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https://api.github.com/repos/huggingface/transformers/issues/4920 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4920/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4920/comments | https://api.github.com/repos/huggingface/transformers/issues/4920/events | https://github.com/huggingface/transformers/pull/4920 | 636,521,373 | MDExOlB1bGxSZXF1ZXN0NDMyNjc4NDM0 | 4,920 | Support multiple choice in tf common model tests | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4920?src=pr&el=h1) Report\n> Merging [#4920](https://codecov.io/gh/huggingface/transformers/pull/4920?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5d63ca6c38cc0f583cdec4c3efcfce13c0a41fdc&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | This the same as #4886, but for tensorflow (first time ever of me coding in tf!) | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,591 | 1,597 | 1,597 | NONE | null | Hi,
In the configuration where the internet is not available the system searches the cache directory. However url_to_filename(url, etag) returns filename with extension in Windows. Thus this line is not able to find the file locations. One remedy could be using filename.split('.')[0] instead of filename
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https://api.github.com/repos/huggingface/transformers/issues/4918 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4918/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4918/comments | https://api.github.com/repos/huggingface/transformers/issues/4918/events | https://github.com/huggingface/transformers/issues/4918 | 636,516,876 | MDU6SXNzdWU2MzY1MTY4NzY= | 4,918 | Pegasus for summarization ! | {
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"Thanks! The model checkpoints are available actually. [Check here](https://github.com/google-research/pegasus#install-library-and-dependencies) :)",
"Hope to provide a pytorch version code ",
"I might try the Huggingface's weight transfer code from tensorflow to pytorch in July if nobody's working on this post... | 1,591 | 1,604 | 1,604 | NONE | null | # 🌟 New model addition
## Model description
https://ai.googleblog.com/2020/06/pegasus-state-of-art-model-for.html?m=1
https://arxiv.org/abs/1912.08777
Abstract
Recent work pre-training Transformers with self-supervised objectives on large text corpora has shown great success when fine-tuned on downstream... | {
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https://api.github.com/repos/huggingface/transformers/issues/4917 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4917/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4917/comments | https://api.github.com/repos/huggingface/transformers/issues/4917/events | https://github.com/huggingface/transformers/pull/4917 | 636,506,387 | MDExOlB1bGxSZXF1ZXN0NDMyNjY2MTMy | 4,917 | enable invocation of run_ner.py and utils_ner.py in cython | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4917?src=pr&el=h1) Report\n> Merging [#4917](https://codecov.io/gh/huggingface/transformers/pull/4917?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef2dcdccaa9a115aca44d81f31c6dc4d32bebb3f&el=desc) will **increase... | 1,591 | 1,597 | 1,597 | CONTRIBUTOR | null | Due to extant issue https://github.com/cython/cython/issues/2903, `run_ner.py` and `utils_ner.py` (among others, I imagine) cannot be invoked inside Cython. By manually adding in annotations, these changes work around the missing features in Cython 3.7 re: PEP557.
https://github.com/cython/cython/pull/3400 ought to ev... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4916?src=pr&el=h1) Report\n> Merging [#4916](https://codecov.io/gh/huggingface/transformers/pull/4916?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef2dcdccaa9a115aca44d81f31c6dc4d32bebb3f&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | MEMBER | null | closes #4893
The TPU device was initialized twice when using a the `xla_spawn.py` script. Removing this initialization solves the issue.
@patrickvonplaten, is this necessary for the benchmarking script? | {
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https://api.github.com/repos/huggingface/transformers/issues/4915 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4915/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4915/comments | https://api.github.com/repos/huggingface/transformers/issues/4915/events | https://github.com/huggingface/transformers/issues/4915 | 636,488,193 | MDU6SXNzdWU2MzY0ODgxOTM= | 4,915 | [generate] Increasing length_penalty makes generations longer | {
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"Yes, I remember being confused about the name earlier as well...I would be in favor of keeping the code and renaming the variable, but I can't think of a good variable name (not a huge fan of `len_adjustment`, but can't really think of a better name - maybe `length_reward`?) ",
"Sorry just catching up :) \r\n\r\... | 1,591 | 1,598 | 1,598 | CONTRIBUTOR | null | In `generate`, we document
```python
length_penalty: Exponential penalty to the length. Default to 1.
```
Given the name and the docstring, you might expect that if you increase the `length_penalty` your model will, on average, produce shorter generations.
You would be wrong! (at least for `bart-large-xsum`)
... | {
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https://api.github.com/repos/huggingface/transformers/issues/4914 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4914/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4914/comments | https://api.github.com/repos/huggingface/transformers/issues/4914/events | https://github.com/huggingface/transformers/issues/4914 | 636,467,273 | MDU6SXNzdWU2MzY0NjcyNzM= | 4,914 | Simple way to convert a Python tokenizer to a fast tokenizer | {
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"requires unigram algo implemented on tokenizers\r\nhttps://github.com/huggingface/tokenizers/pull/292",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"PR merged, closing the issue... | 1,591 | 1,654 | 1,601 | CONTRIBUTOR | null | # 🚀 Feature request
Tokenizer are provided with each model, some have a fast version of their tokenizer (Rust based), others like CamemBERT have only the slow version.
## Motivation
Fast tokenizer improves inference times drastically (in real time inference for instance).
Plus there is no reason it should no... | {
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https://api.github.com/repos/huggingface/transformers/issues/4913 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4913/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4913/comments | https://api.github.com/repos/huggingface/transformers/issues/4913/events | https://github.com/huggingface/transformers/pull/4913 | 636,441,695 | MDExOlB1bGxSZXF1ZXN0NDMyNjEzNDEy | 4,913 | ElectraForQuestionAnswering | {
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"Great, thanks for your help! \r\nCould you also add the new model to [`all_model_classes`](https://github.com/huggingface/transformers/blob/master/tests/test_modeling_electra.py#L41) which would test the model a little bit more?",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4913?src=pr&el=h1... | 1,591 | 1,591 | 1,591 | MEMBER | null | This PR adds `ElectraForQuestionAnswering`. One of the missing models in this [project](https://github.com/huggingface/transformers/projects/17)
@LysandreJik , @sgugger | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4912?src=pr&el=h1) Report\n> Merging [#4912](https://codecov.io/gh/huggingface/transformers/pull/4912?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/355954ffca798bb81d9db8886e30ce10f11e8a40&el=desc) will **decrease... | 1,591 | 1,592 | 1,592 | MEMBER | null | # Benchmarks
This PR adds the functionality to measure the following functionalities for TF and PT:
**Tensorflow:**
- Inference: CPU, GPU, GPU + XLA, GPU + eager mode, CPU + eager mode, TPU
**PyTorch:**
- Inference: CPU, CPU + torchscript, GPU, GPU + torchscript, GPU + mixed precision, Torch/XLA TPU
- T... | {
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"Hi! Why would you prefer using pickle rather than `save_pretrained`/`from_pretrained` or `torch.save`/`torch.save`?",
"HI @LysandreJik, pickle is mainly useful for parallel processing frameworks like `joblib` or `dask`. The use case is to parallelize some (embarassingly parallel) computation on multiple CPUs/GPU... | 1,591 | 1,598 | 1,598 | CONTRIBUTOR | null | this implements `__getstate__` for BERT models to enable pickling (without this PR the pickle attempt due to `weakref` errors). It also adds a unit test. | {
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https://api.github.com/repos/huggingface/transformers/issues/4910 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4910/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4910/comments | https://api.github.com/repos/huggingface/transformers/issues/4910/events | https://github.com/huggingface/transformers/pull/4910 | 636,386,793 | MDExOlB1bGxSZXF1ZXN0NDMyNTY4NjQy | 4,910 | Add more models to common tests | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4910?src=pr&el=h1) Report\n> Merging [#4910](https://codecov.io/gh/huggingface/transformers/pull/4910?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac99217e92c43066af7ec96554054d75532565d7&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | Follow-up to #4886, adds all existing pt models to common tests (with the exception of the longformer task-specific ones, because of some problem with output attention).
Most of them required some fixes in the model files which are also added.
For longformer, a few of the needed fixes are present but there was stil... | {
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https://api.github.com/repos/huggingface/transformers/issues/4909 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4909/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4909/comments | https://api.github.com/repos/huggingface/transformers/issues/4909/events | https://github.com/huggingface/transformers/pull/4909 | 636,333,555 | MDExOlB1bGxSZXF1ZXN0NDMyNTI1Mzg2 | 4,909 | [All models] fix docs after adding output attentions to all forward functions | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4909?src=pr&el=h1) Report\n> Merging [#4909](https://codecov.io/gh/huggingface/transformers/pull/4909?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac99217e92c43066af7ec96554054d75532565d7&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | MEMBER | null | Added the same docs for to all models for `output_attentions` following PR: https://github.com/huggingface/transformers/pull/4538 .
This PR only touches the docs.
Pinging @LysandreJik @Bharat123rox for notification. | {
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https://api.github.com/repos/huggingface/transformers/issues/4908 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4908/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4908/comments | https://api.github.com/repos/huggingface/transformers/issues/4908/events | https://github.com/huggingface/transformers/pull/4908 | 636,324,098 | MDExOlB1bGxSZXF1ZXN0NDMyNTE3NjYy | 4,908 | BartForQuestionAnswering | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4908?src=pr&el=h1) Report\n> Merging [#4908](https://codecov.io/gh/huggingface/transformers/pull/4908?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac99217e92c43066af7ec96554054d75532565d7&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | MEMBER | null | This PR adds `BartForQuestionAnswering`.
Decided to add this models as `BART` is intended for both NLU and NLG tasks and also achieves comparable performance to `ROBERTa` on SQuAD.
Also fine-tuned the model [here](https://colab.research.google.com/drive/1I5cK1M_0dLaf5xoewh6swcm5nAInfwHy?usp=sharing). The metrics ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4907 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4907/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4907/comments | https://api.github.com/repos/huggingface/transformers/issues/4907/events | https://github.com/huggingface/transformers/issues/4907 | 636,318,717 | MDU6SXNzdWU2MzYzMTg3MTc= | 4,907 | ModuleNotFoundError: No module named 'xml.sax'; 'xml' is not a package | {
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"Hello! Is `sacremoses` installed in your environment? Do you mind pasting the result of `pip list` in your environment?",
"Here you go:\r\n\r\n`Package Version \r\n---------------------- -----------\r\nabsl-py 0.9.0 \r\nastunparse 1.6.3 \r\nbeautifulsoup4 ... | 1,591 | 1,597 | 1,597 | NONE | null | I'm running this example:
`from transformers import pipeline
nlp = pipeline("sentiment-analysis")
print(nlp("I hate you"))
print(nlp("I love you"))`
I get this error:
`
Traceback (most recent call last):
File "ttt.py", line 1, in <module>
from transformers import pipeline as ppp
File "/usr/loc... | {
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https://api.github.com/repos/huggingface/transformers/issues/4906 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4906/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4906/comments | https://api.github.com/repos/huggingface/transformers/issues/4906/events | https://github.com/huggingface/transformers/issues/4906 | 636,296,487 | MDU6SXNzdWU2MzYyOTY0ODc= | 4,906 | TypeError: export() got an unexpected keyword argument 'use_external_data_format' | {
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"I just did this too and it seems to work :S ",
"I looked into this and I believe the issue is that use_external_data_format is a recent [addition to PyTorch from the onnx team](https://github.com/pytorch/pytorch/commit/96989a2a114de9b77e7dd9495d62c4a8a549b40d). If you upgrade to torch>=1.5.0 it should work. Also... | 1,591 | 1,702 | 1,596 | NONE | null | Hi,
I tried to run `convert_graph_to_onnx.py` using
`convert(framework="pt", model="bert-base-uncased", output="onnx/bert-base-uncased.onnx", opset=11)`
But I get error in the
```
export(
nlp.model,
model_args,
f=output,
input_names=ordered_input_na... | {
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https://api.github.com/repos/huggingface/transformers/issues/4905 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4905/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4905/comments | https://api.github.com/repos/huggingface/transformers/issues/4905/events | https://github.com/huggingface/transformers/issues/4905 | 636,258,243 | MDU6SXNzdWU2MzYyNTgyNDM= | 4,905 | [How to] Carefully designing the head of a Transformer model? | {
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While using the pre-trained any transformer model, what are the main things we normally should consider while designing the head? Simply like,
```python
distill = transformer.distilbert.... <----- slicing the first position
x = Dense(n, activation = ' ')(distill) <-------- simple classifer... | {
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https://api.github.com/repos/huggingface/transformers/issues/4904 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4904/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4904/comments | https://api.github.com/repos/huggingface/transformers/issues/4904/events | https://github.com/huggingface/transformers/pull/4904 | 636,221,952 | MDExOlB1bGxSZXF1ZXN0NDMyNDM1MDQx | 4,904 | [ctrl] fix pruning of MultiHeadAttention | {
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"Hi @aretius, some (if not all) the tests failing are unrelated to your PR, and should have been solved by the recently merged #4903. Do you mind rebasing on `master` and force pushing so that we may see if all the tests pass?",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4904?src=pr&el=h1) R... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | @sshleifer
Implemented the pruning logic. Fixes - #4798
After enabling `test_pruning` all the previously failing tests are passing. | {
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https://api.github.com/repos/huggingface/transformers/issues/4903 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4903/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4903/comments | https://api.github.com/repos/huggingface/transformers/issues/4903/events | https://github.com/huggingface/transformers/pull/4903 | 636,212,566 | MDExOlB1bGxSZXF1ZXN0NDMyNDI3NDIx | 4,903 | Fix the CI | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4903?src=pr&el=h1) Report\n> Merging [#4903](https://codecov.io/gh/huggingface/transformers/pull/4903?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0a375f5abdefcde1424639f712cf40247135cd64&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | The CI was broken by the merge of #4886 since #4538 was merged between the moment #4886 was tested and the moment it was merged.
This PR fixes the tests. | {
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https://api.github.com/repos/huggingface/transformers/issues/4902 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4902/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4902/comments | https://api.github.com/repos/huggingface/transformers/issues/4902/events | https://github.com/huggingface/transformers/issues/4902 | 636,182,046 | MDU6SXNzdWU2MzYxODIwNDY= | 4,902 | [cleanup] Hoist ModelTester objects to toplevel | {
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"@sshleifer It would be beneficial to provide more context, apologies for the beginner question!\r\nWould be happy to pick it up :)",
"Yeah sure. The high level goal is to reduce the amount of boilerplate code in the unittests.\r\n\r\nFor example, if you look at [T5ModelTester](https://github.com/huggingface/tran... | 1,591 | 1,592 | 1,592 | CONTRIBUTOR | null | https://github.com/huggingface/transformers/pull/4046#issuecomment-628236744
many `ModelTester` objects are defined within classes. If we move them to the top level of the module, we can share code where possible and also have less complexity.
The task here is to move `ModelTester` objects to the top level.
Bo... | {
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https://api.github.com/repos/huggingface/transformers/issues/4901 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4901/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4901/comments | https://api.github.com/repos/huggingface/transformers/issues/4901/events | https://github.com/huggingface/transformers/pull/4901 | 636,134,892 | MDExOlB1bGxSZXF1ZXN0NDMyMzYzMDQ1 | 4,901 | Add MobileBert | {
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"Hi @vshampor, can you let me know when this is ready for review? Thanks!",
"@LysandreJik it is quite impossible to make the CI pass for the check_code_quality stage since locally the `black` and the `isort` commands seem to produce opposite changes when applied at once with `make style` and therefore cancel out;... | 1,591 | 1,592 | 1,592 | CONTRIBUTOR | null | Grabbed the code from https://github.com/lonePatient/MobileBert_PyTorch and added the question answering downstream task.
Should address #4185. Also got the backbone weights' representation in the Pytorch/transformers format (i.e. the `pytorch_model.bin`, `config.json` and `vocab.txt` files) via converting the origi... | {
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https://api.github.com/repos/huggingface/transformers/issues/4900 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4900/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4900/comments | https://api.github.com/repos/huggingface/transformers/issues/4900/events | https://github.com/huggingface/transformers/issues/4900 | 636,133,342 | MDU6SXNzdWU2MzYxMzMzNDI= | 4,900 | Latest version of transformers available via conda-forge? | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,591 | 1,597 | 1,597 | NONE | null | On conda forge the last version is the 2.1.1,
Why is not updated to the latest? Is it in plan to update the version?
We work in a limited environment and we are forced to work with conda-forge channel.
Thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/4899 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4899/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4899/comments | https://api.github.com/repos/huggingface/transformers/issues/4899/events | https://github.com/huggingface/transformers/issues/4899 | 636,129,917 | MDU6SXNzdWU2MzYxMjk5MTc= | 4,899 | Error using inputs_embeds argument in TFXLNetModel | {
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"Hey, @patrickvonplaten I observed the same with TFBertModel. So pretty much evident that the issue must be with the parent (if at all that helps)",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contr... | 1,591 | 1,664 | 1,604 | NONE | null | While using the TFXLNetModel:
`xlnet = TFXLNetModel.from_pretrained('xlnet-base-cased')`
according to the docs, `input_ids` and `inputs_embeds` can be optionally used. However, when I tried using:
`xlnet(inputs_embeds=embeddings, attention_mask=attn_masks)[0]`
it throws: `ValueError: The first argument to Layer.c... | {
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https://api.github.com/repos/huggingface/transformers/issues/4897 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4897/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4897/comments | https://api.github.com/repos/huggingface/transformers/issues/4897/events | https://github.com/huggingface/transformers/issues/4897 | 636,120,883 | MDU6SXNzdWU2MzYxMjA4ODM= | 4,897 | KeyError when using non-default models in Huggingface transformers pipeline | {
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"The \"sentiment-analysis\" pipeline is only compatible with text classification models, i.e. those that can be loaded without error with `AutoModelForSequenceClassification`"
] | 1,591 | 1,591 | 1,591 | NONE | null |
I have no problems using the default model in the sentiment analysis pipeline.
```# Allocate a pipeline for sentiment-analysis
nlp = pipeline('sentiment-analysis')
nlp('I am a black man.')
>>>[{'label': 'NEGATIVE', 'score': 0.5723695158958435}]
```
But, when I try to customise the pipeline a little by ad... | {
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https://api.github.com/repos/huggingface/transformers/issues/4896 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4896/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4896/comments | https://api.github.com/repos/huggingface/transformers/issues/4896/events | https://github.com/huggingface/transformers/pull/4896 | 636,108,996 | MDExOlB1bGxSZXF1ZXN0NDMyMzQyMTc5 | 4,896 | [WIP] Add early stopping to the trainer | {
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"Well that was quick. Awesome! Let me know if you need some help (for the pytorch part) or code review.",
"Looks like a duplicate of https://github.com/huggingface/transformers/pull/4186",
"> Looks like a duplicate of #4186\r\n\r\nYou are absolutely right. Closing this in favour of https://github.com/huggingfac... | 1,591 | 1,592 | 1,592 | NONE | null | closes #4894 | {
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https://api.github.com/repos/huggingface/transformers/issues/4895 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4895/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4895/comments | https://api.github.com/repos/huggingface/transformers/issues/4895/events | https://github.com/huggingface/transformers/issues/4895 | 636,099,377 | MDU6SXNzdWU2MzYwOTkzNzc= | 4,895 | How do I fine-tune hyperparameters for a model from Huggingface library | {
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"You can take a look at this blog post https://mccormickml.com/2019/07/22/BERT-fine-tuning/",
"Thank You"
] | 1,591 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
## Details
Hi, I am new to Hugging-face library and want to fine tune hyper-parameters of the mBert model. I have a simple classification head on top the cls token. I am getting around 76% accuracy.
Is there any read-me or notebook available for doing the same.
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https://api.github.com/repos/huggingface/transformers/issues/4894 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4894/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4894/comments | https://api.github.com/repos/huggingface/transformers/issues/4894/events | https://github.com/huggingface/transformers/issues/4894 | 636,041,737 | MDU6SXNzdWU2MzYwNDE3Mzc= | 4,894 | 🚀 Add early stopping to the trainer | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"Looking at the interest this topic has, I am bumping it to re-open it.",
"Hi,\r\n\r\nSo when #4186 is closed, this will close as well... | 1,591 | 1,646 | 1,646 | COLLABORATOR | null | # 🚀 Feature request
The trainer ([pt](https://github.com/huggingface/transformers/blob/master/src/transformers/trainer.py), [tf](https://github.com/huggingface/transformers/blob/master/src/transformers/trainer_tf.py)) is an easy access point for users who rather not spend too much time building their own trainer cl... | {
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https://api.github.com/repos/huggingface/transformers/issues/4893 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4893/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4893/comments | https://api.github.com/repos/huggingface/transformers/issues/4893/events | https://github.com/huggingface/transformers/issues/4893 | 636,015,473 | MDU6SXNzdWU2MzYwMTU0NzM= | 4,893 | 🐛 TPU Training broken due to recent changes | {
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"See https://github.com/huggingface/transformers/issues/4814 as well. Over there the TPU evaluation is broken.\r\nTo make the TPU pipeline reliable, a end-to-end test could really help.",
"Hi! Thank you for raising this issue, I'll take a look.\r\n\r\nOf course, having an end-to-end test would really help. Unfort... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🐛 Bug
Looks like due to changes in file_utils.py, the TPU Training has become broken. Reverting transformers to a version before https://github.com/huggingface/transformers/commit/2cfb947f59861d5d910f84eba3be57da200b5599 fixes the problem.
## Information
Seems like file_utils.py is trying to reinitialize the TP... | {
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"Still facing this problem. Has anyone else encountered something similar? ",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I also face this problem. How to solve it?"
] | 1,591 | 1,628 | 1,600 | NONE | null | # ❓ Questions & Help
## Details
I trained a RoBERTa model following this colab - https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb#scrollTo=XaFAsB_fnU3K
Here is how my data looked:
```
Merkel bemoans lack of rain as Germany fears for its forests .\n
Germany’... | {
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"Thanks for bringing this up, @Colanim! I worked on #4757, and didn't realize the same could automatically extend to TFTrainer as well.\r\n\r\nPlease take a look at #4925 to see if it'd solve this for you."
] | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🐛 Bug
The argument `dataloader_drop_last` appear to not be used in `TFTrainer`. This is a problem when we need a static batch size.
https://github.com/huggingface/transformers/blob/e8db8b845a971b0cf63a0896b9deb5b316028a8b/src/transformers/trainer_tf.py#L68-L73
## Expected behavior
The argument `dataloade... | {
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"Sure, and you can use the `add_prefix_space` flag to do that."
] | 1,591 | 1,591 | 1,591 | NONE | null | Hello,
From the GPT-2 Tokenizer section of the Hugging Face Transformer documentation, the documentation says that:
```
GPT-2 BPE tokenizer.
Peculiarities:
Byte-level Byte-Pair-Encoding
Requires a space to start the input string => the encoding methods should be called with the add_prefix_space flag set ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4889?src=pr&el=h1) Report\n> Merging [#4889](https://codecov.io/gh/huggingface/transformers/pull/4889?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6e603cb7892b49a2cbbc10ba859759f92c3fb7a6&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | This introduces a method: `Tokenizer.prepare_seq2seq_batch` that calls batch encode plus twice and prepares inputs for seq2seq models.
The seq2seq finetuning example and some seq2seq unittests calls batch encode plus twice. This seems like it should be the work of the tokenizer, and MarianTokenizer, BartTokenizer, ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4888 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4888/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4888/comments | https://api.github.com/repos/huggingface/transformers/issues/4888/events | https://github.com/huggingface/transformers/issues/4888 | 635,839,787 | MDU6SXNzdWU2MzU4Mzk3ODc= | 4,888 | Previous commit introduces bug in `convert_pytorch_checkpoint_to_tf2.py` | {
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"I encountered the same problem.\r\nIf you were converting a local `pytorch_model.bin` model, you can try this\r\n\r\nsomewhere around line 258 in `convert_pytorch_checkpoint_to_tf2.py`\r\n\r\n```\r\naws_model_maps = {}\r\nconfig_class, model_class, pt_model_class, aws_config_map = MODEL_CLASSES[model_type]\r\n# co... | 1,591 | 1,599 | 1,599 | MEMBER | null | This issue concerns the conversion tool `convert_pytorch_checkpoint_to_tf2.py`.
Commit d4c2cb402d6674211726fd5f4803d1090664e438 removed the `*PRETRAINED_MODEL_ARCHIVE_MAP` from the imports so that for each key in `MODEL_CLASSES` is associated to a set of 4 values.
For instance: https://github.com/huggingface/transf... | {
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https://api.github.com/repos/huggingface/transformers/issues/4887 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4887/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4887/comments | https://api.github.com/repos/huggingface/transformers/issues/4887/events | https://github.com/huggingface/transformers/pull/4887 | 635,812,913 | MDExOlB1bGxSZXF1ZXN0NDMyMTEwMDkz | 4,887 | warn with FutureWarning when using `output_attentions` in the configu… | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4887?src=pr&el=h1) Report\n> Merging [#4887](https://codecov.io/gh/huggingface/transformers/pull/4887?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/13aa174112f0c2ee794c44188ecf13b241694db0&el=desc) will **increase... | 1,591 | 1,651 | 1,591 | MEMBER | null | …ration | {
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https://api.github.com/repos/huggingface/transformers/issues/4886 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4886/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4886/comments | https://api.github.com/repos/huggingface/transformers/issues/4886/events | https://github.com/huggingface/transformers/pull/4886 | 635,778,420 | MDExOlB1bGxSZXF1ZXN0NDMyMDgxODc4 | 4,886 | Deal with multiple choice in common tests | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4886?src=pr&el=h1) Report\n> Merging [#4886](https://codecov.io/gh/huggingface/transformers/pull/4886?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **increase... | 1,591 | 1,595 | 1,591 | COLLABORATOR | null | It's a bit heavy but I didn't find another way to reshape the inputs when needed for the multiple choice model. With this, and skipping the input_embeds test when the model is a multiple choice one (current implementation requires `input_ids`), I manage to have the common tests passing for `BertForMultipleChoice`.
L... | {
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https://api.github.com/repos/huggingface/transformers/issues/4885 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4885/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4885/comments | https://api.github.com/repos/huggingface/transformers/issues/4885/events | https://github.com/huggingface/transformers/pull/4885 | 635,731,376 | MDExOlB1bGxSZXF1ZXN0NDMyMDQyOTE3 | 4,885 | Add AlbertForMultipleChoice | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4885?src=pr&el=h1) Report\n> Merging [#4885](https://codecov.io/gh/huggingface/transformers/pull/4885?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f0340b30310cb78555c6f78bed7262101f251940&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | Another [model missing](https://github.com/huggingface/transformers/projects/17).
While implementing it I noticed two things:
- the example in `BertForMultipleChoice` wasn't working, so fixed it.
- some model classes where missing in the `all_model_classes` in the test, fixed it for albert and bert, will look at t... | {
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https://api.github.com/repos/huggingface/transformers/issues/4884 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4884/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4884/comments | https://api.github.com/repos/huggingface/transformers/issues/4884/events | https://github.com/huggingface/transformers/pull/4884 | 635,716,709 | MDExOlB1bGxSZXF1ZXN0NDMyMDMwODg4 | 4,884 | Fix a bug in the initialization and serialization of TFRobertaClassificationHead | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4884?src=pr&el=h1) Report\n> Merging [#4884](https://codecov.io/gh/huggingface/transformers/pull/4884?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | For `TFRobertaClassificationHead`, `config` was being passed as the first parameter to the `__init__` of the parent class `tf.keras.layers.Layer`. The latter [expects](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Layer) trainable as the first parameter.
This fixes #4709 and #3664, making the TFRoberta... | {
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https://api.github.com/repos/huggingface/transformers/issues/4883 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4883/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4883/comments | https://api.github.com/repos/huggingface/transformers/issues/4883/events | https://github.com/huggingface/transformers/pull/4883 | 635,683,547 | MDExOlB1bGxSZXF1ZXN0NDMyMDAzNzQy | 4,883 | check type before logging in trainer to ensure values are scalars | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4883?src=pr&el=h1) Report\n> Merging [#4883](https://codecov.io/gh/huggingface/transformers/pull/4883?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | This change was necessary to avoid https://github.com/lanpa/tensorboardX/issues/567 since a non-scalar value was being passed in. | {
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https://api.github.com/repos/huggingface/transformers/issues/4882 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4882/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4882/comments | https://api.github.com/repos/huggingface/transformers/issues/4882/events | https://github.com/huggingface/transformers/pull/4882 | 635,664,337 | MDExOlB1bGxSZXF1ZXN0NDMxOTg3NTA2 | 4,882 | fix huggingface/tokenizers#297 in 0.8.0 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4882?src=pr&el=h1) Report\n> Merging [#4882](https://codecov.io/gh/huggingface/transformers/pull/4882?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **increase... | 1,591 | 1,597 | 1,597 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4881 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4881/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4881/comments | https://api.github.com/repos/huggingface/transformers/issues/4881/events | https://github.com/huggingface/transformers/pull/4881 | 635,658,084 | MDExOlB1bGxSZXF1ZXN0NDMxOTgyMjY4 | 4,881 | Fix TensorFlow dataset generator | {
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"Nice!! I didn't know that parameter ^^\r\n\r\nDoes it seems better now?",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4881?src=pr&el=h1) Report\n> Merging [#4881](https://codecov.io/gh/huggingface/transformers/pull/4881?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transfor... | 1,591 | 1,594 | 1,593 | CONTRIBUTOR | null | Should fix #4856
The method `glue_convert_examples_to_features` returns a badly formated TensorFlow dataset in case the used model doesn't use `token_type_ids` as feature such as DistilBert.
The fix is to detect when the feature `token_type_ids` should belong to the TensorFlow dataset or not. I'm not really happ... | {
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"This is because the `huggingface/prunebert-xxx` configurations have a model type `masked_bert`.\r\n\r\nSince these files should be loaded directly in `BertForXXX` classes, it would probably be best to update that field to `bert`, right @julien-c?",
"Yes. Can you confirm @VictorSanh?",
"Seems to be working fine... | 1,591 | 1,591 | 1,591 | NONE | null | I am having issues loading the new prunebert model for sequence classification using AutoModelForSequenceClassification.from_pretrained().
```
from transformers import AutoModelForSequenceClassification, BertForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("huggingface/pruneber... | {
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With the question answering pipeline, sometimes the model selects an answer that is out of bounds. This ensures that it will select the maximum token it can select, and prevents KeyErrors from happening | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4878?src=pr&el=h1) Report\n> Merging [#4878](https://codecov.io/gh/huggingface/transformers/pull/4878?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/86578bb04c9b34f9d8e35cd4fad42a85910dd9e9&el=desc) will **decrease... | 1,591 | 1,592 | 1,592 | MEMBER | null | This PR adds `BartTokenizerFast` by subclassing `RobertaTokenizerFast`
@sshleifer @mfuntowicz | {
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"@aretius Thank you for mentioning ProphetNet. ProphetNet for huggingface is sheduled as you suggested. ",
"@qiweizhen this sounds great, I would love to give it a go. Any planned date for delivering this?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be ... | 1,591 | 1,598 | 1,598 | CONTRIBUTOR | null | # 🌟 New model addition
ProphetNet
## Model description
ProphetNet introduces a novel self-supervised objective named future n-gram prediction and the proposed n stream self-attention mechanism. Instead of the optimization of one-step-ahead prediction in the traditional sequence-to-sequence model, the ProphetNet ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4876?src=pr&el=h1) Report\n> Merging [#4876](https://codecov.io/gh/huggingface/transformers/pull/4876?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | Don't think we need a download_cnn_dailymail.py script
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"Hey @cstorm125, \r\n\r\nI think, those `28` leftover embeddings are simply not used. The reason why the embedding matrix is of length 32128 as far as I know is simply because 32128 is a more GPU friendly number `32128 = 128 * 251` than `32100 = 4 * 8025`. That means that the GPU is probably more efficient if it c... | 1,591 | 1,680 | 1,592 | NONE | null | # ❓ Questions & Help
Pretrained `T5Tokenizer ` has vocab size of 32100 (32000 tokens plus 100 extra_ids) but the shared embedding layer of `T5ForConditionalGeneration` has size of (32128, 768). I checked the google-research implementation of T5 and also found that they have vocab size of 32100 also.
Where did the e... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4874?src=pr&el=h1) Report\n> Merging [#4874](https://codecov.io/gh/huggingface/transformers/pull/4874?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3ae2e86baffc1fea8b8b93695fb5a10941fd63dc&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | As discussed in #4711, the `BertForMaskedLM` model should be split in two to avoid having two different labels argument, one model for causal LM, one for masked LM. This PR follows up on that and does the split.
It introduces a new `BertLMHeadModel` (also added to the `__init__` and the docs) with a test. As discuss... | {
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"Thank you for your fast answer.\r\n\r\nYour patch seems to fix some KeyError but not all of them.\r\n\r\nHere is an example of a context and a question that raise it :\r\n\r\n[context2.txt](https://github.com/huggingface/transformers/files/4758844/context2.txt)\r\n\r\nQuestion : \r\nQuel est l'étage se situe les l... | 1,591 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
`Camembert ("illuin/camembert-large-fquad")`
Language I am using the model on (English, Chinese ...):
`French`
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4871?src=pr&el=h1) Report\n> Merging [#4871](https://codecov.io/gh/huggingface/transformers/pull/4871?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4869 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4869/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4869/comments | https://api.github.com/repos/huggingface/transformers/issues/4869/events | https://github.com/huggingface/transformers/pull/4869 | 635,377,474 | MDExOlB1bGxSZXF1ZXN0NDMxNzQ5Njk5 | 4,869 | parse arguments from dict | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4869?src=pr&el=h1) Report\n> Merging [#4869](https://codecov.io/gh/huggingface/transformers/pull/4869?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase... | 1,591 | 1,596 | 1,596 | MEMBER | null | This PR adds parse_dict method to HfArgumentParser to allow parsing arguments from dict
@julien-c
As suggested by you here #4791, I've added a simple unit test to check if the dataclass returned by `parse_dict` is same as manually initialised one. | {
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"Hello! You're using `transformers` version 2.1.1, which didn't have all of these features, as you can see in the [documentation of version 2.1.1](https://huggingface.co/transformers/v2.1.1/main_classes/tokenizer.html#transformers.PreTrainedTokenizer.encode_plus).\r\n\r\nI would recommend upgrading your `transforme... | 1,591 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
tokenizer.encode_plus stopped returning `attention_mask` and pad_to_max_length
## Information
Model I am using (Bert, XLNet ...):
Bert
Language I am using the model on (English, Chinese ...):
English
The problem arises when using:
my own modified scripts: (give details below)
The tasks I am ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4867?src=pr&el=h1) Report\n> Merging [#4867](https://codecov.io/gh/huggingface/transformers/pull/4867?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **increase... | 1,591 | 1,592 | 1,591 | CONTRIBUTOR | null | `is_leaf` may become `False` after `.to(device=device)` function call. | {
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https://api.github.com/repos/huggingface/transformers/issues/4866 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4866/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4866/comments | https://api.github.com/repos/huggingface/transformers/issues/4866/events | https://github.com/huggingface/transformers/issues/4866 | 635,367,503 | MDU6SXNzdWU2MzUzNjc1MDM= | 4,866 | Funnel Transformers | {
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"Duplicate of #4844?",
"my bad. yes"
] | 1,591 | 1,591 | 1,591 | NONE | null | # 🌟 New model addition
Funnel-Transformer
## Model description
Funnel-Transformer is a new self-attention model that gradually compresses the sequence of hidden states to a shorter one and hence reduces the computation cost. More importantly, by re-investing the saved FLOPs from length reduction in constructing a... | {
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https://api.github.com/repos/huggingface/transformers/issues/4865 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4865/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4865/comments | https://api.github.com/repos/huggingface/transformers/issues/4865/events | https://github.com/huggingface/transformers/pull/4865 | 635,351,497 | MDExOlB1bGxSZXF1ZXN0NDMxNzI3NzQx | 4,865 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4865?src=pr&el=h1) Report\n> Merging [#4865](https://codecov.io/gh/huggingface/transformers/pull/4865?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f5d5a531d769d07403f59661884e254f8420afe&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4864 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4864/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4864/comments | https://api.github.com/repos/huggingface/transformers/issues/4864/events | https://github.com/huggingface/transformers/pull/4864 | 635,317,596 | MDExOlB1bGxSZXF1ZXN0NDMxNzAwMDQ2 | 4,864 | Adding 🤗nlp in the examples | {
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"Closing in favor of #5240"
] | 1,591 | 1,651 | 1,593 | MEMBER | null | This PR examines how to best make use of all the features of 🤗nlp in the examples.
First, example studied is GLUE. The main goal is to have a very explicit data processing (target: no data processing happening inside `transformers`) as well as add some efficiency features like dynamic batching. The second goal is t... | {
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https://api.github.com/repos/huggingface/transformers/issues/4863 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4863/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4863/comments | https://api.github.com/repos/huggingface/transformers/issues/4863/events | https://github.com/huggingface/transformers/issues/4863 | 635,293,463 | MDU6SXNzdWU2MzUyOTM0NjM= | 4,863 | how to train mask model e.g Bert using WordPieceToken | {
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"Hi! Can you load your tokenizer using\r\n\r\n```py\r\nfrom transformers import BertTokenizer\r\n\r\ntokenizer = BertTokenizer.from_pretrained(directory_containing_vocab_txt)\r\n```\r\n?",
"> \r\n> \r\n> Hi! Can you load your tokenizer using\r\n> \r\n> ```python\r\n> from transformers import BertTokenizer\r\n> \r... | 1,591 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
When i trained a new token by WordPiece，that generized one vocab.txt file . It couldn't load in train-language-model.py ，since in source code it used bytepiece token. Is there a module out of box could save me a lot of time to do myself？
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"Interesting use-case!\r\n\r\nThe easiest way would be to simply load to models, one with the `bert-base-cased` checkpoint, the other randomly initialized, and to assign trained layers to the new model. Something like this:\r\n\r\n```py\r\nfrom transformers import BertModel, BertConfig\r\nimport torch\r\n\r\nbert_b... | 1,591 | 1,661 | 1,598 | NONE | null | How can I, for example, extract 8 layers from the 12 BertLayers of the _bert-base-uncased_ to form a new model? I want to use the _embedding_ and _pooler_ layer of orginal model, but use only a portion of the _encoder_ layers. | {
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https://api.github.com/repos/huggingface/transformers/issues/4861 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4861/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4861/comments | https://api.github.com/repos/huggingface/transformers/issues/4861/events | https://github.com/huggingface/transformers/issues/4861 | 635,233,480 | MDU6SXNzdWU2MzUyMzM0ODA= | 4,861 | can anyone tell me how to do the pretraining of Reformer model on my text data? | {
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"```python\r\nfrom transformers import ReformerModelWithLMHead, ReformerConfig\r\nconfig = ReformerConfig() # define the config as you like\r\nmodel = ReformerModelWithLMHead(config)\r\nloss = model(input_ids, labels=input_ids) # input_ids are automatically shifted for labels\r\n=> train\r\n```\r\n\r\nAll this ca... | 1,591 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/4860 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4860/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4860/comments | https://api.github.com/repos/huggingface/transformers/issues/4860/events | https://github.com/huggingface/transformers/issues/4860 | 635,176,864 | MDU6SXNzdWU2MzUxNzY4NjQ= | 4,860 | ROUGE_L score of summarization/t5 is very lower than that of paper. | {
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"So, I investigated the google's code, then I found:\r\n\r\nhttps://github.com/google-research/text-to-text-transfer-transformer/blob/master/t5/evaluation/metrics.py#L76\r\n\r\nI think that they uses not \"rougeL\" but \"rougeLsum\".\r\nAnd also, they says:\r\n \"# Add newlines between sentences so that rougeLsum i... | 1,591 | 1,597 | 1,597 | NONE | null | # 🐛 Bug
## Information
I try to use summarization/t5 in examples.
The ROUGE_1 and ROUGE_2 is equals to that of google's paper.
But, only ROUGE_L is very low!
```
ROUGE_1: paper=41.12 | my result=40.48 (almost equal)
ROUGE_2: paper=19.56 | my result=18.59 (almost equal)
ROUGE_L: paper=38.35 | my result=28... | {
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https://api.github.com/repos/huggingface/transformers/issues/4859 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4859/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4859/comments | https://api.github.com/repos/huggingface/transformers/issues/4859/events | https://github.com/huggingface/transformers/issues/4859 | 635,107,710 | MDU6SXNzdWU2MzUxMDc3MTA= | 4,859 | Memory issues in Transformers | {
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<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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https://api.github.com/repos/huggingface/transformers/issues/4858 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4858/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4858/comments | https://api.github.com/repos/huggingface/transformers/issues/4858/events | https://github.com/huggingface/transformers/issues/4858 | 635,038,196 | MDU6SXNzdWU2MzUwMzgxOTY= | 4,858 | Add support for DeBERTa | {
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"Hello, Our code has just been released at [DeBERTa]( https://github.com/microsoft/DeBERTa)\r\nPlease take a try and your feedback will be good for our improvements, we also welcome the community to work together with us to improve it.\r\nWe are also glad to integrate DeBERTa into transformers.\r\n",
"PR Add debe... | 1,591 | 1,606 | 1,606 | COLLABORATOR | null | # 🌟 New model addition
## Model description
DeBERTa (Decoding-enhanced BERT with disentangled attention) is a new model architecture:
> In this paper we propose a new model architecture DeBERTa (Decoding-enhanced BERT with disentangled attention) that improves the BERT and RoBERTa models using two novel tech... | {
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https://api.github.com/repos/huggingface/transformers/issues/4857 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4857/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4857/comments | https://api.github.com/repos/huggingface/transformers/issues/4857/events | https://github.com/huggingface/transformers/issues/4857 | 635,016,815 | MDU6SXNzdWU2MzUwMTY4MTU= | 4,857 | sentencepiece==0.1.92 causing segmentation fault | {
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"@boy2000-007man Hi, folk. Just curious about how do you find this bug? It costs me almost the whole day... Anyway, thank you so much!",
"OMG!!! Awesome Advice!!!! ",
"I spent a whole night to address the dependencies problems and almost lost my mind. This answer saved my life. Appreciate!",
"Thanks for this... | 1,591 | 1,605 | 1,596 | CONTRIBUTOR | null | # 🐛 Bug
## Information
`transformers==2.9.1`
`torch==1.4.0`
Starting from today,
I notice newly released `sentencepiece==0.1.92` causing segmentation fault while calling torch functions.
Downgrade to `sentencepiece==0.1.91` solve it.
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https://api.github.com/repos/huggingface/transformers/issues/4856 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4856/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4856/comments | https://api.github.com/repos/huggingface/transformers/issues/4856/events | https://github.com/huggingface/transformers/issues/4856 | 634,979,117 | MDU6SXNzdWU2MzQ5NzkxMTc= | 4,856 | Tensorflow Glue example script for finetuning not usable with DistilBert | {
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"Hello!\r\n\r\nIndeed, it is a bug in the way the TensorFlow dataset is generated. A fix is on its way :)"
] | 1,591 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using: DistilBert
```
python run_glue.py \
--model_name_or_path distilbert-base-cased \
--task_name MRPC\
--do_train \
--do_eval \
--max_seq_length 128 \
--per_device_train_batch_size 32 \
--learning_rate 2e-5 \
--num_train_epochs 3.0 \
--output_di... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4855?src=pr&el=h1) Report\n> Merging [#4855](https://codecov.io/gh/huggingface/transformers/pull/4855?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a139d1a1602ee72ca98d5e0412efbd68f746d2c8&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | One of the missing [model task](https://github.com/huggingface/transformers/projects/17). | {
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https://api.github.com/repos/huggingface/transformers/issues/4854 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4854/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4854/comments | https://api.github.com/repos/huggingface/transformers/issues/4854/events | https://github.com/huggingface/transformers/pull/4854 | 634,944,824 | MDExOlB1bGxSZXF1ZXN0NDMxNDA1MjQ4 | 4,854 | Hans data | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4854?src=pr&el=h1) Report\n> Merging [#4854](https://codecov.io/gh/huggingface/transformers/pull/4854?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ca5e1cdf8e314288bd0242a531815a6c75d8178e&el=desc) will **not chan... | 1,591 | 1,592 | 1,592 | COLLABORATOR | null | This is the first step toward solving #4742: to be able to use the Trainer API, we first need to remove the TensorDataset and have datasets with dict items. This PR addresses that and updates the training and evaluation script accordingly.
It takes the multiple choice as a reference implementation, using the same fi... | {
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https://api.github.com/repos/huggingface/transformers/issues/4853 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4853/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4853/comments | https://api.github.com/repos/huggingface/transformers/issues/4853/events | https://github.com/huggingface/transformers/pull/4853 | 634,857,353 | MDExOlB1bGxSZXF1ZXN0NDMxMzMzODI4 | 4,853 | Remove unused arguments in Multiple Choice example | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4853?src=pr&el=h1) Report\n> Merging [#4853](https://codecov.io/gh/huggingface/transformers/pull/4853?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/37be3786cf1de9d21233f543c231866e68954998&el=desc) will **increase... | 1,591 | 1,592 | 1,591 | COLLABORATOR | null | In the dataset preparation, the arguments `pad_token_segment_id`, `pad_on_left`, `pad_token` and `mask_padding_with_zero` are inferred from the tokenizer to be sent to `convert_examples_to_features` which then does not use them (since `tokenizer.encode_plus` does all of this using the tokenizer state).
This PR clean... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,591 | 1,597 | 1,597 | NONE | null | # 🐛 Bug
## Information
I am pre-training albert from scratch and it was going fine.(8 v100)
But when I am training using a checkpoint its using single gpu and that also 1gb/32gb GPU ram.
## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
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https://api.github.com/repos/huggingface/transformers/issues/4851 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4851/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4851/comments | https://api.github.com/repos/huggingface/transformers/issues/4851/events | https://github.com/huggingface/transformers/pull/4851 | 634,757,515 | MDExOlB1bGxSZXF1ZXN0NDMxMjUzOTk4 | 4,851 | Run a single wandb instance per TPU run | {
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"Why is it specific to tpu only?\r\nWould the same logic apply in all cases?",
"Yes I'm guessing we only want the global master to log to wandb in DDP, like we do for Tensorboard.\r\n\r\nNot sure why we hadn't done it like that before, @borisdayma – thoughts?",
"I did not consider DP/DDP at the time. Actually T... | 1,591 | 1,591 | 1,591 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4850 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4850/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4850/comments | https://api.github.com/repos/huggingface/transformers/issues/4850/events | https://github.com/huggingface/transformers/pull/4850 | 634,715,244 | MDExOlB1bGxSZXF1ZXN0NDMxMjIwMjYx | 4,850 | [Benchmark] add tpu and torchscipt for benchmark | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4850?src=pr&el=h1) Report\n> Merging [#4850](https://codecov.io/gh/huggingface/transformers/pull/4850?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/42860e92a4a99a8be338644462cfc3f62d1379a3&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | MEMBER | null | This PR adds:
- Torchscript memory and time benchmarking
- TPU memory and time benchmarking | {
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https://api.github.com/repos/huggingface/transformers/issues/4849 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4849/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4849/comments | https://api.github.com/repos/huggingface/transformers/issues/4849/events | https://github.com/huggingface/transformers/pull/4849 | 634,694,915 | MDExOlB1bGxSZXF1ZXN0NDMxMjAzODQw | 4,849 | Clean documentation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4849?src=pr&el=h1) Report\n> Merging [#4849](https://codecov.io/gh/huggingface/transformers/pull/4849?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e817747941c75c8e14f0e93755ec648269f8a14d&el=desc) will **not chan... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | This PR addresses several problems in the documentation:
- not all existing models were present, I added them
- made sure to always follow the same order of sections/classes as bert for consistency, added an Overview section when not present, moved tips at the end of that overview section if they were elsewhere
- fi... | {
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https://api.github.com/repos/huggingface/transformers/issues/4848 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4848/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4848/comments | https://api.github.com/repos/huggingface/transformers/issues/4848/events | https://github.com/huggingface/transformers/issues/4848 | 634,657,085 | MDU6SXNzdWU2MzQ2NTcwODU= | 4,848 | TFXLMRobertaForSequenceClassification: call() got an unexpected keyword argument 'labels' | {
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"Hi! You're on `transformers` version `v2.5.1`, but the TensorFlow models can only accept labels since this PR https://github.com/huggingface/transformers/pull/4530 was merged, 4 days ago.\r\n\r\nThis currently isn't available in any release, so you will have to install from source to use that feature:\r\n\r\n```\r... | 1,591 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using : TFXLMRoberta
Language I am using the model on : cross-lingual
The problem arises when using:
* [ ] the official example scripts:
* [√] my own modified scripts:
```python
import tensorflow as tf
from transformers import TFXLMRobertaForSequenceClassification,X... | {
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https://api.github.com/repos/huggingface/transformers/issues/4847 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4847/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4847/comments | https://api.github.com/repos/huggingface/transformers/issues/4847/events | https://github.com/huggingface/transformers/issues/4847 | 634,586,574 | MDU6SXNzdWU2MzQ1ODY1NzQ= | 4,847 | Add optimal model size and stopping time feature | {
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"Great stuff, thank you! The energy estimates look 1000 worse than reality though, V100 running for 12 h should not consume 5432 kWh I think, else we'd be all dead. 5.4 kWh looks more reasonable.\r\n\r\n<img width=\"424\" alt=\"Screenshot 2020-06-09 at 00 26 45\" src=\"https://user-images.githubusercontent.com/4246... | 1,591 | 1,623 | 1,604 | CONTRIBUTOR | null | # 🚀 Feature request
The [calculator](https://huggingface.co/calculator/) blog post presented an automated way to find scaling laws with model size and compute budget on language modeling tasks. Adding it to the library would help save on training costs by picking an optimal model size and training time.
## Motiv... | {
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"Do you have a paper/link about those \"add\" and \"slots\" that you mention? I have never heard of it.",
"> Do you have a paper/link about those \"add\" and \"slots\" that you mention? I have never heard of it.\r\nSorry, it was __all__.\r\nPlease check the documentation link.\r\nhttps://docs.python.org/3/tutori... | 1,591 | 1,615 | 1,591 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4845?src=pr&el=h1) Report\n> Merging [#4845](https://codecov.io/gh/huggingface/transformers/pull/4845?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f9414f7553d3f1872b372990ef03205c0d1141df&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | MEMBER | null | When doing beam search decoding and sampling instead of argmax (edge case, probably very rarely used), we need to sample **without** replacement. This is implemented by default in torch, but not in TF, see https://pytorch.org/docs/master/generated/torch.multinomial.html#torch.multinomial (torch). An easy solution is t... | {
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https://api.github.com/repos/huggingface/transformers/issues/4844 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4844/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4844/comments | https://api.github.com/repos/huggingface/transformers/issues/4844/events | https://github.com/huggingface/transformers/issues/4844 | 634,355,930 | MDU6SXNzdWU2MzQzNTU5MzA= | 4,844 | Add support for Funnel-Transformer | {
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"Will start to look into this.",
"@sgugger Any updates on this? Thanks! ",
"The first models are uploaded and the base models are available in PyTorch (`FunnelModel` has encoder + decoder and `FunnelBaseModel` just the encoder, for sequence classification and multiple choice) in [this branch](https://github.com... | 1,591 | 1,599 | 1,599 | COLLABORATOR | null | # 🌟 New model addition
## Model description
The recently introduced Funnel-Transformer architecture and models would be a great feature for Transformers:
>Funnel-Transformer is a new self-attention model that gradually compresses the sequence of hidden states to a shorter one and hence reduces the computation... | {
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"Please refer to this issue: [https://github.com/huggingface/transformers/issues/4827](https://github.com/huggingface/transformers/issues/4827)",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contribut... | 1,591 | 1,597 | 1,597 | NONE | null | Is there any way to remove the words from the vocabulary of pretrained model? and is there a way to see the vocabulary of the model?
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"That'd be great! Do you want to open a PR? :-) \r\nI would use this line as the github line: https://github.com/ELS-RD/transformers-notebook/blob/master/Divide_Hugging_Face_Transformers_training_time_by_2_or_more.ipynb\r\n\r\nand this one as the colab notebook line:\r\nhttps://colab.research.google.com/drive/1CBfR... | 1,591 | 1,592 | 1,592 | CONTRIBUTOR | null | # 🖥 Benchmarking `transformers`
## Benchmark
This notebook is about benchmarking model training with/without dynamic padding optimization.
https://github.com/ELS-RD/transformers-notebook
**Would it be possible to add it to the [community notebook](https://github.com/huggingface/transformers/tree/master/not... | {
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"Hello! The cross entropy loss is only used if you provide the `labels` for the model to compute the loss. If you don't provide the labels, the model doesn't output any loss, only the logits!\r\n\r\nYou can then use these logits with your labels and the loss of your choosing.",
"This issue has been automatically ... | 1,591 | 1,597 | 1,597 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
I am trying to build a shipping address to geo-code predictor using RoBERTa. Here the shipping address would be the text input and the outpu... | {
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https://api.github.com/repos/huggingface/transformers/issues/4840 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4840/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4840/comments | https://api.github.com/repos/huggingface/transformers/issues/4840/events | https://github.com/huggingface/transformers/issues/4840 | 634,090,667 | MDU6SXNzdWU2MzQwOTA2Njc= | 4,840 | BUG while calculate LM loss in AlbertForMaskedLM | {
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"That's because the labels of all tokens *except* the mask tokens should be set to -100, as it's written in the [documentation](https://huggingface.co/transformers/model_doc/albert.html#albertformaskedlm).\r\n\r\nSetting these tokens to -100 will result in the cross entropy ignoring them."
] | 1,591 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
Error Code Here: https://github.com/huggingface/transformers/blob/e33fdc93b4ecb571dd7a8002a74789ec8bfffc09/src/transformers/modeling_albert.py#L822
Here calculate the loss of all tokens in a seq. While MLM actually only calculate loss on [MASK] | {
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https://api.github.com/repos/huggingface/transformers/issues/4839 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4839/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4839/comments | https://api.github.com/repos/huggingface/transformers/issues/4839/events | https://github.com/huggingface/transformers/pull/4839 | 634,004,783 | MDExOlB1bGxSZXF1ZXN0NDMwNjAzMjc5 | 4,839 | [Longformer] Remove redundant code | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4839?src=pr&el=h1) Report\n> Merging [#4839](https://codecov.io/gh/huggingface/transformers/pull/4839?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e33fdc93b4ecb571dd7a8002a74789ec8bfffc09&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | This PR fixes class LongformerSelfAttention as follow:
1. Since the method **_mask_invalid_locations()** was already run in **_sliding_chunks_matmul_qk()**, it should be removed from **forward()** to avoid code duplication.
2. In the method **_mask_invalid_locations()**, since the size of the variable **begi... | {
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https://api.github.com/repos/huggingface/transformers/issues/4838 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4838/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4838/comments | https://api.github.com/repos/huggingface/transformers/issues/4838/events | https://github.com/huggingface/transformers/issues/4838 | 633,764,413 | MDU6SXNzdWU2MzM3NjQ0MTM= | 4,838 | [Bert Model] ValueError: not enough values to unpack (expected 3, got 2) | {
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"From the first sight it seems to me you did not specify in your `config` file you want to output the hidden states. You may use these two lines of code:\r\n```\r\nconfig = BertConfig.from_pretrained( 'bert-base-uncased', output_hidden_states=True) \r\nself.bert_model = BertModel.from_pretrained('bert-base-uncas... | 1,591 | 1,635 | 1,591 | NONE | null | # 🐛 Bug: ValueError: not enough values to unpack (expected 3, got 2)
## Information
I am using Bert initialized with 'bert-base-uncased', as per the [documentation](https://huggingface.co/transformers/model_doc/bert.html), the forward step is suppose to yield 4 outputs:
- last_hidden_state
- pooler_output
- hid... | {
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https://api.github.com/repos/huggingface/transformers/issues/4837 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4837/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4837/comments | https://api.github.com/repos/huggingface/transformers/issues/4837/events | https://github.com/huggingface/transformers/pull/4837 | 633,664,541 | MDExOlB1bGxSZXF1ZXN0NDMwMjkyNDIz | 4,837 | [examples] consolidate summarization examples | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4837?src=pr&el=h1) Report\n> Merging [#4837](https://codecov.io/gh/huggingface/transformers/pull/4837?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e33fdc93b4ecb571dd7a8002a74789ec8bfffc09&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | Consolidating summarization examples of T5 & Bertabs models into one - [#3826](https://github.com/huggingface/transformers/issues/3826)
@sshleifer | {
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https://api.github.com/repos/huggingface/transformers/issues/4836 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4836/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4836/comments | https://api.github.com/repos/huggingface/transformers/issues/4836/events | https://github.com/huggingface/transformers/pull/4836 | 633,639,314 | MDExOlB1bGxSZXF1ZXN0NDMwMjY5NjY5 | 4,836 | Remove unneeded call convert_ids_to_tokens. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4836?src=pr&el=h1) Report\n> Merging [#4836](https://codecov.io/gh/huggingface/transformers/pull/4836?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac921f0385616be40adbbd5302d7f58d5c976ca8&el=desc) will **decrease... | 1,591 | 1,595 | 1,595 | NONE | null | On the base `PreTrainedTokenizer` object, calling `convert_tokens_to_string` returns an error because the method tries to call `convert_ids_to_tokens.` however the input should already be a list of tokens not ids.
I noticed this when creating a tokenizer that inherits from the Pretrained Tokenizer, and trying to tes... | {
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https://api.github.com/repos/huggingface/transformers/issues/4835 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4835/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4835/comments | https://api.github.com/repos/huggingface/transformers/issues/4835/events | https://github.com/huggingface/transformers/issues/4835 | 633,585,818 | MDU6SXNzdWU2MzM1ODU4MTg= | 4,835 | Any reason why BART does not have a ForTokenClassification variant? | {
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"No theoretical reasons, go for it!\r\n\r\n",
"@BramVanroy, did you implement BartForTokenClassification?",
"@vgaraujov Sorry, no I did not."
] | 1,591 | 1,692 | 1,591 | COLLABORATOR | null | Are there any theoretical constraints to create a ForTokenClassification variant for BART? In my current project I am using a sequence classification head + a token classification head, so I would like to implement the token classification part manually. However, since it is not implemented in the repository, I wonder ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4834 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4834/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4834/comments | https://api.github.com/repos/huggingface/transformers/issues/4834/events | https://github.com/huggingface/transformers/issues/4834 | 633,584,758 | MDU6SXNzdWU2MzM1ODQ3NTg= | 4,834 | Why init specific layers rather than whole model in BART | {
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"The line \r\n```python\r\nself.model = BartModel(config)\r\n```\r\nalready calls `init_weights`, so no need to run it twice.",
"Ah, you are of course correct. I noticed this because the other models (XXXForXXX) seem to just re-call init_weights, e.g.\r\n\r\nhttps://github.com/huggingface/transformers/blob/e33fdc... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | In BartForSequenceClassification I can see that rather than calling `self.init_weights()` (which most other models use) only specifically the classification head is initialized.
https://github.com/huggingface/transformers/blob/c58e6c129a153ca1a5021e5d7e642d00bf011e20/src/transformers/modeling_bart.py#L1046-L1047
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https://api.github.com/repos/huggingface/transformers/issues/4833 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4833/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4833/comments | https://api.github.com/repos/huggingface/transformers/issues/4833/events | https://github.com/huggingface/transformers/issues/4833 | 633,402,445 | MDU6SXNzdWU2MzM0MDI0NDU= | 4,833 | GlossBert adding | {
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" Actually it already can be loaded and seem to work in some cases,a ll i tested now. \r\n model_a = BertModel.from_pretrained(\"/folder/\")\r\n tokenizer_a = BertTokenizer.from_pretrained(\"/folder/\")",
"It can be downloaded from the link.",
"As you say, it is already available fo... | 1,591 | 1,591 | 1,591 | NONE | null | Here is a link https://github.com/HSLCY/GlossBERT - it should be able to do better for word vectors representations and there is already pretrained model than maybe need to be converted to a different format. | {
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https://api.github.com/repos/huggingface/transformers/issues/4832 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4832/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4832/comments | https://api.github.com/repos/huggingface/transformers/issues/4832/events | https://github.com/huggingface/transformers/issues/4832 | 633,322,230 | MDU6SXNzdWU2MzMzMjIyMzA= | 4,832 | Why exclude LayerNorm.bias from weight decay when finetuning? | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I have the same question",
"Check this [discussion](https://forums.fast.ai/t/is-weight-decay-applied-to-the-bias-term/73212/6)"
] | 1,591 | 1,619 | 1,597 | CONTRIBUTOR | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4831?src=pr&el=h1) Report\n> Merging [#4831](https://codecov.io/gh/huggingface/transformers/pull/4831?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c58e6c129a153ca1a5021e5d7e642d00bf011e20&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | Align how the checkpoints are managed the same way than in the PyTorch trainer. | {
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https://api.github.com/repos/huggingface/transformers/issues/4830 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4830/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4830/comments | https://api.github.com/repos/huggingface/transformers/issues/4830/events | https://github.com/huggingface/transformers/pull/4830 | 633,143,662 | MDExOlB1bGxSZXF1ZXN0NDI5ODIwNzk5 | 4,830 | Add diagnostic dataset of glue tasks for prediction | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,591 | 1,598 | 1,598 | CONTRIBUTOR | null | As diagnostic dataset didn't have train set, it's very common in current research work to use model fine tuned on MNLI task to conduct prediction of diagnostic dataset.
As experimented, by adding logic in this request, we can achieve 47.1% on diagnostic dataset after fine-tuning 10k steps on MNLI dataset. | {
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https://api.github.com/repos/huggingface/transformers/issues/4829 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4829/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4829/comments | https://api.github.com/repos/huggingface/transformers/issues/4829/events | https://github.com/huggingface/transformers/pull/4829 | 633,041,370 | MDExOlB1bGxSZXF1ZXN0NDI5NzI2NDk1 | 4,829 | [examples] Add trainer support for question-answering | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4829?src=pr&el=h1) Report\n> Merging [#4829](https://codecov.io/gh/huggingface/transformers/pull/4829?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d2a93991158f15993eba9ab421d82766b892f948&el=desc) will **increase... | 1,591 | 1,617 | 1,594 | MEMBER | null | This PR adds trainer support for question-answering task. Regarding issue #4784
**TODOs**
- [ ] Add automatic data loading. Right now it requires the user to specify data directory. Decided not to use `tfds` because I think it will be soon replaced by `nlp` here
- [ ] Add evaluation
- [ ] Test all models.
@ju... | {
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https://api.github.com/repos/huggingface/transformers/issues/4828 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4828/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4828/comments | https://api.github.com/repos/huggingface/transformers/issues/4828/events | https://github.com/huggingface/transformers/issues/4828 | 633,005,718 | MDU6SXNzdWU2MzMwMDU3MTg= | 4,828 | `run_glue.py` fails with models `bert-base-cased`, `distil-bert-cased`, others | {
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"update: this also happens with `distil-bert-cased` for `RTE` and `WNLI` tasks:\r\n\r\n```\r\nds) # (bs, seq_length, dim)\r\n File \"/u/.conda/envs/torch/lib/python3.7/site-packages/torch/nn/modules/module.py\", line 532, in __call__\r\n result = self.forward(*input, **kwargs)\r\n File \"/u/.conda/envs/torch/... | 1,591 | 1,630 | 1,598 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): `bert-base-cased`
Language I am using the model on (English, Chinese ...): `English`
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am wor... | {
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https://api.github.com/repos/huggingface/transformers/issues/4827 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4827/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4827/comments | https://api.github.com/repos/huggingface/transformers/issues/4827/events | https://github.com/huggingface/transformers/issues/4827 | 633,002,282 | MDU6SXNzdWU2MzMwMDIyODI= | 4,827 | How to remove token ? | {
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"From what I can observe, there are two types of tokens in your tokenizer: base tokens, which can be derived with `tokenizer.encoder` and the added ones: `tokenizer.added_tokens_encoder`. Depending on which token you want to remove, you use `del tokenizer.encoder` or `del tokenizer.added_tokens_encoder`. \r\n¡NB! D... | 1,591 | 1,641 | 1,597 | NONE | null | I only know how to add token, but how to remoce some special token | {
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https://api.github.com/repos/huggingface/transformers/issues/4826 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4826/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4826/comments | https://api.github.com/repos/huggingface/transformers/issues/4826/events | https://github.com/huggingface/transformers/pull/4826 | 632,908,206 | MDExOlB1bGxSZXF1ZXN0NDI5NjAzNzQ2 | 4,826 | Fix use of mems in Transformer-XL text generation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4826?src=pr&el=h1) Report\n> Merging [#4826](https://codecov.io/gh/huggingface/transformers/pull/4826?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c58e6c129a153ca1a5021e5d7e642d00bf011e20&el=desc) will **increase... | 1,591 | 1,594 | 1,593 | CONTRIBUTOR | null | In Transformer-XL, when ```mems``` is being used to save computation with the ```generate``` function, the inputs are not properly truncated, so that ```mems``` does not actually speed things up, and also seems to create inaccuracies in the output. I have attempted to fix this by changing Transformer-XL's ```prepare_in... | {
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https://api.github.com/repos/huggingface/transformers/issues/4825 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4825/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4825/comments | https://api.github.com/repos/huggingface/transformers/issues/4825/events | https://github.com/huggingface/transformers/issues/4825 | 632,814,781 | MDU6SXNzdWU2MzI4MTQ3ODE= | 4,825 | Onnx converted model has its output shape modified when compared to original (finetuned) model | {
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"Facing the same problem with a BERT model fine-tuned on sequence classification and would love to get an answer :) ",
"This seems to be related to [this issue](https://github.com/huggingface/transformers/issues/4788). \r\n\r\nAs @hrsmanian points it, it seems that in[ convert_graph_to_onnx.py](https://github.com... | 1,591 | 1,647 | 1,595 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): `mrm8488/distilroberta-base-finetuned-sentiment` from the hub
Language I am using the model on (English, Chinese ...): `English`
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X] my own modified scripts... | {
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https://api.github.com/repos/huggingface/transformers/issues/4824 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4824/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4824/comments | https://api.github.com/repos/huggingface/transformers/issues/4824/events | https://github.com/huggingface/transformers/issues/4824 | 632,797,782 | MDU6SXNzdWU2MzI3OTc3ODI= | 4,824 | Top-k sampling and top-p sampling for generating phrases on batches with GPT-2? | {
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"It's on our ToDo-List :-) Currently batch generation with GPT2 is not possible, so you will have to rely on the code in https://github.com/huggingface/transformers/issues/3021",
"Can top-k and top-p sampling be implemented in batches?",
"Sure, the provided `top-k-top-p sampling` function provided that :-) "
] | 1,591 | 1,591 | 1,591 | NONE | null | How can I generate on batches with GPT-2 if I want to make use of these awesome sampling techniques: [top-k sampling and top-p sampling](https://huggingface.co/blog/how-to-generate)?.
There is this implementation for generating phrases on batches already in issue [#3021](https://github.com/huggingface/transformers/... | {
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https://api.github.com/repos/huggingface/transformers/issues/4823 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4823/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4823/comments | https://api.github.com/repos/huggingface/transformers/issues/4823/events | https://github.com/huggingface/transformers/issues/4823 | 632,792,540 | MDU6SXNzdWU2MzI3OTI1NDA= | 4,823 | Discriminative fine-tuning for new (added) words | {
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"Finally found the solution. The optimizer should look like this:\r\n```\r\noptim.SGD([\r\n {'params': model.base.parameters()},\r\n {'params': model.classifier.parameters(), 'lr': 1e-3}\r\n], lr=1e-2, momentum=0.9))\r\n```",
"However, this approach does not work when I need to specify another LR not for th... | 1,591 | 1,597 | 1,597 | CONTRIBUTOR | null | Good afternoon,
I have a question about the way of changing the learning rate for some parameters of the model. Let's say we have a BERT model and we have added a few new tokens. Consequently, we need to resize the embedding layer and initialize the embeddings for new words randomly. Meanwhile the learning rate of 3e-... | {
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"Could you please provide the whole code you use? Your structure works ideally for me, this code outputs the same values:\r\n```\r\nfrom transformers import EncoderDecoderModel, BertTokenizer\r\nimport torch\r\ntokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\r\n\r\nmodel = EncoderDecoderModel.from_en... | 1,591 | 1,591 | 1,591 | NONE | null | # 🐛 Bug in EncoderDecoderModel
I am using EncoderDecoderModel and I have tested the sample code of it which is written in its page.
```
from transformers import EncoderDecoderModel, BertTokenizer
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = EncoderDecoderModel.from_encoder_decoder_... | {
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https://api.github.com/repos/huggingface/transformers/issues/4821 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4821/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4821/comments | https://api.github.com/repos/huggingface/transformers/issues/4821/events | https://github.com/huggingface/transformers/pull/4821 | 632,736,979 | MDExOlB1bGxSZXF1ZXN0NDI5NDQ3MzA2 | 4,821 | Enable multiprocessing in glue datasets | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4821?src=pr&el=h1) Report\n> Merging [#4821](https://codecov.io/gh/huggingface/transformers/pull/4821?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c58e6c129a153ca1a5021e5d7e642d00bf011e20&el=desc) will **increase... | 1,591 | 1,592 | 1,592 | NONE | null | The preprocessing of glue datasets is too slow. This change enables multiprocessing to speed up the process of converting examples to features by utilizing multiple cpu cores. | {
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