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https://api.github.com/repos/huggingface/transformers/issues/11035 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11035/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11035/comments | https://api.github.com/repos/huggingface/transformers/issues/11035/events | https://github.com/huggingface/transformers/issues/11035 | 848,976,468 | MDU6SXNzdWU4NDg5NzY0Njg= | 11,035 | 404 Client Error: Not Found for url: https://huggingface.co/%5CHuggingface-Sentiment-Pipeline/resolve/main/config.json | {
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"Are you able to successfully load your model with e.g. `AutoModel.from_pretrained(local_path)`?",
"> Are you able to successfully load your model with e.g. `AutoModel.from_pretrained(local_path)`?\r\n\r\nNo, same error.",
"Hi @nithinreddyy, could you share information about your setup so that we may investigat... | 1,617 | 1,620 | 1,620 | NONE | null | I'm trying to use the hugging face sentimet-analysis pipeline. I've downloaded the pipeline using save.pretrained(model). And trying to load the pipeline with the help of below code
```
from transformers import pipeline
model = '\Huggingface-Sentiment-Pipeline'
classifier = pipeline(task='sentiment-analysis', mod... | {
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https://api.github.com/repos/huggingface/transformers/issues/11034 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11034/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11034/comments | https://api.github.com/repos/huggingface/transformers/issues/11034/events | https://github.com/huggingface/transformers/issues/11034 | 848,939,310 | MDU6SXNzdWU4NDg5MzkzMTA= | 11,034 | GPT-2 example is broken? | {
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"Hi! Sorry to hear the example doesn't work well for you. To be honest, it doesn't really make sense to try and generate a single token like it is done in that example. I have slightly modified the example so that it generates the 20 following tokens.\r\n\r\nAlso, I've removed the space at the end of the sequence b... | 1,617 | 1,617 | 1,617 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: I have had this issue with both 4.3.0 and 4.4.2 (and probably other versions as well)
- Python version: 3.7.6
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11033 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11033/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11033/comments | https://api.github.com/repos/huggingface/transformers/issues/11033/events | https://github.com/huggingface/transformers/issues/11033 | 848,936,573 | MDU6SXNzdWU4NDg5MzY1NzM= | 11,033 | RuntimeError: The size of tensor a (1024) must match the size of tensor b (1025) at non-singleton dimension 3 | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,661 | 1,620 | NONE | null | Here I try to use gpt2 to generation the text under the prompt text. I have several datasets, some of them, such as AG_NEWS and POP_NEWS, are made of short sentences while when I use YAHOO_NEWS, consisting of longer sentences, the error came out.
Anything to modify for my codes?
Thanks.
```
from transformers imp... | {
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https://api.github.com/repos/huggingface/transformers/issues/11032 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11032/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11032/comments | https://api.github.com/repos/huggingface/transformers/issues/11032/events | https://github.com/huggingface/transformers/issues/11032 | 848,921,982 | MDU6SXNzdWU4NDg5MjE5ODI= | 11,032 | How to get masked word prediction for other languages | {
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"You can filter the model hub on 'ru' (Russian) and 'fill-mask' (masked language modeling): https://huggingface.co/models?filter=ru&pipeline_tag=fill-mask\r\n\r\nrobert-base was trained on English text only, so it will not work for Russian. \r\n\r\nMaybe a good choice is this model: https://huggingface.co/blinoff/r... | 1,617 | 1,620 | 1,620 | NONE | null | Hello,
I trying to get masked words predictions for languages except English with Roberta or XLM Roberta.
```
from transformers import pipeline
nlp = pipeline("fill-mask", model="roberta-base")
template = f"That woman is {nlp.tokenizer.mask_token}."
output = nlp(template)
nlp4 = pipeline("fill-mask", model... | {
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https://api.github.com/repos/huggingface/transformers/issues/11031 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11031/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11031/comments | https://api.github.com/repos/huggingface/transformers/issues/11031/events | https://github.com/huggingface/transformers/issues/11031 | 848,921,632 | MDU6SXNzdWU4NDg5MjE2MzI= | 11,031 | Roberta and XLNet sentence pair training example | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,617 | 1,617 | 1,617 | NONE | null | I want to use RoBERTa and XLNet for sentence pair input task (like sentence similarity task pair input). Can you explain with code example? | {
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https://api.github.com/repos/huggingface/transformers/issues/11030 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11030/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11030/comments | https://api.github.com/repos/huggingface/transformers/issues/11030/events | https://github.com/huggingface/transformers/issues/11030 | 848,823,702 | MDU6SXNzdWU4NDg4MjM3MDI= | 11,030 | pipeline.from_pretrained | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,619 | 1,619 | CONTRIBUTOR | null | # 🚀 Feature request
Nearly everyone who is using the transformers library is aware of the `from_pretrained()` and `save_pretrained()` concept. The [Pipeline class](https://huggingface.co/transformers/main_classes/pipelines.html#parent-class-pipeline) is currently only providing the `save_pretrained()` method which ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11029 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11029/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11029/comments | https://api.github.com/repos/huggingface/transformers/issues/11029/events | https://github.com/huggingface/transformers/pull/11029 | 848,798,224 | MDExOlB1bGxSZXF1ZXN0NjA3Njc4Nzg3 | 11,029 | Documentation about loading a fast tokenizer within Transformers | {
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"Thanks for the suggestion @sgugger!"
] | 1,617 | 1,617 | 1,617 | MEMBER | null | This PR does two things:
- Allows to load a fast tokenizer from an instantiated `tokenizers` object
- Adds a page to document how to use these tokenizers within `transformers`
See [here](https://190138-155220641-gh.circle-artifacts.com/0/docs/_build/html/fast_tokenizers.html) for the generated docs | {
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https://api.github.com/repos/huggingface/transformers/issues/11028 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11028/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11028/comments | https://api.github.com/repos/huggingface/transformers/issues/11028/events | https://github.com/huggingface/transformers/issues/11028 | 848,769,061 | MDU6SXNzdWU4NDg3NjkwNjE= | 11,028 | Fine Tune GPT-NEO 2.7B | {
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"Did you try to use `run_clm.py`?",
"@LysandreJik Yea, it's working. But i cannot fine-tune it using \"GPU\" in colab and the \"TPU\" gives me this error ```exception: process 0 terminated with signal SIGKILL```, I tried the solutions in the issues but still ",
"SIGKILL is probably an out of memory error, mean... | 1,617 | 1,620 | 1,620 | NONE | null | Hello to everyone, is there a script to fine tune this new model?
Thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/11027 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11027/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11027/comments | https://api.github.com/repos/huggingface/transformers/issues/11027/events | https://github.com/huggingface/transformers/pull/11027 | 848,767,936 | MDExOlB1bGxSZXF1ZXN0NjA3NjUzMTAy | 11,027 | Refactor AutoModel classes and add Flax Auto classes | {
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This PR refactors the logic behind all the Auto model classes in one function that automatically builds those classes from a template. In passing, it uses this new function to build the auto classes for FLAX (at least the ones that have at least one model implemented). | {
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https://api.github.com/repos/huggingface/transformers/issues/11026 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11026/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11026/comments | https://api.github.com/repos/huggingface/transformers/issues/11026/events | https://github.com/huggingface/transformers/pull/11026 | 848,754,983 | MDExOlB1bGxSZXF1ZXN0NjA3NjQyMjM1 | 11,026 | Add `examples/language_modeling/run_clm_no_trainer.py` | {
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"@sgugger Awesome, I'll create a new PR for it.",
"Merging this one then, thanks again!"
] | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11025 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11025/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11025/comments | https://api.github.com/repos/huggingface/transformers/issues/11025/events | https://github.com/huggingface/transformers/pull/11025 | 848,727,782 | MDExOlB1bGxSZXF1ZXN0NjA3NjE5NzY0 | 11,025 | fixed typo: logging instead of logger | {
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https://api.github.com/repos/huggingface/transformers/issues/11024 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11024/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11024/comments | https://api.github.com/repos/huggingface/transformers/issues/11024/events | https://github.com/huggingface/transformers/pull/11024 | 848,717,134 | MDExOlB1bGxSZXF1ZXN0NjA3NjEwNjQ1 | 11,024 | Add a script to check inits are consistent | {
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Most inits in the project define the same objects twice (once in `_import_structure` and once in TYPE_CHECKING) to have a fast import so objects are only grabbed when actually needed. The problem is that those two halves have a tendency to diverge as contributors do not always pay attention t... | {
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https://api.github.com/repos/huggingface/transformers/issues/11023 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11023/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11023/comments | https://api.github.com/repos/huggingface/transformers/issues/11023/events | https://github.com/huggingface/transformers/issues/11023 | 848,680,168 | MDU6SXNzdWU4NDg2ODAxNjg= | 11,023 | Strange ValueError with GPT-2 | {
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"Hi, could you give a reproducible code example?",
"With pleasure!\r\n\r\n```\r\nimport tensorflow as tf\r\nfrom transformers import GPT2Config, TFGPT2LMHeadModel\r\nimport numpy as np\r\n\r\n# Prepare the dataset.\r\ninputs = np.random.randint(0, 128, (1025, 256))\r\nlabels = np.random.randint(0, 128, (1025, 256... | 1,617 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.8.6
- PyTorch version (GPU?): 1.7.1 (F... | {
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https://api.github.com/repos/huggingface/transformers/issues/11022 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11022/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11022/comments | https://api.github.com/repos/huggingface/transformers/issues/11022/events | https://github.com/huggingface/transformers/issues/11022 | 848,679,174 | MDU6SXNzdWU4NDg2NzkxNzQ= | 11,022 | cannot import name 'AutoModelForSequenceClassification' from 'transformers' | {
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"Please tell us which version you are using and also check [your SO question](https://stackoverflow.com/questions/66906652/how-to-download-hugging-face-sentiment-analysis-pipeline-to-use-it-offline/66907181#comment118269245_66907181) again because it was revised.\r\n\r\n",
"This issue has been automatically marke... | 1,617 | 1,696 | 1,620 | NONE | null | ```
from transformers import pipeline
classifier = pipeline('sentiment-analysis') #This code will download the pipeline
classifier('We are very happy to show you the 🤗 Transformers library.')
classifier.save_pretrained('/some/directory')
```
I'm trying to save the model and trying to perform the sentiment-ana... | {
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https://api.github.com/repos/huggingface/transformers/issues/11021 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11021/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11021/comments | https://api.github.com/repos/huggingface/transformers/issues/11021/events | https://github.com/huggingface/transformers/issues/11021 | 848,651,434 | MDU6SXNzdWU4NDg2NTE0MzQ= | 11,021 | Module Not found: datasets_modules.datasets.output | {
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"@ashleylew were you able to fix this? Could you please share what did?\r\n",
"I was just loading the data incorrectly. I misunderstood how to load custom data in and was treating it like one of Hugging Face's datasets rather than a custom one, but once I fixed that, everything was fine! I can give more details i... | 1,617 | 1,618 | 1,617 | NONE | null | ## Environment info
- `transformers` version: 4.5.0.dev0
- Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: not sure
- Using distributed or parallel set-up in... | {
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https://api.github.com/repos/huggingface/transformers/issues/11020 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11020/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11020/comments | https://api.github.com/repos/huggingface/transformers/issues/11020/events | https://github.com/huggingface/transformers/issues/11020 | 848,566,666 | MDU6SXNzdWU4NDg1NjY2NjY= | 11,020 | Trainer API crashes GPUs | {
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"Hi! This is a weird error, I haven't seen it before. I don't know how you've setup your installation and which CUDA version is torch using, but I believe it still has incompatibilities with CUDA 11.2. If you installed it as a wheel I think CUDA is included and it doesn't really matter, but as the only thing I see ... | 1,617 | 1,623 | 1,623 | NONE | null | ## Environment info
- `transformers` version: 4.5.0.dev0
- Platform: Ubuntu 20.04.2 LTS
- Python version: Python 3.8.5
- PyTorch version (GPU?): 1.7.1
- Tensorflow version (GPU?): 2.4.1
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: Yes
My scripts that use Trainer API crash G... | {
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https://api.github.com/repos/huggingface/transformers/issues/11019 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11019/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11019/comments | https://api.github.com/repos/huggingface/transformers/issues/11019/events | https://github.com/huggingface/transformers/issues/11019 | 848,543,462 | MDU6SXNzdWU4NDg1NDM0NjI= | 11,019 | Enable multiple `eval_dataset` in `Trainer` API | {
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"cc @sgugger ",
"This would require quite a lot of changes in the main Trainer for a use case that is a bit unique. You should subclass the `Trainer` for this problem and just add a second `evaluate` in the training loop for your second dataset.",
"@sgugger thanks for the reply! Any chance you could provide a l... | 1,617 | 1,617 | null | NONE | null | # 🚀 Feature request
Allow for two or more (equally long) validation sets to be passed to the `Trainer` API which are evaluated sequentially each `eval_steps`.
## Motivation
You can find my motivation in this [thread](https://discuss.huggingface.co/t/use-trainer-api-with-two-valiation-sets/5212) and the refere... | {
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https://api.github.com/repos/huggingface/transformers/issues/11018 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11018/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11018/comments | https://api.github.com/repos/huggingface/transformers/issues/11018/events | https://github.com/huggingface/transformers/issues/11018 | 848,537,240 | MDU6SXNzdWU4NDg1MzcyNDA= | 11,018 | T5 documentation for computing pretraining loss seems to have a mistake | {
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"Hey @dorost1234,\r\n\r\nyou're right to be fully correct we should set the `<extra_id_0>` to `-100`. Maybe we could add the following lines to the doc\r\n\r\n```python\r\n# make sure no loss is computed on sentinel tokens. Sentinel tokens are in `additional_special_tokens`.\r\nlabels = [label if label not in token... | 1,617 | 1,621 | 1,621 | NONE | null | Dear @patrickvonplaten
The documentation of T5 for computing loss of pretraining seems to have a mistake, where it talks on the loss formulation:
https://huggingface.co/transformers/model_doc/t5.html?highlight=decoder_input_ids
```
input_ids = tokenizer('The <extra_id_0> walks in <extra_id_1> park', return_te... | {
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https://api.github.com/repos/huggingface/transformers/issues/11017 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11017/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11017/comments | https://api.github.com/repos/huggingface/transformers/issues/11017/events | https://github.com/huggingface/transformers/issues/11017 | 848,524,306 | MDU6SXNzdWU4NDg1MjQzMDY= | 11,017 | Cannot run the gpt neo 2.7B example | {
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"Hi @donno2048. the GPT Neo is available on the master branch, and is not yet in a release. I invite you to install transformers from source, with the following:\r\n```\r\npip install git+https://github.com/huggingface/transformers\r\n```",
"Thanks",
"Does the min_length param work for you? I do the same as abo... | 1,617 | 1,622 | 1,617 | NONE | null | ## Environment info
- `transformers` version: 4.4.2
- Platform: Windows and Linux (using wsl)
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.1+cpu (False)
- Tensorflow version (GPU?): 2.4.1 (False)
Library:
- text generation: @patrickvonplaten
- pipelines: @LysandreJik
## Information
When runni... | {
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https://api.github.com/repos/huggingface/transformers/issues/11016 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11016/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11016/comments | https://api.github.com/repos/huggingface/transformers/issues/11016/events | https://github.com/huggingface/transformers/issues/11016 | 848,490,060 | MDU6SXNzdWU4NDg0OTAwNjA= | 11,016 | Add new CANINE model | {
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"Update on that: model and checkpoints are released:\r\n\r\nhttps://github.com/google-research/language/tree/master/language/canine\r\n\r\n:hugs: ",
"Hi @stefan-it, thanks for the update.\r\nDo you know how we can use those pre-trained tensorflow checkpoints to get the pooled text representations from CANINE mode... | 1,617 | 1,625 | 1,625 | COLLABORATOR | null | # 🌟 New model addition
## Model description
Google recently proposed a new **C**haracter **A**rchitecture with **N**o tokenization **I**n **N**eural **E**ncoders architecture (CANINE). Not only the title is exciting:
> Pipelined NLP systems have largely been superseded by end-to-end neural modeling, yet nearl... | {
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https://api.github.com/repos/huggingface/transformers/issues/11015 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11015/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11015/comments | https://api.github.com/repos/huggingface/transformers/issues/11015/events | https://github.com/huggingface/transformers/pull/11015 | 848,392,439 | MDExOlB1bGxSZXF1ZXN0NjA3MzM3OTc2 | 11,015 | added new notebook and merge of trainer | {
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* Adds a new Notebook for SageMaker
* Adjusts documentation for the latest merge of `SageMakerTrainer` and `Trainer` | {
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https://api.github.com/repos/huggingface/transformers/issues/11014 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11014/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11014/comments | https://api.github.com/repos/huggingface/transformers/issues/11014/events | https://github.com/huggingface/transformers/issues/11014 | 848,375,119 | MDU6SXNzdWU4NDgzNzUxMTk= | 11,014 | OSError: Can't load config for '/content/wav2vec2-large-xlsr-asr-demo'. Make sure that: | {
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"Can you `ls` what's in `/content/wav2vec2-large-xlsr-asr-demo`?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](htt... | 1,617 | 1,620 | 1,620 | NONE | null | I'm using
pip install transformers==4.4.2
After completing the training process of ASR I can not read the trained file from my local storage. Although the path is right. But can read from hugging face
model = Wav2Vec2ForCTC.from_pretrained("/content/wav2vec2-large-xlsr-asr-demo").to("cuda")
The error:
OS... | {
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https://api.github.com/repos/huggingface/transformers/issues/11013 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11013/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11013/comments | https://api.github.com/repos/huggingface/transformers/issues/11013/events | https://github.com/huggingface/transformers/issues/11013 | 848,349,453 | MDU6SXNzdWU4NDgzNDk0NTM= | 11,013 | use `BaseModelOutput` as common interface for all different `BaseModelOutputWith*`? | {
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I have been taking a look at the `different` output models from your models, and I wonder if it would make sense to inherit all the `BaseModelOutputWithPool` and all the other flavours of modeling output, instead of using `ModelOutput`.
https://github.com/huggingface/transformers/blob/c301c26370dfa48f... | {
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https://api.github.com/repos/huggingface/transformers/issues/11012 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11012/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11012/comments | https://api.github.com/repos/huggingface/transformers/issues/11012/events | https://github.com/huggingface/transformers/pull/11012 | 848,275,273 | MDExOlB1bGxSZXF1ZXN0NjA3MjM3OTQ4 | 11,012 | Add multi-class, multi-label and regression to transformers | {
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https://api.github.com/repos/huggingface/transformers/issues/11011 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11011/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11011/comments | https://api.github.com/repos/huggingface/transformers/issues/11011/events | https://github.com/huggingface/transformers/issues/11011 | 848,073,466 | MDU6SXNzdWU4NDgwNzM0NjY= | 11,011 | a memory leak in evaluation | {
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"Which model are you using? There is no reason the predictions for QQP should OOM even your GPU, unless the model is outputting more than the logits.",
"Thank you very much for your reply! My model config is as below:\r\n```JSON\r\n{\r\n \"architectures\": [\r\n \"AlbertForMaskedLM\"\r\n ],\r\n \"attention_... | 1,617 | 1,617 | 1,617 | NONE | null | ## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Linux-3.10.0-957.el7.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.7.1+cu101 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: True
- Using distributed or parallel set-up in scri... | {
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https://api.github.com/repos/huggingface/transformers/issues/11010 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11010/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11010/comments | https://api.github.com/repos/huggingface/transformers/issues/11010/events | https://github.com/huggingface/transformers/issues/11010 | 848,030,700 | MDU6SXNzdWU4NDgwMzA3MDA= | 11,010 | run_seq2seq.py meet bug in using huggingface datasets billsum | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,620 | 1,620 | NONE | null | run code below
```shell
python examples/seq2seq/run_seq2seq_tune.py --model_name_or_path /home2/zhenggo1/checkpoint/pegasus_billsum --do_eval --task summarization_billsum --dataset_name billsum --output_dir /home2/zhenggo1/checkpoint/pegasus_billsum --per_device_train_batch_size=8 --per_device_eval_batch_size=8 --pre... | {
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https://api.github.com/repos/huggingface/transformers/issues/11009 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11009/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11009/comments | https://api.github.com/repos/huggingface/transformers/issues/11009/events | https://github.com/huggingface/transformers/issues/11009 | 847,973,413 | MDU6SXNzdWU4NDc5NzM0MTM= | 11,009 | How to load weights from a private server? | {
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"My workaround was to manually download checkpoints using `cached_file` function to local, and instantiate a model from the download file using `from_pretrained`.",
"Yes that's indeed the preferred workaround. Thanks!"
] | 1,617 | 1,618 | 1,618 | CONTRIBUTOR | null | Hi, thank you for the great library!
I am trying instantiate a model with weights uploaded on my private server. By looking at [`is_remote_url`](https://github.com/huggingface/transformers/blob/8780caa388c7b2aa937454ed96bcdd3f097f851d/src/transformers/modeling_utils.py#L1011) function, it seems that transformers su... | {
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https://api.github.com/repos/huggingface/transformers/issues/11008 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11008/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11008/comments | https://api.github.com/repos/huggingface/transformers/issues/11008/events | https://github.com/huggingface/transformers/issues/11008 | 847,776,651 | MDU6SXNzdWU4NDc3NzY2NTE= | 11,008 | error: fine-tunes language model with added_tokens | {
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"Could you share the command you are using to launch the script? I'm trying to reproduce but it works fine for me.\r\nAlso your error seems like a CUDA setup error, so is the script running properly without the change?",
"@sgugger \r\n\r\n```\r\nexport BASE_PATH=/data/huyong/code/socialbert\r\nexport CUDA_VISIBLE... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: version: 4.3.3
- Platform: Linux-4.15.0-29-generic-x86_64-with-debian-stretch-sid
- Python version: 3.6.9
- ... | {
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"Hi, could you provide the location of the wrong links? Without additional information we cannot help you.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do no... | 1,617 | 1,620 | 1,620 | NONE | null | i can't download the file" convert_tf_checkpoint_to_pytorch.py" and three other .py file that you set a hyperlink on it. if i click on the link it notice me: 404. Where can i get them? thank you! | {
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https://api.github.com/repos/huggingface/transformers/issues/11006 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11006/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11006/comments | https://api.github.com/repos/huggingface/transformers/issues/11006/events | https://github.com/huggingface/transformers/issues/11006 | 847,755,321 | MDU6SXNzdWU4NDc3NTUzMjE= | 11,006 | "Converting Tensorflow Checkpoints" meets ('Pointer shape torch.Size([312]) and array shape (128,) mismatched', torch.Size([312]), (128,)) | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,620 | 1,620 | NONE | null | when "Converting Tensorflow Checkpoints", I see this "Pointer shape {pointer.shape} and array shape {array.shape} mismatched"
AssertionError: ('Pointer shape torch.Size([312]) and array shape (128,) mismatched', torch.Size([312]), (128,)), and the pretrainmodel comes from https://github.com/ZhuiyiTechnology/pretrained... | {
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https://api.github.com/repos/huggingface/transformers/issues/11005 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11005/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11005/comments | https://api.github.com/repos/huggingface/transformers/issues/11005/events | https://github.com/huggingface/transformers/issues/11005 | 847,400,200 | MDU6SXNzdWU4NDc0MDAyMDA= | 11,005 | ReduceLROnPlateau-like functionality? | {
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<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
**Description:** Dynamic learning rate reduction upon metric saturation, as in `torch.optim.lr_scheduler.ReduceLROnPlateau`, integrated into the `Trainer` AP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11004 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11004/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11004/comments | https://api.github.com/repos/huggingface/transformers/issues/11004/events | https://github.com/huggingface/transformers/issues/11004 | 847,393,804 | MDU6SXNzdWU4NDczOTM4MDQ= | 11,004 | Getting `raise NotImplementedError` for base_model.get_input_embeddings() when upgrading from pytorch-transformers | {
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"Hello! Do you have a reproducible code example so that we can try to understand what's happening here? Thank you!",
"I have generated a simplified version of the original Oscar (https://github.com/microsoft/Oscar) codebase here - https://github.com/gsrivas4/Oscar_latest. The branch `old_transformers` -https://gi... | 1,617 | 1,620 | 1,620 | NONE | null | # 📚 Migration
## Information
<!-- Important information -->
Getting `raise NotImplementedError` at
the lines - https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_utils.py#L474-L477 when I am trying to upgrade my code from pytorch-transformers to transformers
Model I am using... | {
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https://api.github.com/repos/huggingface/transformers/issues/11003 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11003/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11003/comments | https://api.github.com/repos/huggingface/transformers/issues/11003/events | https://github.com/huggingface/transformers/issues/11003 | 847,294,653 | MDU6SXNzdWU4NDcyOTQ2NTM= | 11,003 | conda install transformers (not working) behaving differently from pip install transformers (working) for CentOS 7.9 | {
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"Hello! From what I'm seeing, the error comes from the `tokenizers` library instead:\r\n```\r\n[...]\r\n File \"/homes/gws/hcybay/miniconda3/envs/test2/lib/python3.8/site-packages/transformers-4.4.2-py3.8.egg/transformers/tokenization_utils_fast.py\", line 25, in <module>\r\n File \"/homes/gws/hcybay/miniconda3/e... | 1,617 | 1,617 | 1,617 | NONE | null | A fresh environment where I `conda install pytorch torchvision torchaudio -c pytorch` then `conda install transformers` produces a glibc2.18 error on CentOS 7.9 upon import with `python -c "from transformers import AutoTokenizer"`. I suspect this is a similar error to #2980, i.e., CentOS 7.9 might just be incompatible.... | {
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https://api.github.com/repos/huggingface/transformers/issues/11002 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11002/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11002/comments | https://api.github.com/repos/huggingface/transformers/issues/11002/events | https://github.com/huggingface/transformers/issues/11002 | 847,229,369 | MDU6SXNzdWU4NDcyMjkzNjk= | 11,002 | KeyError: 'gpt_neo' with EleutherAI/gpt-neo-1.3B | {
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"Hello! GPT Neo is available on the master branch, while you're installing the version v4.2.2.\r\n\r\nYou should change `pip install transformers` to `pip install git+https://github.com/huggingface/transformers` and reload your kernel",
"Doing so results in this error: \r\n\r\n```\r\n>>> generator = pipeline('tex... | 1,617 | 1,642 | 1,617 | NONE | null | I am trying to try new GPT-3 checkpoint however I am getting an error on local and Google Colab platform as well.
Google Colab:
```
!pip install transformers
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B")
model = AutoModelF... | {
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https://api.github.com/repos/huggingface/transformers/issues/11001 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11001/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11001/comments | https://api.github.com/repos/huggingface/transformers/issues/11001/events | https://github.com/huggingface/transformers/pull/11001 | 847,097,736 | MDExOlB1bGxSZXF1ZXN0NjA2MTM2NzQ2 | 11,001 | Add `examples/language_modeling/run_mlm_no_trainer.py` | {
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"Thanks again!",
"How to distributed training?~~~ In no trainer mlm",
"The same way as any other scripts: `python -m torch.distributed.launch --nproc_per_node xxx run_mlm_no_trainer.py --script_args`.",
"hello@sgugger , when I used multi-gpu, I got this error message:\r\n(basic_dl) root@PM00011093:/data/zhaoy... | 1,617 | 1,621 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
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## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#star... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,620 | 1,620 | NONE | null | It appears the current ROUGE metric computes the score with 1 reference per candidate. I was wondering if there is way to compute ROUGE with multiple references per candidate? Thanks | {
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"Hi @mandareln \r\n\r\nYou should use `BertLMHeadModel` class if you want to use bert as decoder, here you are using `BertForMaskedLM` which is the reason for this error as it does not have the `use_cache` argument.",
"This issue has been automatically marked as stale because it has not had recent activity. If yo... | 1,617 | 1,621 | 1,621 | NONE | null | Hi
I am trying to create an EncoderDecoder model where i want to use a pre-trained encoder model and initialise decoder from scratch. Following the code snippet.
----------------------------------------------------------
encoder = AutoModel.from_pretrained('bert-base-uncased')
decoder_config = BertConfig(vocab... | {
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"cc @sgugger "
] | 1,617 | 1,617 | 1,617 | MEMBER | null | # What does this PR do?
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"You're doing something wrong here:\r\n```py\r\nlogits, past = model(myinput, past_key_values = past)\r\n```\r\n\r\nThe model returns a dict. Your `logits` and `past` are the keys of the dicts.\r\n\r\nIf you want the values, then either do:\r\n```py\r\noutput = model(myinput, past_key_values = past)\r\nlogits = out... | 1,617 | 1,620 | 1,620 | NONE | null |
This code is supposed to generate the next most probable word. However, the following problem arises.
```
!pip install git+https://github.com/huggingface/transformers.git
import torch
from transformers import GPTNeoForCausalLM, AutoTokenizer
model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
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Fixes https://github.com/huggingface/transformers/issues/10990 | {
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Fix example in doc
Thanks a lot for spotting this @NielsRogge
cc @LysandreJik | {
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This PR fixes that! | {
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"For running conversion script for `BigBirdPegasus`:\r\n\r\n```shell\r\npython3 src/transformers/models/bigbird_pegasus/convert_bigbird_pegasus_tf_to_pytorch.py --tf_ckpt_path src/tf_ckpt/bigbird-pegasus-large-arxiv/model.ckpt-300000 --save_dir src/google/bigbird-pegasus-large-arxiv\r\n```\r\n\r\nFor running conver... | 1,617 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
This PR will add Google's BigBird-Pegasus. Extending #10183
Following checkpoints will be added:
- [x] [bigbird-pegasus-large-pubmed](https://huggingface.co/google/bigbird-pegasus-large-pubmed)
- [x] [bigbird-pegasus-large-arxiv](https://huggingface.co/google/bigbird-pegasus-large-arxiv)... | {
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"Hi @shon-otmazgin, here's the model: https://huggingface.co/kssteven/ibert-roberta-base\r\n\r\nThe documentation is unfortunately wrong. I'm updating it.",
"Fixing it in https://github.com/huggingface/transformers/pull/10994",
"Hello @LysandreJik, \r\nWe should specify `kssteven/ibert-roberta-base` in `from_p... | 1,617 | 1,617 | 1,617 | NONE | null | ## Environment info
- `transformers` version: 4.4.2
- Platform: Linux-4.15.0-1109-azure-x86_64-with-Ubuntu-16.04-xenial
- Python version: 3.6.13
- PyTorch version (GPU?): 1.4.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10989 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10989/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10989/comments | https://api.github.com/repos/huggingface/transformers/issues/10989/events | https://github.com/huggingface/transformers/pull/10989 | 846,367,862 | MDExOlB1bGxSZXF1ZXN0NjA1NDY4Nzkw | 10,989 | Fixed some typos and removed legacy url | {
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"Thanks a lot for doing this!"
] | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
Removed legacy url to colab notebook in examples/multiple-choice/README.md
Fixed some typos.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/... | {
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https://api.github.com/repos/huggingface/transformers/issues/10988 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10988/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10988/comments | https://api.github.com/repos/huggingface/transformers/issues/10988/events | https://github.com/huggingface/transformers/issues/10988 | 846,343,138 | MDU6SXNzdWU4NDYzNDMxMzg= | 10,988 | unable to use multiple GPUs with HF integration of DeepSpeed on Jupyter notebooks | {
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"That's correct. \r\n\r\nYou need a separate process for each gpu under DeepSpeed for communications to work. I will update the docs to make this clear.\r\n\r\nIf you want to use multiple gpus you must use the launcher. So you can still use the notebook to set things up, but the training must happen in external pro... | 1,617 | 1,617 | 1,617 | NONE | null | Hi ,
I'm using HF integration of DeepSpeed in my Jupyter Notebook by setting following env variables as suggested [here](https://huggingface.co/transformers/main_classes/trainer.html#deployment-in-notebooks)
```
os.environ['MASTER_ADDR'] = 'localhost'
os.environ['MASTER_PORT'] = '9889'
os.environ['RANK'] = "0"... | {
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Fixed test documentation `makefile` command and PyTorch-ddp test when #10975 is merged. Different validation function for `sagemaker-data-parallel`. Can be merged already. | {
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"This is not an issue with Transformers but with using Apex with the \"O3\" opt-level. This changes your model during the training and results in the error you're seeing. The best is to re-instantiate a clean `Trainer` for evaluation after you're done with training.",
"Thank you for your reply, I just tried it an... | 1,617 | 1,617 | 1,617 | NONE | null | ## Environment info
- `transformers` version: 4.4.2
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (True)
- Tensorflow version (GPU?): 2.4.1 (True)
- Using GPU in script?: True
- Using distributed or parallel set-up in script?: False
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10985 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10985/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10985/comments | https://api.github.com/repos/huggingface/transformers/issues/10985/events | https://github.com/huggingface/transformers/pull/10985 | 846,083,976 | MDExOlB1bGxSZXF1ZXN0NjA1MjA2ODUy | 10,985 | [WIP] GPT Neo cleanup | {
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"As explained in https://github.com/huggingface/transformers/issues/11076#issuecomment-814218202, the loss did decrease over time on this small sample so it looks like there are no regressions w.r.t training.\r\n\r\n~Merge when ready @patil-suraj.~ :point_down: ",
"It seems I'm not passing the slow tests locally,... | 1,617 | 1,617 | 1,617 | MEMBER | null | # What does this PR do?
This PR refactors the `GPTNeoLocalSelfAttention` layer and adds more tests for it.
This PR
- adds the `AttentionMixin` class which contains the shared utilities for both global and local attention. The class is meant to be used as a mixin and makes it easy to test it.
- the `look_around`... | {
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"Same issue for me. \r\n\r\nWhen running\r\n```python\r\npython run_benchmark.py --no_speed --models a-ware/roberta-large-squad-classification --sequence_lengths 32 --batch_sizes 32\r\n```\r\nI get:\r\n```\r\nAttributeError: Can't pickle local object 'separate_process_wrapper_fn.<locals>.multi_process_func.<locals>... | 1,617 | 1,634 | 1,624 | NONE | null | Hi there,
likely my fault, but I can't find a proper solution yet. Tried to follow the structure as in `examples/benchmarking/run_benchmark.py`.
My Code:
```python
from transformers import AutoConfig, PyTorchBenchmark, PyTorchBenchmarkArguments
def main():
config = AutoConfig.from_pretrained('robe... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,620 | 1,620 | NONE | null | Hi, can i ask is there anyone facing issues fine tuning wav2vec2 for languages not in the common dataset.
I am trying to finetune for a language not within in the common datasets, but i get a WER of 1 not matter how many steps i tried to finetune, I have a similar issue here #10884
You can check my code in the ... | {
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"for error fixation"
] | 1,617 | 1,617 | 1,617 | NONE | null | # What does this PR do?
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/10980 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10980/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10980/comments | https://api.github.com/repos/huggingface/transformers/issues/10980/events | https://github.com/huggingface/transformers/pull/10980 | 845,684,749 | MDExOlB1bGxSZXF1ZXN0NjA0ODMyNDE5 | 10,980 | Enforce string-formatting with f-strings | {
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This PR removes any strings formatted with `.format` or `%` to use f-strings exclusively (unless there is a very good reason to use the other syntax, or the file is in a research_project/legacy folder).
The mix of three syntaxes does not make any sense and we all agree in the team that f-s... | {
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"I think you're using it wrong indeed. As said in the [docs](https://huggingface.co/transformers/model_sharing.html#model-versioning), you can either specify a tag name, branch name, or commit hash.",
"To reiterate over what @NielsRogge already said, this is the revision of the *model*, not the repository. You ca... | 1,617 | 1,617 | 1,617 | NONE | null | I am trying to download a specific version of the `roberta-large` model using the `revision` parameter of `from_pretrained()` as shown below:
```
from transformers import RobertaForSequenceClassification
model_type = "roberta-large"
v1 = "v3.5.0"
model = RobertaForSequenceClassification.from_pretrained(model_typ... | {
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"Very much needed!"
] | 1,617 | 1,622 | null | NONE | null | # 🚀 Feature request
Would it be possible to get the newly-added GPT Neo models usable on Write With Transformer?
## Motivation
It would be helpful to use the new models in the Write With Transformer app since it supports newlines.
CC @LysandreJik | {
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https://api.github.com/repos/huggingface/transformers/issues/10977 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10977/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10977/comments | https://api.github.com/repos/huggingface/transformers/issues/10977/events | https://github.com/huggingface/transformers/pull/10977 | 845,373,902 | MDExOlB1bGxSZXF1ZXN0NjA0NTQzNzcz | 10,977 | [Flax] Add other BERT classes | {
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"> It is so similar to the PyTorch implementation it seems a script could take care of the implementation by copying the PyTorch one and replacing a few strings!\r\n\r\n@marcvanzee and I were also wondering about this in general -- is there a 80/20 solution that requires user input in some cases? It would have to n... | 1,617 | 1,619 | 1,617 | MEMBER | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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"I re-launched the app.\r\n\r\nThe app itself doesn't have much information to help recreate the system though (and is not designed for heavy use :) )\r\n\r\nI'd recommend reading through the blog post instead: https://yjernite.github.io/lfqa.html",
"Thank you so much @yjernite "
] | 1,617 | 1,617 | 1,617 | NONE | null |
Transformers QA Online Demo is not working: https://huggingface.co/qa/
I am trying to recreate ELI5 but unable to find enough information @yjernite Can you Please help.
Please let me know if I can help
Thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/10975 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10975/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10975/comments | https://api.github.com/repos/huggingface/transformers/issues/10975/events | https://github.com/huggingface/transformers/pull/10975 | 845,176,019 | MDExOlB1bGxSZXF1ZXN0NjA0MzU4Mjgw | 10,975 | Merge trainers | {
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"I tested run all our `sagemaker/tests` and a few additional `model_parallel` tests. ✅ \r\nI also tested everything with the upcoming `pytorch 1.7.1` image with the new `smp 1.3.0` (their model parallelism library)✅\r\n\r\nWhat is still open for me is how does this behaves with `Seq2SeqTrainer`. Can users now use t... | 1,617 | 1,617 | 1,617 | COLLABORATOR | null | # What does this PR do?
This PR merges the specific `SageMakerTrainer` into the main `Trainer` to make all the scripts work directly with model parallelism. In passing, a few internal breaking changes:
- `is_sagemaker_distributed_available` is renamed to `is_sagemaker_dp_enabled` since it's about data parallelism a... | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nYou can ping @VictorSanh as he'll be the most helpful regarding distillation.\r\n\r\nThanks!",
"Apologies, I've posted to ... | 1,617 | 1,617 | 1,617 | NONE | null | I've been trying to retrain DistilRoBERTa from the information given [here](https://huggingface.co/distilroberta-base) along with the example code/documentation [here](https://github.com/huggingface/transformers/tree/master/examples/research_projects/distillation).
I'm a bit unclear on the exact configuration used t... | {
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https://api.github.com/repos/huggingface/transformers/issues/10973 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10973/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10973/comments | https://api.github.com/repos/huggingface/transformers/issues/10973/events | https://github.com/huggingface/transformers/pull/10973 | 845,041,256 | MDExOlB1bGxSZXF1ZXN0NjA0MjMzMDY1 | 10,973 | accelerate scripts for question answering and qa with beam search | {
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Adding example script for question answering and question answering beam search using accelerate library .
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://git... | {
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This PR adds a bit more metadata to the user agent to allow us to have more statistics on the usage, more precisely, it registers:
- the type of the file asked on the hub ("config", "tokenizer", "model" or "model_card")
- the framework used for the model ("pytorch", "tensorflow" or "flax").... | {
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"Thanks a lot for adding this!"
] | 1,617 | 1,617 | 1,617 | MEMBER | null | # What does this PR do?
This PR adds `py7zr` to use `samsum` as a dataset.
```python
[1,14]<stdout>: use_auth_token=use_auth_token,
[1,14]<stdout>: File "/opt/conda/lib/python3.6/site-packages/datasets/load.py", line 448, in prepare_module
[1,14]<stdout>: f"To be able to use this {module_type}, you nee... | {
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We simply forgot to change the call for this one when this landed:
https://github.com/huggingface/transformers/pull/10888
It's odd that tests didn't catch that. Should we add some ?
(It's a pretty edgy test case, but it does run within the API).
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Update defaults , `max_length=50` and `do_sample=True` | {
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- update checkpoint names
- auto model
| {
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https://api.github.com/repos/huggingface/transformers/issues/10967 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10967/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10967/comments | https://api.github.com/repos/huggingface/transformers/issues/10967/events | https://github.com/huggingface/transformers/pull/10967 | 844,587,182 | MDExOlB1bGxSZXF1ZXN0NjAzODE3MTgz | 10,967 | [BigBird] Fix big bird gpu test | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/10966 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10966/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10966/comments | https://api.github.com/repos/huggingface/transformers/issues/10966/events | https://github.com/huggingface/transformers/pull/10966 | 844,577,613 | MDExOlB1bGxSZXF1ZXN0NjAzODA4ODAy | 10,966 | improved sagemaker documentation for git_config and examples | {
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This PR improves Amazon SageMaker documentation to make it more clear how `git_config` works with `examples/`. Related to #10957. | {
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https://api.github.com/repos/huggingface/transformers/issues/10965 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10965/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10965/comments | https://api.github.com/repos/huggingface/transformers/issues/10965/events | https://github.com/huggingface/transformers/issues/10965 | 844,556,461 | MDU6SXNzdWU4NDQ1NTY0NjE= | 10,965 | Gradient checkpointing in Wav2Vec2 | {
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"Hi! You can check out this related issue: https://github.com/huggingface/transformers/issues/10366",
"Thanks @LysandreJik! Yeah, one solution could be modify the `run_asr.py` script and add segmenting long speech samples by manually splitting each `batch[\"speech\"]` into smaller chunks before passing to the _wa... | 1,617 | 1,632 | 1,620 | NONE | null | Hi,
Has anyone managed to fine-tune a **Wav2Vec2** model on long audio recordings which cannot fit into a GPU even with `batch_size=1`? I tried out to set `gradient_checkpointing=true`, but it didn't help to solve the _CUDA Out of Memory Error_. Could it mean that gradient checkpointing does not work properly with **... | {
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https://api.github.com/repos/huggingface/transformers/issues/10964 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10964/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10964/comments | https://api.github.com/repos/huggingface/transformers/issues/10964/events | https://github.com/huggingface/transformers/issues/10964 | 844,409,264 | MDU6SXNzdWU4NDQ0MDkyNjQ= | 10,964 | pkg_resources' working_set caching breaks transformers import on google colab | {
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"Thank you for this awesome report, @konstin, and identifying the cause of the problem and the solution.\r\n\r\nThis looks like a bug in `pkg_resources`. It should update its cache after install. \r\n\r\nThe other workaround that seems to work is to just do:\r\n```\r\n!pip install -U \"transformers<5.0.0,>=4.0.0\" ... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.4.2
- Platform: google colab
- Python version: 3.7.10
- PyTorch version (GPU?): n/a
- Tensorflow version (GPU?): n/a
- Using GPU in script?: n/a
- Using distributed or parallel set-up in script?: n/a
### Who can help
CC @stas00 as this was implemented in... | {
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https://api.github.com/repos/huggingface/transformers/issues/10963 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10963/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10963/comments | https://api.github.com/repos/huggingface/transformers/issues/10963/events | https://github.com/huggingface/transformers/issues/10963 | 844,388,116 | MDU6SXNzdWU4NDQzODgxMTY= | 10,963 | compute perplexity using a custom metric function | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\ncc @sgugger \r\n\r\nThanks!",
"The predictions are the logits of your model, so in the case of a language model, it will b... | 1,617 | 1,617 | 1,617 | NONE | null | Hello,
I am trying to replicate the "On the Cross-lingual Transferability of Monolingual Representations" paper from Artetxe et al. and I am using the code you're providing, specifically [run_mlm.py]
(https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py)
I wanted to log ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10962 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10962/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10962/comments | https://api.github.com/repos/huggingface/transformers/issues/10962/events | https://github.com/huggingface/transformers/pull/10962 | 844,341,148 | MDExOlB1bGxSZXF1ZXN0NjAzNTk4NDIx | 10,962 | fix md file to avoid evaluation crash | {
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"@patrickvonplaten It seems the finetune notebook is on your own github repository, not on HuggingFace's transformers.",
"@ydshieh yes this is correct - if it's ok for you feel free to open a PR there :-) "
] | 1,617 | 1,651 | 1,617 | COLLABORATOR | null | # What does this PR do?
Fix the crash due to the memory usage in the instructions for model evaluation in `FINE_TUNE_XLSR_WAV2VEC2.md`.
The original version `test_dataset["speech"][:2]` load the whole speech array into memory which is too large.
Change it to `test_dataset[:2]["speech"]` runs smoothly and much fast... | {
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https://api.github.com/repos/huggingface/transformers/issues/10961 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10961/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10961/comments | https://api.github.com/repos/huggingface/transformers/issues/10961/events | https://github.com/huggingface/transformers/issues/10961 | 844,294,932 | MDU6SXNzdWU4NDQyOTQ5MzI= | 10,961 | Supporting `config_path` for `AutoModel` | {
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"Hey @hwijeen! Would the `AutoModel.from_config()` method work for you?",
"Thank you @LysandreJik for your quick reply! I checked out the `AutoModel.from_config()` method. It is a convenient method but does not fit my use case, as **it does NOT load weights**.",
"Hi @LysandreJik , I update this issue to clarify... | 1,617 | 1,620 | 1,620 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
Creating a model like this:
```python
AutoModel.from_pretrained('https://myserver/model/pytorch_model.bin', config='path/to/local/config.json')
```
## Mo... | {
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https://api.github.com/repos/huggingface/transformers/issues/10960 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10960/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10960/comments | https://api.github.com/repos/huggingface/transformers/issues/10960/events | https://github.com/huggingface/transformers/issues/10960 | 844,191,886 | MDU6SXNzdWU4NDQxOTE4ODY= | 10,960 | What is the score of trainer.predict()? | {
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"These are the logits from your model, check:- https://github.com/huggingface/transformers/blob/8780caa388c7b2aa937454ed96bcdd3f097f851d/src/transformers/trainer.py#L1852",
"I see! Thank you so much!!"
] | 1,617 | 1,617 | 1,617 | NONE | null | I want to know the meaning of output of trainer.predict().
example:
`PredictionOutput(predictions=array([[-2.2704859, 2.442343 ]], dtype=float32), label_ids=array([1]), metrics={'eval_loss': 0.008939245715737343, 'eval_runtime': 0.0215, 'eval_samples_per_second': 46.56})`
What is this score? -> predictions=arra... | {
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https://api.github.com/repos/huggingface/transformers/issues/10959 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10959/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10959/comments | https://api.github.com/repos/huggingface/transformers/issues/10959/events | https://github.com/huggingface/transformers/pull/10959 | 844,128,755 | MDExOlB1bGxSZXF1ZXN0NjAzNDE4Nzkz | 10,959 | Fix summarization notebook link | {
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"Correct me if I am wrong but I think the reason why it's not included in the model output is because it's an utility function and not a direct output of the model.\r\n\r\nIf I am not wrong, calculating the confidence score in a non-pipeline method is straight forward, like how it's done below \r\nhttps://github.c... | 1,617 | 1,641 | null | NONE | null | # 🚀 Feature request
HF's Extract QA pipeline provides an excellent interface for start. It returns 4 values including a **probability score / confidence score**. Unfortunately same is not the case when using the non-pipeline approach i.e using model and tokenizer for question answering.
[Both methods are mentione... | {
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"Hi, what's the problem?",
"> Hi, what's the problem?\r\n\r\nSorry, I accidentally saved the ticket before I was done. Then I had to leave my desk for a while. I have updated the ticket with all the info now.\r\n\r\nThanks!",
"Ah, I see! This is because you're using a script which comes from the `master` bran... | 1,617 | 1,617 | 1,617 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: AWS Sagemaker
- Python version: 3.6
- PyTorch version (GPU?): N/A
- Tensorflow version (G... | {
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"> But the 1.2GB download is somewhat big even for @slow tests.\r\n\r\nThe downloads are cached on a shared disk across slow self-hosted runners, so that's not an issue!",
"Before I approached this problem, I did a bit of a study on the bfloat16 vs float16 properties. This is not fully complete, but you can see m... | 1,617 | 1,694 | null | CONTRIBUTOR | null | As reported in multiple issues t5/mt5 models produce loss of `nan` under mixed precision training, starting with t5-large and mt5-small and up. This PR is an attempt to fix this issue. This is crucial for DeepSpeed where it's always mixed precision training.
I spent some time with the debugger and the new `detect_ov... | {
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"It seems that the `encoder_hidden_states` are passed as `key_value_states` into the `MBartAttention` down the line and are not used in case `past_key_value` is given.\r\nhttps://github.com/huggingface/transformers/blob/90ecc29656ce37fdbe7279cf586511ed678c0cb7/src/transformers/models/mbart/modeling_mbart.py#L183\r\... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | I'm trying to convert the mBART decoder to onnx and have the problem, that one of the inputs gets lost during the conversion, which leads to errors when trying to use the onnx model. (See code example below.)
I'm trying to understand why this is the case and how to circumvent this.
Thanks alot for any help!
##... | {
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"Oh, is this process somehow automated and I didn't know about it? All I see is the file which it complains about and no suggestion to automate the fix.",
"Yeah, but usually it's not as good as your suggestion as it offers `==` while you offer `>=`.\r\n\r\nI think I mentioned it here: https://github.com/huggingfa... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | Fixes https://github.com/huggingface/transformers/security/dependabot/examples/research_projects/lxmert/requirements.txt/Pygments/open
@LysandreJik
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A new argument `length_column_name` has been added to
`TrainingArguments`, with default value `"length"`. If this column
exists and `group_by_length` is `True`, the train sampler will use
it for grouping rather than computing all lengths before training starts.
This is an optimization t... | {
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"I don't have a setup with 8Gb so I have to rely on nvidia-smi numbers. First command is 13.2Gb on GPU0, 6.5Gb on GPU1, second command is 11.2GB on GPU0 and 10.1GB on GPU1.",
"Thank you for the sanity check, @sgugger \r\n\r\nThis is very odd that we get such a discrepancy in memory allocation between the 2 gpus o... | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | I think we may have created a memory regression somewhere recently.
I tried with pt-1.7 and pt-1.8 with the same results.
memory limit on this setup is 8gb
on `transformers` master:
This takes about 5.5GB/gpu:
```
PYTHONPATH=src USE_TF=0 CUDA_VISIBLE_DEVICES=0,1 python examples/seq2seq/run_translation.py ... | {
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Fixes a few things I noticed from new models PR in the templates directly. | {
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"I've addressed all comments. The pooler now more closely matches the one of `BertModel`. \r\n\r\nOnly `make fix-copies` is giving an error on CircleCI for now. Other than that the PR is ready.\r\n\r\n",
"Thanks for all your work on this @NielsRogge !"
] | 1,617 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
Opening up a new PR based on #10513 which uses @sgugger's new `image_utils.py` instead of `torchvision` for the image transformations, and is up-to-date with master.
Things to do:
- [x] fix one integration test (currently `ViTFeatureExtractor` converts the numpy arrays into DoubleTensor... | {
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"See #400",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CO... | 1,617 | 1,620 | 1,620 | NONE | null | # 📚 Migration
## Information
<!-- Important information -->
Model I am using (Bert, XLNet ...):
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The ta... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,622 | 1,622 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.1.1
- Platform: Google Colab
- Python version: 3.7
- PyTorch version (GPU?): 1.8.1
- Tensorflow version (... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,623 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.0
- Platform: Linux-4.19.0-14-cloud-amd64-x86_64-with-debian-10.8
- Python version: 3.7.10
- PyTorch ver... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,620 | 1,620 | NONE | null | # What does this PR do?
To implement the integral in [this paper](https://arxiv.org/abs/2004.11207), users need to take two items out: Output and Attention weights. However, the "Output" here is somewhat special; the attention weights of each layer should be multiplied by a scalar "alpha". I try to put this "alpha" in... | {
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https://api.github.com/repos/huggingface/transformers/issues/10945 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10945/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10945/comments | https://api.github.com/repos/huggingface/transformers/issues/10945/events | https://github.com/huggingface/transformers/issues/10945 | 843,134,577 | MDU6SXNzdWU4NDMxMzQ1Nzc= | 10,945 | Are there memory leaks when using DeepSpeed on training T5? | {
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"Hi, we'll need a bit more information to understand what's going on here. What command did you use? Did you use one of our scripts? What data are you using? What version of Transformers? The more information, the more we'll be able to understand and help you.\r\n\r\nPinging @stas00 ",
"Thank you for reporting th... | 1,617 | 1,620 | 1,620 | NONE | null | We’ve been pretraining a T5-small model from scratch with using DeepSpeed v0.3.10.
We’ve found that cpu memory was increasing over time. (We’ve trained about 150 hours)
Are there memory leaks when using DeepSpeed on training T5?
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https://api.github.com/repos/huggingface/transformers/issues/10944 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10944/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10944/comments | https://api.github.com/repos/huggingface/transformers/issues/10944/events | https://github.com/huggingface/transformers/issues/10944 | 843,129,702 | MDU6SXNzdWU4NDMxMjk3MDI= | 10,944 | Please implement DUMA: Reading Comprehension with Transposition Thinking | {
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"Are the source code and the model weights avaiable?\r\n\r\nhttps://arxiv.org/abs/2001.09415",
"> Are the source code and the model weights avaiable?\r\n> \r\n> https://arxiv.org/abs/2001.09415\r\n\r\nI do not have the source code and model weights."
] | 1,617 | 1,617 | null | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
This one is on the race leaderborad top, will you guys consider implement this?
## Motivation
<!-- Please outline the motivation for the proposal. Is you... | {
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https://api.github.com/repos/huggingface/transformers/issues/10943 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10943/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10943/comments | https://api.github.com/repos/huggingface/transformers/issues/10943/events | https://github.com/huggingface/transformers/issues/10943 | 843,119,654 | MDU6SXNzdWU4NDMxMTk2NTQ= | 10,943 | Converting marian tatoeba models | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,617 | 1,634 | 1,634 | NONE | null | ## Environment info
- `transformers` version: 4.4.2
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.0+cu101 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: False
- Using distributed or parallel set-up in script?: Fals... | {
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https://api.github.com/repos/huggingface/transformers/issues/10942 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10942/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10942/comments | https://api.github.com/repos/huggingface/transformers/issues/10942/events | https://github.com/huggingface/transformers/issues/10942 | 843,119,297 | MDU6SXNzdWU4NDMxMTkyOTc= | 10,942 | Wav2Vec2CTCTokenizer does not take the vocabulary into account when identifying tokens in a sentence | {
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"Hey @guillaume-wisniewski ,\r\n\r\nThanks a lot for the very clear error description.The PR attached should fix the problem :-) Let me know if you still encounter any problems."
] | 1,617 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.4.0
- Platform: Darwin-19.6.0-x86_64-i386-64bit
- Python version: 3.7.9
- PyTorch version (GPU?): 1.8.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
### Who can help
@pa... | {
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https://api.github.com/repos/huggingface/transformers/issues/10941 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10941/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10941/comments | https://api.github.com/repos/huggingface/transformers/issues/10941/events | https://github.com/huggingface/transformers/pull/10941 | 842,837,261 | MDExOlB1bGxSZXF1ZXN0NjAyMzE0MzA5 | 10,941 | Added documentation for data collator. | {
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"Thanks again for your contribution!"
] | 1,616 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
This PR aims to improve coverage of the documentation for the Data Collators.
Fixes #9035
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.c... | {
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https://api.github.com/repos/huggingface/transformers/issues/10940 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10940/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10940/comments | https://api.github.com/repos/huggingface/transformers/issues/10940/events | https://github.com/huggingface/transformers/issues/10940 | 842,826,172 | MDU6SXNzdWU4NDI4MjYxNzI= | 10,940 | Addition of SequenceClassification config specific documentation to XModelForSequenceClassification. | {
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"Those are generic config parameters and as such, they can't be documented on a model (they are config parameters, not model parameters). The documentation is in the [config page](https://huggingface.co/transformers/main_classes/configuration.html).\r\n\r\nThe documentation of the `from_pretrained` [method](https:/... | 1,616 | 1,617 | 1,617 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform: Windows 10
- Python version: 3.6.12
- Tensorflow version (GPU?): 2.3.1
- Using GPU in script?: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10939 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10939/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10939/comments | https://api.github.com/repos/huggingface/transformers/issues/10939/events | https://github.com/huggingface/transformers/pull/10939 | 842,739,284 | MDExOlB1bGxSZXF1ZXN0NjAyMjQyMDY2 | 10,939 | [Example] Fixed finename for Saving null_odds in the evaluation stage in QA Examples | {
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Earlier file `eval_null_odds_eval.json` because of a typo in code now it will save it like `eval_null_odds.json` for squadv2 dataset Saving null_odds in the evaluation stage
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's th... | {
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https://api.github.com/repos/huggingface/transformers/issues/10938 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10938/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10938/comments | https://api.github.com/repos/huggingface/transformers/issues/10938/events | https://github.com/huggingface/transformers/issues/10938 | 842,713,901 | MDU6SXNzdWU4NDI3MTM5MDE= | 10,938 | saving pretrained models that were obtained from another model | {
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"@dar-tau even though the file stores only weights, but if you added more layers those weights should be saved right? And when you try to load that model into RobertaForQuestionAnswering without your extra layers it should fail. ",
"Thanks for your reply. \r\nI'm using AutoModelForQuestionAnswering.from_pretraine... | 1,616 | 1,620 | 1,620 | NONE | null | I am trying to save a pretrained model that I created from RobertaForQuestionAnswering by changing some layers.
However, when I load the model with from_pretrained, my new layers disappear.. It makes sense since binary seems to save only the model weights, but I wonder if there's a way to work around this? | {
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https://api.github.com/repos/huggingface/transformers/issues/10937 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10937/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10937/comments | https://api.github.com/repos/huggingface/transformers/issues/10937/events | https://github.com/huggingface/transformers/pull/10937 | 842,669,671 | MDExOlB1bGxSZXF1ZXN0NjAyMTkxMTQz | 10,937 | [trainer metrics] fix cpu mem metrics; reformat runtime metric | {
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"Woops, didn't mean to approve",
"> Thanks for the fix! Like @LysandreJik I would avoid adding `psutils` as a main dependency. We can have it come with a `is_psutils_available` and only compute the mems metrics when it's there.\r\n\r\nOh, I was thinking to assert to say to install it. They can disable the mem met... | 1,616 | 1,617 | 1,617 | CONTRIBUTOR | null | This PR improves and fixes trainer metrics:
* reworks the general ram memory tracking replacing `tracemalloc`, with "sampling" via `psutil` - in particular for peak tracking using a thread. `tracemalloc` proved to not track anything but python memory allocations, so we were missing most of the general RAM from repor... | {
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https://api.github.com/repos/huggingface/transformers/issues/10936 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10936/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10936/comments | https://api.github.com/repos/huggingface/transformers/issues/10936/events | https://github.com/huggingface/transformers/pull/10936 | 842,668,919 | MDExOlB1bGxSZXF1ZXN0NjAyMTkwNTcy | 10,936 | Fix initializing BertJapaneseTokenizer with AutoTokenizers | {
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This PR fixes a bug in loading some kinds of tokenizers using `AutoTokenizers.from_pretrained()`.
This issue is discussed in https://github.com/cl-tohoku/bert-japanese/issues/25.
When `sentencepiece` is not installed, the initialization of several tokenizers such as `BertJapaneseTokenizer... | {
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