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- Remove metrics | {
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https://api.github.com/repos/huggingface/transformers/issues/3208 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3208/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3208/comments | https://api.github.com/repos/huggingface/transformers/issues/3208/events | https://github.com/huggingface/transformers/issues/3208 | 578,828,557 | MDU6SXNzdWU1Nzg4Mjg1NTc= | 3,208 | Error loading pretrained bert-base-multilingual-cased | {
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"You're creating a configuration based on the size of `bert-base-uncased`, so yes, it will work for that checkpoint. For any other checkpoint, however, you would need to change the values which are different (e.g. vocab size, which is what's failing in your case). It is indicated in the [documentation](https://hugg... | 1,583 | 1,584 | 1,584 | NONE | null | # 🐛 Bug
## Information
Loading `bert-base-multilingual-cased` from pretrained gives an error:
```
Traceback (most recent call last):
File "error.py", line 4, in <module>
bert_model = transformers.AutoModel.from_pretrained('bert-base-multilingual-cased', config=config)
File "/scratch/gobi1/bai/bai-... | {
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https://api.github.com/repos/huggingface/transformers/issues/3207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3207/comments | https://api.github.com/repos/huggingface/transformers/issues/3207/events | https://github.com/huggingface/transformers/issues/3207 | 578,744,211 | MDU6SXNzdWU1Nzg3NDQyMTE= | 3,207 | Pipeline for Question Answering: How to return multiple correct answers output? | {
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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 need a solution to this problem as well please help\r\n\r\nThanks.",
"The solution is to use the `topk` parameter, for example, fol... | 1,583 | 1,674 | 1,589 | NONE | null | Very simple question I'm using transformer pipelines question answering on a very long piece of text. And, it is the cases that the are are multiple cases for the correct answer. I want them all.
I was wondering if I could retrieve the 10 best scores of output instead of just one.
Many thanks. | {
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https://api.github.com/repos/huggingface/transformers/issues/3206 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3206/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3206/comments | https://api.github.com/repos/huggingface/transformers/issues/3206/events | https://github.com/huggingface/transformers/issues/3206 | 578,736,258 | MDU6SXNzdWU1Nzg3MzYyNTg= | 3,206 | More details about DistilBERT experiment setting. | {
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"Did you take a look at the [distillation README](https://github.com/huggingface/transformers/tree/master/examples/distillation)? It shows the command that was used to train the distilled model.",
"Hey @silencio94, if you need help with distillation, drop me an email at clement [at] huggingface [dot] co.",
"Tha... | 1,583 | 1,584 | 1,584 | NONE | null | NIPS workshop paper (http://arxiv.org/abs/1910.01108) does not provide loss weights and other distillation hyper-paramerters (temperature, learning rate, epoch, step... ). and also (https://medium.com/huggingface/distilbert-8cf3380435b5). So when I try to experiment with this scripts(/transformers/examples/distillation... | {
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https://api.github.com/repos/huggingface/transformers/issues/3205 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3205/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3205/comments | https://api.github.com/repos/huggingface/transformers/issues/3205/events | https://github.com/huggingface/transformers/issues/3205 | 578,583,425 | MDU6SXNzdWU1Nzg1ODM0MjU= | 3,205 | where is the position emdeddings in bert for training a new model from scratch ? | {
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"Right here\r\n\r\nhttps://github.com/huggingface/transformers/blob/31f2437f07cf014a042789f52fa1519a485e8b2b/src/transformers/modeling_bert.py#L150\r\n\r\nIn the future, please make an effort to write a decent post that explains exactly what you need. This is very low quality.",
"Sry for low quality. But how abou... | 1,583 | 1,589 | 1,589 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/3204 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3204/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3204/comments | https://api.github.com/repos/huggingface/transformers/issues/3204/events | https://github.com/huggingface/transformers/issues/3204 | 578,542,586 | MDU6SXNzdWU1Nzg1NDI1ODY= | 3,204 | UnboundLocalError: local variable 'tokenizer' referenced before assignment | {
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"Plus：I have seen a similiar issue in this project,however the problem in that issue is that he did not input the right pretrain_weights.But I do not think that will be the solution in here",
"Similiarly,I aslo tried DistilBert,Roberta,XLMRoberta,these 3 models also cannot work for me,the error message is the sam... | 1,583 | 1,590 | 1,590 | NONE | null | I am runnnig the example code on the homepage.
However,I met this problem.
```
import torch
from transformers import *
MODELS = [(BertModel, BertTokenizer, 'bert-base-uncased'),
(OpenAIGPTModel, OpenAIGPTTokenizer, 'openai-gpt'),
(GPT2Model, GPT2Tokenizer, 'gpt2'),... | {
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"**EDIT** : \r\nI've been accidentally testing this code on the 2.4.1 version in a different environment. Since I've updated to 2.5.1 the behavior is as expected."
] | 1,583 | 1,583 | 1,583 | NONE | null | # 🐛 Bug
## Information
The model i'm using is CamebertTokenizer for the French language
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the n... | {
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- Clarify that the model is not trained on the evaluation set | {
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"For some reason there isn't a TF pretrained checkpoint for gpt2-xl [here](https://github.com/huggingface/transformers/blob/9499a3778e1b782f03bc3b15b2ae0cbd20b6391f/src/transformers/modeling_tf_gpt2.py#L39) but there is for Pytorch [here](https://github.com/huggingface/transformers/blob/4134100363e878693aa41f4a25a6... | 1,583 | 1,584 | 1,584 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): TFGPT2LMHeadModel
The colab notebook works for all model sizes except for gpt2-xl, where it throws an error. It looks like it can't download the correct checkpoint from the model name (gpt2-xl)
I tried running the colab notebook with other gpt2-mod... | {
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"This solved a CUDA runtime error for me. Strange! Thanks for this PR!"
] | 1,583 | 1,584 | 1,584 | MEMBER | null | XLM-R Tokenizer had a lot of issues that were not identified as no testing was done on it.
closes #2993
closes #2795
closes #2741
closes #2727
closes #2508
This fixes all the above issues, and works for all official checkpoints as well as other SPM files.
However, there are a few things I dislike about th... | {
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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"
] | 1,583 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
Model I am using (RoBerta):
Language I am using the model on (English):
The problem arises when using:
* [ ] the official example scripts: (give details below)
Using the script provided in run_language_modeling.py I tried to fine tune the model on my
own dataset. But ... | {
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"It's in your torch home:\r\n\r\n```py\r\n>>> from torch.hub import _get_torch_home\r\n>>> _get_torch_home()\r\n'/home/<USER>/.cache/torch'\r\n```"
] | 1,583 | 1,583 | 1,583 | NONE | null | # ❓ Questions & Help
```
from transformers import DistilBertTokenizer, DistilBertModel
tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
model = DistilBertModel.from_pretrained('distilbert-base-uncased')
```
I can't find the downloaded file.
Thanks for your help | {
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https://api.github.com/repos/huggingface/transformers/issues/3192 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3192/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3192/comments | https://api.github.com/repos/huggingface/transformers/issues/3192/events | https://github.com/huggingface/transformers/issues/3192 | 578,071,935 | MDU6SXNzdWU1NzgwNzE5MzU= | 3,192 | Provide comprehensive guide & best-practices for run_language_modeling.py | {
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"Even I tried to follow the blog and train a LM from scratch but the instructions are ambiguous. Like for ex config file is passed as command line args but if its passed it tries to load it and throws error .",
"I've covered some of the parts here: https://zablo.net/blog/post/training-roberta-from-scratch-the-mis... | 1,583 | 1,596 | 1,596 | CONTRIBUTOR | null | # 🚀 Feature request
Provide comprehensive guide for running scripts included in the repository, especially `run_language_modeling.py` it's parameters and model configurations.
## Motivation
1. Current version has `argparse` powered help, from which a lot of parameters seem to be either mysterious or have va... | {
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https://api.github.com/repos/huggingface/transformers/issues/3191 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3191/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3191/comments | https://api.github.com/repos/huggingface/transformers/issues/3191/events | https://github.com/huggingface/transformers/pull/3191 | 577,932,162 | MDExOlB1bGxSZXF1ZXN0Mzg1NjA3MTA3 | 3,191 | Add integration tests lm generate torch tf | {
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"Approx. how long do these tests take on a single V100?",
"> Approx. how long do these tests take on a single V100?\r\n\r\nDon't know how long they take on a V100. On a cpu, all tests combined (7 model tests for PT and 6 model tests for TF) take less than 10min (whereas `test_modeling_tf_xlnet.py`, `test_modeling... | 1,583 | 1,583 | 1,583 | MEMBER | null | Add integration tests for all LM models that are able to generate language.
- All integration tests use `do_sample=False` (greedy) generation and verify that TF 2.0 and PT yield the same results.
- Fixed a small bug with TFXLMModelWithLMHead | {
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https://api.github.com/repos/huggingface/transformers/issues/3190 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3190/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3190/comments | https://api.github.com/repos/huggingface/transformers/issues/3190/events | https://github.com/huggingface/transformers/pull/3190 | 577,930,759 | MDExOlB1bGxSZXF1ZXN0Mzg1NjA1OTI3 | 3,190 | fix repetition penalty mask in tf | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3190?src=pr&el=h1) Report\n> Merging [#3190](https://codecov.io/gh/huggingface/transformers/pull/3190?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b29fed790bdaa4be38b6d2c5de88e307474ea38d?src=pr&el=desc) will **i... | 1,583 | 1,583 | 1,583 | MEMBER | null | Fixed bug with TF 2.0 `repetition_penalty` when doing generation add make `early_stopping` an argument to the function `generate()`. | {
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https://api.github.com/repos/huggingface/transformers/issues/3189 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3189/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3189/comments | https://api.github.com/repos/huggingface/transformers/issues/3189/events | https://github.com/huggingface/transformers/issues/3189 | 577,928,756 | MDU6SXNzdWU1Nzc5Mjg3NTY= | 3,189 | I want to import the model path on my owm computer? | {
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"There are a lot of examples in [the documentation](https://huggingface.co/transformers/main_classes/model.html#transformers.PreTrainedModel)."
] | 1,583 | 1,583 | 1,583 | NONE | null | hi, I want to import the model path from my own computer, how to write or change the code, can u give me a example? | {
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"@Laksh1997 thanks a lot for reporting this error. Can you provide a code snippet and maybe a link to your data to easily reproduce this error? \r\n\r\nIn the meantime: \r\n\r\n- There has been a lot of changes recently in the beam search decoding -> I would recommend using the master branch of beam search decodin... | 1,583 | 1,598 | 1,589 | NONE | null | # 🐛 Bug
## Information
Model I am using:
GPT2 with custom config (vocab=27)
Language I am using the model on (English, Chinese ...):
Molecules... (see https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system)
The problem arises when using:
Using the .generate(beam=2) function
The t... | {
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https://api.github.com/repos/huggingface/transformers/issues/3187 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3187/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3187/comments | https://api.github.com/repos/huggingface/transformers/issues/3187/events | https://github.com/huggingface/transformers/issues/3187 | 577,875,174 | MDU6SXNzdWU1Nzc4NzUxNzQ= | 3,187 | Knowing the specific data set used for DistilBertForQuestionAnswering | {
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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"
] | 1,583 | 1,589 | 1,589 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/3186 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3186/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3186/comments | https://api.github.com/repos/huggingface/transformers/issues/3186/events | https://github.com/huggingface/transformers/pull/3186 | 577,857,555 | MDExOlB1bGxSZXF1ZXN0Mzg1NTQ0NTc0 | 3,186 | CPU/GPU memory benchmarking utilities - Remove support for python 3.5 (now only 3.6+) | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3186?src=pr&el=h1) Report\n> Merging [#3186](https://codecov.io/gh/huggingface/transformers/pull/3186?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e03129ad447ad7670fcc6206e5eb27a5435d4d86&el=desc) will **decrease... | 1,583 | 1,584 | 1,584 | MEMBER | null | This PR add some utilities to benchmark (RAM) memory consumption of the models.
This is actually a generic utility that can work with any arbitrary python code
Ex:
```python
import torch
from transformers import GPT2Model, GPT2Tokenizer
from transformers import start_memory_tracing, stop_memory_tracing
token... | {
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https://api.github.com/repos/huggingface/transformers/issues/3185 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3185/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3185/comments | https://api.github.com/repos/huggingface/transformers/issues/3185/events | https://github.com/huggingface/transformers/pull/3185 | 577,807,710 | MDExOlB1bGxSZXF1ZXN0Mzg1NTA0OTMx | 3,185 | Tokenizers v3.0.0 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3185?src=pr&el=h1) Report\n> Merging [#3185](https://codecov.io/gh/huggingface/transformers/pull/3185?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7420a6a9cc1750c2bd2c2c245d00048ec36d3bf0?src=pr&el=desc) will **d... | 1,583 | 1,586 | 1,586 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3184 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3184/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3184/comments | https://api.github.com/repos/huggingface/transformers/issues/3184/events | https://github.com/huggingface/transformers/issues/3184 | 577,747,855 | MDU6SXNzdWU1Nzc3NDc4NTU= | 3,184 | `Failed to build tokenizers` when installing 2.5.1 version. | {
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"`tokenizers` is only required when you wish to use the new, fast [tokenizers](https://github.com/huggingface/tokenizers). By default, though, the standard (slower) tokenizers are used. So you do not actually need the `tokenizers` library to run the `transformers` library.\r\n\r\nRelated:\r\nhttps://github.com/hugg... | 1,583 | 1,704 | 1,583 | NONE | null | `Failed to build tokenizers` when i try to install transformers==2.5.1
`Failed to build tokenizers` when i try to install tokenizers == 0.5.2
so, i want to know `tokenizers == 0.5.2` is must ?
thanks~ | {
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https://api.github.com/repos/huggingface/transformers/issues/3183 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3183/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3183/comments | https://api.github.com/repos/huggingface/transformers/issues/3183/events | https://github.com/huggingface/transformers/issues/3183 | 577,747,540 | MDU6SXNzdWU1Nzc3NDc1NDA= | 3,183 | About the examples document of bert with SQuAD 2.0 | {
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"Indeed, I think this is a mistake, I think it should be `bert-base-uncased` instead. I'm updating it."
] | 1,583 | 1,583 | 1,583 | NONE | null | I'm wondering if there is a mistake.
In the README document of /examples, the training parameters setting for training on SQuAD dataset, the first code block:
```
export SQUAD_DIR=/path/to/SQUAD
python run_squad.py \
--model_type bert \
--model_name_or_path bert-base-cased \
--do_train \
--do_eval \
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3182 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3182/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3182/comments | https://api.github.com/repos/huggingface/transformers/issues/3182/events | https://github.com/huggingface/transformers/issues/3182 | 577,719,178 | MDU6SXNzdWU1Nzc3MTkxNzg= | 3,182 | How can i use pipeline with pretrained automodel ? | {
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"There are many examples in [the docs](https://huggingface.co/transformers/usage.html). The [pipeline reference](https://huggingface.co/transformers/main_classes/pipelines.html) will also be helpful."
] | 1,583 | 1,583 | 1,583 | NONE | null | how can i use pipeline with pretrained auto model and tokenizer ? | {
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https://api.github.com/repos/huggingface/transformers/issues/3181 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3181/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3181/comments | https://api.github.com/repos/huggingface/transformers/issues/3181/events | https://github.com/huggingface/transformers/issues/3181 | 577,633,825 | MDU6SXNzdWU1Nzc2MzM4MjU= | 3,181 | The implementation of GPT2 masked attention mechanism will cause errors when the model was trained after some iterations. | {
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"Thanks for the bug report @xunzi2020! Did you by any chance measure the degree results would differ when replacing `-1e4` by `-1e10`? ",
"Yes, I trained with chinese text (~30GB), it happened.\n\n\nPatrick von Platen <notifications@github.com> 于2020年3月9日周一 下午4:11写道：\n\n> Thanks for the bug report @xunzi2020 <htt... | 1,583 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
Model I am using (GPT2):
Language I am using the model on ( Chinese ...):
File in modeling_gpt2.py：
146 w = w * b - 1e4 * (1 - b) # here the bias "-1e4" is too big, suggest replace it to "-1e10"
The item value of "query * key" may be close to or lower to "-1e4" , then after... | {
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https://api.github.com/repos/huggingface/transformers/issues/3180 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3180/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3180/comments | https://api.github.com/repos/huggingface/transformers/issues/3180/events | https://github.com/huggingface/transformers/pull/3180 | 577,585,880 | MDExOlB1bGxSZXF1ZXN0Mzg1MzI4Njg1 | 3,180 | NER - pl example | {
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"This looks great to me. Thanks @shubhamagarwal92. \r\n\r\nYou need to just run the black command, I believe to is `make style` to fix formatting. Otherwise it looks good.",
"@srush I ran the `make style` which changed a lot of files, however, the `check_code_quality` is still failing! \r\nDo you want me to rever... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | 1. Solves most of the issues raised in #3159
2. Streamlines shell script pipeline
3. pl logs related changes
4. added in Readme | {
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https://api.github.com/repos/huggingface/transformers/issues/3179 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3179/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3179/comments | https://api.github.com/repos/huggingface/transformers/issues/3179/events | https://github.com/huggingface/transformers/issues/3179 | 577,520,458 | MDU6SXNzdWU1Nzc1MjA0NTg= | 3,179 | I can not import transformers | {
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"I have solved it by rebooting my computer and reinstall some modules that transformers can not found but have been installed",
"This issue still exists. I have Tensorflow 2.1 with GPU and transformers version 2.8.0\r\n\r\nI tried with rebooting and creating new conda environments multiple times but still no succ... | 1,583 | 1,586 | 1,583 | NONE | null | # 🐛 Bug
## Information
when I execute "from transformers import TFBertModel, BertModel" in ipython, the error, "ImportError: cannot import name 'BartConfig' from 'transformers.configuration_auto'" was raised.
This error occured after the tensorflow update from version 2.0 to version 2.1 and the python update from... | {
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https://api.github.com/repos/huggingface/transformers/issues/3178 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3178/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3178/comments | https://api.github.com/repos/huggingface/transformers/issues/3178/events | https://github.com/huggingface/transformers/issues/3178 | 577,492,306 | MDU6SXNzdWU1Nzc0OTIzMDY= | 3,178 | Pretraining QA corpora from scratch with sentence pairs | {
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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"
] | 1,583 | 1,589 | 1,589 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/3177 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3177/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3177/comments | https://api.github.com/repos/huggingface/transformers/issues/3177/events | https://github.com/huggingface/transformers/pull/3177 | 577,486,120 | MDExOlB1bGxSZXF1ZXN0Mzg1MjU2MDg1 | 3,177 | Distilgpt2 finetuning and text generation | {
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"Hi @BlackJack01 - thanks so much for this great contribution! We are still going through the notebook and discussing how to add it :-) Will let you know soon! ",
"Hi @BlackJack01, sorry for the late answer. \r\nWe now have community notebooks here: https://github.com/huggingface/transformers/tree/master/notebook... | 1,583 | 1,591 | 1,591 | CONTRIBUTOR | null | This ipynb notebook contains a finetuning and text generation tutorial for distilgpt2. The tutorial also have used code from run_generation.py file to make generation faster than using the original file for every iteration. | {
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https://api.github.com/repos/huggingface/transformers/issues/3176 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3176/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3176/comments | https://api.github.com/repos/huggingface/transformers/issues/3176/events | https://github.com/huggingface/transformers/issues/3176 | 577,473,552 | MDU6SXNzdWU1Nzc0NzM1NTI= | 3,176 | GLUE test set predictions | {
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"hi @shoarora \r\n\r\ncan you share the script to to report performance on test set?",
"@Mahmedturk you can check out the branch in PR #3405 \r\n\r\nIt's diverge pretty heavily from master and I haven't updated it yet, but you should still be able to run `run_glue.py` off that branch with the `--do_test` flag tha... | 1,583 | 1,594 | 1,590 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
The `run_glue` script is super helpful. But it currently doesn't implement producing predictions on the test datasets for the GLUE tasks. I ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3175 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3175/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3175/comments | https://api.github.com/repos/huggingface/transformers/issues/3175/events | https://github.com/huggingface/transformers/pull/3175 | 577,473,168 | MDExOlB1bGxSZXF1ZXN0Mzg1MjQ2NTky | 3,175 | Updated `Tokenw ise` in print statement to `Token wise` | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3175?src=pr&el=h1) Report\n> Merging [#3175](https://codecov.io/gh/huggingface/transformers/pull/3175?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e03129ad447ad7670fcc6206e5eb27a5435d4d86?src=pr&el=desc) will **n... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3174 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3174/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3174/comments | https://api.github.com/repos/huggingface/transformers/issues/3174/events | https://github.com/huggingface/transformers/issues/3174 | 577,451,938 | MDU6SXNzdWU1Nzc0NTE5Mzg= | 3,174 | How can I assign a specific gpu when using examples/run_language_modeling.py? | {
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"This might answer your question: https://stackoverflow.com/questions/39649102/how-do-i-select-which-gpu-to-run-a-job-on",
"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"
] | 1,583 | 1,589 | 1,589 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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"Its a typo in the docs. I just used cnn.",
"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"
] | 1,583 | 1,589 | 1,589 | CONTRIBUTOR | null | @sshleifer
In the README for the BART summarization it says:
> download both CNN and Daily Mail datasets from Kyunghyun Cho's website
`tar -xvf cnn_stories.tgz && tar -xvf dailymail_stories.tgz`
> this should make a directory called cnn_dm/ with files like test.source. To use your own data, copy that files forma... | {
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"Our models are TensorFlow 2.x only, while your notebook is in TensorFlow 1.x:\r\n\r\n```\r\nThe default version of TensorFlow in Colab will soon switch to TensorFlow 2.x.\r\nWe recommend you upgrade now or ensure your notebook will continue to use TensorFlow 1.x via the %tensorflow_version 1.x magic: more info.\r\... | 1,583 | 1,583 | 1,583 | NONE | null | # 🐛 Bug
## Information
I am trying **Quick tour TF 2.0**.
The problem arises when using a quick example: **How a TensorFlow 2.0 model can be trained in 12 lines of code**:
```python
import tensorflow as tf
import tensorflow_datasets
from transformers import *
# Load dataset, tokenizer, model from pre... | {
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"Yes, there are a few available on the hub, you can search for [whole word masking](https://huggingface.co/models?search=whole-word-masking) or [wwm](https://huggingface.co/models?search=wwm).\r\n\r\nFor your second question, you would have a better answer if you opened an issue on [huggingface/toeknizers](https://... | 1,583 | 1,583 | 1,583 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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"You might be interested in:\r\n- https://huggingface.co/huggingface/CodeBERTa-small-v1#codeberta and https://huggingface.co/huggingface/CodeBERTa-language-id\r\n- more generally, https://huggingface.co/blog/how-to-train",
"Wow, it helped a lot @julien-c. Basically, did you train a language model using CodeSearch... | 1,583 | 1,602 | 1,590 | NONE | null | I am entering the world of transformers and would like to use some architectures to create a semantic search engine to retrieve source code (Python, Javascript, Ruby, Go, Java, and PHP code).
Currently, the [dataset ](https://github.com/github/CodeSearchNet#data-details)contains 2 million pairs **(code, docstring)**... | {
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https://api.github.com/repos/huggingface/transformers/issues/3169 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3169/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3169/comments | https://api.github.com/repos/huggingface/transformers/issues/3169/events | https://github.com/huggingface/transformers/issues/3169 | 577,281,139 | MDU6SXNzdWU1NzcyODExMzk= | 3,169 | issues while modifying modeling_roberta.py file | {
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"That's more of a general Python question related to imports than an issue with the library, you would have more luck in trying with stack overflow.\r\n\r\nI believe the easiest way to modify files is to clone the repository and install it in your environment as an editable:\r\n\r\n```\r\ngit clone https://github.c... | 1,583 | 1,583 | 1,583 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
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"GPT-2 and BERT are both transformer networks with very similar architectures. You can use the GPT-2 embeddings the same way you used BERT embeddings.\r\n\r\nAs you said, GPT-2 only handles left context. You can read [the paper](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitas... | 1,583 | 1,600 | 1,597 | CONTRIBUTOR | null | I am experimenting on the use of transformer embeddings in sentence classification tasks **without finetuning them**. I have used BERT embeddings and those experiments gave me very good results. Now I want to use GPT-2 embeddings (without fine-tuning). So I have two questions,
1. Can I use GPT-2 embeddings like that... | {
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"Hi mainulquraishi, \r\n\r\nAs mentioned in earlier issues #3031, #3021, #2975, #3069 it is not advised to use GPT2LMHeadModel in inference using a padded batch. To answer your two questions:\r\n\r\n1. You don't get the same output in your second code snippet as in your first code snippet because you \"argmax\" th... | 1,583 | 1,587 | 1,583 | NONE | null | The following code is without batch:
```
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import torch
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained('gpt2')
model.eval()
context=torch.tensor([tokenizer.encode("This is")])
output, past = model(context)
token ... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I have the same issue.. anyone has any inputs on this "
] | 1,583 | 1,614 | 1,589 | NONE | null | I was trying to look for the references where the sliding window is implemented to process long sequences. How do we split a long sequence and then after getting the embeddings, how do we unpack them? I am unable to find the code segments that handle these operations.
Also, is it possible to describe the main trick?... | {
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https://api.github.com/repos/huggingface/transformers/issues/3165 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3165/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3165/comments | https://api.github.com/repos/huggingface/transformers/issues/3165/events | https://github.com/huggingface/transformers/issues/3165 | 577,238,599 | MDU6SXNzdWU1NzcyMzg1OTk= | 3,165 | Reason for speedup | {
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"Depending on which version you are using, it might be that you are using the fast [tokenizers ](https://github.com/huggingface/tokenizers) library which offers a much improved tokenizer interface built on Rust. ",
"Thanks for the reply. I don't think it is because of the tokenizer. I measured the encoder part an... | 1,583 | 1,589 | 1,589 | NONE | null | I used to develop a code based on the pytorch_transformers package (v1.1) and now transfering to the current version. I see a 2x speedup in Bert run_glue.py. Wondering what is the major reason? Looking at the code, I couldn't find major differences. | {
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https://api.github.com/repos/huggingface/transformers/issues/3164 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3164/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3164/comments | https://api.github.com/repos/huggingface/transformers/issues/3164/events | https://github.com/huggingface/transformers/issues/3164 | 577,163,002 | MDU6SXNzdWU1NzcxNjMwMDI= | 3,164 | wrong configuration of ALBERT xlarge | {
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"Where did you get 32 from?\r\n\r\nThe [official file ](https://tfhub.dev/google/albert_xlarge/2)says 16.",
"Well, the model configuration in tar file downloaded from TF Hub shows 32, which conflicts with the official definition.",
"Indeed, that's right. I'll follow the issue you opened https://github.com/googl... | 1,583 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
If you are **reproducing** the [ALBERT](https://github.com/google-research/albert), the `num_attention_heads` of albert xlarge should be 32 instead of 16 as
https://github.com/huggingface/transformers/blob/db9279dedbb9c5e7d24569a1ac3f74f9d5c3eb18/src/transformers/configuration_albert.py#L2... | {
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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"
] | 1,583 | 1,589 | 1,589 | CONTRIBUTOR | null | Hi @julien-c,
I know that @loretoparisi already talked with you guys about some problems we have with inference using BertTokenizer and BertForSequenceClassification Classes.
So for starting to discuss about that, we would like to show you the most important lines of our inference and training code, that probably can... | {
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https://api.github.com/repos/huggingface/transformers/issues/3162 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3162/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3162/comments | https://api.github.com/repos/huggingface/transformers/issues/3162/events | https://github.com/huggingface/transformers/issues/3162 | 577,076,625 | MDU6SXNzdWU1NzcwNzY2MjU= | 3,162 | Does this project have this function ? | {
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"https://github.com/huggingface/transformers/issues/2311",
"@frankniujc it is helpful\r\nbut maybe a better way is take the all tokens in a whole, not prediction the next tokens",
"The probability of a sentence P(s0s1s2s3s4...sn) = P(s1|s0) * P(s2|s0s1) * P(s3|s0s1s2) * ... * P(sn|s0s1s2...sn-1)\r\n\r\nSo you ... | 1,583 | 1,592 | 1,592 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
can we use this project to calculate the probability that a input text as a real/resonable sentence base on the corpus we trained | {
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https://api.github.com/repos/huggingface/transformers/issues/3161 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3161/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3161/comments | https://api.github.com/repos/huggingface/transformers/issues/3161/events | https://github.com/huggingface/transformers/issues/3161 | 577,053,270 | MDU6SXNzdWU1NzcwNTMyNzA= | 3,161 | urgent - ROBERTA on WSC | {
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"The conversion script should pretty much work out of the box, so feel free to do it and we welcome a PR (and we can upload the converted weights to our S3)",
"which script you mean? sorry i did not get it. i think this is not possible\nto train it on huggingface is this?\n\nOn Fri, Mar 6, 2020, 10:12 PM Julien C... | 1,583 | 1,589 | 1,589 | NONE | null | Hi
I am looking for how to run ROBERTA on WSC data, similar to the example in fairseq:
https://github.com/pytorch/fairseq/tree/master/examples/roberta
However, fairseq is hard to use and modify and I really appreciate if you could add this to your great repo
thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/3160 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3160/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3160/comments | https://api.github.com/repos/huggingface/transformers/issues/3160/events | https://github.com/huggingface/transformers/pull/3160 | 577,031,078 | MDExOlB1bGxSZXF1ZXN0Mzg0OTAzMjYw | 3,160 | [Bart] add imports to examples | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3160?src=pr&el=h1) Report\n> Merging [#3160](https://codecov.io/gh/huggingface/transformers/pull/3160?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6ffe03a0a1d472a4e5941793fd361d2b82c8be3f?src=pr&el=desc) will **i... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3159 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3159/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3159/comments | https://api.github.com/repos/huggingface/transformers/issues/3159/events | https://github.com/huggingface/transformers/issues/3159 | 577,009,536 | MDU6SXNzdWU1NzcwMDk1MzY= | 3,159 | NER: some issues in PyTorch Lightning example | {
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"After fixing the these issues the output predictions seems very weird, maybe this is in an label 2 id bug?\r\n\r\n```bash\r\nNachdem I-OTH\r\ner I-PERpart\r\n1907 B-ORGderiv\r\nnicht I-PER\r\nzum I-PER\r\nDirektor I-PER\r\nder I-PERderiv\r\nBibliothek B-ORGpart\r\nberufen I-PER\r\nwurde I-PER\r\n, I-PER\r\nverließ... | 1,583 | 1,589 | 1,589 | COLLABORATOR | null | Hi,
I wanted to try out the new NER example script (`./ner/run_pl_ner.py`) that uses PyTorch Lightning.
Here are some bugs that I've found:
Dataset preparation method is not called. Usually, InputBatch batches or input features are written and stored in a file. However, the `prepare_data()` [1] method is not c... | {
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https://api.github.com/repos/huggingface/transformers/issues/3158 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3158/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3158/comments | https://api.github.com/repos/huggingface/transformers/issues/3158/events | https://github.com/huggingface/transformers/pull/3158 | 577,008,664 | MDExOlB1bGxSZXF1ZXN0Mzg0ODg0NjE3 | 3,158 | [Bart] _prepare_decoder_inputs should use large negative | {
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"Thanks @tomhosking for noticing!",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3158?src=pr&el=h1) Report\n> Merging [#3158](https://codecov.io/gh/huggingface/transformers/pull/3158?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6ffe03a0a1d472a4e5941793fd3... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | Also renames some things and adds a nice test.
I suspect that this didn't break integration tests because we don't have a serious integration test with decoder_input_ids set (e.g. calculating loss for a summarization example) | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3157?src=pr&el=h1) Report\n> Merging [#3157](https://codecov.io/gh/huggingface/transformers/pull/3157?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6ffe03a0a1d472a4e5941793fd361d2b82c8be3f?src=pr&el=desc) will **d... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | Hi,
this PR adds the model card for albert-chinese model
- albert_chinese_tiny
- albert_chinese_small
- albert_chinese_base
- albert_chinese_large
- albert_chinese_xlarge
- albert_chinese_xxlarge
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It fixes the issue for all non BPE-based tokenizers. For BPE ones, the output is different from Python and Rust:
GPT2:
- Python : `[]`
- Rust: `['Ġ']`
Roberta:
- Python: `[]`
- Rust: `['<s>', 'Ġ', '</s>']`
Rust seems the right one here. I should have a look at Roberta why it incl... | {
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"\r\n"
] | 1,583 | 1,583 | 1,583 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"Hi @minimaxir - thanks for the Feature request! \r\n\r\nNot too sure about this though. Two arguments against it from my side:\r\n\r\n1. I feel like it's very easy to set the seed parameter before calling `generate()` without any real drawback. \r\n2. Also we want all our `generate()` arguments to have default val... | 1,583 | 1,583 | 1,583 | NONE | null | # 🚀 Feature request
There should be a `seed` parameter for the `generate()` function of a model.
Although a seed can be manually set before calling `generate()` (as tested in #3063), using it as a parameter is more intuitive (and covers all the bases)
## Motivation
Generation reproducibility (also good for... | {
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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"
] | 1,583 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
Fresh Install errors out on import
## Information
Following from the README instructions, created a venv, installed torch and tensorflow. Installed transformers. Upon import
Model I am using (Bert, XLNet ...):
transformers==2.5.1
Language I am using the model on (English, Chinese ...):
N/A
The p... | {
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"1) Identical to my benchmark for speed. Hadn't tested memory but I'm not surprised that their implementation is less.\r\n\r\nFor both memory and speed, they have a lot of clever tricks that we haven't implemented yet.\r\n\r\n4) Summarization Pipeline will not help, but I will take a longer look at this tomorrow an... | 1,583 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🐛 Performance issues
I did a quick benchmark between HuggingFace's implementation of **BART** and FairSeq's implementation.
You can find the benchmark code [here](https://gist.github.com/Colanim/cc418d19e5e107f462bac306f53ba994).
---
Here is my results, on a single GPU GTX 1080 (12 GiB of memory) :
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"很简单哦。看我的代码：\r\n\r\n\r\n\"\"\"\r\nTraining the distilled model.\r\nSupported architectures include: BERT -> DistilBERT, RoBERTa -> DistilRoBERTa, GPT2 -> DistilGPT2.\r\n\"\"\"\r\nimport argparse\r\nimport json\r\nimport os\r\nimport pickle\r\nimport shutil\r\n\r\nimport numpy as np\r\nimport torch\r\n\r\nfrom disti... | 1,583 | 1,662 | 1,584 | NONE | null | Hi! Thanks for everything.
I'm interested in training a distilled version of gpt2, because I want it to be even smaller than the distilled gpt2 model.
In https://github.com/huggingface/transformers/tree/master/examples/distillation , there is a tutorial about how to get a distilled bert. Could you give instructions a... | {
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"I tried to replicate the input as close as I could given the output you gave:\r\n\r\n```py\r\nfrom transformers import BertModel\r\nimport torch\r\n\r\ntoken_id = torch.tensor([[ 101, 5292, 3270, 102, 8638, 2060, 102]])\r\ntoken_types = torch.tensor([[0, 0, 0, 0, 1, 1, 1]])\r\nmask = torch.tensor([[1., 1., 1., 1... | 1,583 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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"good to merge for me",
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closes #3093 | {
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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"
] | 1,583 | 1,589 | 1,589 | NONE | null | # ❓ Questions & Help
In PyTorch, model.__call__ returns the output tensor and users have to call a loss function to get the loss. I wonder why models in transformers doesn't follow this convention? Any specific reason? | {
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"Very good catch"
] | 1,583 | 1,583 | 1,583 | MEMBER | null | closes #3142
The problem came from the fact that `from_pretrained` set the model on which to load the weights to the base model: it detected that the state dict was made for the base, therefore loading only onto the base.
It didn't look for the weights it didn't load. Here, both state dicts are analyzed and the ... | {
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## Information
If a base model (e.g. `BertModel`, `DistilBertModel`, ...) is saved using `save_pretrained` and a model with an additional head (e.g. `BertForSequenceClassification`, `DistilBertForQuestionAnswering`, ...) is loaded from that checkpoint, it will not detect that it is missing layers.
## ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3141 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3141/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3141/comments | https://api.github.com/repos/huggingface/transformers/issues/3141/events | https://github.com/huggingface/transformers/issues/3141 | 576,335,370 | MDU6SXNzdWU1NzYzMzUzNzA= | 3,141 | GPU memory getting out of bound | {
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"Hi, could you provide a reproducible example so that we may test on our side?",
"Thank you for your reply. \r\nHere is the code and my 32GB GPU memory getting out of bound before 500 iteration. \r\n```\r\nfrom transformers import GPT2LMHeadModel, GPT2Tokenizer\r\nimport torch\r\n\r\ntokenizer = GPT2Tokenizer.fr... | 1,583 | 1,667 | 1,589 | NONE | null | I am trying to run the pre-trained small GPT model with language head with batch size 16. Problem is, after each iteration about 440MB of memory is allocated and quickly the GPU memory is getting out of bound. I am not running the pre-trained model in training mode.
In my understanding, in each iteration a single wor... | {
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https://api.github.com/repos/huggingface/transformers/issues/3140 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3140/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3140/comments | https://api.github.com/repos/huggingface/transformers/issues/3140/events | https://github.com/huggingface/transformers/pull/3140 | 576,327,375 | MDExOlB1bGxSZXF1ZXN0Mzg0MzM1MzEz | 3,140 | Merge bart generate into default generate | {
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"clarification:\r\n\r\n`bart.generate` doesn't add EOS if `max_length` is hit, or require EOS to pass integration tests. It just \"finalizes\" a hypothesis when the model predicts EOS for a beam.\r\n\r\nExample:\r\n\r\n```python\r\nARTICLE_TO_SUMMARIZE = \"code doesnt generate EOS if max_length is hit\"\r\ninputs =... | 1,583 | 1,584 | 1,583 | MEMBER | null | This PR is a first version of how the bart generation() code can be merged into the "default" generation function. I think it's actually much better feasible than we originally thought.
Please not that this change also includes all the changes from PR #3135 , so the code changes will be much less cluttered after #313... | {
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https://api.github.com/repos/huggingface/transformers/issues/3139 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3139/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3139/comments | https://api.github.com/repos/huggingface/transformers/issues/3139/events | https://github.com/huggingface/transformers/pull/3139 | 576,315,567 | MDExOlB1bGxSZXF1ZXN0Mzg0MzI1ODQx | 3,139 | Remove excess line breaks in DeepPavlov model cards | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3139?src=pr&el=h1) Report\n> Merging [#3139](https://codecov.io/gh/huggingface/transformers/pull/3139?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8a2d9bc9ef38452e80ce872505a5ad5623c12657?src=pr&el=desc) will **d... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3138 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3138/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3138/comments | https://api.github.com/repos/huggingface/transformers/issues/3138/events | https://github.com/huggingface/transformers/pull/3138 | 576,287,423 | MDExOlB1bGxSZXF1ZXN0Mzg0MzAyOTc3 | 3,138 | Add model cards for DeepPavlov models | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3138?src=pr&el=h1) Report\n> Merging [#3138](https://codecov.io/gh/huggingface/transformers/pull/3138?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e9e6efdc452b74947d40a5a2e8af2fc444c63b5b?src=pr&el=desc) will **d... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | Sorry about the Cyrillic `с` yesterday. | {
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https://api.github.com/repos/huggingface/transformers/issues/3137 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3137/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3137/comments | https://api.github.com/repos/huggingface/transformers/issues/3137/events | https://github.com/huggingface/transformers/pull/3137 | 576,267,439 | MDExOlB1bGxSZXF1ZXN0Mzg0Mjg2ODUw | 3,137 | Refactor BartModel so that input checks are handled within enc/dec | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3137?src=pr&el=h1) Report\n> Merging [#3137](https://codecov.io/gh/huggingface/transformers/pull/3137?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/30624f7056ae3b607ba1d02f474f2c7986e87dff?src=pr&el=desc) will **i... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | Implementing #3133
I've left the code that creates dummy inputs and checks/filters the outputs, this could potentially also be moved to `BartEncoder` and `BartDecoder`. | {
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https://api.github.com/repos/huggingface/transformers/issues/3136 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3136/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3136/comments | https://api.github.com/repos/huggingface/transformers/issues/3136/events | https://github.com/huggingface/transformers/issues/3136 | 576,245,911 | MDU6SXNzdWU1NzYyNDU5MTE= | 3,136 | links of the model's pretrained weights | {
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"We have a `HfApi.model_list()` method on this PR https://github.com/huggingface/transformers/pull/3132 that might be of interest to you.\r\n\r\nDo let us know if it solves your use case or not.",
"I use the following script in an interactive enviroment:\r\n\r\n```python\r\n>> from transformers.hf_api import HfAp... | 1,583 | 1,583 | 1,583 | NONE | null | where can I find all the links of the model's pretrained weights,please?to download them by IDE is too slow. | {
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https://api.github.com/repos/huggingface/transformers/issues/3135 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3135/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3135/comments | https://api.github.com/repos/huggingface/transformers/issues/3135/events | https://github.com/huggingface/transformers/pull/3135 | 576,209,777 | MDExOlB1bGxSZXF1ZXN0Mzg0MjQxMDQw | 3,135 | Refactoring and bug fixing beam search generate | {
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"Good to merge for me"
] | 1,583 | 1,583 | 1,583 | MEMBER | null | This PR cleanes the beam_search decoding part of language generation. It simplifies the code and fixes a small bug for do_sample=True (see comments in code).
It was also tested on all language generation slow tests.
### Future PR
- [x] Do the same change for TF 2.0 if ok -> #3148 | {
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https://api.github.com/repos/huggingface/transformers/issues/3134 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3134/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3134/comments | https://api.github.com/repos/huggingface/transformers/issues/3134/events | https://github.com/huggingface/transformers/issues/3134 | 576,198,549 | MDU6SXNzdWU1NzYxOTg1NDk= | 3,134 | Cant import my pretrained bert model from NVIDIA/DeepLearningExamples/ | {
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"Try:\r\n\r\n```\r\nmodel.eval()\r\n```\r\n\r\nbefore you access the weights.",
"Its seems not work. \r\n```\r\nembeddings.word_embeddings.weight\r\ntensor([[ 0.0073, 0.0080, 0.0307, ..., -0.0172, 0.0148, -0.0401],\r\n [-0.0271, 0.0110, 0.0011, ..., -0.0079, 0.0236, -0.0037],\r\n [ 0.0005, ... | 1,583 | 1,589 | 1,589 | NONE | null |
Trained with **NVIDIA/DeepLearningExamples/** and got my_bert_model/ckpt_1000.pt
**.pt to .bin**
Edit my_bert_model/ckpt_1000.pt to my_bert_model/pytorch_model.bin
**My code**
```configuration = BertConfig(3258, 768, 12, 12, 3072)
model = BertModel(configuration)
model = model.from_pretrained('/home/my... | {
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https://api.github.com/repos/huggingface/transformers/issues/3133 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3133/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3133/comments | https://api.github.com/repos/huggingface/transformers/issues/3133/events | https://github.com/huggingface/transformers/issues/3133 | 576,194,591 | MDU6SXNzdWU1NzYxOTQ1OTE= | 3,133 | BART: move boilerplate code inside encoder/decoder | {
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"Sounds good to me"
] | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | # 🚀 Feature request
Could we move the boilerplate code in the `BartModel` `forward()` method inside the `forward()` methods for the encoder and decoder? That way, the encoder and decoder can be called separately as independent modules more easily.
## Motivation
Currently, there's some cleanup work that is d... | {
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https://api.github.com/repos/huggingface/transformers/issues/3131 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3131/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3131/comments | https://api.github.com/repos/huggingface/transformers/issues/3131/events | https://github.com/huggingface/transformers/issues/3131 | 575,950,245 | MDU6SXNzdWU1NzU5NTAyNDU= | 3,131 | Converting tf weights: AttributeError: 'GPT2Model' object has no attribute 'zeLoss' | {
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"@LysandreJik Any update on this? Thanks",
"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"
] | 1,583 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using: gpt-2
I am trying to convert a fine-tuned gpt-2 model on tensroflow to pytorch state_dict. I used the nice script [here](https://github.com/huggingface/transformers/blob/ce50305e5b8c8748b81b0c8f5539a337b6a995b9/src/transformers/convert_gpt2_original_tf_checkpoint_to_pyto... | {
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https://api.github.com/repos/huggingface/transformers/issues/3130 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3130/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3130/comments | https://api.github.com/repos/huggingface/transformers/issues/3130/events | https://github.com/huggingface/transformers/issues/3130 | 575,937,199 | MDU6SXNzdWU1NzU5MzcxOTk= | 3,130 | Performance Issue about pretrained bert migration from tensorflow to pytorch | {
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"Are you using the latest version? `transformers` and not `pytorch-transformers`. It works with both TF2 and PT. You can test both and compare.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contribut... | 1,583 | 1,589 | 1,589 | NONE | null | # ❓ Questions & Help
Hi,
I have a question about migration from tensorflow to pytorch.
if I change pretrained BERT with google tensorflow 1.x version to pytorch transformers BERT through transformers-cli, performance drops a lot. I wonder why.
Is there any similar case? | {
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https://api.github.com/repos/huggingface/transformers/issues/3129 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3129/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3129/comments | https://api.github.com/repos/huggingface/transformers/issues/3129/events | https://github.com/huggingface/transformers/issues/3129 | 575,927,895 | MDU6SXNzdWU1NzU5Mjc4OTU= | 3,129 | Load pretrained roberta model from fairseq? | {
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"Try https://github.com/huggingface/transformers/blob/master/src/transformers/convert_roberta_original_pytorch_checkpoint_to_pytorch.py\r\n\r\nYou might have to make some modifications, I have never tried this. Good luck!\r\n",
"huggingface/transformers can be used to train from scratch. See [how to train a LM fr... | 1,583 | 1,611 | 1,583 | NONE | null | # ❓ Questions & Help
Would it be possible to load pretrained model of roberta-base that is trained by myself using fairseq, following the instructions in https://github.com/pytorch/fairseq/blob/master/examples/roberta/README.pretraining.md?
Since the current transformers library is not suitable for pretraining from... | {
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1) This is not TextGenerationPipeline, so it only supports bart-large-cnn.
1) It doesn't return the input back to the caller because it is annoyingly long. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3127?src=pr&el=h1) Report\n> Merging [#3127](https://codecov.io/gh/huggingface/transformers/pull/3127?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ec60e0ae7a88e46ac2bfbf6234d14381a01be06a?src=pr&el=desc) will **i... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | {
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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"
] | 1,583 | 1,589 | 1,589 | CONTRIBUTOR | null | tok.encode('<mask>') -> 52064, but BartForMaskedLM.from_pretrained('bart-large-cnn') does not support a mask token. | {
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https://api.github.com/repos/huggingface/transformers/issues/3125 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3125/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3125/comments | https://api.github.com/repos/huggingface/transformers/issues/3125/events | https://github.com/huggingface/transformers/issues/3125 | 575,563,170 | MDU6SXNzdWU1NzU1NjMxNzA= | 3,125 | NER tutorial: run_tf_ner.py reports an entity number not matching the one in the .txt files | {
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"I'm currently not able to run the TF ner training script - I'm using TF in version 2.0.0b1 and the following error message is thrown:\r\n\r\n```bash\r\n...\r\n File \"/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/init_ops_v2.py\", line 769, in _assert_float_dtype\r\n raise ValueError(\"Expected ... | 1,583 | 1,589 | 1,589 | NONE | null | Hi everyone,
I'm following this tutorial https://github.com/huggingface/transformers/tree/master/examples/ner .
Generated results are the same but I noticed that the reported entity numbers ("support" column) are not the same B-entity numbers I can count through Notepad++ in *.txt files used as source for trainin... | {
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https://api.github.com/repos/huggingface/transformers/issues/3124 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3124/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3124/comments | https://api.github.com/repos/huggingface/transformers/issues/3124/events | https://github.com/huggingface/transformers/pull/3124 | 575,561,287 | MDExOlB1bGxSZXF1ZXN0MzgzNjkxMDg3 | 3,124 | [Broken Proposal] CircleCI runs tests with torch=1.0.0 | {
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"need to avoid the torchscript tests",
"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"
] | 1,583 | 1,651 | 1,589 | CONTRIBUTOR | null | Goal: maintain backwards compatibility! | {
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"@julien-c this should fix the sklearn problem for the moment",
"👍 \r\n",
"reverted on master as they pushed a fixed release right after that one."
] | 1,583 | 1,585 | 1,583 | MEMBER | null | new sklearn release (https://github.com/scikit-learn/scikit-learn/releases) seems to be broken or leads to errors for PR since this morning - go back to previous version for now to avoid circle ci errors | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3122?src=pr&el=h1) Report\n> Merging [#3122](https://codecov.io/gh/huggingface/transformers/pull/3122?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/34de670dbe70a9ead31d0692ad9dc726d3ea4edb?src=pr&el=desc) will **d... | 1,583 | 1,583 | 1,583 | MEMBER | null | Test TF GPT2 for correct behavior regarding the past and attn mask variable. Translated code from torch to TF 2.0.
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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",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occu... | 1,583 | 1,589 | 1,589 | NONE | null | In the `forward()` method of the `BertModel` (https://huggingface.co/transformers/_modules/transformers/modeling_bert.html#BertModel.forward), the `extended_attention_mask` is processed in the following way:
> extended_attention_mask = (1.0 - extended_attention_mask) * -10000.0
I know this is to make an additive... | {
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"Up for discussion @LysandreJik @thomwolf @julien-c ",
"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"
] | 1,583 | 1,589 | 1,589 | MEMBER | null | # 🚀 Feature request
And the moment, the variables **past** / **mems** have the shape:
`(2, batch_size, num_heads, sequence_length, embed_size_per_head)` and `(mem_len, batch_size, embed_size)` , respectively.
meaning that the variable `batch_size` dim is not on first position. Change the variables structure to... | {
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https://api.github.com/repos/huggingface/transformers/issues/3119 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3119/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3119/comments | https://api.github.com/repos/huggingface/transformers/issues/3119/events | https://github.com/huggingface/transformers/pull/3119 | 575,263,191 | MDExOlB1bGxSZXF1ZXN0MzgzNDQwNzky | 3,119 | rename variables named 'word' to 'token' in generate fn | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3119?src=pr&el=h1) Report\n> Merging [#3119](https://codecov.io/gh/huggingface/transformers/pull/3119?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/34de670dbe70a9ead31d0692ad9dc726d3ea4edb?src=pr&el=desc) will **d... | 1,583 | 1,583 | 1,583 | MEMBER | null | Rename `word` to `token` in generate() function. | {
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https://api.github.com/repos/huggingface/transformers/issues/3118 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3118/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3118/comments | https://api.github.com/repos/huggingface/transformers/issues/3118/events | https://github.com/huggingface/transformers/pull/3118 | 575,262,425 | MDExOlB1bGxSZXF1ZXN0MzgzNDQwMTcw | 3,118 | Add beam search to generation tf 2 0 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3118?src=pr&el=h1) Report\n> Merging [#3118](https://codecov.io/gh/huggingface/transformers/pull/3118?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/34de670dbe70a9ead31d0692ad9dc726d3ea4edb?src=pr&el=desc) will **i... | 1,583 | 1,583 | 1,583 | MEMBER | null | Add beam search to the TF generate function as it is done for torch at the moment. Use same TF syntax that was used in PR #3063
EDIT: Also included a quick fix that `TF GPT2 past.shape == PT GPT2 past.shape` | {
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https://api.github.com/repos/huggingface/transformers/issues/3117 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3117/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3117/comments | https://api.github.com/repos/huggingface/transformers/issues/3117/events | https://github.com/huggingface/transformers/issues/3117 | 575,101,017 | MDU6SXNzdWU1NzUxMDEwMTc= | 3,117 | BART FP16 | {
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"Not on my roadmap just yet, but I would definitely consider it if there were lots of demand. Since we only have inference code right now, the benefit seems marginal. ",
"@BramVanroy Should this issue be closed ?\r\n\r\nFP16 is not implemented yet. And the `wontfix` label is clear.\r\n\r\nKeeping the issue open m... | 1,583 | 1,583 | 1,583 | CONTRIBUTOR | null | # 🚀 Feature request
I would like to use BART in FP16 mode, but it seems impossible for now :
```
config = BartConfig(vocab_size=50264, output_past=True)
model = AutoModelWithLMHead.from_pretrained('bart-large-cnn', config=config).cuda().half()
tokenizer = AutoTokenizer.from_pretrained('bart-large-cnn')
ARTIC... | {
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https://api.github.com/repos/huggingface/transformers/issues/3116 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3116/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3116/comments | https://api.github.com/repos/huggingface/transformers/issues/3116/events | https://github.com/huggingface/transformers/pull/3116 | 575,025,964 | MDExOlB1bGxSZXF1ZXN0MzgzMjQ4NDEw | 3,116 | Skipping outputs | {
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"Nice.\r\n\r\nOne question: do we want to have a `skip_output` flag or to have a `keep_output` flag.\r\n\r\n`skip_output` seems to me as introducing a dependency to be maintained between all the models (if we add a model with additional output that are processed by encode_plus later, we would have to update all th... | 1,583 | 1,585 | 1,583 | MEMBER | null | Currently, `encode_plus` and `batch_encode_plus` return the same outputs for different models.
This is sub-optimal as we can't do the following for each model:
```py
inputs = tokenizer.encode_plus(sequence, return_tensors="pt")
model(**inputs)
```
This will crash for DistilBERT as the tokenizer would return... | {
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https://api.github.com/repos/huggingface/transformers/issues/3115 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3115/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3115/comments | https://api.github.com/repos/huggingface/transformers/issues/3115/events | https://github.com/huggingface/transformers/pull/3115 | 575,018,815 | MDExOlB1bGxSZXF1ZXN0MzgzMjQyNDgx | 3,115 | fix: passing config as Layer trainable param | {
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"That's great, thanks a lot @gthb "
] | 1,583 | 1,584 | 1,583 | CONTRIBUTOR | null | Lurking bugs discovered while working on other stuff. | {
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https://api.github.com/repos/huggingface/transformers/issues/3114 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3114/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3114/comments | https://api.github.com/repos/huggingface/transformers/issues/3114/events | https://github.com/huggingface/transformers/pull/3114 | 575,004,022 | MDExOlB1bGxSZXF1ZXN0MzgzMjI5NTUy | 3,114 | Rename BartForMaskedLM -> BartForConditionalGeneration | {
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