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https://api.github.com/repos/huggingface/transformers/issues/2212 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2212/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2212/comments | https://api.github.com/repos/huggingface/transformers/issues/2212/events | https://github.com/huggingface/transformers/issues/2212 | 539,526,643 | MDU6SXNzdWU1Mzk1MjY2NDM= | 2,212 | Fine-tuning TF models on Colab TPU | {
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"I've read your code, and I don't see anything strange in it (I hope). It seems to be an error due to training a (whatever) model on TPUs rather than Transformers.\r\n\r\nDo you see [this](https://github.com/tensorflow/tensorflow/issues/29896) issue reported in TensorFlow's GitHub? It seems to be the same error, an... | 1,576 | 1,586 | 1,586 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi,
I am trying to fine-tune TF BERT on Imdb dataset on Colab TPU. Here is the full notebook:
https://colab.research.google.com/drive/16ZaJaXXd2R1gRHrmdWDkFh6U_EB0ln0z
Can anyone help me what I am doing wrong?
Thanks
| {
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"Can you remind why you moved those options to initialization vs. at `encode` time?\r\n\r\nIs that a hard requirement of the native implem?",
"Sure! The native implementation doesn't have `kwargs` so we need to define a static interface with pre-defined function arguments. This means that the configuration of the... | 1,576 | 1,651 | 1,577 | MEMBER | null | I am opening this PR to track the integration of `tokenizers`.
At the moment, we created two new classes to represent the fast version of both GPT2 and Bert tokenizers. There are a few breaking changes compared to the current `GPT2Tokenizer` and `BertTokenizer`:
- `add_special_token` is now specified during init... | {
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https://api.github.com/repos/huggingface/transformers/issues/2210 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2210/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2210/comments | https://api.github.com/repos/huggingface/transformers/issues/2210/events | https://github.com/huggingface/transformers/issues/2210 | 539,373,044 | MDU6SXNzdWU1MzkzNzMwNDQ= | 2,210 | training a new BERT tokenizer model | {
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"Follow sentencepiece github or Bert tensorflow GitHub. You will have some\nfeedback\n\nOn Wed, Dec 18, 2019 at 07:52 Younggyun Hahm <notifications@github.com>\nwrote:\n\n> ❓ Questions & Help\n>\n> I would like to train a new BERT model.\n> There are some way to train BERT tokenizer (a.k.a. wordpiece tokenizer) ?\n... | 1,576 | 1,643 | 1,578 | NONE | null | ## ❓ Questions & Help
I would like to train a new BERT model.
There are some way to train BERT tokenizer (a.k.a. wordpiece tokenizer) ?
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https://api.github.com/repos/huggingface/transformers/issues/2209 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2209/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2209/comments | https://api.github.com/repos/huggingface/transformers/issues/2209/events | https://github.com/huggingface/transformers/issues/2209 | 539,265,078 | MDU6SXNzdWU1MzkyNjUwNzg= | 2,209 | ```glue_convert_examples_to_features``` for sequence labeling tasks | {
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"duplicate to 2208"
] | 1,576 | 1,576 | 1,576 | NONE | null | ## 🚀 Feature
<!-- A clear and concise description of the feature proposal. Please provide a link to the paper and code in case they exist. -->
I would like a function like ```glue_convert_examples_to_features``` for sequence labelling tasks.
## Motivation
<!-- Please outline the motivation for the proposal. ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2208 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2208/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2208/comments | https://api.github.com/repos/huggingface/transformers/issues/2208/events | https://github.com/huggingface/transformers/issues/2208 | 539,259,772 | MDU6SXNzdWU1MzkyNTk3NzI= | 2,208 | ```glue_convert_examples_to_features``` for sequence labeling tasks | {
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"Do you mean the one already into Transformers in the [glue.py](https://github.com/huggingface/transformers/blob/d46147294852694d1dc701c72b9053ff2e726265/transformers/data/processors/glue.py) at line 30 or a different function? \r\n\r\n> glue_convert_examples_to_features",
"A different one. Does this proposal ma... | 1,576 | 1,582 | 1,582 | NONE | null | ## 🚀 Feature
<!-- A clear and concise description of the feature proposal. Please provide a link to the paper and code in case they exist. -->
I would like a function like ```glue_convert_examples_to_features``` for sequence labelling tasks.
## Motivation
<!-- Please outline the motivation for the proposal. ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2207/comments | https://api.github.com/repos/huggingface/transformers/issues/2207/events | https://github.com/huggingface/transformers/pull/2207 | 539,253,243 | MDExOlB1bGxSZXF1ZXN0MzU0MjYxODg0 | 2,207 | Fix segmentation fault | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2207?src=pr&el=h1) Report\n> Merging [#2207](https://codecov.io/gh/huggingface/transformers/pull/2207?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f061606277322a013ec2d96509d3077e865ae875?src=pr&el=desc) will **i... | 1,576 | 1,576 | 1,576 | MEMBER | null | Fix segmentation fault that started happening yesterday night.
Following the fix from #2205 that could be reproduced using circle ci ssh access.
~Currently fixing the unforeseen event with Python 2.~ The error with Python 2 was due to Regex releasing a new version (2019.12.17) that couldn't be built on Python 2.7. | {
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https://api.github.com/repos/huggingface/transformers/issues/2206 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2206/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2206/comments | https://api.github.com/repos/huggingface/transformers/issues/2206/events | https://github.com/huggingface/transformers/issues/2206 | 539,196,159 | MDU6SXNzdWU1MzkxOTYxNTk= | 2,206 | Transformers Encoder and Decoder Inference | {
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"As said in #2117 by @rlouf (an author of Transformers), **at the moment** you can use `PreTrainedEncoderDecoder` with only **BERT** model both as encoder and decoder.\r\n\r\nIn more details, he said: \"_Indeed, as I specified in the article, PreTrainedEncoderDecoder only works with BERT as an encoder and BERT as a... | 1,576 | 1,592 | 1,576 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [X ] the official example scripts: (give details)
* [ ] my own modified scripts: (give details)
The tasks I am working on is:
* [ ] an o... | {
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https://api.github.com/repos/huggingface/transformers/issues/2205 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2205/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2205/comments | https://api.github.com/repos/huggingface/transformers/issues/2205/events | https://github.com/huggingface/transformers/issues/2205 | 539,184,004 | MDU6SXNzdWU1MzkxODQwMDQ= | 2,205 | Segmentation fault when GPT2-chinese import transformers | {
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"Is it related to #2204 ?\r\n**Segmentation fault** (usually) means that you tried to access memory that you do not have access to.",
"> Is it related to #2204 ?\r\n\r\nYes, it looks like the same bug as this. I know how to solve it but do not know why.😂\r\n Xeon(R) CPU E5-2680 v4 @ 2.40GHz
GPU: Tesla P40
OS Platform: Ubuntu 16.04.3 LTS
transformers version: 2.2.2
TensorFlow version: 2.0.0
PyTorch version: 1.3.1
Python version: 3.6.2
Hi
When I trained the model in [GPT2-chinese](https://github.com/Morizeyao/GPT2-Chinese), it i... | {
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"#2207 ",
"Solved by @LysandreJik yesterday (this was due to upstream dependency bug)"
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I've seen that many recent PRs (e.g. [2201](https://github.com/huggingface/transformers/pull/2201), [2203](https://github.com/huggingface/transformers/pull/2203), [2190](https://github.com/huggingface/transformers/pull/2190), [2189](https://github.com/huggingface/transformers/pull/2189), ...) have encounte... | {
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https://api.github.com/repos/huggingface/transformers/issues/2203 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2203/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2203/comments | https://api.github.com/repos/huggingface/transformers/issues/2203/events | https://github.com/huggingface/transformers/pull/2203 | 539,170,739 | MDExOlB1bGxSZXF1ZXN0MzU0MTkzMDA0 | 2,203 | fix: wrong architecture count in README | {
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https://api.github.com/repos/huggingface/transformers/issues/2202 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2202/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2202/comments | https://api.github.com/repos/huggingface/transformers/issues/2202/events | https://github.com/huggingface/transformers/issues/2202 | 539,103,930 | MDU6SXNzdWU1MzkxMDM5MzA= | 2,202 | weights not initialised in pre-trained Roberta | {
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"Thanks for the bug report. Fixed on `master` in 9a399ead253e27792cbf0ef386cc39f9b7084f8f by reverting the output of #1778."
] | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Robert
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [ ] the official example scripts: (give details)
* [X] my own modified scripts: see below
The tasks I am working on is:
*... | {
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https://api.github.com/repos/huggingface/transformers/issues/2201 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2201/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2201/comments | https://api.github.com/repos/huggingface/transformers/issues/2201/events | https://github.com/huggingface/transformers/pull/2201 | 538,944,838 | MDExOlB1bGxSZXF1ZXN0MzU0MDAzNDY3 | 2,201 | [WAITING YOUR REVIEW] Issue #2196: now it's possible to save PreTrainedEncoderDecoder objects correctly to file system | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2201?src=pr&el=h1) Report\n> Merging [#2201](https://codecov.io/gh/huggingface/transformers/pull/2201?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f061606277322a013ec2d96509d3077e865ae875?src=pr&el=desc) will **d... | 1,576 | 1,576 | 1,576 | NONE | null | **Details implemented in this PR:**
- [X] Create the output directory (whose name is passed by the user in the "save_directory" parameter) where it will be saved encoder and decoder, if not exists.
- [X] Empty the output directory, if it contains any files or subdirectories.
- [X] Create the "encoder" directory in... | {
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https://api.github.com/repos/huggingface/transformers/issues/2200 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2200/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2200/comments | https://api.github.com/repos/huggingface/transformers/issues/2200/events | https://github.com/huggingface/transformers/issues/2200 | 538,917,448 | MDU6SXNzdWU1Mzg5MTc0NDg= | 2,200 | run_ner.py example fails | {
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"A few questions (the ones asked in the issue templates...):\r\n- which version/branch of `transformers` are you using?\r\n- which exact command line are you running?",
"Hi,\r\nsorry, my bad.\r\n\r\nI am calling run_ner.py with\r\n```\r\n python .\\run_ner.py --data_dir ./ --model_type bert --labels .\\labels.txt... | 1,576 | 1,576 | 1,576 | NONE | null | I am trying to run the run_ner.py example described here: (https://huggingface.co/transformers/examples.html#named-entity-recognition)
When running the example I get the following exception:
```
I1217 09:36:10.744300 14416 file_utils.py:40] PyTorch version 1.3.1 available.
W1217 09:36:11.329299 14416 run_ner.py:4... | {
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https://api.github.com/repos/huggingface/transformers/issues/2199 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2199/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2199/comments | https://api.github.com/repos/huggingface/transformers/issues/2199/events | https://github.com/huggingface/transformers/issues/2199 | 538,917,120 | MDU6SXNzdWU1Mzg5MTcxMjA= | 2,199 | How to add traditional features for transformers? | {
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"What do you mean \"for training\"? Training what? I imagine that you wish to do this for a downstream task. In that case you can just use BERT for feature extraction and use its features in another system. I suppose one could also fine-tune the model during training where you somewhere inject other features into t... | 1,576 | 1,576 | 1,576 | NONE | null | ## ❓ Questions & Help
I don't know whether models like Bert can capture some traditional features or not, such as the number of nouns in a sentence, the number of words in a sentence, etc. But I want to add these features to Bert or xlnet for training. Can anyone help me?
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https://api.github.com/repos/huggingface/transformers/issues/2198 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2198/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2198/comments | https://api.github.com/repos/huggingface/transformers/issues/2198/events | https://github.com/huggingface/transformers/issues/2198 | 538,907,064 | MDU6SXNzdWU1Mzg5MDcwNjQ= | 2,198 | How to output labels for GLUE test set | {
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"Hi, if you're working on a clone/fork of this library, then you can freely change the following lines in `transformers/data/processors/glue.py` (lines 254-262 on the current master):\r\n\r\n```py\r\n def get_train_examples(self, data_dir):\r\n \"\"\"See base class.\"\"\"\r\n return self._create_ex... | 1,576 | 1,586 | 1,581 | CONTRIBUTOR | null | ## ❓ Questions & Help
Thanks for your great work.
I have done some modification based on your library. I'd like to test it on GLUE test set (not dev set). Is there any way I can do it? Do you have a script for output GLUE submission files?
Thanks. | {
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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"
] | 1,576 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi!
I'm wondering whether my speed of fine-tuning is normal.
Training is taking **2~3hours per epoch**.
I am using [fast-bert](https://github.com/kaushaltrivedi/fast-bert) to train multi-label classifier, with
- model = xlnet-... | {
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"I resolved this issue you've raised correctly. I'll make a PR today to solve this bug! :)\r\nUPDATE: I've made the PR: you can look [here](https://github.com/huggingface/transformers/pull/2201).\r\n\r\n> ## Bug\r\n> Model I am using (Bert, XLNet....):\r\n> \r\n> Language I am using the model on (English, Chinese.... | 1,576 | 1,576 | 1,576 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [ ] the official example scripts: (give details)
* [X] my own modified scripts: (give details)
The tasks I am working on is:
* [ ] an of... | {
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https://api.github.com/repos/huggingface/transformers/issues/2195 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2195/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2195/comments | https://api.github.com/repos/huggingface/transformers/issues/2195/events | https://github.com/huggingface/transformers/pull/2195 | 538,819,773 | MDExOlB1bGxSZXF1ZXN0MzUzOTAxNjUx | 2,195 | Fixing checks test pr, will be closed | {
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"@thomwolf or @julien-c any idea what's going on with the seg fault in the `build_py3_torch_and_tf` [run](https://circleci.com/gh/huggingface/transformers/9811?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link)? was able to run and pass locally...\r\n the program would just hang at `f.read()` 😢
- Speeds up `lowercase_text` in the `BasicTokenizer` with a simpl... | {
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"Hi, you can add new vocabulary using the tokenizer's `add_tokens` method.",
"Thanks for the quick response!"
] | 1,576 | 1,576 | 1,576 | NONE | null | ## ❓ Questions & Help
I am fine-tuning the GPT2 on a domain-specific corpus and I was wondering if there is a way to add new vocabulary to the model. I am checking the ```vocab.json``` file after saving the model into ```output``` directory and don't find the any new vocabulary in there.
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2192?src=pr&el=h1) Report\n> Merging [#2192](https://codecov.io/gh/huggingface/transformers/pull/2192?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d8034092153a6850052862f154a398b88b8ba4e5?src=pr&el=desc) will **i... | 1,576 | 1,651 | 1,576 | MEMBER | null | Fix loading a PyTorch model from TF and vice-versa when model architectures are not the same
Fix #2109 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2191?src=pr&el=h1) Report\n> Merging [#2191](https://codecov.io/gh/huggingface/transformers/pull/2191?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ceae85ad60da38cacb14eca49f752669a4fe31dc?src=pr&el=desc) will **d... | 1,576 | 1,578 | 1,576 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2190 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2190/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2190/comments | https://api.github.com/repos/huggingface/transformers/issues/2190/events | https://github.com/huggingface/transformers/pull/2190 | 538,548,730 | MDExOlB1bGxSZXF1ZXN0MzUzNjc2MTcz | 2,190 | Adding Finnish BERT. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2190?src=pr&el=h1) Report\n> Merging [#2190](https://codecov.io/gh/huggingface/transformers/pull/2190?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e92bcb7eb6c5b9b6ed313cc74abaab50b3dc674f?src=pr&el=desc) will **n... | 1,576 | 1,578 | 1,576 | CONTRIBUTOR | null | We have trained BERT-base on Finnish text and wish to have it included in the library. Both cased and uncased models are available. You can see the paper [here](https://arxiv.org/abs/1912.07076) and a website for the model can be found [here](http://turkunlp.org/FinBERT/).
These changes passed all the relevant tests... | {
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https://api.github.com/repos/huggingface/transformers/issues/2189 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2189/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2189/comments | https://api.github.com/repos/huggingface/transformers/issues/2189/events | https://github.com/huggingface/transformers/pull/2189 | 538,509,824 | MDExOlB1bGxSZXF1ZXN0MzUzNjQ0MDQ5 | 2,189 | Add support for XLM-RoBERTa | {
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"@stefan-it Following the merge of #1959, you should not have to duplicate the weights conversion script anymore. It should work out of the box, `fairseq.XLMRModel` being a subclass of `fairseq.RobertaModel`.",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2189?src=pr&el=h1) Report\n> Merging [... | 1,576 | 1,576 | 1,576 | COLLABORATOR | null | Hi,
this model adds support for the recently released XLM-RoBERTa model from the Facebook AI team.
XLM-RoBERTa is described in the ["Unsupervised Cross-lingual Representation Learning at Scale](https://arxiv.org/abs/1911.02116) paper from Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guilla... | {
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https://api.github.com/repos/huggingface/transformers/issues/2188 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2188/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2188/comments | https://api.github.com/repos/huggingface/transformers/issues/2188/events | https://github.com/huggingface/transformers/issues/2188 | 538,390,847 | MDU6SXNzdWU1MzgzOTA4NDc= | 2,188 | About QuestionAnswering on SQuAD2.0 Dataset | {
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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"
] | 1,576 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Do anyone understand the paper " QuestionAnswering on SQuAD2.0 Dataset" in section 5.1. It says
"As we increase the number of epochs in training, the performance of the answerable questions is improved while the performance for the no... | {
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https://api.github.com/repos/huggingface/transformers/issues/2187 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2187/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2187/comments | https://api.github.com/repos/huggingface/transformers/issues/2187/events | https://github.com/huggingface/transformers/issues/2187 | 538,179,898 | MDU6SXNzdWU1MzgxNzk4OTg= | 2,187 | Output diverging on different GPUs using same prompt? | {
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"How do you set your seed? Personally I use the following, which sets... a lot of seeds but also useful variables for the backend.\r\n\r\n```python\r\n def set_seed(seed: Optional[int]):\r\n \"\"\" Set all seeds to make results reproducible (deterministic mode).\r\n When seed is None, disables... | 1,576 | 1,582 | 1,582 | NONE | null | ## 🐛 Bug
Wondering if anyone else is noticing this, or I'm missing something.
GPT-2 transformer run_generation.py
Running on both AWS p2 and p3, which have different GPUs.
Same text seed, same numerical seed (default: 42)
The output is identical for a long segment, and then suddenly diverges, picking a... | {
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https://api.github.com/repos/huggingface/transformers/issues/2186 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2186/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2186/comments | https://api.github.com/repos/huggingface/transformers/issues/2186/events | https://github.com/huggingface/transformers/issues/2186 | 538,104,237 | MDU6SXNzdWU1MzgxMDQyMzc= | 2,186 | summarization code is incomplete | {
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"I'm sorry that you're angry with Transformers library and its authors, but I'm not share your opinion. This framework is well documented, developed and updated (the most important part of each library).\r\n\r\nHowever, if you want to watch and/or train the model for the summarization task, you can refer [here](htt... | 1,576 | 1,582 | 1,582 | NONE | null | Hi
in the summarization code you have removed all the training part, why is that?
Solely evaluating an existing model does not really have any point.
While I really find this repo great, incomplete work like this summarization folder, defenitely degrade from the dignity of this repo. I greatly appreciate either re... | {
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https://api.github.com/repos/huggingface/transformers/issues/2185 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2185/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2185/comments | https://api.github.com/repos/huggingface/transformers/issues/2185/events | https://github.com/huggingface/transformers/issues/2185 | 538,094,409 | MDU6SXNzdWU1MzgwOTQ0MDk= | 2,185 | RuntimeError: CUDA error: device-side assert triggered when using Roberta | {
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"Bert, XLnet all work fine for me",
"Have you ever read in the Issues section, e.g. #1852, #1848, #1849 and #1805? They suggest different solutions for your problem, e.g. changing the input sequence limit to 128.\r\n\r\n> ## Bug\r\n> Model I am using (Bert, XLNet....):\r\n> Roberta\r\n> Language I am using the m... | 1,576 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Roberta
Language I am using the model on (English, Chinese....):
English
The problem arise when using:
* [ ] the official example scripts: (give details)
* [x] my own modified scripts: (give details)
```
class QuestModel(nn.Mod... | {
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https://api.github.com/repos/huggingface/transformers/issues/2184 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2184/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2184/comments | https://api.github.com/repos/huggingface/transformers/issues/2184/events | https://github.com/huggingface/transformers/issues/2184 | 538,094,098 | MDU6SXNzdWU1MzgwOTQwOTg= | 2,184 | T5Tokenizer: Using cls_token, but it is not set yet. | {
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"I'm **not** able to import T5Tokenizer in my environment: I received an **ImportError** exception.\r\nI'm using Python 3.6.9, OS Ubuntu 16.04, Transformers 2.2.2 (installed now with `pip install transformers`), PyTorch 1.3.1 and TensorFlow 2.0. What am I missing?\r\nThe stack trace is the following:\r\n```\r\n>>> ... | 1,576 | 1,582 | 1,582 | COLLABORATOR | null | ## 🐛 Bug
Model I am using (Bert, XLNet....): T5
## To Reproduce
Steps to reproduce the behavior:
1. Load T5Tokenizer
2. Try getting the CLS or SEP token: `tokenizer.sep_token` or `tokenizer.cls_token`
3. An error will be raised "Using cls_token, but it is not set yet."
Running the latest commit on the... | {
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https://api.github.com/repos/huggingface/transformers/issues/2183 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2183/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2183/comments | https://api.github.com/repos/huggingface/transformers/issues/2183/events | https://github.com/huggingface/transformers/issues/2183 | 538,072,464 | MDU6SXNzdWU1MzgwNzI0NjQ= | 2,183 | Unit of the prediction scores of a language model | {
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"These are logits, i.e. unnormalized scores for each possible token at the masked token position. You can convert them in (normalized) probabilities by taking their softmax. I don't think you can really assign any unit to these scores, in particular, because they are not normalized so you can add any constant value... | 1,576 | 1,582 | 1,582 | COLLABORATOR | null | I have used the base transformer models for downstream tasks for a while now but I haven't had the time to dig into how the models were actually trained. When looking at the *ForMaskedLM models, I can see the return tuple contains `prediction_scores` for each token.
> prediction_scores: torch.FloatTensor of shape (b... | {
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https://api.github.com/repos/huggingface/transformers/issues/2182 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2182/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2182/comments | https://api.github.com/repos/huggingface/transformers/issues/2182/events | https://github.com/huggingface/transformers/issues/2182 | 538,052,267 | MDU6SXNzdWU1MzgwNTIyNjc= | 2,182 | sts-b task score is far worse than other GLUE tasks | {
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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",
"Have you resolved this issue? I observed a much worse result."
] | 1,576 | 1,600 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hello,
I'm evaluating my GPT style model pretrained on TEXT8 dataset with GLUE.
Below is the evaluation result.
```
CoLA | SST-2 | MRPC | QQP | STS-B | MNLI | QNLI | RTE | WNLI
19.1 | 85 | 82.5 / 71.6 | 78.... | {
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https://api.github.com/repos/huggingface/transformers/issues/2181 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2181/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2181/comments | https://api.github.com/repos/huggingface/transformers/issues/2181/events | https://github.com/huggingface/transformers/issues/2181 | 538,020,090 | MDU6SXNzdWU1MzgwMjAwOTA= | 2,181 | Conda version is not the latest | {
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"Do you mean lines 66-67 and 153 in the [modeling_albert.py](https://github.com/huggingface/transformers/blob/master/transformers/modeling_albert.py) script?\r\n\r\n> ## Feature\r\n> The conda package in conda forge channel (v2.1.1) is not the latest released version (v2.2.2) so the ALBERT model is missing from th... | 1,576 | 1,582 | 1,582 | NONE | null | ## 🚀 Feature
The conda package in conda forge channel (v2.1.1) is not the latest released version (v2.2.2) so the ALBERT model is missing from the package.
## Motivation
In conda environment we need the latest packages containing the ALBERT model.
## Additional context
Also, for the ALBERT model in its ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2180 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2180/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2180/comments | https://api.github.com/repos/huggingface/transformers/issues/2180/events | https://github.com/huggingface/transformers/issues/2180 | 538,018,046 | MDU6SXNzdWU1MzgwMTgwNDY= | 2,180 | Pretty sure patch in Pull Request #1313 is incorrect | {
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"And yes, the above code does fix it.\r\n\r\nExample:\r\n--stop_token=\"wake\"\r\n\r\ntext = ' to the same conclusion: that her husband, the guy she had chosen for her favorite, had been'\r\n\r\ntrimmed text = ' to the same conclusion: that her husband, the guy she had chosen for her favorite, had been'\r\n\r\n\r\n... | 1,576 | 1,576 | 1,576 | NONE | null | ## 🐛 Bug
The bug was introduced in pull request #1313
If a stop_token is specified, but does not exist in **text**, then the last character of the text string is trimmed off. text.find will return -1 in that case, which seems to remove the last character from the string.
Example:
--stop_token="wake"
`tex... | {
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https://api.github.com/repos/huggingface/transformers/issues/2179 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2179/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2179/comments | https://api.github.com/repos/huggingface/transformers/issues/2179/events | https://github.com/huggingface/transformers/issues/2179 | 538,001,905 | MDU6SXNzdWU1MzgwMDE5MDU= | 2,179 | Should I always use bert as a teacher to distillation distilbert as a student? | {
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"Hello @graykode \r\nYou can use whichever teacher you want, however in the method we propose, you need to make sure that the vocabularies match (knowledge distillation loss is applied to the distributions over the vocabulary).\r\nVictor",
"Thanks for your advice! I will close this issue"
] | 1,576 | 1,576 | 1,576 | NONE | null | ## ❓ Questions & Help
Should I always use bert as a teacher to distill distilbert as a student?
Is it fine RoBERTa model as a teacher to distill [distilbert](https://github.com/huggingface/transformers/blob/master/transformers/modeling_distilbert.py)?
I assume roberta and distilbert use the same tokenizer and datalo... | {
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https://api.github.com/repos/huggingface/transformers/issues/2178 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2178/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2178/comments | https://api.github.com/repos/huggingface/transformers/issues/2178/events | https://github.com/huggingface/transformers/pull/2178 | 537,997,406 | MDExOlB1bGxSZXF1ZXN0MzUzMjM1NTgz | 2,178 | Tokenize with offsets | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2178?src=pr&el=h1) Report\n> Merging [#2178](https://codecov.io/gh/huggingface/transformers/pull/2178?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/26e04e51ef0774e681784d7be900c1119d46c52e?src=pr&el=desc) will **d... | 1,576 | 1,641 | 1,588 | CONTRIBUTOR | null | Similar purpose to https://github.com/huggingface/transformers/pull/1274 (which I also used for most of the testing) but different approach.
It keeps track of token offsets by trying to progressively tokenize the text character by character, and consume matching tokens along the way.
It returns just the start of a sp... | {
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https://api.github.com/repos/huggingface/transformers/issues/2177 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2177/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2177/comments | https://api.github.com/repos/huggingface/transformers/issues/2177/events | https://github.com/huggingface/transformers/pull/2177 | 537,922,695 | MDExOlB1bGxSZXF1ZXN0MzUzMTgxODAx | 2,177 | :zip: #2106 tokenizer.tokenize speed improvement (3-8x) by caching added_tokens in a Set | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2177?src=pr&el=h1) Report\n> Merging [#2177](https://codecov.io/gh/huggingface/transformers/pull/2177?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e92bcb7eb6c5b9b6ed313cc74abaab50b3dc674f?src=pr&el=desc) will **i... | 1,576 | 1,576 | 1,576 | NONE | null | in #2106, we see that adding tokens to tokenizer decreases progressively tokenization performance which is not really a surprise as you need to go through the list of tokens which grows. But it sounds that this increase is not linear.
By having a quick look at code, I've seen that:
- `added_tokens` list is built fo... | {
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https://api.github.com/repos/huggingface/transformers/issues/2176 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2176/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2176/comments | https://api.github.com/repos/huggingface/transformers/issues/2176/events | https://github.com/huggingface/transformers/issues/2176 | 537,912,450 | MDU6SXNzdWU1Mzc5MTI0NTA= | 2,176 | run_squad.py for SQuAD2.0 have bad f1 score | {
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"Can you please post the required version numbers? (Should be in the issue template)",
"the version numbers is 2.2.0",
"- Is it answering every question? for V2 you might want this flag passed\r\nhttps://github.com/huggingface/transformers/blob/master/examples/run_squad.py#L409\r\n\r\n- Your model is cased?\r\n... | 1,576 | 1,577 | 1,577 | NONE | null | why I use run_squad.py for SQuAD2.0 have bad f1 score 43.638
The noanser_f1=0.0 it look like do not deal with not answerable situation
I don't have change anything
I just run like this
python3 run_squad.py \
--model_type bert \
--model_name_or_path bert-base-cased \
--do_train \
--do_eval \
--do_lo... | {
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https://api.github.com/repos/huggingface/transformers/issues/2175 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2175/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2175/comments | https://api.github.com/repos/huggingface/transformers/issues/2175/events | https://github.com/huggingface/transformers/pull/2175 | 537,906,689 | MDExOlB1bGxSZXF1ZXN0MzUzMTcwNTA3 | 2,175 | merge new version | {
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https://api.github.com/repos/huggingface/transformers/issues/2174 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2174/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2174/comments | https://api.github.com/repos/huggingface/transformers/issues/2174/events | https://github.com/huggingface/transformers/issues/2174 | 537,890,998 | MDU6SXNzdWU1Mzc4OTA5OTg= | 2,174 | RobertaTokenizer token type issue | {
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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",
"having the same question... why add two seps instead of one? "
] | 1,576 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Why the two middle `<\s>` are both assigned with token type 0?
https://github.com/huggingface/transformers/blob/e92bcb7eb6c5b9b6ed313cc74abaab50b3dc674f/transformers/tokenization_roberta.py#L149
Could this one be better?
```pyt... | {
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https://api.github.com/repos/huggingface/transformers/issues/2173 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2173/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2173/comments | https://api.github.com/repos/huggingface/transformers/issues/2173/events | https://github.com/huggingface/transformers/pull/2173 | 537,844,159 | MDExOlB1bGxSZXF1ZXN0MzUzMTI3MTUy | 2,173 | run_squad with roberta | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2173?src=pr&el=h1) Report\n> Merging [#2173](https://codecov.io/gh/huggingface/transformers/pull/2173?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7bd11dda6f43656cf0a3891b7f61a67196d233b4?src=pr&el=desc) will **d... | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | Hi, @julien-c @thomwolf this PR is based on #1386 and #1984.
- This PR modified run_squad.py and models_roberta to support Roberta.
- This PR also made use of multiple processing to accelerate converting examples to features. (Converting examples to feature needed **15minus before and 34 seconds now** with 24... | {
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https://api.github.com/repos/huggingface/transformers/issues/2172 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2172/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2172/comments | https://api.github.com/repos/huggingface/transformers/issues/2172/events | https://github.com/huggingface/transformers/pull/2172 | 537,778,994 | MDExOlB1bGxSZXF1ZXN0MzUzMDc1MTg1 | 2,172 | [cli] Upload is now compatible with folders | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2172?src=pr&el=h1) Report\n> Merging [#2172](https://codecov.io/gh/huggingface/transformers/pull/2172?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d46147294852694d1dc701c72b9053ff2e726265?src=pr&el=desc) will **i... | 1,576 | 1,576 | 1,576 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2171 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2171/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2171/comments | https://api.github.com/repos/huggingface/transformers/issues/2171/events | https://github.com/huggingface/transformers/issues/2171 | 537,760,889 | MDU6SXNzdWU1Mzc3NjA4ODk= | 2,171 | Small run_squad nit: eliminate trailing "_" in "best_predictions_.json" when no prefix | {
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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",
"As it's only a cosmetic change and for the sake of not breaking backward compat over cosmetic issues I'm reluctant to change this."
] | 1,576 | 1,582 | 1,582 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Prior convention for tf-based run_squad is to output best predictions in an nbest_predictions.json file. Now with the new convention of including a "prefix" in the generation of potentially many nbest files, in cases where there's not prefix, the name becomes nbest_predictio... | {
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https://api.github.com/repos/huggingface/transformers/issues/2170 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2170/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2170/comments | https://api.github.com/repos/huggingface/transformers/issues/2170/events | https://github.com/huggingface/transformers/pull/2170 | 537,742,990 | MDExOlB1bGxSZXF1ZXN0MzUzMDQ0NjM1 | 2,170 | BertForSequenceClassification() model TF to pytorch conversion | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2170?src=pr&el=h1) Report\n> Merging [#2170](https://codecov.io/gh/huggingface/transformers/pull/2170?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c8ed1c82c8a42ef700d4129d227fa356385c1d60?src=pr&el=desc) will **d... | 1,576 | 1,584 | 1,584 | CONTRIBUTOR | null | I added a script convert_bert_seqclass_tf_checkpoint_to_pytorch.py for the conversion a trained BertForSequenceClassification model from TF to pytorch.
I had to modify modeling_bert.py to support it, as well. | {
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https://api.github.com/repos/huggingface/transformers/issues/2169 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2169/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2169/comments | https://api.github.com/repos/huggingface/transformers/issues/2169/events | https://github.com/huggingface/transformers/issues/2169 | 537,714,233 | MDU6SXNzdWU1Mzc3MTQyMzM= | 2,169 | How to structure input data for training TFGPT2LMHeadModel using model.fit() in TF2.0? | {
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"Hi, there is a fundamental difference between PyTorch and TensorFlow in that the losses for PyTorch can be computed both inside the model forward method as well as outside, whereas it is only outside for TensorFlow.\r\n\r\nThis makes a difference when comparing the torch script and keras fit, as our GPT-2 impleme... | 1,576 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I am able to use the run_lm_finetuning.py script easily, but I wish to be able to use TF2.0 and call model.fit() on distilgpt2.
using the fine-tuning script as an example, I structured my dataset as such:
```
#split text file b... | {
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https://api.github.com/repos/huggingface/transformers/issues/2168 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2168/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2168/comments | https://api.github.com/repos/huggingface/transformers/issues/2168/events | https://github.com/huggingface/transformers/issues/2168 | 537,692,176 | MDU6SXNzdWU1Mzc2OTIxNzY= | 2,168 | CUDA error at 'cublasSgemm' when using the pretrained BERT | {
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"In [this](https://github.com/pytorch/pytorch/issues/24018) thread on PyTorch's GitHub, they said that this bug has been fixed. In more details, _\"this bug was solved in cublas 10.2.0.186. The latest public version of cublas is 10.2.1.243 that was released with CUDA 10.1 Update 2.\"_",
"This issue has been autom... | 1,576 | 1,582 | 1,582 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [ ] the official example scripts: (give details)
* [v] my own modified scripts: (give details)
The tasks I am working on is:
* [ ] an of... | {
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https://api.github.com/repos/huggingface/transformers/issues/2167 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2167/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2167/comments | https://api.github.com/repos/huggingface/transformers/issues/2167/events | https://github.com/huggingface/transformers/issues/2167 | 537,609,529 | MDU6SXNzdWU1Mzc2MDk1Mjk= | 2,167 | using run_squad.py for predict and specifying config_name as path, config.json not found | {
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"@LysandreJik - Note changes above.",
"I believe the issue stems from the fact that the model cannot be evaluated unless it has been trained. A workaround is to specify the `model_name_or_path` to be the same as the `output_dir` so that it loads that when evaluating, but it isn't the best user experience.\r\n\r\n... | 1,576 | 1,576 | 1,576 | NONE | null | ## 🐛 Bug
<!-- Important information -->
The situation is that, when running a predict-only task and specifying 1) an explicit path for a fine-tuned albert model and 2) specifying a specific path to the corresponding config.json file, run_squad attempts to seek the config file in the location of the --output_dir.... | {
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https://api.github.com/repos/huggingface/transformers/issues/2166 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2166/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2166/comments | https://api.github.com/repos/huggingface/transformers/issues/2166/events | https://github.com/huggingface/transformers/issues/2166 | 537,600,034 | MDU6SXNzdWU1Mzc2MDAwMzQ= | 2,166 | How to do the further pretraining ? | {
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"We have no scripts for pre-training, but we do have scripts for fine-tuning (which seems to be what you want to do). Take a look at [run_lm_finetuning.py](https://github.com/huggingface/transformers/blob/master/examples/run_lm_finetuning.py) for more information. \r\n\r\nWe don't have examples that do NSP however,... | 1,576 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hello ! How could I futher Pre-train the BERT ( including the unsupervised masked language model
and next sentence prediction tasks ) **using my own corpus** ? thank you very much ! | {
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https://api.github.com/repos/huggingface/transformers/issues/2165 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2165/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2165/comments | https://api.github.com/repos/huggingface/transformers/issues/2165/events | https://github.com/huggingface/transformers/pull/2165 | 537,596,440 | MDExOlB1bGxSZXF1ZXN0MzUyOTIyNjM1 | 2,165 | Model parallelism + Adapters | {
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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"
] | 1,576 | 1,651 | 1,583 | MEMBER | null | Adding model parallelism for large T5 models and other models if needed.
Adding adapters (a generalization of #1289) at the same time. | {
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https://api.github.com/repos/huggingface/transformers/issues/2164 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2164/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2164/comments | https://api.github.com/repos/huggingface/transformers/issues/2164/events | https://github.com/huggingface/transformers/pull/2164 | 537,554,789 | MDExOlB1bGxSZXF1ZXN0MzUyODg4NzU2 | 2,164 | [SMALL BREAKING CHANGE] Cleaning up configuration classes - Adding Model Cards | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2164?src=pr&el=h1) Report\n> Merging [#2164](https://codecov.io/gh/huggingface/transformers/pull/2164?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e92bcb7eb6c5b9b6ed313cc74abaab50b3dc674f?src=pr&el=desc) will **d... | 1,576 | 1,576 | 1,576 | MEMBER | null | Clean up configuration.
Previously loading a JSON file in the configuration could be done either by `config = config_class(json_file)` or by `config = config_class.from_pretrained(json_file)`.
This was a historical artifact from the time configuration classes didn't use `from_pretrained()` method. This introduced... | {
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https://api.github.com/repos/huggingface/transformers/issues/2163 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2163/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2163/comments | https://api.github.com/repos/huggingface/transformers/issues/2163/events | https://github.com/huggingface/transformers/issues/2163 | 537,520,691 | MDU6SXNzdWU1Mzc1MjA2OTE= | 2,163 | PreTrainedEncoderDecoder on tensorflow | {
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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",
"We are still settling on the proper API for the pytorch version, so it will probably be awhile (months) before we make a tensorflow ver... | 1,576 | 1,584 | 1,581 | CONTRIBUTOR | null | ## 🚀 Feature
Hi, would it be possible to create a tensorflow version of `PreTrainedEncoderDecoder`?
## Motivation
The main motivation is that I would like to use `PreTrainedEncoderDecoder` in TensorFlow. Yeah, I got it, PyTorch is better and I totally agree but unfortunately, I have to use TensorFlow.
## Add... | {
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https://api.github.com/repos/huggingface/transformers/issues/2162 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2162/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2162/comments | https://api.github.com/repos/huggingface/transformers/issues/2162/events | https://github.com/huggingface/transformers/issues/2162 | 537,466,834 | MDU6SXNzdWU1Mzc0NjY4MzQ= | 2,162 | pad_to_max_length param is not supported in PreTrainedTokenizer.encode | {
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"Hello, can you try with the patch that was released today (2.2.2) and let me know if it works for you?",
"By updating the Transformers library from 2.2.1 to 2.2.2, **it works as expected without the bug** highlighted by @madrugado.\r\n\r\nMy environment is the following:\r\n- **Python** 3.6.9\r\n- **OS**: Ubuntu... | 1,576 | 1,598 | 1,576 | NONE | null | ## ❓ Questions & Help
Hello,
I've installed the current version of transformers package (2.2.1) through pip on Python 3.6.8rc1 on Windows 10 Pro (build 17763.678 if it is important). I am trying to get a sentence encoded and padded at the same time:
```python
tokenizer = BertTokenizer.from_pretrained('bert-ba... | {
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https://api.github.com/repos/huggingface/transformers/issues/2161 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2161/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2161/comments | https://api.github.com/repos/huggingface/transformers/issues/2161/events | https://github.com/huggingface/transformers/issues/2161 | 537,464,351 | MDU6SXNzdWU1Mzc0NjQzNTE= | 2,161 | Adding model type to config.json | {
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"Is now solved by this [PR](https://github.com/huggingface/transformers/pull/2494)\r\nThanks a lot!",
"Yes, thanks for the contribution @perdix!"
] | 1,576 | 1,579 | 1,579 | NONE | null | ## Feature
Add `model_type` to the *config.json* to define the model_type and make it independent from the name
## Motivation
Currently, the model type is automatically discovered from the name. So if it is a Bert model, the autoloader is choosing the right methods if the name contains `bert`. If not, an error wou... | {
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https://api.github.com/repos/huggingface/transformers/issues/2160 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2160/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2160/comments | https://api.github.com/repos/huggingface/transformers/issues/2160/events | https://github.com/huggingface/transformers/pull/2160 | 537,423,872 | MDExOlB1bGxSZXF1ZXN0MzUyNzgyMzUz | 2,160 | [WIP] Add UniLM model | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2160?src=pr&el=h1) Report\n> Merging [#2160](https://codecov.io/gh/huggingface/transformers/pull/2160?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f061606277322a013ec2d96509d3077e865ae875?src=pr&el=desc) will **i... | 1,576 | 1,669 | 1,592 | NONE | null | # Typical workflow for including a model
Here an overview of the general workflow:
- [x] add model/configuration/tokenization classes
- [x] add conversion scripts
- [x] add tests
- [x] finalize
Let's detail what should be done at each step
## Adding model/configuration/tokenization classes
Here is th... | {
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https://api.github.com/repos/huggingface/transformers/issues/2159 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2159/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2159/comments | https://api.github.com/repos/huggingface/transformers/issues/2159/events | https://github.com/huggingface/transformers/issues/2159 | 537,372,674 | MDU6SXNzdWU1MzczNzI2NzQ= | 2,159 | Low ROUGE scores for BertSum | {
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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'm struggling with this also :( did you make any progress diagnosing the problem?",
"No, I did not...I decided to go with a differen... | 1,576 | 1,604 | 1,593 | NONE | null | Great work, very easy to pick up and play with. I downloaded the CNN/DM stories from the link provided and selected only the files that belong to the test set following See et al.'s dataset splits (https://github.com/abisee/cnn-dailymail/blob/master/url_lists/all_test.txt). Then I ran the model using the first command ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2158 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2158/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2158/comments | https://api.github.com/repos/huggingface/transformers/issues/2158/events | https://github.com/huggingface/transformers/issues/2158 | 537,306,855 | MDU6SXNzdWU1MzczMDY4NTU= | 2,158 | gpt-2 implement issue | {
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"Hi, this is for the initialization. We don't have any scripts that show how to pretrain GPT-2 (therefore no need for initialization), only scripts to fine-tune it from a checkpoint.",
"thanks for your reply\r\n"
] | 1,576 | 1,577 | 1,577 | NONE | null | Thanks for your good implementation some model in pytorch!
gpt-2 paper mentioned that they did few modifications with original gpt, included "A modified initialization which accounts
for the accumulation on the residual path with model depth
is used. We scale the weights of residual layers at initialization by a fa... | {
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https://api.github.com/repos/huggingface/transformers/issues/2157 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2157/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2157/comments | https://api.github.com/repos/huggingface/transformers/issues/2157/events | https://github.com/huggingface/transformers/issues/2157 | 537,301,309 | MDU6SXNzdWU1MzczMDEzMDk= | 2,157 | How to find the corresponding download models from Amazon? | {
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"Hi, they are named as such because that's a clean way to make sure the model on the S3 is the same as the model in the cache. The name is created from the `etag` of the file hosted on the S3.\r\n\r\nIf you want to save it with a given name, you can save it as such:\r\n\r\n```py\r\nfrom transformers import BertMode... | 1,576 | 1,677 | 1,583 | NONE | null | ## ❓ Questions & Help
As we know, the TRANSFORMER could easy auto-download models by the pretrain( ) function.
And the pre-trained BERT/RoBerta model are stored at the path of
./cach/.pytorch/.transformer/....
But, all the name of the download models are like this:
d9fc1956a01fe24af529f239031a439661e7634e6... | {
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https://api.github.com/repos/huggingface/transformers/issues/2156 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2156/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2156/comments | https://api.github.com/repos/huggingface/transformers/issues/2156/events | https://github.com/huggingface/transformers/issues/2156 | 537,270,511 | MDU6SXNzdWU1MzcyNzA1MTE= | 2,156 | End-Task Distillation with DistilBERT | {
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"Hello @shreydesai,\r\nYou should have a look at [run_squad_w_distillation.py](https://github.com/huggingface/transformers/blob/master/examples/distillation/run_squad_w_distillation.py) which is the script used in the experiment you are mentioning.\r\nVictor",
"This issue has been automatically marked as stale be... | 1,576 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
The DistilBERT paper notes the IMDB and SQuAD results were obtained "with a second step of distillation during fine-tuning". What does this involve exactly and how can it be performed with the DistilBERT model in this repo? | {
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https://api.github.com/repos/huggingface/transformers/issues/2155 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2155/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2155/comments | https://api.github.com/repos/huggingface/transformers/issues/2155/events | https://github.com/huggingface/transformers/issues/2155 | 537,209,959 | MDU6SXNzdWU1MzcyMDk5NTk= | 2,155 | Special Tokens are Split by BPE | {
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"Hello! Indeed this is a known issue with version 2.2.1. You can either revert to 2.2.0 or install from source (`pip install git+https://github.com/huggingface/transformers`) until we push a new version (2.2.2) which should happen before the end of the week.",
"I confirm that reverting to 2.2.0 solves the problem... | 1,576 | 1,667 | 1,576 | NONE | null | ## 🐛 Bug
When I load 'distilbert-base-uncased' DistilBertTokenizer (with do_basic_tokenize=False) and call tokenize() on a string that includes special tokens, the special tokens are broken up by BPE.
Model I am using (Bert, XLNet....): DistilBertForSequenceClassification
Language I am using the model on (Eng... | {
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https://api.github.com/repos/huggingface/transformers/issues/2154 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2154/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2154/comments | https://api.github.com/repos/huggingface/transformers/issues/2154/events | https://github.com/huggingface/transformers/issues/2154 | 537,089,530 | MDU6SXNzdWU1MzcwODk1MzA= | 2,154 | AlBERT UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte | {
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"Hello! Could you please tell me which model you are trying to download? I've just tried the following command and it succeeded without any issues:\r\n```py\r\nAlbertForQuestionAnswering.from_pretrained(\"albert-base-v2\", force_download=True)\r\n```\r\n\r\nI put the `force_download` flag to True to make sure I was... | 1,576 | 1,576 | 1,576 | NONE | null | ## ❓ Questions & Help
Hi! There is some problem while downloading any of the pre-trained Al... | {
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https://api.github.com/repos/huggingface/transformers/issues/2153 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2153/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2153/comments | https://api.github.com/repos/huggingface/transformers/issues/2153/events | https://github.com/huggingface/transformers/issues/2153 | 536,784,738 | MDU6SXNzdWU1MzY3ODQ3Mzg= | 2,153 | BertAbs decoder_input_ids | {
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"Could you please post the full stack trace as well as the part of the code you use for fine-tuning?",
"See here: https://gist.github.com/ohmeow/f2cc6ea0a9d0e4a5fa227942edcfa723\n\nI think it has something to do with how I'm preparing the target tokens but\nI'm not sure what the appropriate fix is. Looked at th... | 1,576 | 1,583 | 1,583 | CONTRIBUTOR | null | ## ❓ Questions & Help
What should the `decoder_input_ids` look like if we are fine-tuning the model on our own dataset?
I tried `[unused0] [unused2] summary_sent_toks [unused2] summary_sent_toks2 [unused1]` (looking at the paper) ... but I get shape errors because of line 150 in `modeling_bertabs.py`:
```
dec... | {
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https://api.github.com/repos/huggingface/transformers/issues/2152 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2152/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2152/comments | https://api.github.com/repos/huggingface/transformers/issues/2152/events | https://github.com/huggingface/transformers/issues/2152 | 536,712,877 | MDU6SXNzdWU1MzY3MTI4Nzc= | 2,152 | RoBERTa/GPT-2 tokenization: Why we call all_special_tokens for each token in split_all_tokens? | {
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"Hi, could you provide an example that was sped up by replacing that variable? When tokenizing 55k tokens 10 times without creating a variable for all_special_tokens I get the result in 3.88s whereas when creating a variable I get the result in 3.87s. This doesn't seem like such a big difference!",
"In my case, I... | 1,576 | 1,576 | 1,576 | NONE | null | Is there a reason why the property function `all_special_tokens` is called in each iteration in `split_on_tokens()` when looping over all tokens?
When I initialize a new variable and call all_special_tokens only once in the tokenizer init, the tokenization is speed-up around 2~3 times for me. Maybe I am missing some... | {
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When I initialize a new variable and call `all_special_tokens` only once in the tokenizer init, the tokenization is speed-up around 2~3 times for me. | {
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https://api.github.com/repos/huggingface/transformers/issues/2150 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2150/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2150/comments | https://api.github.com/repos/huggingface/transformers/issues/2150/events | https://github.com/huggingface/transformers/issues/2150 | 536,709,591 | MDU6SXNzdWU1MzY3MDk1OTE= | 2,150 | RoBERTa tokenization: Why do we call 'all_special_tokens' in each tokenize loop? | {
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https://api.github.com/repos/huggingface/transformers/issues/2149 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2149/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2149/comments | https://api.github.com/repos/huggingface/transformers/issues/2149/events | https://github.com/huggingface/transformers/pull/2149 | 536,676,301 | MDExOlB1bGxSZXF1ZXN0MzUyMTY2OTE2 | 2,149 | :bug: #2120 in model.from_pretrained, PosixPath crashes at "albert" check | {
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"Ok, I've checked the errors in CI. Those are linked to the fact that in older python version, PosixPath is not converted automatically to String and `os.path.isdir/isfile` crash because it expects a string or int. So my patch works perfectly in latest version of python (like 3.7) but not older (like 3.5) which is ... | 1,576 | 1,576 | 1,576 | NONE | null | - `pretrained_model_name_or_path` is now stringified to allow the "albert" and "v2" checks with PosixPath (or any other path representation that isn't iterable).
- If `pretrained_model_name_or_path` is None, it gives string "None" which doesn't contain "albert" so it's OK.
- 2 x `str(pretrained_model_name_or_path)` d... | {
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https://api.github.com/repos/huggingface/transformers/issues/2148 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2148/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2148/comments | https://api.github.com/repos/huggingface/transformers/issues/2148/events | https://github.com/huggingface/transformers/pull/2148 | 536,592,500 | MDExOlB1bGxSZXF1ZXN0MzUyMDk2ODI0 | 2,148 | Fix encode plus | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2148?src=pr&el=h1) Report\n> Merging [#2148](https://codecov.io/gh/huggingface/transformers/pull/2148?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/030faccb8d45be9bdd2b4b80ff26f36dc41f622a?src=pr&el=desc) will **d... | 1,576 | 1,576 | 1,576 | MEMBER | null | Fixing the tensor creation in encode_plus | {
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https://api.github.com/repos/huggingface/transformers/issues/2147 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2147/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2147/comments | https://api.github.com/repos/huggingface/transformers/issues/2147/events | https://github.com/huggingface/transformers/issues/2147 | 536,532,557 | MDU6SXNzdWU1MzY1MzI1NTc= | 2,147 | Recommended way for creating distillBERT container and serving | {
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"You can find the s3 URL of models here for distilbert: https://github.com/huggingface/transformers/blob/master/transformers/configuration_distilbert.py\r\n\r\nIf you build the docker on your machine, first download model files on your machine.\r\nThen just add those files to your container through Dockerfile.\r\n\... | 1,576 | 1,579 | 1,579 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
As per documentation, I am supposed to load distilbert as below.
question_answering_model = torch.hub.load('huggingface/pytorch-transformers', 'modelForQuestionAnswering', 'distilbert-base-uncased-distilled-squad')
question_answerin... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2146?src=pr&el=h1) Report\n> Merging [#2146](https://codecov.io/gh/huggingface/transformers/pull/2146?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2e2f9fed554bb5f147ea3d9573004b447dd7c9e7?src=pr&el=desc) will **n... | 1,576 | 1,576 | 1,576 | COLLABORATOR | null | Hi,
this PR fixes the pretrained models table, see #2145. | {
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https://api.github.com/repos/huggingface/transformers/issues/2145 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2145/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2145/comments | https://api.github.com/repos/huggingface/transformers/issues/2145/events | https://github.com/huggingface/transformers/issues/2145 | 536,484,061 | MDU6SXNzdWU1MzY0ODQwNjE= | 2,145 | the docs pretrained models is missing | {
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"Should be working now :)",
"Thanks @PiotrCzapla for raising the issue, @stefan-it fixed it earlier today!"
] | 1,576 | 1,576 | 1,576 | NONE | null | Hi,
your docs have the table with pretrained models missing, probably some formatting error, as the source code has the table
<img width="1280" alt="Screenshot 2019-12-11 at 17 31 01" src="https://user-images.githubusercontent.com/340180/70640463-4174a380-1c3c-11ea-9c6e-ca343ef46332.png">
https://huggingface.co/tra... | {
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https://api.github.com/repos/huggingface/transformers/issues/2144 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2144/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2144/comments | https://api.github.com/repos/huggingface/transformers/issues/2144/events | https://github.com/huggingface/transformers/pull/2144 | 536,477,233 | MDExOlB1bGxSZXF1ZXN0MzUyMDAwNDAy | 2,144 | Allowing from_pretrained to load from url directly | {
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"cc @mfuntowicz ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2144?src=pr&el=h1) Report\n> Merging [#2144](https://codecov.io/gh/huggingface/transformers/pull/2144?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2d103546ef102d69ea12cdca3ec3163052886851?src... | 1,576 | 1,576 | 1,576 | MEMBER | null | Allowing `from_pretrained` to load from url directly. | {
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https://api.github.com/repos/huggingface/transformers/issues/2143 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2143/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2143/comments | https://api.github.com/repos/huggingface/transformers/issues/2143/events | https://github.com/huggingface/transformers/pull/2143 | 536,436,213 | MDExOlB1bGxSZXF1ZXN0MzUxOTY2MDI4 | 2,143 | Fix typo in examples/run_glue.py args declaration. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2143?src=pr&el=h1) Report\n> Merging [#2143](https://codecov.io/gh/huggingface/transformers/pull/2143?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4c12860f7ae61659aed2675498350a386fc4e122?src=pr&el=desc) will **n... | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | deay -> decay | {
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https://api.github.com/repos/huggingface/transformers/issues/2142 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2142/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2142/comments | https://api.github.com/repos/huggingface/transformers/issues/2142/events | https://github.com/huggingface/transformers/issues/2142 | 536,425,082 | MDU6SXNzdWU1MzY0MjUwODI= | 2,142 | master branch examples/run_squad.py: missing --predict_file argparse argument | {
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"In order to use the **evaluation** mode, you have to pass from script the `do_eval` parameter (in addition to the \"classical\" input parameters for evaluation).\r\n\r\n> ## Bug\r\n> Model I am using: albert\r\n> \r\n> Language I am using the model on (English, Chinese....): English\r\n> \r\n> The problem arise w... | 1,576 | 1,581 | 1,581 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using: albert
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [X] the official example scripts: (give details)
examples/run_squad/py: --predict_file not recognized
* [ ] my own modified scripts: (give det... | {
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"_DistilGPT2Config_, _DistilGPT2LMHeadModel_ and _DistilGPT2Tokenizer_ **don't exist**. In order to fine-tuning the DistilGPT2 model for LM, you can use the following settings of tokenizer, config and model:\r\n**Tokenizer**:\r\n```\r\n> from transformers import GPT2Tokenizer\r\n> tokenizer = GPT2Tokenizer.from_pr... | 1,576 | 1,694 | 1,576 | NONE | null | ## ❓ Questions & Help
To my understanding, examples/run_lm_finetuning.py can be used to fine-tune the model to new data. How do I fine-tune a distilled GPT-2? To be precise, I assume that I can use the entire code, but I just need to import the right module. I tried importing DistilGPT2Config, DistilGPT2LMHeadModel,... | {
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https://api.github.com/repos/huggingface/transformers/issues/2140 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2140/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2140/comments | https://api.github.com/repos/huggingface/transformers/issues/2140/events | https://github.com/huggingface/transformers/issues/2140 | 536,364,547 | MDU6SXNzdWU1MzYzNjQ1NDc= | 2,140 | return_tokens_mapped_to_origin not working | {
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"What is the idea here? That for each (sub)token its \"parent\" token ID is remembered? That would be so great. I can definitely use functionality like that.",
"> What is the idea here? That for each (sub)token its \"parent\" token ID is remembered? That would be so great. I can definitely use functionality like ... | 1,576 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
Model I am using: **Bert**
Language I am using the model on: **English**
## To Reproduce
Call `bertTokenizer.tokenize("text", return_tokens_mapped_to_origin=True)`
Result:
> TypeError: _tokenize() got an unexpected keyword argument 'return_tokens_mapped_to_origin'
## Expected behavior
The offi... | {
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"If you want to look the source code used for training the model, you can look at the source [GitHub](https://github.com/nlpyang/PreSumm), in particular you can view the `src/train.py`, `src/train_abstractive.py` or `src/train_extractive.py` Python scripts.",
"@TheEdoardo93 Thank you for your reply. I know, will ... | 1,576 | 1,584 | 1,583 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Thank you very much for your wonderful work. I found that some new code for summarization has been added from "pretrained encoder" paper. However, I see only the evaluation part of the code. I want to ask if you will add the code for th... | {
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"Hi, thanks for raising this issue!\r\n\r\nWhen running this code on the master branch, I do get the attention mask as output, but only when removing the `return_tensors` argument. When running with this argument, it crashes because a list is being concatenated to a tensor. I'm fixing this in #2148.\r\n\r\nIt's wei... | 1,576 | 1,594 | 1,594 | COLLABORATOR | null | ## 🐛 Bug
Tested on RoBERTa and BERT of the master branch, the [`encode_plus`](https://huggingface.co/transformers/main_classes/tokenizer.html#transformers.PreTrainedTokenizer.encode_plus) method of the tokenizer does not return an attention mask. The documentation states that by default an attention_mask is returne... | {
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https://api.github.com/repos/huggingface/transformers/issues/2137 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2137/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2137/comments | https://api.github.com/repos/huggingface/transformers/issues/2137/events | https://github.com/huggingface/transformers/issues/2137 | 536,211,148 | MDU6SXNzdWU1MzYyMTExNDg= | 2,137 | Tokenization in C++ | {
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"You should wait a few days if you can because @n1t0 is working on something that will very likely solve your problem and it should be ready for a first release before the end of the year.",
"Any update on this? It is already beyond \"the end of the year\".",
"I also tried to figure out an alternative beyond ma... | 1,576 | 1,685 | 1,578 | NONE | null | Is there any general strategy for tokenizing text in C++ in a way that's compatible with the existing pretrained `BertTokenizer` implementation?
I'm looking to use a finetuned BERT model in C++ for inference, and currently the only way seems to be to reproduce the `BertTokenizer` code manually (or modify it to be comp... | {
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"This should be fixed in the current master but not in a release AFAIK. See https://github.com/huggingface/transformers/issues/2132 and close this issue please.",
"Okay thanks!"
] | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | ## 🐛 Bug
<!-- Important information -->
Model I am using is `bert-base-uncased`:
Language I am using the model on (English):
## To Reproduce
Steps to reproduce the behavior:
1. Just Ran the example from the docs
```
import torch
from transformers import BertTokenizer, BertModel, BertForMaskedLM
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https://api.github.com/repos/huggingface/transformers/issues/2135 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2135/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2135/comments | https://api.github.com/repos/huggingface/transformers/issues/2135/events | https://github.com/huggingface/transformers/issues/2135 | 536,111,524 | MDU6SXNzdWU1MzYxMTE1MjQ= | 2,135 | Is there support for TensorflowJs? | {
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"My understanding is that tfjs is still kinda unstable so you’d be better off bringing that issue there.\r\n\r\nThat being said, @Pierrci has tried to do similar stuff so might be able to chime in.",
"thanks, @julien-c I will repost there. Do you think I could have better luck if I try this with torchjs instead? ... | 1,576 | 1,576 | 1,576 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I managed to save my tenforflow 2.0 model and I see keras .h5 and config.json files.
When I run the tensorflowjs converter it seems to run with no issues.
!tensorflowjs_converter --input_format=keras save/tf_model.h5 save/tfjs_mod... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2134?src=pr&el=h1) Report\n> Merging [#2134](https://codecov.io/gh/huggingface/transformers/pull/2134?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/18601c3b6e46e05c4a78303a9e6036f795f82180?src=pr&el=desc) will **d... | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | #1987 was merged in before I could update the other pytorch examples. This should also close #1960 once it's merged in. | {
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"Thanks a lot for your input. We're trying to continually improve our training scripts and would like to keep them efficient while keeping them understandable.\r\n\r\nAs you have noticed, we have recently refactored the glue and squad scripts somewhat, and will continue to do so. Your input is appreciated and we're... | 1,576 | 1,581 | 1,581 | NONE | null | ## Request
Push some/most/all the functionality of the squad training scripts into the class ``XXXForQuestionAnswering``.
## Alt Request.
I'm guessing this is immediately objectionable, since ``XXXForQuestionAnswering`` is just the nice clean NN.
No messy string manipulation functions welcome here.
So pe... | {
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"`git bisect` says the commit introducing this problem is 7246d3c2f93c4461f3ec8ada7a26a002d8f196ea.",
"Any way you could run the same test on `master`? It might have been fixed since.",
"I did. It was not fixed in master.\n\nIt only affects the [MASK] token.\n\nOn Tue, Dec 10, 2019, 16:25 Julien Chaumond <notif... | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | In `v2.2.1`, the `bert-base-uncased` tokenizer changed in a way that's probably not intentional:
```
Python 3.7.5 (default, Oct 25 2019, 10:52:18)
[Clang 4.0.1 (tags/RELEASE_401/final)] :: Anaconda, Inc. on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from transformers.tokeni... | {
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- adds progress bars to tokenization | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2130?src=pr&el=h1) Report\n> Merging [#2130](https://codecov.io/gh/huggingface/transformers/pull/2130?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6a73382706ce3c6905023872f63a680f0eb419a4?src=pr&el=desc) will **d... | 1,576 | 1,651 | 1,576 | MEMBER | null | The CrossEntropy loss, as well as other losses, accept a value as an index they will ignore when computing the loss. This value was set to -1 in some cases, but left to the default value (-100) in other cases.
To stay consistent we're setting the value to be the default PyTorch one in all cases.
Includes a few do... | {
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```
4%|▉ | 257561600/6431878936 [00:33<16:12, 6351328.14B/s]
```
With this change, the progress bar is much more readable:
```
Downloading: 3%|▋ ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2128 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2128/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2128/comments | https://api.github.com/repos/huggingface/transformers/issues/2128/events | https://github.com/huggingface/transformers/issues/2128 | 535,940,115 | MDU6SXNzdWU1MzU5NDAxMTU= | 2,128 | In which directory the downloaded roberta-base models will be stored on linux server conda environment | {
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"Models downloaded with the `XXXModel.from_pretrained` method are usually in the torch home folder, which is `~/.cache/torch/transformers`",
"Thanks for your response. I could see there are some files with below names\r\nb35e7cd126cd4229a746b5d5c29a749e8e84438b14bcdb575950584fe33207e8.70bec105b4158ed9a1747fea67a4... | 1,576 | 1,612 | 1,583 | NONE | null | ## In which directory the downloaded roberta-base models will be stored on linux server conda environment
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https://api.github.com/repos/huggingface/transformers/issues/2127 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2127/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2127/comments | https://api.github.com/repos/huggingface/transformers/issues/2127/events | https://github.com/huggingface/transformers/issues/2127 | 535,870,276 | MDU6SXNzdWU1MzU4NzAyNzY= | 2,127 | Where is extract_features.py and run_classifier.py ? | {
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"Reading the answer given by @thomwolf in #1123, I'm sure that `extract_features.py` script has been removed from repo, but in the future it could be updated!\r\n\r\nReading the answer given by @ningjize in #1011, I'm sure that `run_classifier.py` script has been updated as `run_glue.py` script, that you can find i... | 1,575 | 1,576 | 1,576 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hello! I couldn't find the extract_features.py and run_classifier.py. Have they been renamed ? | {
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https://api.github.com/repos/huggingface/transformers/issues/2126 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2126/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2126/comments | https://api.github.com/repos/huggingface/transformers/issues/2126/events | https://github.com/huggingface/transformers/issues/2126 | 535,844,695 | MDU6SXNzdWU1MzU4NDQ2OTU= | 2,126 | Model2Model: RuntimeError: expected device cpu and dtype Float but got device cpu and dtype Bool | {
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"In my environment, the code you've posted **works as expected**.\r\n- Python: 3.6.9\r\n- Transformers: 2.2.1 (installed from PyPi with pip install transformers)\r\n- PyTorch: 1.3.1\r\n- TensorFlow: 2.0\r\n- OS: Ubuntu 16.04\r\n\r\nHere the stack trace:\r\n```\r\nPython 3.6.9 |Anaconda, Inc.| (default, Jul 30 2019,... | 1,575 | 1,575 | 1,575 | NONE | null | ## ❓ Questions & Help
I'm going to try the new Model2Model feature:
```
import torch
import numpy as np
from transformers import Model2Model, BertTokenizer, BertModel
# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
device = torch.device("cpu")
tokenizer = BertTokenizer.from_pretr... | {
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https://api.github.com/repos/huggingface/transformers/issues/2125 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2125/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2125/comments | https://api.github.com/repos/huggingface/transformers/issues/2125/events | https://github.com/huggingface/transformers/issues/2125 | 535,810,897 | MDU6SXNzdWU1MzU4MTA4OTc= | 2,125 | DistilmBERT training/distillation dataset | {
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"By reading the [official docs](https://github.com/huggingface/transformers/tree/master/examples/distillation), I think that they have trained Distil**m**BERT . For what concern the pre-processing steps, there are no information about that (surely I'm interested in these steps too). It would be more useful and prec... | 1,575 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
Thanks a lot for Distil**m**BERT (amongst everything else), is there any info on the dataset used in the distillation process?
Both the dataset itself or the process used to obtain it would be greatly appreciated!
Am I right to assume you used a similar (if not the same) data as the ori... | {
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https://api.github.com/repos/huggingface/transformers/issues/2124 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2124/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2124/comments | https://api.github.com/repos/huggingface/transformers/issues/2124/events | https://github.com/huggingface/transformers/issues/2124 | 535,761,421 | MDU6SXNzdWU1MzU3NjE0MjE= | 2,124 | Is there a way to evaluate models during training in Multi-gpu setting | {
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"Yes. After each batch has been completed by a GPU, you can store its results and corresponding labels in a shared space (e.g. CPU/memory). Then, when all batches are done, you can evaluate the epoch by calculating your metric/avg loss over all gathered results. It has been suggested to only keep track of the batch... | 1,575 | 1,609 | 1,581 | NONE | null | ## ❓ Questions & Help
Hi all,
I always see comments in examples saying that "when single GPU otherwise metrics may not average well". So is this really something that shouldn't be done? I mean, is there a way to evaluate the model safely after each epoch in the multi-gpu training setting? Thanks.
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https://api.github.com/repos/huggingface/transformers/issues/2123 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2123/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2123/comments | https://api.github.com/repos/huggingface/transformers/issues/2123/events | https://github.com/huggingface/transformers/issues/2123 | 535,749,750 | MDU6SXNzdWU1MzU3NDk3NTA= | 2,123 | Transformers for Tabular data extraction - e.g., wikitables | {
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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)... | 1,575 | 1,619 | 1,619 | NONE | null | Hi Team,
Can you please let us know if Transformers can be used to extract information from tabular data. Example is - [https://demo.allennlp.org/wikitables-parser](https://demo.allennlp.org/wikitables-parser) . WikiTables is the dataset.
Example questions can be: show me all students who got marks greater than 4... | {
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https://api.github.com/repos/huggingface/transformers/issues/2122 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2122/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2122/comments | https://api.github.com/repos/huggingface/transformers/issues/2122/events | https://github.com/huggingface/transformers/pull/2122 | 535,744,737 | MDExOlB1bGxSZXF1ZXN0MzUxNDAyMjMw | 2,122 | Remove misplaced summarization documentation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2122?src=pr&el=h1) Report\n> Merging [#2122](https://codecov.io/gh/huggingface/transformers/pull/2122?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e57d00ee108595375504eb21c230ce35428aae5e?src=pr&el=desc) will **n... | 1,575 | 1,575 | 1,575 | CONTRIBUTOR | null | Documentation for the previous version of abstractive summarization is still present in the repository:
https://twitter.com/DavidMezzetti/status/1204123548966621184
This PR removes it. | {
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https://api.github.com/repos/huggingface/transformers/issues/2121 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2121/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2121/comments | https://api.github.com/repos/huggingface/transformers/issues/2121/events | https://github.com/huggingface/transformers/issues/2121 | 535,593,876 | MDU6SXNzdWU1MzU1OTM4NzY= | 2,121 | "Write With Transformer" interface returning 502 on gpt2/xl model | {
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The "Write With Transformer" interface is returning a `502` when the API calls the gpt2/xl model.
See: https://transformer.huggingface.co/doc/gpt2-xl
## To Reproduce
Steps to reproduce the behavior just using the API request:
```
curl 'https://transformer.huggingface.co/autocomplete/gpt2/xl' -... | {
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https://api.github.com/repos/huggingface/transformers/issues/2120 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2120/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2120/comments | https://api.github.com/repos/huggingface/transformers/issues/2120/events | https://github.com/huggingface/transformers/issues/2120 | 535,551,148 | MDU6SXNzdWU1MzU1NTExNDg= | 2,120 | BertModel.from_pretrained() doesn't accept pathlib.PosixPath anymore | {
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"It comes from this line https://github.com/huggingface/transformers/blob/master/transformers/modeling_utils.py#L321-L324\r\nIf it's a PosixPath, it's not an iterable so `\"albert\" in path` crashes.\r\nPatch already pushed in previous PR!",
"This issue has been automatically marked as stale because it has not ha... | 1,575 | 1,581 | 1,581 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Bert
Language I am using the model on (English, Chinese....): Japanese
The problem arise when using:
* [ ] the official example scripts: (give details)
* [x] my own modified scripts: (give details)
The tasks I am working on is... | {
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https://api.github.com/repos/huggingface/transformers/issues/2119 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2119/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2119/comments | https://api.github.com/repos/huggingface/transformers/issues/2119/events | https://github.com/huggingface/transformers/issues/2119 | 535,491,079 | MDU6SXNzdWU1MzU0OTEwNzk= | 2,119 | Finetune and generate text with BertForMaskedLM | {
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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",
"did you find a solution?",
"Hi, I am also encountering this problem. Is it possible to please provide an example for fine tuning Bert... | 1,575 | 1,594 | 1,581 | NONE | null | ## ❓ Questions & Help
I am trying to fine-tune and generate text using BertForMaskedLM. Although my script works I am not getting the output I am expecting. I am confused on what should I pass to BertForMaskedLM when training (attention mask, token types ids, etc) and how to generate text once the model is fine tune... | {
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https://api.github.com/repos/huggingface/transformers/issues/2118 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2118/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2118/comments | https://api.github.com/repos/huggingface/transformers/issues/2118/events | https://github.com/huggingface/transformers/issues/2118 | 535,479,745 | MDU6SXNzdWU1MzU0Nzk3NDU= | 2,118 | Could convert_pytorch_checkpoint_to_tf2.py convert any pytorch model to tf2? | {
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"I think **no**. You can use this Python script to convert a PyTorch implementation of one of the models supported by Transformers to TensorFlow 2.0 version.\r\n\r\nHave you ever tried to use this Python script to convert **any** PyTorch model to TensorFlow 2.0?\r\n\r\n> ## Questions & Help",
"@TheEdoardo93 No,h... | 1,575 | 1,581 | 1,581 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
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"Hi @anandhperumal,\r\n\r\nThank you for posting an issue. Just to clarify:\r\n\r\n1. Indeed, as I specified in the article, `PreTrainedEncoderDecoder` only works with BERT as an encoder and BERT as a decoder. GPT2 shouldn't take too much work to adapt, but we haven't had the time to do it yet. Try `PreTrainedEncod... | 1,575 | 1,597 | 1,592 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [X ] the official example scripts: (give details)
* [ ] my own modified scripts: (give details)
The tasks I am working on is:
* [ ] an o... | {
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https://api.github.com/repos/huggingface/transformers/issues/2116 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2116/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2116/comments | https://api.github.com/repos/huggingface/transformers/issues/2116/events | https://github.com/huggingface/transformers/issues/2116 | 535,459,196 | MDU6SXNzdWU1MzU0NTkxOTY= | 2,116 | Couldn't reach server at '{}' to download vocabulary files. | {
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"Did you find out what the problem was @venusafroid ?",
"> Did you find out what the problem was @venusafroid ?\r\n\r\nI think op had a problem connecting to s3 as shown in the log\r\n```\r\nrequests.exceptions.ConnectionError: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url:... | 1,575 | 1,593 | 1,575 | NONE | null | Traceback (most recent call last):
File "/home/hgy/anaconda3/envs/pytorch-python3/lib/python3.6/site-packages/urllib3/connection.py", line 157, in _new_conn
(self._dns_host, self.port), self.timeout, **extra_kw
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https://api.github.com/repos/huggingface/transformers/issues/2115 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2115/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2115/comments | https://api.github.com/repos/huggingface/transformers/issues/2115/events | https://github.com/huggingface/transformers/pull/2115 | 535,456,054 | MDExOlB1bGxSZXF1ZXN0MzUxMTcwMjYz | 2,115 | [WIP] Add MMBT Model to Transformers Repo | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2115?src=pr&el=h1) Report\n> Merging [#2115](https://codecov.io/gh/huggingface/transformers/pull/2115?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1d189304624db17749aee23fa2345f009cc48215?src=pr&el=desc) will **d... | 1,575 | 1,585 | 1,576 | NONE | null | Implements the MMBT Model from Supervised Multimodal Bitransformers for Classifying Images and Text by Douwe Kiela, Suvrat Bhooshan, Hamed Firooz, Davide Testuggine (https://arxiv.org/abs/1909.02950) (https://github.com/facebookresearch/mmbt/)
Adds run_mmimdb.py to show example training run on MM-IMDb dataset (http:... | {
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https://api.github.com/repos/huggingface/transformers/issues/2114 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2114/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2114/comments | https://api.github.com/repos/huggingface/transformers/issues/2114/events | https://github.com/huggingface/transformers/issues/2114 | 535,193,475 | MDU6SXNzdWU1MzUxOTM0NzU= | 2,114 | Split models to multiple GPUs | {
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"Indeed, as of now we don't support model splitting across different GPUs. However, I believe Tesla P100s have 16gb (or 12?) of VRAM and GPT-2 XL fits in ~7-8gb of VRAM. Do you get an OOM error when loading GPT-2 large in memory?",
"Thanks @LysandreJik. I trained gpt2-medium and it took almost the whole ram ~15gb... | 1,575 | 1,576 | 1,576 | NONE | null | I am willing to fine-tune GPT2-large which simply does not fit into GPU memory. I wanted to run the script `run_lm_finetuning.py` with GPT2-large having two Nvidia Tesla P100, but I suppose model splitting in not supported. Or am I wrong?
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https://api.github.com/repos/huggingface/transformers/issues/2113 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2113/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2113/comments | https://api.github.com/repos/huggingface/transformers/issues/2113/events | https://github.com/huggingface/transformers/issues/2113 | 535,083,709 | MDU6SXNzdWU1MzUwODM3MDk= | 2,113 | Running run_lm_finetuning.py within python | {
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"You have two choices:\r\n- transform the code into `run_lm_finetuning.py` as Python functions and use them (I think it's **the most elegant solution**). In order to do that, you've to convert the `main` method with `argparse` arguments to a method without `argparse` and after that you can use the script as given\r... | 1,575 | 1,575 | 1,575 | NONE | null | ## Setup
* Model: roberta-base
* Language: english
* OS: Ubuntu 18.04.3
* Python version: 3.7.3
* PyTorch version: 1.3.1+cpu
* PyTorch Transformers version (or branch): 2.2.0
* Using GPU ? No
* Distributed of parallel setup ? No
* Script inputs:
```
python run_lm_finetuning.py \
--output_dir=$OUTPUT_DIR \
... | {
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