com/repos/huggingface/transformers/issues/11220 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11220/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11220/comments | https://api.github.com/repos/huggingface/transformers/issues/11220/events | https://github.com/huggingface/transformers/pull/11220 | 856,782,642 | MDExOlB1bGxSZXF1ZXN0NjE0MzA3ODcx | 11,220 | added cache_dir=model_args.cache_dir to all example with cache_dir arg | {
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This PR adds `cache_dir=model_args.cache_dir` to all example scripts using `load_dataset` and having `cache_dir` as args.
Close #11205 | {
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https://api.github.com/repos/huggingface/transformers/issues/11219 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11219/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11219/comments | https://api.github.com/repos/huggingface/transformers/issues/11219/events | https://github.com/huggingface/transformers/pull/11219 | 856,755,977 | MDExOlB1bGxSZXF1ZXN0NjE0Mjg1NDcx | 11,219 | Add documentation for BertJapanese | {
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"Thanks a lot for your help!",
"@sgugger @LysandreJik \r\nThank you for your quick reviewing this PR!\r\n\r\n@sgugger \r\nThank you for telling me how to format the code block!\r\n\r\n> Thanks a lot for your PR! I made a couple of suggestions. Mostly, the example should follow the syntax\r\n> \r\n> ```\r\n> >>> c... | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
Add documentation for BertJapanese
Regarding #9035
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTR... | {
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https://api.github.com/repos/huggingface/transformers/issues/11218 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11218/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11218/comments | https://api.github.com/repos/huggingface/transformers/issues/11218/events | https://github.com/huggingface/transformers/pull/11218 | 856,735,882 | MDExOlB1bGxSZXF1ZXN0NjE0MjY4Nzcw | 11,218 | [WIP] FSMT bart-like refactor | {
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"Thanks Stas! I'm not sure what exactly introduced this memory/speed regression, so I'm going to investigate it and won't merge this PR before that.",
"> Thank you for doing this refactoring, @patil-suraj!\r\n> \r\n> It's a bit hard to review since all the code is moved around, so no easy diff to follow - so whil... | 1,618 | 1,648 | null | MEMBER | null | # What does this PR do?
This PR refactors `FSMT` to align it with other (bart-like) seq-2-seq models in the lib.
This PR refactors `FSMT` similar to `Bart` in that it moves the time dimension to be always at the 2nd place and the batch dimensions always in the first place. Also, the cache is refactored to consist... | {
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https://api.github.com/repos/huggingface/transformers/issues/11217 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11217/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11217/comments | https://api.github.com/repos/huggingface/transformers/issues/11217/events | https://github.com/huggingface/transformers/issues/11217 | 856,663,440 | MDU6SXNzdWU4NTY2NjM0NDA= | 11,217 | Question about validation_set | {
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"Hi,\r\n\r\nYou can use Stackoverflow for that: https://stats.stackexchange.com/questions/19048/what-is-the-difference-between-test-set-and-validation-set\r\n\r\nWe like to keep Github issues for feature requests/bug reports. There's also the [forum](https://discuss.huggingface.co/) where you can ask training-relat... | 1,618 | 1,621 | 1,621 | NONE | null | I want to ask a simple question. The parameters of the model have been set before model training. What is the purpose of the validation set in model training? Thank you！ | {
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https://api.github.com/repos/huggingface/transformers/issues/11216 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11216/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11216/comments | https://api.github.com/repos/huggingface/transformers/issues/11216/events | https://github.com/huggingface/transformers/issues/11216 | 856,439,814 | MDU6SXNzdWU4NTY0Mzk4MTQ= | 11,216 | Load BART-base error | {
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"This seems to be an issue with `simpletransformers` so please post it there since we won't get time to look into other code bases to fix such issues.",
"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 t... | 1,618 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0
- simpletransformers: 0.61.4
- Platform: CentOS
- Python version: Python 3.8.2
- PyTorch version (GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11215 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11215/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11215/comments | https://api.github.com/repos/huggingface/transformers/issues/11215/events | https://github.com/huggingface/transformers/issues/11215 | 856,429,370 | MDU6SXNzdWU4NTY0MjkzNzA= | 11,215 | It don't find simple logic sequences | {
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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)... | 1,618 | 1,621 | 1,621 | NONE | null | 
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https://api.github.com/repos/huggingface/transformers/issues/11214 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11214/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11214/comments | https://api.github.com/repos/huggingface/transformers/issues/11214/events | https://github.com/huggingface/transformers/pull/11214 | 856,415,928 | MDExOlB1bGxSZXF1ZXN0NjEzOTk2ODE2 | 11,214 | Import torch.utils.checkpoint in ProphetNet | {
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https://api.github.com/repos/huggingface/transformers/issues/11213 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11213/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11213/comments | https://api.github.com/repos/huggingface/transformers/issues/11213/events | https://github.com/huggingface/transformers/pull/11213 | 856,393,634 | MDExOlB1bGxSZXF1ZXN0NjEzOTc4MDQy | 11,213 | Fix GPT-2 warnings | {
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When loading from a pytorch checkpoint to a tensorflow checkpoint, there was no issue, but doing so the other way around wouldn't check the `_keys_to_ignore_on_load_missing` and `_keys_to_ignore_on_load_unexpected` variables before printing a warning.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11212 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11212/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11212/comments | https://api.github.com/repos/huggingface/transformers/issues/11212/events | https://github.com/huggingface/transformers/pull/11212 | 856,356,669 | MDExOlB1bGxSZXF1ZXN0NjEzOTQ2OTIz | 11,212 | Add Matt as the TensorFlow reference | {
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https://api.github.com/repos/huggingface/transformers/issues/11211 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11211/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11211/comments | https://api.github.com/repos/huggingface/transformers/issues/11211/events | https://github.com/huggingface/transformers/issues/11211 | 856,321,423 | MDU6SXNzdWU4NTYzMjE0MjM= | 11,211 | Beam search on BART seq2seq | {
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"Hi @ashleylew \r\n\r\nThe `run_translation.py` uses the `Seq2SeqTrainer` which does not pass the `num_return_sequences` argument to `generate`, this is because if multiple sequences are returned then its not clear what sequence should be used to compute the metrics. \r\n\r\nyou could generate test set predictions ... | 1,618 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0.dev0
- Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyT... | {
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https://api.github.com/repos/huggingface/transformers/issues/11210 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11210/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11210/comments | https://api.github.com/repos/huggingface/transformers/issues/11210/events | https://github.com/huggingface/transformers/issues/11210 | 856,290,522 | MDU6SXNzdWU4NTYyOTA1MjI= | 11,210 | Documentation enhancement - model_type | {
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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)... | 1,618 | 1,621 | 1,621 | NONE | null | # 🚀 Feature request
Please provide a clear explanation of what the valid values would be for "model_type". I think that the answer is any model name you would use in from_pretrained() but I am not sure.
## Motivation
Clarity of the parameter and saving time on trial and error and guesswork.
## Your cont... | {
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https://api.github.com/repos/huggingface/transformers/issues/11209 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11209/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11209/comments | https://api.github.com/repos/huggingface/transformers/issues/11209/events | https://github.com/huggingface/transformers/issues/11209 | 856,166,780 | MDU6SXNzdWU4NTYxNjY3ODA= | 11,209 | [RFC] introduce `config.trained_precision` | {
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"Would that information not be better on the respective model cards? I think that's more on that side that it should go with the rest of the training setup.",
"1. It'd be difficult to enforce that it's being filled out\r\n2. It'd be difficult to tell the user at run time that model A pre-trained in fp32, is attem... | 1,618 | 1,706 | null | CONTRIBUTOR | null | # 🚀 Feature request
As we are discovering that `bf16`-pretrained models don't do well on `fp16` "regime" (and surely vice-versa), and some models are pre-trained in `fp32` and surely won't do well on either `bf16` or `fp16`, and the problem is going to grow as more `bf16`-supporting hardware comes out, I propose we... | {
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https://api.github.com/repos/huggingface/transformers/issues/11208 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11208/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11208/comments | https://api.github.com/repos/huggingface/transformers/issues/11208/events | https://github.com/huggingface/transformers/issues/11208 | 856,151,898 | MDU6SXNzdWU4NTYxNTE4OTg= | 11,208 | Issue: Trainer error on `evaluate()` in multithreaded/distributed context (shape mismatch) | {
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"I am unsure on what you want us to do: all the example scripts have been tested with evaluation and work in a distributed setup. Unless you share your script, there is little we can do to fix an issue we have not encountered.\r\n\r\nAlso make sure you have the latest version of Transformers installed as this bug m... | 1,618 | 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: 4.3.3
- Platform: Linux-5.4.83.1.fi-x86_64-with-centos-7.8.2003-Core
- Python version: 3.7.3
- PyTorch versi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11207/comments | https://api.github.com/repos/huggingface/transformers/issues/11207/events | https://github.com/huggingface/transformers/pull/11207 | 856,068,229 | MDExOlB1bGxSZXF1ZXN0NjEzNzA2NjQw | 11,207 | Replace error by warning when loading an architecture in another | {
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"Would you consider this solution instead?\r\n\r\n```\r\n--- a/src/transformers/models/bert_generation/configuration_bert_generation.py\r\n+++ b/src/transformers/models/bert_generation/configuration_bert_generation.py\r\n@@ -78,7 +78,7 @@ class BertGenerationConfig(PretrainedConfig):\r\n >>> # Accessing the... | 1,618 | 1,618 | 1,618 | COLLABORATOR | null | # What does this PR do?
#10586 introduced a breaking change by mistake by removing the possibility to do something like:
```
from transformers import BertGenerationEncoder
model = BertGenerationEncoder.from_pretrained("bert-large-uncased", bos_token_id=101, eos_token_id=102)
```
which is perfectly acceptable an... | {
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https://api.github.com/repos/huggingface/transformers/issues/11206 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11206/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11206/comments | https://api.github.com/repos/huggingface/transformers/issues/11206/events | https://github.com/huggingface/transformers/pull/11206 | 856,066,037 | MDExOlB1bGxSZXF1ZXN0NjEzNzA0ODIz | 11,206 | Sagemaker test docs update for framework upgrade | {
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This PR resolves the last todo in the sagemaker test `Readme.md` and increase a test metric to stable the test for `model_parallelism`. | {
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https://api.github.com/repos/huggingface/transformers/issues/11205 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11205/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11205/comments | https://api.github.com/repos/huggingface/transformers/issues/11205/events | https://github.com/huggingface/transformers/issues/11205 | 855,983,813 | MDU6SXNzdWU4NTU5ODM4MTM= | 11,205 | Rework examples/ to overwrite cache_dir for datasets too. | {
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"Well someone would need to go other all the examples and add it as an argument in those calls to `load_dataset`.",
"Would you still keep it in \r\n```python\r\n@dataclass\r\nclass ModelArguments:\r\n```\r\nI can adjust the examples in the near future. I just wanted to align on we can adjust this. ",
"We can sw... | 1,618 | 1,618 | 1,618 | MEMBER | null | # 🚀 Feature request
Currently, you can pass [cache_dir](https://github.com/huggingface/transformers/blob/ef102c48865d70ff354b8ba1488d3fa8bfc116d8/examples/seq2seq/run_summarization.py#L79) into the `examples/` script to overwrite the `cache_dir` of [model config and tokenizers](https://github.com/huggingface/transf... | {
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https://api.github.com/repos/huggingface/transformers/issues/11204 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11204/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11204/comments | https://api.github.com/repos/huggingface/transformers/issues/11204/events | https://github.com/huggingface/transformers/issues/11204 | 855,917,098 | MDU6SXNzdWU4NTU5MTcwOTg= | 11,204 | ModuleNotFoundError: No module named 'transformers.modeling_camembert' | {
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"Which version of Transformers are you using?\r\n\r\nIf you're using one of the latest versions of Transformers, `modeling_camembert.py` will be located at `transformers.models.camembert.modeling_camembert.py`. ",
"This issue has been automatically marked as stale because it has not had recent activity. If you th... | 1,618 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
`transformers` version: 4.2.2
-Python version: 3.7.9
- PyTorch version (GPU?):1.7.1
- Tensorflow version (GPU?) : 2.4.1
- Using GPU i... | {
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https://api.github.com/repos/huggingface/transformers/issues/11203 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11203/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11203/comments | https://api.github.com/repos/huggingface/transformers/issues/11203/events | https://github.com/huggingface/transformers/issues/11203 | 855,915,125 | MDU6SXNzdWU4NTU5MTUxMjU= | 11,203 | How to extract the specific output using the method "encoder_output[0]" | {
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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!"
] | 1,618 | 1,618 | 1,618 | NONE | null | Dear Transformers Team
Thank you very much for Transformers which provides me solutions for relation extraction problems. I have a question. My input is like " [E1]Jack[/E2] was born in [E2]London[/E2]". I want to only extract the sequence output of "[E1] and "[E2]" with the method of "encoder_output[0]". And then c... | {
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https://api.github.com/repos/huggingface/transformers/issues/11202 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11202/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11202/comments | https://api.github.com/repos/huggingface/transformers/issues/11202/events | https://github.com/huggingface/transformers/pull/11202 | 855,903,593 | MDExOlB1bGxSZXF1ZXN0NjEzNTY4MDQw | 11,202 | Fix TFBert embedding tf variables with the same name - Fixes problems with checkpoints under tf.distribute.Strategy | {
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"Hi! I'm the new Tensorflow maintainer at Hugging Face. Your PR looks good, and you're right that unique weight names is a better strategy than relying on `name_scope`. Now that you've raised the issue, doing a check for that across the whole codebase is definitely on my to-do list.\r\n\r\nThe main issue for us is ... | 1,618 | 1,624 | 1,624 | NONE | null | # What does this PR do?
Removes usage of tf.name_scope() in BERT like models and replaces it with layers.
Ideally all erroneous use of tf.name_scope() should be fixed across all models, but this PR will at least make the TFBert like models work.
<!-- Remove if not applicable -->
Fixes # (issue)
#11169
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"The error seems to come from your dataset, and you did not share the code you used to create and process it, so there is little we can do to help.",
"Thanks for the quick reply. Here is the code I used to prepare the data:\r\n\r\n```\r\ntrain_data = datasets.load_dataset(\"cnn_dailymail\", \"3.0.0\", split=\"tra... | 1,618 | 1,618 | 1,618 | NONE | null | ## Environment info
- `transformers` version: v4.5.0
- Platform: Google Colab
- Python version: Python 3.7
- Using GPU in script? Yes
## Who can help
- tokenizers: @LysandreJik
- trainer: @sgugger
## Information
I am using a pre-trained Bert in order to train an abstractive summarization model. The problem... | {
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https://api.github.com/repos/huggingface/transformers/issues/11200 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11200/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11200/comments | https://api.github.com/repos/huggingface/transformers/issues/11200/events | https://github.com/huggingface/transformers/issues/11200 | 855,819,202 | MDU6SXNzdWU4NTU4MTkyMDI= | 11,200 | Issue: Adding new tokens to bert tokenizer in QA | {
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"I am unable to reproduce: the notebook with your added code works smoothly on my side.",
"Thank you @sgugger.\r\nI want ask you sorry, I can't figure out on what's going on my side.\r\nNow I have cloned again the notebook and the example works.\r\nIn the next days I want test it again and I will tell you more ab... | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | **WARNING**: This issue is a replica of this other [issue](https://github.com/huggingface/notebooks/issues/21) open by me, I ask you sorry if I have open it in the wrong place.
Hello Huggingface's team (@sgugger , @joeddav, @LysandreJik)
I have a problem with this code base
notebooks/examples/question_answering... | {
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https://api.github.com/repos/huggingface/transformers/issues/11199 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11199/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11199/comments | https://api.github.com/repos/huggingface/transformers/issues/11199/events | https://github.com/huggingface/transformers/pull/11199 | 855,798,100 | MDExOlB1bGxSZXF1ZXN0NjEzNDc2OTQy | 11,199 | Add examples/bert-loses-patience who can help | {
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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)... | 1,618 | 1,651 | 1,621 | NONE | null | # What does this PR do?
hello
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11198 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11198/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11198/comments | https://api.github.com/repos/huggingface/transformers/issues/11198/events | https://github.com/huggingface/transformers/issues/11198 | 855,786,309 | MDU6SXNzdWU4NTU3ODYzMDk= | 11,198 | trainer.evaluate() expects batch_size to match target batch_size | {
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"You will need to update to the last version of Transformers (I'm seeing 4.0.1 in your report), we fixed this issue so the evaluation loop uses the `compute_loss` function too.",
"> You will need to update to the last version of Transformers (I'm seeing 4.0.1 in your report), we fixed this issue so the evaluation... | 1,618 | 1,618 | 1,618 | NONE | null | @LysandreJik
@sgugger
## 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: 4.0.1
- Platform: Windows/Ubuntu 18.04.3
- Python version: 3.7.6
- PyTorch version... | {
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https://api.github.com/repos/huggingface/transformers/issues/11197 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11197/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11197/comments | https://api.github.com/repos/huggingface/transformers/issues/11197/events | https://github.com/huggingface/transformers/pull/11197 | 855,664,431 | MDExOlB1bGxSZXF1ZXN0NjEzMzYyNTQ2 | 11,197 | [T5] Add 3D attention mask to T5 model (2) (#9643) | {
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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)... | 1,618 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
It allows for 3D attention mask in T5 model (modeling_t5.py) with an accompanying test.
Fixes #9643
This is a clean version for an earlier PR #10903.
This is a solution for allowing the 3D attention mask in the T5 model by making it broadcastable. It is based on what is used in BERT.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11196 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11196/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11196/comments | https://api.github.com/repos/huggingface/transformers/issues/11196/events | https://github.com/huggingface/transformers/pull/11196 | 855,550,778 | MDExOlB1bGxSZXF1ZXN0NjEzMjY0MjM0 | 11,196 | Added translation example script | {
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"Hey @rajvi-k, I believe there is just the styling issue left to fix before we can merge this. Just run `make style` on your branch!"
] | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | This PR adds the translation example script using the Accelerate library.
@sgugger
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https://api.github.com/repos/huggingface/transformers/issues/11195 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11195/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11195/comments | https://api.github.com/repos/huggingface/transformers/issues/11195/events | https://github.com/huggingface/transformers/issues/11195 | 855,510,754 | MDU6SXNzdWU4NTU1MTA3NTQ= | 11,195 | Getting no attribute 'output_attentions' error when upgrading to latest huggingface transformers | {
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"#### Update: \r\nI changed the following line of code from \r\n`outputs = (context_layer, attention_probs) if self.output_attentions else (context_layer,)` to \r\n `outputs = (context_layer,)` \r\nand my code seems to run fine with the latest transformers - https://github.com/gsrivas4/Oscar_latest/blob/latest_tran... | 1,618 | 1,621 | 1,621 | NONE | null | # 📚 Migration
## Information
I am getting `torch.nn.modules.module.ModuleAttributeError: 'CaptionBertSelfAttention' object has no attribute 'output_attentions'` error when upgrading my code from pytorch-transformers to latest version of huggingface transformers.
Model I am using (Bert, XLNet ...): Bert
Lan... | {
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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!"
] | 1,618 | 1,618 | 1,618 | NONE | null | We take pretrained bert model and passing our dataset we save model on .bin file and we take predictions.
But how can we retrain a model with new data set on top of generated bin file
Please help me on this issue | {
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- `transformers` version: 4.5.0
- Platform: Linux-5.4.0-70-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.6
- PyTorch version (GPU?): 1.7.1 (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/11192 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11192/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11192/comments | https://api.github.com/repos/huggingface/transformers/issues/11192/events | https://github.com/huggingface/transformers/issues/11192 | 855,471,665 | MDU6SXNzdWU4NTU0NzE2NjU= | 11,192 | Loading a model saved with `TFGPT2LMHeadModel.save_pretrained` with `GPT2LMHeadModel.from_pretrained(..., from_tf=True)` | {
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"Actually that's not an issue, this warning shouldn't be here. I'll open a PR to remove it shortly.",
"If you try generating text with it, you should get sensible results!",
"Great to hear, thanks."
] | 1,618 | 1,618 | 1,618 | NONE | null | ## Environment info
- `transformers` version: 4.5.0
- Platform: Linux-4.19.0-16-cloud-amd64-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.1+cu102 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
##... | {
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"I get `rate` printed out on my setup! Do you mind sharing your `pip list`?",
"This was mentioned in #4857 and #5359 ....fiixed it after reinstalling. ",
"For me, i didn't have sentencepiece installed. I needed to import torch before transformers to fix this"
] | 1,618 | 1,674 | 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: 4.4.2
- Platform: Linux-5.8.0-48-generic-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/11190 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11190/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11190/comments | https://api.github.com/repos/huggingface/transformers/issues/11190/events | https://github.com/huggingface/transformers/issues/11190 | 855,397,284 | MDU6SXNzdWU4NTUzOTcyODQ= | 11,190 | wav2vec 2.0 doesn't appear to do vector quantization | {
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"Hi, I think VQ only works for Pretraining, it doesn't look like Transformers currently support Pretrain",
"Vector quantization is only required for pretraining which is currently not supported. It should be added soon: https://github.com/huggingface/transformers/issues/10873.",
"Thanks! Just to clarify, was th... | 1,618 | 1,621 | 1,621 | CONTRIBUTOR | null | In the [paper](https://arxiv.org/abs/2006.11477) from FAIR, they describe wav2vec 2.0 as using a vector quantization module to learn discrete vectors of speech units (section 2.) As far as I know, this should be happening between `Wav2Vec2FeatureExtractor` and `Wav2Vec2FeatureProjection`.
The HuggingFace implementat... | {
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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)... | 1,618 | 1,621 | 1,621 | NONE | null | I found two places with minor typo in transformers/docs/source/preprocessing.rst.
First, the example output does not match the input in Base use section. "Hello, I'm a single sentence!" should be mapped to [101, 8667, 117, 146, 112, 182, 170, 1423, 5650, 106, 102] rather than [101, 138, 18696, 155, 1942, 3190, 1144... | {
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https://api.github.com/repos/huggingface/transformers/issues/11188 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11188/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11188/comments | https://api.github.com/repos/huggingface/transformers/issues/11188/events | https://github.com/huggingface/transformers/pull/11188 | 855,305,717 | MDExOlB1bGxSZXF1ZXN0NjEzMDczNTIw | 11,188 | Fix typo | {
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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/11187 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11187/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11187/comments | https://api.github.com/repos/huggingface/transformers/issues/11187/events | https://github.com/huggingface/transformers/issues/11187 | 855,294,496 | MDU6SXNzdWU4NTUyOTQ0OTY= | 11,187 | ELECTRA-large-discriminator results are not stable | {
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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)... | 1,618 | 1,621 | 1,621 | CONTRIBUTOR | null | I'm fine tuning ELECTRA-large-discriminator (https://huggingface.co/google/electra-large-discriminator) for my classification task.
The problem is that the results are not stable. First time I fine tuned it with validation accuracy around 97%. The second try, i got 7x% accuracy. The third is 5x% accuracy.
I just did... | {
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https://api.github.com/repos/huggingface/transformers/issues/11186 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11186/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11186/comments | https://api.github.com/repos/huggingface/transformers/issues/11186/events | https://github.com/huggingface/transformers/issues/11186 | 855,283,989 | MDU6SXNzdWU4NTUyODM5ODk= | 11,186 | strange memory usage for t5 models | {
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"Which model are you using? What's the command you're using to launch the training?",
"Hi\r\nI will close this issue and open up a proper reporting as I see the issue is arising from loading a checkpointin trainer class "
] | 1,618 | 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: 4.4.3
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): yes
- Tensorflow version (GPU?): -... | {
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https://api.github.com/repos/huggingface/transformers/issues/11185 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11185/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11185/comments | https://api.github.com/repos/huggingface/transformers/issues/11185/events | https://github.com/huggingface/transformers/issues/11185 | 855,278,641 | MDU6SXNzdWU4NTUyNzg2NDE= | 11,185 | Loading pretrained mBART model always generate the same output | {
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I trained mBART with pytorch lightning with the model MBartForConditionalGeneration.from_pretrained('facebook/mbart-large-cc25') to do summaries. As output I got a checkpoint.ckpt. Moreover, I used model.model.save_pretrained to have a config.json and pytorch_model.bin.
During the training and testing, I saw ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11184 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11184/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11184/comments | https://api.github.com/repos/huggingface/transformers/issues/11184/events | https://github.com/huggingface/transformers/issues/11184 | 855,196,324 | MDU6SXNzdWU4NTUxOTYzMjQ= | 11,184 | Can not instantiate BertGenerationEncoder or BertGenerationDecoder from bert model | {
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"I met the same issues.",
"This was fixed by #11207 and was released in patch 4.5.1. Please install the latest version and let us know if it works for you!",
"It works in patch 4.5.1, thanks.\r\nI still wonder what is the difference between the following two methods to instantiate the BERT encoder-decoder model... | 1,618 | 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: 4.5.0
- Platform: Ubuntu 18.04.5 LTS
- Python version: 3.6.9
- PyTorch version (GPU?): 1.8.1 (Quadro GV100 ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11183 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11183/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11183/comments | https://api.github.com/repos/huggingface/transformers/issues/11183/events | https://github.com/huggingface/transformers/pull/11183 | 855,179,803 | MDExOlB1bGxSZXF1ZXN0NjEyOTgwNjY0 | 11,183 | Replaced `which` with `who` | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/11182 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11182/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11182/comments | https://api.github.com/repos/huggingface/transformers/issues/11182/events | https://github.com/huggingface/transformers/pull/11182 | 855,179,468 | MDExOlB1bGxSZXF1ZXN0NjEyOTgwNDE1 | 11,182 | Minor typos fixed | {
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Fixes minor typos.
## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11181 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11181/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11181/comments | https://api.github.com/repos/huggingface/transformers/issues/11181/events | https://github.com/huggingface/transformers/issues/11181 | 855,086,262 | MDU6SXNzdWU4NTUwODYyNjI= | 11,181 | How to kill bad starts when pre-training from scratch | {
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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)... | 1,618 | 1,621 | 1,621 | NONE | null | ### Environment info
transformers version: 4.4.3
Platform: linux
Python version: 3.8.5
PyTorch version (GPU?): -
Tensorflow version (GPU?): 2.4.1
Using GPU in script?: yes
Using distributed or parallel set-up in script?: parallel
### Information
Hi!
I am pre-training a RoBERTa model from scratch and was won... | {
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https://api.github.com/repos/huggingface/transformers/issues/11180 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11180/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11180/comments | https://api.github.com/repos/huggingface/transformers/issues/11180/events | https://github.com/huggingface/transformers/issues/11180 | 855,083,234 | MDU6SXNzdWU4NTUwODMyMzQ= | 11,180 | Sequential constraints? | {
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"Has anyone working on this yet?",
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This is more advanced than the single-token const... | {
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https://api.github.com/repos/huggingface/transformers/issues/11179 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11179/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11179/comments | https://api.github.com/repos/huggingface/transformers/issues/11179/events | https://github.com/huggingface/transformers/issues/11179 | 855,059,723 | MDU6SXNzdWU4NTUwNTk3MjM= | 11,179 | Why couldn't I use encoder_hidden_states when position_ids is not None? GPT2Model.foward() | {
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"Ah, I think this is an issue indeed, the device statement shouldn't be inside that `if` statement. Do you want to open a PR to fix this?",
"Sure. ",
"Fixed by #11292 "
] | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | `device` is required in GPT2Model.foward() if I'd like to use encoder_hidden_states.
```
if self.config.add_cross_attention and encoder_hidden_states is not None:
encoder_batch_size, encoder_sequence_length, _ = encoder_hidden_states.size()
encoder_hidden_shape = (encoder_batch... | {
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https://api.github.com/repos/huggingface/transformers/issues/11178 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11178/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11178/comments | https://api.github.com/repos/huggingface/transformers/issues/11178/events | https://github.com/huggingface/transformers/pull/11178 | 855,052,710 | MDExOlB1bGxSZXF1ZXN0NjEyODg3NjUz | 11,178 | Use MSELoss with single class label in (M)BartForSequenceClassification | {
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Similar to `BertForSequenceClassification`, `(M)BartForSequenceClassification` now uses a regression loss in case `num_labels` equals 1 (as already documented for both model classes). E.g. required when running the GLUE script for STS-B with these model classes.
## Before submitting
- [x]... | {
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https://api.github.com/repos/huggingface/transformers/issues/11177 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11177/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11177/comments | https://api.github.com/repos/huggingface/transformers/issues/11177/events | https://github.com/huggingface/transformers/issues/11177 | 854,999,874 | MDU6SXNzdWU4NTQ5OTk4NzQ= | 11,177 | TypeError: expected str, bytes or os.PathLike object, not NoneType | {
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"from transformers import LongformerModel, LongformerTokenizer, RobertaTokenizer, AutoTokenizer\r\n \r\npretrain_model_path = 'schen/longformer-chinese-base-4096'\r\ntokenizer = LongformerTokenizer.from_pretrained(pretrain_model_path)\r\n",
"This issue has been automatically marked as stale because it has not had... | 1,618 | 1,621 | 1,621 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/11176 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11176/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11176/comments | https://api.github.com/repos/huggingface/transformers/issues/11176/events | https://github.com/huggingface/transformers/pull/11176 | 854,992,965 | MDExOlB1bGxSZXF1ZXN0NjEyODQzODM2 | 11,176 | bug fix | {
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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)... | 1,618 | 1,621 | 1,621 | NONE | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11175 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11175/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11175/comments | https://api.github.com/repos/huggingface/transformers/issues/11175/events | https://github.com/huggingface/transformers/issues/11175 | 854,977,638 | MDU6SXNzdWU4NTQ5Nzc2Mzg= | 11,175 | MemoryError: when we run_language_model.py to train an English Adapter | {
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"You could try the another one [run_language_modeling.py](https://github.com/Adapter-Hub/adapter-transformers/blob/master/examples/contrib/legacy/run_language_modeling.py) with `line-by-line` and add a `batch_size` along with `batched=True` to eliminate the memory error:\r\n\r\n```\r\n tokenized_datasets = ... | 1,618 | 1,621 | 1,621 | NONE | null | run run_language_model.py
https://github.com/Adapter-Hub/adapter-transformers/blob/master/examples/contrib/legacy/run_language_modeling.py
in such codes:
python3 run_language_modeling.py \
--output_dir=/mnt/localdata/cao/output_language_adapter_en/ \
--model_type=bert \
--model_name_or_path=bert-base-multilingu... | {
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https://api.github.com/repos/huggingface/transformers/issues/11174 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11174/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11174/comments | https://api.github.com/repos/huggingface/transformers/issues/11174/events | https://github.com/huggingface/transformers/issues/11174 | 854,962,915 | MDU6SXNzdWU4NTQ5NjI5MTU= | 11,174 | Using BART for Mask Infilling makes all the first tokens missing | {
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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)... | 1,618 | 1,620 | 1,620 | CONTRIBUTOR | null | I'm fine-tuning BART ```"facebook/bart-large"``` model for mask infilling. My dataset looks like below.
The original sentence BART should predict is `taste the rainbow.`, and the input data it gets is `<mask> taste <mask> rainbow <mask>`, or it should predict `global asset management`, given `<mask> global <mask> as... | {
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https://api.github.com/repos/huggingface/transformers/issues/11173 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11173/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11173/comments | https://api.github.com/repos/huggingface/transformers/issues/11173/events | https://github.com/huggingface/transformers/issues/11173 | 854,917,009 | MDU6SXNzdWU4NTQ5MTcwMDk= | 11,173 | Encoder-Decoder Models Can't Generate using Apex | {
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"I was able to get a fix working for ProphetNetForConditionalGeneration",
"Hi @ManavR123 \r\n\r\n> I figured out the main cause of the error: apex converts BaseModelOutput objects into dictionaries, but a lot of the code functionality relies on receiving the former. I don't know if there is a way to avoid this.\r... | 1,618 | 1,621 | 1,621 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Linux-5.4.0-1041-aws-x86_64-with-debian-buster-sid
- Python version: 3.7.10
- PyTorch vers... | {
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https://api.github.com/repos/huggingface/transformers/issues/11172 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11172/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11172/comments | https://api.github.com/repos/huggingface/transformers/issues/11172/events | https://github.com/huggingface/transformers/pull/11172 | 854,844,748 | MDExOlB1bGxSZXF1ZXN0NjEyNzIxMzk4 | 11,172 | Run CI on deepspeed and fairscale | {
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https://api.github.com/repos/huggingface/transformers/issues/11171 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11171/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11171/comments | https://api.github.com/repos/huggingface/transformers/issues/11171/events | https://github.com/huggingface/transformers/issues/11171 | 854,803,689 | MDU6SXNzdWU4NTQ4MDM2ODk= | 11,171 | Error in running run_tf_text_classification.py | {
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"@Rocketknight1 can you help in this",
"@sgugger can you help in this",
"Hi, we have a new, simpler and more robust text classification in TensorFlow script contributed by @Rocketknight1 [here](https://github.com/huggingface/transformers/blob/master/examples/tensorflow/text-classification/run_text_classificatio... | 1,617 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Windows-10-10.0.18362-SP0
- Python version: 3.8.0
- PyTorch version (GPU?): 1.7.1+cpu (Fal... | {
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https://api.github.com/repos/huggingface/transformers/issues/11170 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11170/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11170/comments | https://api.github.com/repos/huggingface/transformers/issues/11170/events | https://github.com/huggingface/transformers/pull/11170 | 854,751,364 | MDExOlB1bGxSZXF1ZXN0NjEyNjQ1MDM1 | 11,170 | [examples/translation] support mBART-50 and M2M100 fine-tuning | {
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"@patil-suraj , can you please help in suggesting how to finetune m2m100 on more than one-pair.I am able to finetune for one lang pair using below script:\r\n\r\nCUDA_VISIBLE_DEVICES=0,1,2,3,6 python -m torch.distributed.run --nproc_per_node=5 run_translation.py --model_name_or_path=m2m100_418M_new_token --do_train... | 1,617 | 1,640 | 1,617 | MEMBER | null | # What does this PR do?
the `run_translation.py` does not support fine-tuning mBART-50 and M2M100 as we need to set `src_lang` and `tgt_lang` attributes, but the script only checks for `MBartTokenizer`, this PR
- adds the `MULTILINGUAL_TOKENIZERS` list where we can add all tokenizers which require setting `src_la... | {
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https://api.github.com/repos/huggingface/transformers/issues/11169 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11169/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11169/comments | https://api.github.com/repos/huggingface/transformers/issues/11169/events | https://github.com/huggingface/transformers/issues/11169 | 854,726,738 | MDU6SXNzdWU4NTQ3MjY3Mzg= | 11,169 | Unable to resume checkpoints with TFBertModel using tf.distribute.Strategy and a custom LM head that shares the underlying TFBertEmbeddings layer | {
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"I have tested it locally under tf.distribute.OneDeviceStrategy and the problem seems to be the same.\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"/home/marhlder/unsilo/unsilo-ml/unsilo_ml/python/run.py\", line 73, in <module>\r\n cli()\r\n File \"/home/marhlder/anaconda3/envs/unsilo-ml/lib/pyth... | 1,617 | 1,621 | 1,621 | NONE | null | ## Environment info
- `transformers` version: 4.5.0
- Platform: Linux (Ubuntu 18.04, 20.04 + CentOs)
- Python version: 3.7.4
- PyTorch version (GPU?): N/A
- Tensorflow version (GPU?): 2.4.1 GPU
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: Yes, using MirroredStrategy
Models:... | {
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https://api.github.com/repos/huggingface/transformers/issues/11168 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11168/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11168/comments | https://api.github.com/repos/huggingface/transformers/issues/11168/events | https://github.com/huggingface/transformers/pull/11168 | 854,692,881 | MDExOlB1bGxSZXF1ZXN0NjEyNTk2OTA4 | 11,168 | [examples run_clm] fix _LazyModule hasher error | {
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`datasets.fingerprint.Hasher` fails to run
```
hasher = Hasher()
hasher.update(tokenize_function)
```
getting:
```
TypeError: cannot pickl... | {
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https://api.github.com/repos/huggingface/transformers/issues/11167 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11167/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11167/comments | https://api.github.com/repos/huggingface/transformers/issues/11167/events | https://github.com/huggingface/transformers/pull/11167 | 854,691,880 | MDExOlB1bGxSZXF1ZXN0NjEyNTk2MTQ0 | 11,167 | added json dump and extraction of train run time | {
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This PR adjusts to the latest metric exposing changes that `train_runtime` is now logged as `hh:mm:ss.ms`. So instead of extracting the `train_runtime` from the logs it is using the `sagemaker-sdk` to get the full train time. Additionally, I added a JSON dump for all tests to share the result... | {
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https://api.github.com/repos/huggingface/transformers/issues/11166 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11166/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11166/comments | https://api.github.com/repos/huggingface/transformers/issues/11166/events | https://github.com/huggingface/transformers/issues/11166 | 854,655,625 | MDU6SXNzdWU4NTQ2NTU2MjU= | 11,166 | [run_clm] tokenize_function clarification makes it non-hashable => no-reusing cache | {
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"Thank you for the report, @VictorSanh!\r\n\r\nI can reproduce the problem separately:\r\n\r\n```\r\n import transformers\r\n from transformers import AutoTokenizer\r\n from transformers.testing_utils import CaptureLogger\r\n tokenizer = AutoTokenizer.from_pretrained(\"t5-small\")\r\n def tokenize_fu... | 1,617 | 1,625 | 1,617 | MEMBER | 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 at commit acc851e1ff92835d2a3ee9774d9d0abfda6e3f36 (from yesterday)
- Platform:
- Python version:
- P... | {
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https://api.github.com/repos/huggingface/transformers/issues/11165 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11165/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11165/comments | https://api.github.com/repos/huggingface/transformers/issues/11165/events | https://github.com/huggingface/transformers/issues/11165 | 854,587,231 | MDU6SXNzdWU4NTQ1ODcyMzE= | 11,165 | tokenizer.encode_plus returns torch.tensors loaded on the desired device | {
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"Hi! You can cast the `BatchEncoding` output by `encode_plus` to your device:\r\n```py\r\nmodel_input = tokenizer.encode_plus(xxx, return_tensors=\"pt\")\r\nmodel_input.to(\"cuda\")\r\n```",
"niiice, thank you!!\r\n"
] | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | # 🚀 Feature request
add device attribute to tokenizer.encode_plus so when it returns a torch.tensors it loads it on the desired device
## Motivation
- to pass the output of tokenizer to the model, one only can unpack the returned output using ** without bothering about the content of tokenizer, that only true... | {
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https://api.github.com/repos/huggingface/transformers/issues/11164 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11164/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11164/comments | https://api.github.com/repos/huggingface/transformers/issues/11164/events | https://github.com/huggingface/transformers/issues/11164 | 854,558,146 | MDU6SXNzdWU4NTQ1NTgxNDY= | 11,164 | error while training wave2vec on arabic text | {
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"Hello, Can you provide more information about the dataset you are using. The error message alone seems very vague, but pointing towards input.",
"Its my custom dataset. Arabic audio and arabic transcription",
"This issue has been automatically marked as stale because it has not had recent activity. If you thin... | 1,617 | 1,621 | 1,621 | NONE | null | Traceback (most recent call last):
File "/content/transformers/examples/research_projects/wav2vec2/run_asr.py", line 480, in <module>
main()
File "/content/transformers/examples/research_projects/wav2vec2/run_asr.py", line 430, in main
num_proc=2,
File "/usr/local/lib/python3.7/dist-packages/datasets... | {
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https://api.github.com/repos/huggingface/transformers/issues/11163 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11163/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11163/comments | https://api.github.com/repos/huggingface/transformers/issues/11163/events | https://github.com/huggingface/transformers/pull/11163 | 854,554,209 | MDExOlB1bGxSZXF1ZXN0NjEyNDgxODM1 | 11,163 | Make `get_special_tokens_mask` consider all tokens | {
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"Thanks a lot for your super-fast feedback! Your projects are big inspiration to me. Thank you."
] | 1,617 | 1,617 | 1,617 | COLLABORATOR | null | # What does this PR do?
As discovered via #11155, some tokenizers do not return the proper special tokens mask in the `get_special_tokens_mask` when `already_has_special_tokens=True` because they only check for the CLS and SEP tokens. This PR fixes that by delegating to the superclass the call when `already_has_spec... | {
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https://api.github.com/repos/huggingface/transformers/issues/11162 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11162/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11162/comments | https://api.github.com/repos/huggingface/transformers/issues/11162/events | https://github.com/huggingface/transformers/issues/11162 | 854,547,322 | MDU6SXNzdWU4NTQ1NDczMjI= | 11,162 | ZeroDivisionError: float division by zero after some epochs while training using run_mmimdb.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)... | 1,617 | 1,621 | 1,621 | NONE | null | I am trying to train image+test model using the run_mmiddb.py(https://github.com/huggingface/transformers/tree/master/examples/research_projects/mm-imdb). I have two classes in this task.
Initially i ran it for 1 epoch with below input parameters and it went well::
--model_name_or_path bert-base-cased \
--max_seq_le... | {
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https://api.github.com/repos/huggingface/transformers/issues/11161 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11161/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11161/comments | https://api.github.com/repos/huggingface/transformers/issues/11161/events | https://github.com/huggingface/transformers/pull/11161 | 854,473,857 | MDExOlB1bGxSZXF1ZXN0NjEyNDEzNjI0 | 11,161 | Correct typographical error in README.md | {
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# 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 aweso... | {
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https://api.github.com/repos/huggingface/transformers/issues/11160 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11160/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11160/comments | https://api.github.com/repos/huggingface/transformers/issues/11160/events | https://github.com/huggingface/transformers/issues/11160 | 854,385,822 | MDU6SXNzdWU4NTQzODU4MjI= | 11,160 | Why optimizer need split parameter group? | {
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"Difficult to tell what happens when you apply weight_decay to those layers as well. I think you should just give it a try and tells us what has happened. \r\nThe shown code that applies different weight_decay to different parameters is in line with the original bert implementation ([link](https://github.com/google... | 1,617 | 1,621 | 1,621 | NONE | null | I want to ask some question about follow codes:
```
no_decay = ['bias', 'LayerNorm.weight']
optimizer_grouped_parameters = [
{'params': [p for n, p in model.named_parameters() if not any(nd in n for nd in no_decay)], 'weight_decay': 0.01},
{'params': [p for n, p in model.named_parameters() if any(nd in n f... | {
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https://api.github.com/repos/huggingface/transformers/issues/11159 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11159/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11159/comments | https://api.github.com/repos/huggingface/transformers/issues/11159/events | https://github.com/huggingface/transformers/issues/11159 | 854,384,384 | MDU6SXNzdWU4NTQzODQzODQ= | 11,159 | LM finetuning on domain specific unlabelled data | {
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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!"
] | 1,617 | 1,617 | 1,617 | NONE | null | Hello Team,
Thanks a lot for the awesome work!
Can you please tell me how to finetune a(any) MLM model on domain specific corpus ? I am following this [link](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/language_modeling.ipynb) obtained from the huggingface documentation. Is th... | {
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https://api.github.com/repos/huggingface/transformers/issues/11158 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11158/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11158/comments | https://api.github.com/repos/huggingface/transformers/issues/11158/events | https://github.com/huggingface/transformers/issues/11158 | 854,284,028 | MDU6SXNzdWU4NTQyODQwMjg= | 11,158 | Why padding tokens can be masked in albert model? Is it bug or right? | {
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"Related to #11163 by @sgugger ",
"This is solved by #11163 "
] | 1,617 | 1,617 | 1,617 | NONE | null | I tried to run run_mlm.py for bert model and albert model.
"pad" token is not masked when I run bert-base-uncased model , but "pad" token can be masked when I run albert-base-v2
[bert command]
```
% python run_mlm.py --model_name_or_path bert-base-uncased --dataset_name wikitext --dataset_config_name wikitext-2-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11157 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11157/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11157/comments | https://api.github.com/repos/huggingface/transformers/issues/11157/events | https://github.com/huggingface/transformers/pull/11157 | 854,213,614 | MDExOlB1bGxSZXF1ZXN0NjEyMTkyMzQz | 11,157 | model_path should be ignored as the checkpoint path | {
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"No this will then make it impossible to resume from a checkpoint if you pass `--output_dir path_to_specific_checkpoint`. This should only be ignored if the checkpoints are the wrong number of labels like [here](https://github.com/huggingface/transformers/blob/45fc8c7951f978c0f8f13c8bab52c744cd5c4784/examples/text-... | 1,617 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
When the directory which holds the transformer model is given the command line argument, the script `run_xnli.py` arises the following error. This PR fixes this problem.
```sh
$ python3 run_xnli.py \
--model_name_or_path ./NICT_BERT-base_JapaneseWikipedia_32K_BPE \
--do_train \
... | {
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"This can all be done in one `Dataset` that randomly picks elements from subdatasets, so there is no need to add anything to the `Trainer` to support this.",
"Hi! Sorry to bother you again. I could not find any example code, that's why I opened the issue.\r\nLater after your comment, I search through the [repo](h... | 1,617 | 1,618 | 1,618 | NONE | null | # 🚀 Feature request
The current Huggingface Trainer Supports, a single `train_dataset` (torch.utils.data.dataset.Dataset). While it makes sense for most of the training setups, there are still some cases where it is convenient to have a list of `train_dataset`. The trainer can randomly select or follow a specific s... | {
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https://api.github.com/repos/huggingface/transformers/issues/11155 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11155/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11155/comments | https://api.github.com/repos/huggingface/transformers/issues/11155/events | https://github.com/huggingface/transformers/issues/11155 | 854,117,684 | MDU6SXNzdWU4NTQxMTc2ODQ= | 11,155 | [BUG] padding tokens are also masked in DataCollatorForLanguageModeling | {
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"I have similar issues.\r\n\r\n\"pad\" token is not masked when I run bert-base-uncased model , but \"pad\" token can be masked when I run albert-base-v2\r\n\r\nIn examples/language-modeliing/run_mlm.py, I try to call tokenizer.get_special_tokens_mask.\r\n```\r\nprint(tokenizer.get_special_tokens_mask([0, 100, 101,... | 1,617 | 1,617 | 1,617 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.2
- Platform: Linux
- Python version: 3.6
- PyTorch version (GPU?): 1.7.1 GPU
- Tensorflow version (GPU... | {
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https://api.github.com/repos/huggingface/transformers/issues/11154 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11154/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11154/comments | https://api.github.com/repos/huggingface/transformers/issues/11154/events | https://github.com/huggingface/transformers/issues/11154 | 854,116,038 | MDU6SXNzdWU4NTQxMTYwMzg= | 11,154 | Using run_language_modeling.py to train an English adapter | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,621 | 1,621 | NONE | null | # 📚 Migration
## Information
<!-- Important information -->
Model I am using bert-base-multilingual-cased:
Language I am using the model on English:
The problem arises when using:
When I entered the codes in the command line and run, the process just stuck here for a long time and did nothing, I trie... | {
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https://api.github.com/repos/huggingface/transformers/issues/11153 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11153/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11153/comments | https://api.github.com/repos/huggingface/transformers/issues/11153/events | https://github.com/huggingface/transformers/issues/11153 | 854,107,997 | MDU6SXNzdWU4NTQxMDc5OTc= | 11,153 | cannot import name 'BigBirdModel' from 'transformers' | {
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"Hello! Please respect the issue template so that we can help you. Big Bird is only available in the latest transformers version, do you have this version in your setup?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed pleas... | 1,617 | 1,621 | 1,621 | NONE | null | when I write the “from transformers import BigBirdModel”， the error is “cannot import name 'BigBirdConfig' from 'transformers'”,how to solve the problem? thank you. | {
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https://api.github.com/repos/huggingface/transformers/issues/11152 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11152/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11152/comments | https://api.github.com/repos/huggingface/transformers/issues/11152/events | https://github.com/huggingface/transformers/pull/11152 | 854,093,859 | MDExOlB1bGxSZXF1ZXN0NjEyMDk0NTMw | 11,152 | typo | {
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https://api.github.com/repos/huggingface/transformers/issues/11151 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11151/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11151/comments | https://api.github.com/repos/huggingface/transformers/issues/11151/events | https://github.com/huggingface/transformers/pull/11151 | 853,954,770 | MDExOlB1bGxSZXF1ZXN0NjExOTc2MTk0 | 11,151 | [setup] make fairscale and deepspeed setup extras | {
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```
pip install transformers[deepspeed]
pip install transformers[fairscale]
```
so moving the version minimums into `setup.py`, and also had to add a helper function `dep_version_check`
@LysandreJik, @sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/11150 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11150/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11150/comments | https://api.github.com/repos/huggingface/transformers/issues/11150/events | https://github.com/huggingface/transformers/pull/11150 | 853,820,541 | MDExOlB1bGxSZXF1ZXN0NjExODUzNTUw | 11,150 | Add support for multiple models for one config in auto classes | {
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This PR adds support for having multiple models with the same config be in the same auto class. For instance `FunnelBaseModel` and `FunnelModel` are both valid models for the class `AutoModel` but since they both rely on `FunnelConfig`, only `FunnelModel` was in the model mapping for `AutoMod... | {
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https://api.github.com/repos/huggingface/transformers/issues/11149 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11149/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11149/comments | https://api.github.com/repos/huggingface/transformers/issues/11149/events | https://github.com/huggingface/transformers/pull/11149 | 853,786,971 | MDExOlB1bGxSZXF1ZXN0NjExODIzMTc2 | 11,149 | Enable option for subword regularization in `XLMRobertaTokenizer` | {
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"It would be awesome if you ( @LysandreJik and @stefan-it ) could give some feedback on this - although some tests still fail.\r\nIs it a good idea? Would you merge it if everything is cleaned up?",
"I added a test, everything is green and IMO ready for review. @LysandreJik @stefan-it",
"@LysandreJik and @n1t0 ... | 1,617 | 1,619 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
I would like to use [subword regularization](https://github.com/google/sentencepiece#subword-regularization-and-bpe-dropout) from [google/sentencepiece](https://github.com/google/sentencepiece). The reason is that it might be used to improve downstream task performance.
Since `XLMRobertaToke... | {
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@sgugger, @LysandreJik | {
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"@sgugger, @LysandreJik - so after this move we have a problem of dependencies now - the extended integration tests need be able to check score metrics, but the main tests don't have `sacrebleu` and other dependencies installed. How do we resolve this conundrum?\r\n\r\nLysandre replied on slack to add them to `extr... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | This PR
* moves `deepspeed`/`fairscale`/extended trainer tests from `examples` to `tests`
* updates docs to point to the new sample config files
* adds a new `testing_utils.py`'s context manager `ExtendSysPath` that allows temporary `sys.path` changing to import something locally in the tests and uses it (otherwi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11145 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11145/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11145/comments | https://api.github.com/repos/huggingface/transformers/issues/11145/events | https://github.com/huggingface/transformers/pull/11145 | 853,621,711 | MDExOlB1bGxSZXF1ZXN0NjExNjgxODcy | 11,145 | [run_clm] clarify why we get the tokenizer warning on long input | {
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https://api.github.com/repos/huggingface/transformers/issues/11144 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11144/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11144/comments | https://api.github.com/repos/huggingface/transformers/issues/11144/events | https://github.com/huggingface/transformers/pull/11144 | 853,615,136 | MDExOlB1bGxSZXF1ZXN0NjExNjc2MTk4 | 11,144 | [trainer] solve "scheduler before optimizer step" warning | {
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"I'm a bit torn about this solution: it solves the problem exposed by the warning but it creates another problem with no warning, which I had flagged in #11106 as \r\n\r\n> If we somehow manage to catch those skipped optimizer steps and delay the scheduler steps, then we won't respect the number of steps in the sch... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | As discussed in https://github.com/huggingface/transformers/issues/11106 fp16 scaler leads to a warning:
> torch/optim/lr_scheduler.py:132: UserWarning: Detected call of lr_scheduler.step() before optimizer.step(). In PyTorch 1.1.0 and later, you should call them in the opposite order: optimizer.step() before lr_sch... | {
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https://api.github.com/repos/huggingface/transformers/issues/11143 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11143/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11143/comments | https://api.github.com/repos/huggingface/transformers/issues/11143/events | https://github.com/huggingface/transformers/issues/11143 | 853,589,178 | MDU6SXNzdWU4NTM1ODkxNzg= | 11,143 | Training loss is not logged correctly when doing evaluation with Trainer | {
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"I am not able to reproduce, on my side I do see logs every logging_steps for the training loss and learning rate, and every eval_steps for the validation loss and metrics, both in the console and TensorBoard. Could you try again with a source install?",
"After I restarted TensorBoard, training loss showed up cor... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Linux-5.4.0-62-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11142 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11142/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11142/comments | https://api.github.com/repos/huggingface/transformers/issues/11142/events | https://github.com/huggingface/transformers/pull/11142 | 853,570,587 | MDExOlB1bGxSZXF1ZXN0NjExNjM4NTcz | 11,142 | [Community notebooks] Add Wav2Vec notebook for creating captions for YT Clips | {
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"Very nice! @patil-suraj do you want to give this a look and merge if it looks good to you too?",
"Very cool! LGTM, thanks a lot for adding this!"
] | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/11141 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11141/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11141/comments | https://api.github.com/repos/huggingface/transformers/issues/11141/events | https://github.com/huggingface/transformers/pull/11141 | 853,482,731 | MDExOlB1bGxSZXF1ZXN0NjExNTY1MzYz | 11,141 | Don't duplicate logs in TensorBoard and handle --use_env | {
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This PR fixes a few bugs in the `Trainer` and `TrainingArguments`. First it cleans up the `TensorBoardCallback` to make sure the logs are not duplicated (I think they were not for some convoluted logic with the `tb_writer` never set but now I'm sure).
The second part is more important and ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11140 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11140/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11140/comments | https://api.github.com/repos/huggingface/transformers/issues/11140/events | https://github.com/huggingface/transformers/pull/11140 | 853,423,861 | MDExOlB1bGxSZXF1ZXN0NjExNTE2MTQ5 | 11,140 | Updates SageMaker docs for updating DLCs | {
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Adds a Link to an example PR for what content someone needs to put into the PR comment. | {
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https://api.github.com/repos/huggingface/transformers/issues/11139 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11139/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11139/comments | https://api.github.com/repos/huggingface/transformers/issues/11139/events | https://github.com/huggingface/transformers/issues/11139 | 853,283,208 | MDU6SXNzdWU4NTMyODMyMDg= | 11,139 | OOM issue with prediction | {
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"Hi @XinnuoXu \r\n\r\nyou should pass the `--predict_with_generate` arg for summarization evaluation, this will use the `generate` method to generate the summaries. \r\n\r\nI think one possible reason for this issue is that when `predict_with_generate` is not passed the final hidden_states from the model are used a... | 1,617 | 1,621 | 1,621 | NONE | null | Hi! I fine-tuned the bart model on XSum (both training and validation are fine). However, the OOM appeared during the prediction using the same machine. @patrickvonplaten @patil-suraj Here is my code:
```
python3 run_summarization.py \
--output_dir ./tmp/xsum-test/ \
--overwrite_output_dir \
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11138 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11138/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11138/comments | https://api.github.com/repos/huggingface/transformers/issues/11138/events | https://github.com/huggingface/transformers/pull/11138 | 853,279,488 | MDExOlB1bGxSZXF1ZXN0NjExMzkzNjIy | 11,138 | Fix typing error in Trainer class (prediction_step) | {
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https://api.github.com/repos/huggingface/transformers/issues/11137 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11137/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11137/comments | https://api.github.com/repos/huggingface/transformers/issues/11137/events | https://github.com/huggingface/transformers/issues/11137 | 853,234,383 | MDU6SXNzdWU4NTMyMzQzODM= | 11,137 | Inference time got very high, very low CUDA activity | {
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"I'm having a similar issue as well but occurring at both test and training time - <3% GPU utilization. When executing the `run_qa.py` script using the command line arguments in the first example of the question answering example, it takes much longer than when I was running `transformers` v4.3.3.\r\n\r\nHowever, t... | 1,617 | 1,624 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0.dev0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.1 (Tr... | {
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https://api.github.com/repos/huggingface/transformers/issues/11136 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11136/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11136/comments | https://api.github.com/repos/huggingface/transformers/issues/11136/events | https://github.com/huggingface/transformers/issues/11136 | 853,212,671 | MDU6SXNzdWU4NTMyMTI2NzE= | 11,136 | Trainer callbacks such as on_epoch_end do not pass in the documented eval dataloader | {
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"It seems like the solution would be to just add\r\n```\r\nself.callback_handler.eval_dataloader = eval_dataloader\r\n```\r\nbelow line 1051 in trainer.py and then fix the documentation. \r\n\r\nI see the eval_dataloader can be attached in the prediction_loop function but that doesn't seem to take effect when my ca... | 1,617 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: ubuntu 20
- Python version: 3.8.5
- PyTorch version (GPU?): Happens on GPU and no GPU
- T... | {
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