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https://api.github.com/repos/huggingface/transformers/issues/1710 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1710/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1710/comments | https://api.github.com/repos/huggingface/transformers/issues/1710/events | https://github.com/huggingface/transformers/issues/1710 | 516,858,820 | MDU6SXNzdWU1MTY4NTg4MjA= | 1,710 | CTRL does not react to the "seed" argument | {
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"Noticed the same thing on the Salesforce version as well. ",
"Do you test with [this url](https://github.com/salesforce/ctrl/blob/master/generation.py)?\r\n@tanselmi If not, please specify which script do you try out\r\n\r\nN.B. if you see this code, the lines 40-41-42-43 assign the seed passed as argument (defa... | 1,572 | 1,572 | 1,572 | NONE | null | Using latest master branch and run_generation.py.
When passing different seeds to GPT-2 it produces different results, as expected,
however CTRL does not.
**GPT-2**
python run_generation.py **--seed=42** --model_type=gpt2 --length=10 --model_name_or_path=gpt2 --prompt="Transformers movie is"
**>>> a great examp... | {
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https://api.github.com/repos/huggingface/transformers/issues/1709 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1709/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1709/comments | https://api.github.com/repos/huggingface/transformers/issues/1709/events | https://github.com/huggingface/transformers/pull/1709 | 516,809,901 | MDExOlB1bGxSZXF1ZXN0MzM2MDEyNTk2 | 1,709 | Fixing mode in evaluate during training | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1709?src=pr&el=h1) Report\n> Merging [#1709](https://codecov.io/gh/huggingface/transformers/pull/1709?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8a62835577a2a93642546858b21372e43c1a1ff8?src=pr&el=desc) will **n... | 1,572 | 1,572 | 1,572 | CONTRIBUTOR | null | This fixs the error of not passing mode while using the option of evaluate_during_training option. | {
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https://api.github.com/repos/huggingface/transformers/issues/1708 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1708/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1708/comments | https://api.github.com/repos/huggingface/transformers/issues/1708/events | https://github.com/huggingface/transformers/issues/1708 | 516,802,267 | MDU6SXNzdWU1MTY4MDIyNjc= | 1,708 | The id of the word obtained by tokenizer.encode does not correspond to the id of the word in vocab.txt | {
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"Hi, in the `bert-base-uncased` vocab.txt file, the id of the token \"the\" is 1996. You can see it [inside the file, where \"the\" is on the row 1996](https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt). You can also check it out directly in the tokenizer with the following command: \r... | 1,572 | 1,578 | 1,578 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
hello，I encountered a problem，code show as below.
tokenizer=BertTokenizer.from_pretrained('bert-base-uncased')
input_ids=torch.LongTensor(tokenizer.encode("[CLS] the 2018 boss nationals [SEP]"))
print(input_ids)
The result is:tensor... | {
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https://api.github.com/repos/huggingface/transformers/issues/1707 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1707/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1707/comments | https://api.github.com/repos/huggingface/transformers/issues/1707/events | https://github.com/huggingface/transformers/issues/1707 | 516,800,055 | MDU6SXNzdWU1MTY4MDAwNTU= | 1,707 | bugs with run_summarization script | {
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"The summarization/generation scripts are still work in progress. They should be included in the next release.",
"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"
] | 1,572 | 1,578 | 1,578 | NONE | null | Hi
The evaluation part of this script is missing, I tried to complete it myself but this code does not generation proper string during decoding part for me and does not converege, encoder and decoder weights are not tied as the paper, could you please add the generated text as the output of evaluation code, also pleas... | {
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https://api.github.com/repos/huggingface/transformers/issues/1706 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1706/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1706/comments | https://api.github.com/repos/huggingface/transformers/issues/1706/events | https://github.com/huggingface/transformers/issues/1706 | 516,774,805 | MDU6SXNzdWU1MTY3NzQ4MDU= | 1,706 | Regression Loss | {
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"That is a good way to load the labels! \r\n\r\nPlease be aware, however, that by loading the configuration this way you will not load the weights for your model associated with the `bert-base-uncased` checkpoint as you would have done had you used the `BertForSequenceClassification.from_pretrained(...)` method.",
... | 1,572 | 1,578 | 1,578 | NONE | null | I want `BertForSequenceClassification` to compute regression loss. I load the pre-trained model through
```
config = BertConfig.from_pretrained('bert-base-uncased')
config.num_labels = 1 # Is it proper to set the num_label in this way?
model = BertForSequenceClassification(config)
```
How shall I change the nu... | {
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https://api.github.com/repos/huggingface/transformers/issues/1705 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1705/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1705/comments | https://api.github.com/repos/huggingface/transformers/issues/1705/events | https://github.com/huggingface/transformers/issues/1705 | 516,746,127 | MDU6SXNzdWU1MTY3NDYxMjc= | 1,705 | unable to import from utils_squad | {
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"try this \r\n\r\n```\r\n%%bash\r\nrm -r hugging-face-squad\r\nmkdir hugging-face-squad\r\necho > hugging-face-squad/__init__.py\r\ncd hugging-face-squad\r\nwget 'https://raw.githubusercontent.com/huggingface/pytorch-transformers/master/examples/run_squad.py'\r\nwget 'https://raw.githubusercontent.com/huggingface/p... | 1,572 | 1,613 | 1,573 | NONE | null | Hi,
I am using BertForQuestionAnswering on colab and I have installed
`
!pip install transformers
!pip install pytorch-transformers
`
when I import
` from utils_squad import (read_squad_examples, convert_examples_to_features) `
I get the following error:
ModuleNotFoundError: No module named 'util... | {
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https://api.github.com/repos/huggingface/transformers/issues/1704 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1704/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1704/comments | https://api.github.com/repos/huggingface/transformers/issues/1704/events | https://github.com/huggingface/transformers/issues/1704 | 516,688,608 | MDU6SXNzdWU1MTY2ODg2MDg= | 1,704 | loss is nan, for training on MNLI dataset | {
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"extra details:\r\n\r\nexample = list(bert_validation_matched_dataset.__iter__())[0]\r\nexample\r\n```\r\n{'hypothesis': <tf.Tensor: id=4914985, shape=(64,), dtype=string, numpy=\r\n array([b'The St. Louis Cardinals have always won.',\r\n b'The fortress was built a number of years after the caravanserai.',\r... | 1,572 | 1,572 | 1,572 | NONE | null | ## ❓ Questions & Help
Recently I read a tutorial
https://medium.com/tensorflow/using-tensorflow-2-for-state-of-the-art-natural-language-processing-102445cda54a
which you can also see in this notebook
https://colab.research.google.com/drive/16ClJxutkdOqXjBm_PKq6LuuAuLsInGC-
In this tutorial, MRPC dataset is us... | {
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https://api.github.com/repos/huggingface/transformers/issues/1703 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1703/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1703/comments | https://api.github.com/repos/huggingface/transformers/issues/1703/events | https://github.com/huggingface/transformers/pull/1703 | 516,681,543 | MDExOlB1bGxSZXF1ZXN0MzM1OTA4NDE4 | 1,703 | Add `model.train()` line to ReadMe training example | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1703?src=pr&el=h1) Report\n> Merging [#1703](https://codecov.io/gh/huggingface/transformers/pull/1703?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8a62835577a2a93642546858b21372e43c1a1ff8?src=pr&el=desc) will **n... | 1,572 | 1,572 | 1,572 | CONTRIBUTOR | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I added `model.train()` line to ReadMe training example, at this section
https://github.com/huggingface/transformers#optimizers-bertadam--openaiadam-are-now-adamw-schedules-are-standard-pytorch-schedules
```
for batch in train_da... | {
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https://api.github.com/repos/huggingface/transformers/issues/1702 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1702/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1702/comments | https://api.github.com/repos/huggingface/transformers/issues/1702/events | https://github.com/huggingface/transformers/issues/1702 | 516,464,207 | MDU6SXNzdWU1MTY0NjQyMDc= | 1,702 | Interpretation of output from fine-tuned BERT for Masked Language Modeling. | {
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"My bad! Should have read the documentation for BertForMaskedLM code:\r\n```\r\nOutputs: `Tuple` comprising various elements depending on the configuration (config) and inputs:\r\n **masked_lm_loss**: (`optional`, returned when ``masked_lm_labels`` is provided) ``torch.FloatTensor`` of shape ``(1,)``:\r\n ... | 1,572 | 1,586 | 1,575 | NONE | null | ## ❓ Questions & Help
Hi,
I need some help with interpretation of the output from a fine-tuned bert model.
Here is what I have done so far:
I used `run_lm_finetuning.py` to fine-tune 'bert-base-uncased' model on my domain specific text data.
I fine-tuned the model for 3 epochs, and I get the following files ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1701 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1701/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1701/comments | https://api.github.com/repos/huggingface/transformers/issues/1701/events | https://github.com/huggingface/transformers/issues/1701 | 516,450,359 | MDU6SXNzdWU1MTY0NTAzNTk= | 1,701 | When I uesd gpt2, I got a error | {
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"We had a temporary issue with our `gpt2` model, should be fixed now.",
"I reinstalled `transformers` (`pip install transformers`), and the error remains.",
"> We had a temporary issue with our `gpt2` model, should be fixed now.\r\nI reinstalled transformers (pip install transformers), and the error remains.\r\... | 1,572 | 1,572 | 1,572 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
` File "test.py", line 92, in <module>
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
File "/home/ruiy/anaconda3/envs/pytorch101/lib/python3.6/site-packages/transformers/tokenization_utils.py", line 282, in from_pretrained
... | {
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https://api.github.com/repos/huggingface/transformers/issues/1700 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1700/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1700/comments | https://api.github.com/repos/huggingface/transformers/issues/1700/events | https://github.com/huggingface/transformers/issues/1700 | 516,448,086 | MDU6SXNzdWU1MTY0NDgwODY= | 1,700 | Best practices for Bert passage similarity. Perhaps further processing Bert vectors; Bert model inside another model | {
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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"
] | 1,572 | 1,578 | 1,578 | CONTRIBUTOR | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I'm trying develop Bert passage similarity, specifically question/ answer-retrieval. The architecture is pooling bert contextualized embeddings for passages of text, and then doing cos similarity. Basically the architecture is as it's... | {
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https://api.github.com/repos/huggingface/transformers/issues/1699 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1699/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1699/comments | https://api.github.com/repos/huggingface/transformers/issues/1699/events | https://github.com/huggingface/transformers/issues/1699 | 516,446,367 | MDU6SXNzdWU1MTY0NDYzNjc= | 1,699 | Why do I get 13 hidden layers? | {
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"The first element is the embedding output.\r\n\r\nYes, use `hidden_layers[-1]`."
] | 1,572 | 1,572 | 1,572 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi,
When I try to type
```
model = TFRobertaForSequenceClassification.from_pretrained('roberta-base', output_hidden_states=True)
hidden_layers = model([input])
```
The length of hidden_layers is 13. But base model should hav... | {
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https://api.github.com/repos/huggingface/transformers/issues/1698 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1698/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1698/comments | https://api.github.com/repos/huggingface/transformers/issues/1698/events | https://github.com/huggingface/transformers/issues/1698 | 516,425,503 | MDU6SXNzdWU1MTY0MjU1MDM= | 1,698 | add_tokens() leading to wrong behavior | {
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"I guess that's why add_prefix_space=True would be needed here."
] | 1,572 | 1,574 | 1,574 | NONE | null | Hey folks, I am using GPT2Tokenizer and tried add_tokens() below. But it gives unintended behavior and this is because of #612 in tokenization_utils.py
sub_text = sub_text.strip()
As you see, dollars is split because of space removal. Could someone look into it please.
```
t1 = GPT2Tokenizer.from_... | {
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https://api.github.com/repos/huggingface/transformers/issues/1697 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1697/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1697/comments | https://api.github.com/repos/huggingface/transformers/issues/1697/events | https://github.com/huggingface/transformers/pull/1697 | 516,333,884 | MDExOlB1bGxSZXF1ZXN0MzM1NjA1MDU1 | 1,697 | PPLM (squashed) | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1697?src=pr&el=h1) Report\n> Merging [#1697](https://codecov.io/gh/huggingface/transformers/pull/1697?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e85855f2c408f65a4aaf5d15baab6ca90fd26050?src=pr&el=desc) will **i... | 1,572 | 1,575 | 1,575 | MEMBER | null | Update: not the case anymore as #1695 was merged.
~~This also contains https://github.com/huggingface/transformers/pull/1695 to make it easy to test in a stand-alone way, but those changes won't be in the final commit~~ | {
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https://api.github.com/repos/huggingface/transformers/issues/1696 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1696/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1696/comments | https://api.github.com/repos/huggingface/transformers/issues/1696/events | https://github.com/huggingface/transformers/issues/1696 | 516,268,120 | MDU6SXNzdWU1MTYyNjgxMjA= | 1,696 | Invalid argument error with TFRoberta on GLUE | {
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"I have encountered this embedding error and I found that wrapping the model in a tf.distribute strategy fixes it (extremely odd...)\r\n\r\nYou can wrap the model in `tf.distribute.OneDeviceStrategy` and it will work.",
"Did you ever figure it out? ",
"This issue has been automatically marked as stale because i... | 1,572 | 1,582 | 1,582 | NONE | null | ## 🐛 Bug
I am unable to get TFRoberta working on the GLUE benchmark.
Model I am using (Bert, XLNet....): TFRoberta
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... | {
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https://api.github.com/repos/huggingface/transformers/issues/1695 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1695/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1695/comments | https://api.github.com/repos/huggingface/transformers/issues/1695/events | https://github.com/huggingface/transformers/pull/1695 | 516,217,137 | MDExOlB1bGxSZXF1ZXN0MzM1NTA2MDM5 | 1,695 | model forwards can take an inputs_embeds param | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1695?src=pr&el=h1) Report\n> Merging [#1695](https://codecov.io/gh/huggingface/transformers/pull/1695?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/68f7064a3ea979cdbdadfed62ad655eac4c53463?src=pr&el=desc) will **i... | 1,572 | 1,573 | 1,572 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/1694 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1694/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1694/comments | https://api.github.com/repos/huggingface/transformers/issues/1694/events | https://github.com/huggingface/transformers/pull/1694 | 516,209,856 | MDExOlB1bGxSZXF1ZXN0MzM1NDk5OTU3 | 1,694 | solves several bugs in the summarization codes | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1694?src=pr&el=h1) Report\n> Merging [#1694](https://codecov.io/gh/huggingface/transformers/pull/1694?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/93d2fff0716d83df168ca0686d16bc4cd7ccb366?src=pr&el=desc) will **n... | 1,572 | 1,576 | 1,576 | NONE | null | Hi,
This pull requests solves several small bugs in this summarization script:
- call the evaluation code
- fix the iterating over batch in eval part
- create the folders before saving encoder/decoder to avoid the crash
- first creates output_dir, then use it during the saving of the model part.
- tokenizer... | {
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https://api.github.com/repos/huggingface/transformers/issues/1693 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1693/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1693/comments | https://api.github.com/repos/huggingface/transformers/issues/1693/events | https://github.com/huggingface/transformers/issues/1693 | 516,206,714 | MDU6SXNzdWU1MTYyMDY3MTQ= | 1,693 | TFXLNet Incompatible shapes in relative attention | {
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"I have a fix for this in #1763 ",
"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"
] | 1,572 | 1,578 | 1,578 | NONE | null | ## 🐛 Bug
TFXLNet fails to run due to incompatible shapes when computing relative attention.
Model I am using (Bert, XLNet....):
TFXLNet
Language I am using the model on (English, Chinese....):
English
The problem arise when using:
* [ ] the official example scripts: (give details)
* [x] my own modi... | {
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https://api.github.com/repos/huggingface/transformers/issues/1692 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1692/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1692/comments | https://api.github.com/repos/huggingface/transformers/issues/1692/events | https://github.com/huggingface/transformers/issues/1692 | 516,188,063 | MDU6SXNzdWU1MTYxODgwNjM= | 1,692 | TFXLNet int32 to float promotion error | {
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"Problem can be addressed by updating line 542 in transformers/modeling_tf_xlnet.py to :\r\n```python\r\n input_mask = 1.0 - tf.cast(attention_mask, dtype=dtype_float)\r\n```",
"The above solution is not present in the current version. Why ?\r\nIt is still showing the same error as a result.",
"@Prad... | 1,572 | 1,580 | 1,576 | NONE | null | ## 🐛 Bug
Using TFXLNet on GLUE datasets results in a TypeError when computing the input_mask because the attention_mask is represented as an int32 and is not automatically cast or promoted to a float.
Model I am using (Bert, XLNet....):
TFXLNet
Language I am using the model on (English, Chinese....):
En... | {
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https://api.github.com/repos/huggingface/transformers/issues/1691 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1691/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1691/comments | https://api.github.com/repos/huggingface/transformers/issues/1691/events | https://github.com/huggingface/transformers/issues/1691 | 516,178,388 | MDU6SXNzdWU1MTYxNzgzODg= | 1,691 | ALbert Model implementation is finished on squad qa task. but some format is different with huggingface.(specify on albert qa task) | {
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## Model description
<!-- Important information -->
Hey, seems like your community creates the same one branch for Albert, actually, I also reimplement the code and transfer from tf-hub to PyTorch by referencing your other preview convert_tf_xxx.py code. and also reproduce the author's per... | {
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https://api.github.com/repos/huggingface/transformers/issues/1690 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1690/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1690/comments | https://api.github.com/repos/huggingface/transformers/issues/1690/events | https://github.com/huggingface/transformers/issues/1690 | 516,174,420 | MDU6SXNzdWU1MTYxNzQ0MjA= | 1,690 | T5 | {
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"duplicate of #1617 "
] | 1,572 | 1,572 | 1,572 | NONE | null | # 🌟New model addition
[Exploring the Limits of Transfer Learning with a
Unified Text-to-Text Transformer](https://arxiv.org/pdf/1910.10683.pdf)
## Open Source status
Code and model are open sourced | {
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https://api.github.com/repos/huggingface/transformers/issues/1689 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1689/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1689/comments | https://api.github.com/repos/huggingface/transformers/issues/1689/events | https://github.com/huggingface/transformers/issues/1689 | 516,072,121 | MDU6SXNzdWU1MTYwNzIxMjE= | 1,689 | Can't export TransfoXLModel model | {
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"Yes, this is a known issue, `TransformerXL` is not traceable.\r\n\r\nFixing this is not on our short-term roadmap (cc @LysandreJik) but feel free to investigate and propose a solution in a PR if you want.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be clos... | 1,572 | 1,597 | 1,578 | NONE | null | ## 🐛 Bug
<!-- Important information -->
I am trying to export TransfoXLModel and use it for inference from C++ API.
I tried torch.jit.trace(), torch.jit.script() and torch.onnx.export(). But none of these work.
Model I am using - TransfoXLModel:
Language I am using the model on - English
The problem aris... | {
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https://api.github.com/repos/huggingface/transformers/issues/1688 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1688/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1688/comments | https://api.github.com/repos/huggingface/transformers/issues/1688/events | https://github.com/huggingface/transformers/issues/1688 | 516,053,884 | MDU6SXNzdWU1MTYwNTM4ODQ= | 1,688 | fine tuning bert and roberta_base model | {
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"There is an example in [the documentation](https://huggingface.co/transformers/examples.html#roberta-bert-and-masked-language-modeling)."
] | 1,572 | 1,572 | 1,572 | NONE | null | could you please let me know how to fine tune the BERT/ ROBERTA_Base models? | {
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https://api.github.com/repos/huggingface/transformers/issues/1687 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1687/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1687/comments | https://api.github.com/repos/huggingface/transformers/issues/1687/events | https://github.com/huggingface/transformers/issues/1687 | 516,014,970 | MDU6SXNzdWU1MTYwMTQ5NzA= | 1,687 | request for a Bert_base uncase model.bin file | {
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"As with any model hosted on our S3, you can do as follows to load one of the checkpoints:\r\n\r\n```py\r\nfrom transformers import BertModel\r\n\r\nmodel = BertModel.from_pretrained(\"bert-base-uncased\")\r\n```\r\n\r\nYou can find the list of pre-trained models in [the documentation](https://huggingface.co/transf... | 1,572 | 1,572 | 1,572 | NONE | null | ## 🚀 Feature
currently we r using BERT_Large uncased which slows down our application we like to use BERT_Base uncased model but BERT_base uncased model does not contain bin file.could you please let me know where I get model.bin file. | {
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https://api.github.com/repos/huggingface/transformers/issues/1686 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1686/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1686/comments | https://api.github.com/repos/huggingface/transformers/issues/1686/events | https://github.com/huggingface/transformers/issues/1686 | 515,900,619 | MDU6SXNzdWU1MTU5MDA2MTk= | 1,686 | OpenAIGPTDoubleHeadsModel Not working (even with the official example...) | {
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"Indeed thanks, fixed"
] | 1,572 | 1,572 | 1,572 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using : OpenAI GPT (DoubleHeadsModel)
Language I am using the model on : English
The problem arise when using:
* [ ] the official example scripts: [link](https://huggingface.co/transformers/model_doc/gpt.html)
```
tokenizer = OpenAIGPTTokenizer.from_p... | {
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https://api.github.com/repos/huggingface/transformers/issues/1685 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1685/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1685/comments | https://api.github.com/repos/huggingface/transformers/issues/1685/events | https://github.com/huggingface/transformers/issues/1685 | 515,743,299 | MDU6SXNzdWU1MTU3NDMyOTk= | 1,685 | Unpickling errors when running examples | {
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"Closing this in favor of #1684"
] | 1,572 | 1,572 | 1,572 | NONE | null | ## ❓ Questions & Help
Hi there, when I run the examples
```
%run run_generation.py \
--model_type=gpt2 \
--model_name_or_path=gpt2
```
I keep getting the following errors:
```
---------------------------------------------------------------------------
UnpicklingError ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1684 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1684/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1684/comments | https://api.github.com/repos/huggingface/transformers/issues/1684/events | https://github.com/huggingface/transformers/issues/1684 | 515,742,869 | MDU6SXNzdWU1MTU3NDI4Njk= | 1,684 | Access denied to pretrained GPT2 model | {
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"I'm having the same error",
"There is a known (temporary) issue with our `gpt2` model – can you guys use `gpt2-medium` or `distilgpt2` instead for now?\r\n\r\ncc @LysandreJik @thomwolf @n1t0 @clmnt ",
"Sure thing! Thanks for letting us know :)",
"(should be fixed now)",
"Thank you!",
"This issue has been... | 1,572 | 1,577 | 1,577 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): GPT2
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: I cannot load the GPT2 small pretrained model.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/1683 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1683/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1683/comments | https://api.github.com/repos/huggingface/transformers/issues/1683/events | https://github.com/huggingface/transformers/pull/1683 | 515,645,871 | MDExOlB1bGxSZXF1ZXN0MzM1MDcyNTY3 | 1,683 | Add ALBERT to the library | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1683?src=pr&el=h1) Report\n> Merging [#1683](https://codecov.io/gh/huggingface/transformers/pull/1683?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/fa735208c96c18283b8d2f3fcbfc3157bbd12b1e?src=pr&el=desc) will **i... | 1,572 | 1,581 | 1,574 | MEMBER | null | This PR adds ALBERT to the library. It offers two new model architectures:
- AlbertModel
- AlbertForMaskedLM
AlbertModel acts in a similar way to BertModel as it returns a sequence output as well as a pooled output. AlbertForMaskedLM exposes an additional language modeling head.
A total of four pre-trained ch... | {
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https://api.github.com/repos/huggingface/transformers/issues/1682 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1682/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1682/comments | https://api.github.com/repos/huggingface/transformers/issues/1682/events | https://github.com/huggingface/transformers/pull/1682 | 515,574,551 | MDExOlB1bGxSZXF1ZXN0MzM1MDE0MjU1 | 1,682 | xnli benchmark | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1682?src=pr&el=h1) Report\n> Merging [#1682](https://codecov.io/gh/huggingface/transformers/pull/1682?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7daacf00df433621e3d3872a9f3bb574d1b00f5a?src=pr&el=desc) will **i... | 1,572 | 1,651 | 1,574 | MEMBER | null | adapted from `run_glue.py` | {
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https://api.github.com/repos/huggingface/transformers/issues/1681 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1681/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1681/comments | https://api.github.com/repos/huggingface/transformers/issues/1681/events | https://github.com/huggingface/transformers/issues/1681 | 515,567,446 | MDU6SXNzdWU1MTU1Njc0NDY= | 1,681 | Wrong Roberta special tokens in releases on GitHub | {
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"You are right the release is wrong, it should be `<s> SEQUENCE_0 </s></s> SEQUENCE_1 </s>`. I just updated it; thank you!"
] | 1,572 | 1,572 | 1,572 | NONE | null | ## 🐛 Bug
Model I am using (Bert, XLNet....): Roberta
Language I am using the model on (English, Chinese....): Potentially wrong on any language
The problem arise when using the official example scripts: see https://github.com/huggingface/transformers/releases/tag/1.1.0
In the section `Tokenizer sequence pa... | {
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https://api.github.com/repos/huggingface/transformers/issues/1680 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1680/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1680/comments | https://api.github.com/repos/huggingface/transformers/issues/1680/events | https://github.com/huggingface/transformers/issues/1680 | 515,319,280 | MDU6SXNzdWU1MTUzMTkyODA= | 1,680 | Error when creating RobertTokenizer for distilroberta-base | {
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"It's not in a pip released version yet so you need to pull from master if you want to use it for now.\r\n\r\nWe'll do a release soon.",
"Thanks for the info. Do you have an estimation when that pip release would be, @julien-c ?",
"Reviving this thread. I just cloned 2.2.2 from the master and updated `transform... | 1,572 | 1,576 | 1,572 | NONE | null | ## 🐛 Bug
Model I am using (Bert, XLNet....): DistilRoberta
Language I am using the model on (English, Chinese....): EN
The problem arise when using the official example scripts: https://github.com/huggingface/transformers/tree/master/examples/distillation
## To Reproduce
```
RobertaTokenizer.from_pretrai... | {
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https://api.github.com/repos/huggingface/transformers/issues/1679 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1679/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1679/comments | https://api.github.com/repos/huggingface/transformers/issues/1679/events | https://github.com/huggingface/transformers/pull/1679 | 515,273,087 | MDExOlB1bGxSZXF1ZXN0MzM0NzYwMDUz | 1,679 | Fix https://github.com/huggingface/transformers/issues/1673 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1679?src=pr&el=h1) Report\n> Merging [#1679](https://codecov.io/gh/huggingface/transformers/pull/1679?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/fa735208c96c18283b8d2f3fcbfc3157bbd12b1e?src=pr&el=desc) will **i... | 1,572 | 1,572 | 1,572 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/1678 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1678/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1678/comments | https://api.github.com/repos/huggingface/transformers/issues/1678/events | https://github.com/huggingface/transformers/issues/1678 | 515,256,159 | MDU6SXNzdWU1MTUyNTYxNTk= | 1,678 | Download assets directly to the specified cache_dir | {
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"I have read the comment part of the reference code:\r\n```\r\n# Download to temporary file, then copy to cache dir once finished.\r\n# Otherwise you get corrupt cache entries if the download gets interrupted.\r\n```\r\nSo I would change my proposal:\r\n* Either let it be configurable to skip the tmp folder and dow... | 1,572 | 1,578 | 1,576 | NONE | null | ## 🚀 Feature
```
import torch
from transformers import *
TRANSFORMERS_CACHE='/path/to/my/transformers-cache'
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased', cache_dir=TRANSFORMERS_CACHE)
```
Actual behavior: It downloads the asset into a temp folder and then copies it to the specified cache_... | {
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"run_multiple_choice.py will be a good choice.\r\nin case ‘bert’, it uses \r\nhttps://github.com/huggingface/transformers/blob/master/transformers/modeling_bert.py#L1021\r\n\r\nbut i think your problem formulation is odd.\r\nwhat about classifying ‘request_*’ intent as normal classification problem and slot tagging... | 1,572 | 1,578 | 1,578 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
i want to use bert pre-trained modle in a text classification problem which the text with Multi-labels. Which program and task should i select between run_glue.py、run_multiple_choice.py、run_squad.py and so on？
for example of my text：“I... | {
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https://api.github.com/repos/huggingface/transformers/issues/1676 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1676/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1676/comments | https://api.github.com/repos/huggingface/transformers/issues/1676/events | https://github.com/huggingface/transformers/issues/1676 | 515,116,704 | MDU6SXNzdWU1MTUxMTY3MDQ= | 1,676 | 🌟 BART | {
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"@thomwolf another encoder-decoder",
"Was released today: https://github.com/pytorch/fairseq/tree/master/examples/bart 🎉",
"Let me know if you guys plan to add xsum/eli5/cnn-dm ft with our released bart into hugging face. ",
"Is there any news on this?",
"any progress on this one? also thanks :)",
"I'm g... | 1,572 | 1,582 | 1,582 | CONTRIBUTOR | null | # 🌟New model addition
## Model description
method for pre-training seq2seq models by de-noising text. BART outperforms previous work on a bunch of generation tasks (summarization/dialogue/QA), while getting similar performance to RoBERTa on SQuAD/GLUE
[BART: Denoising Sequence-to-Sequence Pre-training for Nat... | {
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https://api.github.com/repos/huggingface/transformers/issues/1675 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1675/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1675/comments | https://api.github.com/repos/huggingface/transformers/issues/1675/events | https://github.com/huggingface/transformers/issues/1675 | 515,063,490 | MDU6SXNzdWU1MTUwNjM0OTA= | 1,675 | Any example of how to do multi-class classification with TFBertSequenceClassification | {
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"im asking for the same thing",
"I also need this. experts, please help/guide.",
"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"
] | 1,572 | 1,584 | 1,584 | NONE | null | ## ❓ Questions & Help
I am trying to create a multi-class text classification model using BertSequenceClassifier for Tensorflow 2.0. Any help with the implementation strategy would be appreciated. Also, are there any recommendations as to how to convert a simple CSV file containing text and labels into TF dataset fo... | {
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https://api.github.com/repos/huggingface/transformers/issues/1674 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1674/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1674/comments | https://api.github.com/repos/huggingface/transformers/issues/1674/events | https://github.com/huggingface/transformers/issues/1674 | 514,957,059 | MDU6SXNzdWU1MTQ5NTcwNTk= | 1,674 | possible issues with run_summarization_finetuning.py | {
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"Hi!\r\n\r\nThanks for pointing these out. The summarization is still work in progress and should be included in the next release. Latest changes are in the `example-summarization` branch.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further ... | 1,572 | 1,578 | 1,578 | NONE | null | Hi,
thanks for pushing summarization codes, here are my comments on this file:
- line 473: checkpoints = [] is empty and will not be evaluated. Also, the evaluation script is not called.
- line 482: results = "placeholder" is set to the placeholder, I was wondering if the function could return the generated tex... | {
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https://api.github.com/repos/huggingface/transformers/issues/1673 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1673/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1673/comments | https://api.github.com/repos/huggingface/transformers/issues/1673/events | https://github.com/huggingface/transformers/issues/1673 | 514,645,589 | MDU6SXNzdWU1MTQ2NDU1ODk= | 1,673 | BertModel.from_pretrained is failing with "HTTP 407 Proxy Authentication Required" during model weight download when running behing a proxy | {
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<!-- Important information -->
Hello,
I'am using transformers behind a proxy. `BertConfig.from_pretrained(..., proxies=proxies)` is working as expected, where `BertModel.from_pretrained(..., proxies=proxies)` gets a
`OSError: Tunnel connection failed: 407 Proxy Authentication Required` . This could b... | {
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https://api.github.com/repos/huggingface/transformers/issues/1672 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1672/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1672/comments | https://api.github.com/repos/huggingface/transformers/issues/1672/events | https://github.com/huggingface/transformers/issues/1672 | 514,638,168 | MDU6SXNzdWU1MTQ2MzgxNjg= | 1,672 | Is HuggingFace TransfoXLLMHeadModels trainable from scratch? | {
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"Hi @h56cho,\r\n\r\nThe loss is actually returned if labels are present.\r\n\r\nCheck https://github.com/huggingface/transformers/blob/master/transformers/modeling_transfo_xl.py#L793",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activi... | 1,572 | 1,578 | 1,578 | NONE | null | Hello,
Is HuggingFace TransfoXLLMHeadModels trainable from scratch? The documentation makes it look like it is possible to train the TransfoXLLMHeadModel from scratch, since (according to the documentation) the loss can be returned via TransfoXLLMHeadModel( ) as long as labels are provided (https://huggingface.co/tr... | {
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https://api.github.com/repos/huggingface/transformers/issues/1671 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1671/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1671/comments | https://api.github.com/repos/huggingface/transformers/issues/1671/events | https://github.com/huggingface/transformers/issues/1671 | 514,577,669 | MDU6SXNzdWU1MTQ1Nzc2Njk= | 1,671 | Quick Tour TF2.0 Training Script has Control Flow Error when Replacing TFBERT with TFRoberta | {
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"Hi, I think this was fixed by #1601, could you try now by cloning and installing from master?",
"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"
] | 1,572 | 1,578 | 1,578 | NONE | null | ## 📚 Migration
<!-- Important information -->
Model I am using (Bert, XLNet....): TFRoberta.
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [x] the official example scripts: Quick Tour TF2.0 Training Script.
* [ ] my own modified scripts:
Details of t... | {
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https://api.github.com/repos/huggingface/transformers/issues/1670 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1670/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1670/comments | https://api.github.com/repos/huggingface/transformers/issues/1670/events | https://github.com/huggingface/transformers/pull/1670 | 514,560,216 | MDExOlB1bGxSZXF1ZXN0MzM0MTU3MDgz | 1,670 | Templates and explanation for adding a new model and example script | {
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"Thanks @stefan-it, feel free to give your opinion on the explanation/templates as well, always happy to have your feedback"
] | 1,572 | 1,578 | 1,572 | MEMBER | null | This PR adds:
- templates and explantations for all the steps needed to add a new model
- a simple template for adding a new example script (basically the current `run_squad` example).
- links to them in the `README` and `CONTRIBUTING` docs.
@LysandreJik and @rlouf, feel free to update if you want to add stuff or... | {
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https://api.github.com/repos/huggingface/transformers/issues/1669 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1669/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1669/comments | https://api.github.com/repos/huggingface/transformers/issues/1669/events | https://github.com/huggingface/transformers/issues/1669 | 514,529,835 | MDU6SXNzdWU1MTQ1Mjk4MzU= | 1,669 | How to load trained model of distilbert | {
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"Hello @ANSHUMAN87,\r\n\r\nCould you share the command you're using (and the error you get)?\r\nYou should have at least these arguments: `--model_type distilbert --model_name_or_path <your_model_path>`.\r\n\r\nVictor",
"I have mentioned below the steps i followed.\r\n\r\nStep 1: python3 train.py --student_type d... | 1,572 | 1,592 | 1,578 | NONE | null | ## ❓ Questions & Help
Hi,
I have trained distilbert using the steps mentioned in example/distillation.
saved the checkpoints into one directory.
But i cant use run_glue.py using the checkpoint path i saved for distilbert.
It throws error for tokenizer missing.
Would you please help me, how to achieve that. I... | {
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https://api.github.com/repos/huggingface/transformers/issues/1668 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1668/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1668/comments | https://api.github.com/repos/huggingface/transformers/issues/1668/events | https://github.com/huggingface/transformers/pull/1668 | 514,336,719 | MDExOlB1bGxSZXF1ZXN0MzMzOTcyNjM5 | 1,668 | Fixed training for TF XLM | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1668?src=pr&el=h1) Report\n> Merging [#1668](https://codecov.io/gh/huggingface/transformers/pull/1668?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/079bfb32fba4f2b39d344ca7af88d79a3ff27c7c?src=pr&el=desc) will **n... | 1,572 | 1,572 | 1,572 | CONTRIBUTOR | null | This PR fixes `model.fit()` training for TF XLM model, and tested in a script similar to `run_tf_glue.py`. It also is tested and works with AMP and tf.distribute for mixed precision and multi-GPU training.
This changes some Python `assert` statements to `tf.debugging.assert_equal` both in `TFXLMMainLayer.call()` and... | {
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https://api.github.com/repos/huggingface/transformers/issues/1667 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1667/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1667/comments | https://api.github.com/repos/huggingface/transformers/issues/1667/events | https://github.com/huggingface/transformers/pull/1667 | 514,330,723 | MDExOlB1bGxSZXF1ZXN0MzMzOTY3NTU3 | 1,667 | Added FP16 support to benchmarks.py | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1667?src=pr&el=h1) Report\n> Merging [#1667](https://codecov.io/gh/huggingface/transformers/pull/1667?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/079bfb32fba4f2b39d344ca7af88d79a3ff27c7c?src=pr&el=desc) will **i... | 1,572 | 1,572 | 1,572 | CONTRIBUTOR | null | This PR adds in FP16 support for the inference benchmarks for TensorFlow and PyTorch, and presents the collected results. This is a "re-do" of a previous PR (#1567) taking into account changes to `benchmark.py` and also adding in the PyTorch component with additional results collected.
**TensorFlow**
Added a auto... | {
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https://api.github.com/repos/huggingface/transformers/issues/1666 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1666/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1666/comments | https://api.github.com/repos/huggingface/transformers/issues/1666/events | https://github.com/huggingface/transformers/issues/1666 | 514,298,535 | MDU6SXNzdWU1MTQyOTg1MzU= | 1,666 | Question: Token sequence length longer maximum sequence length | {
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"Going through the source code, the sequence is actually truncated.\r\n\r\nhttps://github.com/huggingface/transformers/blob/079bfb32fba4f2b39d344ca7af88d79a3ff27c7c/transformers/tokenization_utils.py#L846-L853\r\n\r\nThe warning occurs because `encode_plus` calls `convert_tokens_to_ids` _first_ and only then the ID... | 1,572 | 1,580 | 1,580 | NONE | null | ## ❓ Questions & Help
I'm using `run_glue.py` with a task name of `SST-2` to fine-tune a binary classifier on my data, which I put into the required format. However, some of my data's sentences are longer than the `max_seq_length` of `512` for `BERT` and `RoBERTa`; so, I get
`WARNING - transformers.tokenization_u... | {
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https://api.github.com/repos/huggingface/transformers/issues/1665 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1665/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1665/comments | https://api.github.com/repos/huggingface/transformers/issues/1665/events | https://github.com/huggingface/transformers/issues/1665 | 514,231,190 | MDU6SXNzdWU1MTQyMzExOTA= | 1,665 | Allowing PR#1455 to be merged in the master | {
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"Please don't post issues like this. I'm sure the maintainers work as hard as they can. Asking them to _work faster_ doesn't help. In fact, adding these kind of non-issues only distract the maintainers from actually working on the actual issues at hand. Please close this question."
] | 1,572 | 1,572 | 1,572 | NONE | null | Hi Thomas
Remi was saying in PR:#1455 it has the bert seq2seq ready, could you move in a gradual way please and allow this PR to be merged at this stage that is working for BERT? Then people can use the BERT one, this is already great, then after a while when this is ready for also other encoders, you can add them lat... | {
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https://api.github.com/repos/huggingface/transformers/issues/1664 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1664/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1664/comments | https://api.github.com/repos/huggingface/transformers/issues/1664/events | https://github.com/huggingface/transformers/issues/1664 | 514,229,270 | MDU6SXNzdWU1MTQyMjkyNzA= | 1,664 | Moving model from GPU -> CPU doesn't work | {
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"`.to()` is not an in-place operation. You should use `model = model.to('cpu')`. If that doesn't work, it might be that you need to access the module as part of the DataParallel object, like this:\r\n\r\n```python\r\nmodel = model.module.to('cpu')\r\n```",
"Ahh gotcha. Thanks for the quick reply!"
] | 1,572 | 1,572 | 1,572 | NONE | null | ## 🐛 Bug
Hi,
I tried creating a model (doesn't matter which one from my experiments), moving it first to multiple GPUs and then back to CPU. But I think it doesn't work as intended.
The following is the code to reproduce the error:
```python
import torch
import torch.nn as nn
from transformers import Be... | {
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https://api.github.com/repos/huggingface/transformers/issues/1663 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1663/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1663/comments | https://api.github.com/repos/huggingface/transformers/issues/1663/events | https://github.com/huggingface/transformers/issues/1663 | 514,127,536 | MDU6SXNzdWU1MTQxMjc1MzY= | 1,663 | Problem with restoring GPT-2 weights | {
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"I found a bug, it's TPU related. For some reason, after I move the mode to TPU, using `model = model.to(device)`, the weights become decoupled. Then I save decoupled weights and during restore it ties them again. It loads correctly, it just doesn't expect tied weights to be different.\r\n\r\nThe workaround is to t... | 1,572 | 1,584 | 1,584 | CONTRIBUTOR | null | Hello, I've been debugging an issue for a while and it seem it's a model-specific issue.
I'm training GPT-2 on a TPU and I can't save and restore it. It looks like there is a code that silently changes parameter values right in `load_state_dict()`.
```
print(state_dict['transformer.wte.weight'])
print(... | {
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https://api.github.com/repos/huggingface/transformers/issues/1662 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1662/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1662/comments | https://api.github.com/repos/huggingface/transformers/issues/1662/events | https://github.com/huggingface/transformers/issues/1662 | 514,080,904 | MDU6SXNzdWU1MTQwODA5MDQ= | 1,662 | Tokenizer.tokenize return none on some utf8 string in current pypi version | {
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"We've seen this issues also with other tokenizers, like XLNet. \r\n\r\nIt would be awesome to have a unified tokenization strategy (across all `Tokenizer` classes) that return `unk_token` in these cases. And of course we should discuss other possibilities here :)\r\n",
"@voidful this behavior arises because `ber... | 1,572 | 1,572 | 1,572 | CONTRIBUTOR | null | Tokenizer.tokenize return none on some utf8 string in current pypi version
## 🐛 Bug
<!-- Important information -->
Model I am using (Bert):
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [ ] the official example scripts:
The tasks I am working on is:
* [ ] m... | {
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https://api.github.com/repos/huggingface/transformers/issues/1661 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1661/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1661/comments | https://api.github.com/repos/huggingface/transformers/issues/1661/events | https://github.com/huggingface/transformers/issues/1661 | 514,001,706 | MDU6SXNzdWU1MTQwMDE3MDY= | 1,661 | BERT multi heads attentions | {
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"I think the [BERTology](https://huggingface.co/transformers/bertology.html) section could help, especially the [run_bertology.py](https://github.com/huggingface/transformers/blob/master/examples/run_bertology.py) script can perform pruning and includes other useful functions :)",
"I am beginner to BERT, can you ... | 1,572 | 1,578 | 1,578 | NONE | null | Hello,
I would like to analysis the effect of specific heads' attention.
Is it possible to turn off some heads attentions in a particular layer?
if yes, can you please tell me how to do that or share any helpful document?
Thank you in advance | {
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https://api.github.com/repos/huggingface/transformers/issues/1660 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1660/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1660/comments | https://api.github.com/repos/huggingface/transformers/issues/1660/events | https://github.com/huggingface/transformers/issues/1660 | 513,890,625 | MDU6SXNzdWU1MTM4OTA2MjU= | 1,660 | How to fine-tune CTRL? | {
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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",
"@zhongpeixiang do you have any info about finetuning ctrl?",
"@saippuakauppias No, in the end I chose the original CTRL repo from Sal... | 1,572 | 1,644 | 1,577 | NONE | null | How to fine-tune CTRL on a custom dataset with custom control codes using the transformers package?
I'm aware of the [guide](https://github.com/salesforce/ctrl/tree/master/training_utils) for tensorflow users. However, as a PyTorch user, the guide is not friendly to me.
I'm also aware of the language modelling f... | {
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https://api.github.com/repos/huggingface/transformers/issues/1659 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1659/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1659/comments | https://api.github.com/repos/huggingface/transformers/issues/1659/events | https://github.com/huggingface/transformers/issues/1659 | 513,693,304 | MDU6SXNzdWU1MTM2OTMzMDQ= | 1,659 | How is the interactive GPT-2 implemented? | {
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"Hi, the models are not fine-tuned on the fly. Language models like GPT-2 are very context-aware and are strong at generating words related to the inputs they were given. \r\n\r\nWe are not training the models in that demo, we are only using them for inference.",
"This issue has been automatically marked as stale... | 1,572 | 1,578 | 1,578 | NONE | null | ## ❓ Questions & Help
I came across this online demo from HuggingFace for GPT-2 writing: https://transformer.huggingface.co/doc/gpt2-large. The demo is really amazing, both accurate and fast. My major observation is that the service actually uses user's earlier writing examples in later prediction, almost instantly. I... | {
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https://api.github.com/repos/huggingface/transformers/issues/1658 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1658/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1658/comments | https://api.github.com/repos/huggingface/transformers/issues/1658/events | https://github.com/huggingface/transformers/issues/1658 | 513,634,072 | MDU6SXNzdWU1MTM2MzQwNzI= | 1,658 | How to fine tune xlm-mlm-100-128 model. | {
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"If you're looking to fine-tune it on an MLM task you could simply re-use some parts of the `run_lm_finetuning.py` script to do it. ",
"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"
] | 1,572 | 1,578 | 1,578 | NONE | null | ## ❓ Questions & Help
How to fine tune xlm-mlm-17-128 model for own dataset. Since, run_lm_finetuning.py has no option to fine tune XLM models.
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https://api.github.com/repos/huggingface/transformers/issues/1657 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1657/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1657/comments | https://api.github.com/repos/huggingface/transformers/issues/1657/events | https://github.com/huggingface/transformers/pull/1657 | 513,620,448 | MDExOlB1bGxSZXF1ZXN0MzMzMzc1NDg4 | 1,657 | [WIP] Raise error if larger sequences | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1657?src=pr&el=h1) Report\n> Merging [#1657](https://codecov.io/gh/huggingface/transformers/pull/1657?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/079bfb32fba4f2b39d344ca7af88d79a3ff27c7c?src=pr&el=desc) will **d... | 1,572 | 1,578 | 1,578 | NONE | null | Hi,
I suggest to improve a bit user experience when using pretrained models by raising more errors if some of parameters are incoherent.
For example, in this PR, there is a suggestion to raise error and thus inform user about potential error as "RuntimeError: cublas runtime error ..." which can be harder to find i... | {
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"What is your suggestion, then? Adding a mp_encode function? Perhaps this is something that should stay at the user's side. ",
"Hello @jianwolf,\r\nYes indeed, I've never taken the time to do it (mainly because most of the I do pre-processing are one-shot: I launch it before leaving the office 😴).\r\nIf you feel... | 1,572 | 1,578 | 1,578 | NONE | null | ## 🚀 Feature
Use the `multiprocessing.Pool` function to parallelize the text tokenization and uint16 conversion in `transformers/examples/distillation/scripts/binarized_data.py`.
## Motivation
I tried to preprocess a 2.6 GB txt file using the python script, but the expected time is 2.4 hours. I tried to paral... | {
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https://api.github.com/repos/huggingface/transformers/issues/1655 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1655/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1655/comments | https://api.github.com/repos/huggingface/transformers/issues/1655/events | https://github.com/huggingface/transformers/issues/1655 | 513,605,355 | MDU6SXNzdWU1MTM2MDUzNTU= | 1,655 | Missing a line in examples/distillation/README.md | {
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"Oh yes indeed. Let me correct it. Thank you for pointing that out @jianwolf!"
] | 1,572 | 1,572 | 1,572 | NONE | null | In How to train Distil* -> B, in both of the training commands, you should add `--alpha_clm 0.0 \`, otherwise an assertion error will be triggered (https://github.com/huggingface/transformers/blob/079bfb32fba4f2b39d344ca7af88d79a3ff27c7c/examples/distillation/train.py#L49). | {
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https://api.github.com/repos/huggingface/transformers/issues/1654 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1654/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1654/comments | https://api.github.com/repos/huggingface/transformers/issues/1654/events | https://github.com/huggingface/transformers/issues/1654 | 513,563,441 | MDU6SXNzdWU1MTM1NjM0NDE= | 1,654 | Can I load a CTRL model that was fine-tuned using the Salesforce code? | {
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"cc @keskarnitish :)",
"Sure, I'll get on this soon. I'll push it to https://github.com/salesforce/ctrl and link here once I'm done. ",
"Thanks @keskarnitish! That would be great!",
"Added in https://github.com/salesforce/ctrl/commit/a0d0b4d2f38ae55a1396dfad4d6bff7cc9435c2d , see updated `README.md` for usag... | 1,572 | 1,572 | 1,572 | NONE | null | ## ❓ Questions & Help
I have a custom CTRL model that I trained using the Salesforce TF code and I was hoping that I could convert it into the transformers format and load it there. Any advice?
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https://api.github.com/repos/huggingface/transformers/issues/1653 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1653/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1653/comments | https://api.github.com/repos/huggingface/transformers/issues/1653/events | https://github.com/huggingface/transformers/issues/1653 | 513,539,451 | MDU6SXNzdWU1MTM1Mzk0NTE= | 1,653 | No way to control ID of special chars e.g. mask IDs | {
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"To answer question 2:\r\nYou can see the assumed indices for special characters by loading a tokenizer and inspecting the `vocab` attribute.\r\n\r\nFor example:\r\n```\r\nfrom transformers import BertTokenizer\r\ntokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\r\nprint(tokenizer.vocab)\r\n```\r\nThi... | 1,572 | 1,578 | 1,578 | NONE | null | ## Summary
Hi, many thanks for the library - this is a fantastic tool for the NLP community!
I notice there are a number of constants defined in code that the user cannot inject whilst initialising.
Some examples are:
- `padding_idx = 1` in `RobertaEmbeddings`
- `CrossEntropyLoss(ignore_index=-1)` in `Roberta... | {
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https://api.github.com/repos/huggingface/transformers/issues/1652 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1652/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1652/comments | https://api.github.com/repos/huggingface/transformers/issues/1652/events | https://github.com/huggingface/transformers/issues/1652 | 513,517,144 | MDU6SXNzdWU1MTM1MTcxNDQ= | 1,652 | Missing required argument 'mode' in run_ner. | {
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"yes sure, happy to welcome a PR on this",
"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"
] | 1,572 | 1,578 | 1,578 | CONTRIBUTOR | null | ## 🐛 Bug
<!-- Important information -->
Model I am using: BERT
Language I am using the model on: Polish (irrelevant for the error)
The problem arise when using:
* [x] the official example scripts: run_ner.py
The tasks I am working on is:
* [x] my own task or dataset: token classification (aka NER)
... | {
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https://api.github.com/repos/huggingface/transformers/issues/1651 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1651/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1651/comments | https://api.github.com/repos/huggingface/transformers/issues/1651/events | https://github.com/huggingface/transformers/issues/1651 | 513,393,327 | MDU6SXNzdWU1MTMzOTMzMjc= | 1,651 | How to set local_rank argument in run_squad.py | {
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"The easiest way is to use the torch launch script. It will automatically set the local rank correctly. It would look something like this (can't test, am on phone) :\r\n\r\n```bash\r\npython -m torch.distributed.launch --nproc_per_node 8 run_squad.py <your arguments>\r\n```",
"Hi,\r\n\r\nThanks for the fast answe... | 1,572 | 1,587 | 1,572 | NONE | null | Hi!
I would like to try out the run_squad.py script (with AWS SageMaker in a PyTorch container).
I will use 8 x 100V 16 GB GPUs for the training.
How should I set the the local_rank parameter in this case?
( I tried to understand it from the code, but I couldn't really.)
Thank you for the help! | {
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https://api.github.com/repos/huggingface/transformers/issues/1650 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1650/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1650/comments | https://api.github.com/repos/huggingface/transformers/issues/1650/events | https://github.com/huggingface/transformers/issues/1650 | 513,099,026 | MDU6SXNzdWU1MTMwOTkwMjY= | 1,650 | Custom language text generation | {
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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"
] | 1,572 | 1,577 | 1,577 | NONE | null | ## ❓ Questions & Help
How to generate text in non english languages. Is xlm-mlm-100-1280 best for this, I tried but results are too worst.
Also tried things mentioned here:
https://github.com/huggingface/transformers/issues/1414
https://github.com/huggingface/transformers/issues/1068
https://github.com/huggingf... | {
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https://api.github.com/repos/huggingface/transformers/issues/1649 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1649/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1649/comments | https://api.github.com/repos/huggingface/transformers/issues/1649/events | https://github.com/huggingface/transformers/issues/1649 | 513,084,312 | MDU6SXNzdWU1MTMwODQzMTI= | 1,649 | ALBERT | {
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"Merging with #1370 "
] | 1,572 | 1,572 | 1,572 | NONE | null | # 🌟New model addition
## Model description
ALBERT is "A Lite" version of BERT, a popular unsupervised language representation learning algorithm. ALBERT uses parameter-reduction techniques that allow for large-scale configurations, overcome previous memory limitations, and achieve better behavior with respect to... | {
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https://api.github.com/repos/huggingface/transformers/issues/1648 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1648/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1648/comments | https://api.github.com/repos/huggingface/transformers/issues/1648/events | https://github.com/huggingface/transformers/issues/1648 | 513,051,893 | MDU6SXNzdWU1MTMwNTE4OTM= | 1,648 | Changing LM loss function | {
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"This is quite a general question. Perhaps it's more useful to put this on Stack Overflow. ",
"We plan to have a forum associated to the repo to discuss these types of general questions.\r\nIn the meantime, we are still happy to welcome them in the PR but the visibility is limited indeed.",
"This issue has been... | 1,572 | 1,578 | 1,578 | NONE | null | Hi all,
I am modifying gpt2 loss function. My new code looks like that:
lm_logits = self.lm_head(hidden_states)
outputs = (lm_logits,) + transformer_outputs[1:]
if labels is not None:
# Shift so that tokens < n predict n
shift_logits = lm_logits[..., :-1, :]... | {
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https://api.github.com/repos/huggingface/transformers/issues/1647 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1647/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1647/comments | https://api.github.com/repos/huggingface/transformers/issues/1647/events | https://github.com/huggingface/transformers/issues/1647 | 513,041,736 | MDU6SXNzdWU1MTMwNDE3MzY= | 1,647 | distilroberta-base unavailable in pip install transformers | {
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"Yes, we should push a new pip release this coming week. In the meantime please use master."
] | 1,572 | 1,572 | 1,572 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi,
Would you please update the `pip install transformers` with the addition of `distilroberta-base`?
As of 28 Nov 2019, I tried `pip install transformers` or `pip install --upgrade transformers` but the `distilroberta-base` mo... | {
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https://api.github.com/repos/huggingface/transformers/issues/1646 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1646/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1646/comments | https://api.github.com/repos/huggingface/transformers/issues/1646/events | https://github.com/huggingface/transformers/issues/1646 | 513,015,282 | MDU6SXNzdWU1MTMwMTUyODI= | 1,646 | Undefined behavior | {
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"Yes thanks would be happy to welcome a PR.\r\nThanks for ca(t😂)ching that",
"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"
] | 1,572 | 1,578 | 1,578 | NONE | null | ## 🐛 Bug
There is an undefined behavior in `get_from_cache()` method in `transformers/transformers/file_utils.py`:
```python3
if not os.path.exists(cache_path) and etag is None:
matching_files = fnmatch.filter(os.listdir(cache_dir), filename + '.*')
matching_files = list(filter(lambda s: not s.endswith(... | {
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https://api.github.com/repos/huggingface/transformers/issues/1645 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1645/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1645/comments | https://api.github.com/repos/huggingface/transformers/issues/1645/events | https://github.com/huggingface/transformers/issues/1645 | 513,011,014 | MDU6SXNzdWU1MTMwMTEwMTQ= | 1,645 | Error while importing RoBERTa model | {
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"You have opened an issue for the transformers repository but executed code from fairseq. Don't you think you should create an issue there [1]?\r\n\r\n[1] https://github.com/pytorch/fairseq/blob/master/examples/roberta/README.md",
"Right. Sorry! I made a mistake.",
"I have error when i run this code : please ... | 1,572 | 1,671 | 1,572 | NONE | null | I tried to import RoBERTa model.
But running the following snippet:
# Load the model in fairseq
`from fairseq.models.roberta import RobertaModel`
`roberta = RobertaModel.from_pretrained('./roberta.large', checkpoint_file='model.pt')`
`roberta.eval() # disable dropout (or leave in train mode to finetune)`
I go... | {
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"What model are you using?",
"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"
] | 1,572 | 1,578 | 1,578 | NONE | null | I would like to generate a text of about 3000 words.
However the run_generation.py file limits it to 1024, and produces only 1021 words. I have tried changing the internal parameters for the same but in vain. | {
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https://api.github.com/repos/huggingface/transformers/issues/1643 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1643/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1643/comments | https://api.github.com/repos/huggingface/transformers/issues/1643/events | https://github.com/huggingface/transformers/issues/1643 | 512,995,838 | MDU6SXNzdWU1MTI5OTU4Mzg= | 1,643 | how to use 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"
] | 1,572 | 1,577 | 1,577 | NONE | null | Hi
I want to use BertForMaskedLM as a decoder, apparently I need to give ids and then this function generates the ids and computes the loss. could you tell me how the generation with this function work? I see for instance in run_generation.py codes you use neucleus sampling or beam search, I see none of them used her... | {
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https://api.github.com/repos/huggingface/transformers/issues/1642 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1642/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1642/comments | https://api.github.com/repos/huggingface/transformers/issues/1642/events | https://github.com/huggingface/transformers/issues/1642 | 512,960,391 | MDU6SXNzdWU1MTI5NjAzOTE= | 1,642 | How to compute loss with HuggingFace transformers? | {
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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"
] | 1,572 | 1,577 | 1,577 | NONE | null | Hello,
Is it possible to train HuggingFace TransfoXLLMHeadModel on a dataset different than WikiText103, say, on the combined WikiText2 and WikiText103 dataset?
Below are my code:
```js
# Import packages
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import TransfoXL... | {
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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"
] | 1,572 | 1,577 | 1,577 | NONE | null | Hello,
I am trying to use my custom built vocabulary which I defined using Torchtext functions with the HuggingFace TransfoXLLMHeadModel, and I am having some troubles with it.
I defined my text field as below:
```js
# Import packages
import torch
import torch.nn as nn
import torch.nn.functional as F
from ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1640 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1640/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1640/comments | https://api.github.com/repos/huggingface/transformers/issues/1640/events | https://github.com/huggingface/transformers/issues/1640 | 512,932,580 | MDU6SXNzdWU1MTI5MzI1ODA= | 1,640 | Why DistilBertTokenizer and BertTokenizer are creating different number of features?? | {
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I tried working with DistilBertTokenizer and BertTokenizer from transformers. And according to documentation DistilBertTokenizer was identical to the BertTokenizer . But while creating features for a particular Dataset it creates different number of examples. Why? I also tried using distilbert model with BertT... | {
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https://api.github.com/repos/huggingface/transformers/issues/1639 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1639/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1639/comments | https://api.github.com/repos/huggingface/transformers/issues/1639/events | https://github.com/huggingface/transformers/issues/1639 | 512,819,257 | MDU6SXNzdWU1MTI4MTkyNTc= | 1,639 | Add Transformer-XL fine-tuning support. | {
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"We don't have the bandwidth for that at the moment. But if somebody in the community is interested in working on that, happy to welcome a PR.",
"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 contributi... | 1,572 | 1,578 | 1,578 | NONE | null | ## 🚀 Feature
Add Transformer-XL fine-tuning support.
## Motivation
This model archieves good language modeling result while having a "saner" number of parameters compared with GPT-2 or other language modeling.
| {
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https://api.github.com/repos/huggingface/transformers/issues/1638 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1638/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1638/comments | https://api.github.com/repos/huggingface/transformers/issues/1638/events | https://github.com/huggingface/transformers/issues/1638 | 512,792,224 | MDU6SXNzdWU1MTI3OTIyMjQ= | 1,638 | how can I pre-training my own model from the existed model or from scratch | {
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"Hi, you can see how to use the library in the [documentation](https://huggingface.co/transformers/). You might be interested in the library philosophy and the way to load pre-trained models, which is [described here](https://huggingface.co/transformers/quickstart.html). You might also be interested in the [example... | 1,572 | 1,578 | 1,578 | NONE | null | ## ❓ Questions & Help
I want to load the pre-training model like bert offered by google,and train language model on more corpus,how can I do it ?thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/1637 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1637/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1637/comments | https://api.github.com/repos/huggingface/transformers/issues/1637/events | https://github.com/huggingface/transformers/issues/1637 | 512,769,356 | MDU6SXNzdWU1MTI3NjkzNTY= | 1,637 | Installation error :Command "python setup.py egg_info" failed with error code 1 | {
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"@thomwolf Please if you could provide your insights on the issue.\r\n\r\nThanks",
"https://github.com/google/sentencepiece/issues/386"
] | 1,572 | 1,572 | 1,572 | NONE | null | [puttyerrortransformers2.log](https://github.com/huggingface/transformers/files/3774258/puttyerrortransformers2.log)
## 🐛 Bug
Hello Everyone,
I am trying to install transformers using the command:
pip3 install -v --no-binary :all: --prefix=/short/oe7/uk1594 transformers
* Python version: Python 3.6.7
* ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1636 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1636/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1636/comments | https://api.github.com/repos/huggingface/transformers/issues/1636/events | https://github.com/huggingface/transformers/issues/1636 | 512,739,758 | MDU6SXNzdWU1MTI3Mzk3NTg= | 1,636 | AttributeError: 'CTRLTokenizer' object has no attribute 'control_codes' | {
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"I had the same issue. As a temporary workaround you can simply comment out the following lines as long as you remember to use a control token at the beginning of every prompt that you supply to ctrl:\r\nif args.model_type == \"ctrl\":\r\n if not any(context_tokens[0] == x for x in tokenizer.control_code... | 1,572 | 1,573 | 1,572 | NONE | null | ## 🐛 Bug
I can't seem to get ctrl generation working.
This is with a pull of the repo from master, and pip3 install as recommended during installation:
The problem arise when using:
* [ X ] the official example scripts:
```bash
$ uname -a
Linux ctrl 4.9.0-11-amd64 #1 SMP Debian 4.9.189-3+deb9u1 (2019-... | {
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https://api.github.com/repos/huggingface/transformers/issues/1635 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1635/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1635/comments | https://api.github.com/repos/huggingface/transformers/issues/1635/events | https://github.com/huggingface/transformers/issues/1635 | 512,695,142 | MDU6SXNzdWU1MTI2OTUxNDI= | 1,635 | Training DistilBert - RuntimeError: index out of range at /pytorch/aten/src/TH/generic/THTensorEvenMoreMath.cpp:237 | {
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"I re-downloaded PyTorch 1.2.0 and the problem was fixed for some reason..."
] | 1,572 | 1,585 | 1,572 | NONE | null | ## 🐛 Bug
Hello,
<!-- Important information -->
Model I am using (Bert, XLNet....): DistilBert
Language I am using the model on (English, Chinese....): French
The problem arise when using:
* [ ] the official example scripts: examples/distillation/train.py
The tasks I am working on is:
* [ ] the offi... | {
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https://api.github.com/repos/huggingface/transformers/issues/1634 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1634/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1634/comments | https://api.github.com/repos/huggingface/transformers/issues/1634/events | https://github.com/huggingface/transformers/issues/1634 | 512,533,012 | MDU6SXNzdWU1MTI1MzMwMTI= | 1,634 | How to initialize AdamW optimizer in HuggingFace transformers? | {
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"I had the same issue, apparently it should be model.params()",
"Thank you! This is helpful",
"You have to tell the optimizer which parameters it should optimize. Theoretically you could use multiple optimizers for different parameters. This is useful if you want to use different learning rates or different wei... | 1,572 | 1,581 | 1,572 | NONE | null | Hello,
I am new to Python and NLP and so I have some questions that may sound a bit funny to the experts.
I had been trying to set my optimizer by setting
`optimizer = AdamW()`
but of course it failed, because I did not specify the required parameter `'param'` (for lr, betas, eps, weight_decay, and correct_bias... | {
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https://api.github.com/repos/huggingface/transformers/issues/1633 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1633/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1633/comments | https://api.github.com/repos/huggingface/transformers/issues/1633/events | https://github.com/huggingface/transformers/pull/1633 | 512,436,897 | MDExOlB1bGxSZXF1ZXN0MzMyNDQ3Mzg4 | 1,633 | Fix for mlm evaluation in run_lm_finetuning.py | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1633?src=pr&el=h1) Report\n> Merging [#1633](https://codecov.io/gh/huggingface/transformers/pull/1633?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ae1d03fc51bb22ed59517ee6f92c560417fdb049?src=pr&el=desc) will **n... | 1,571 | 1,572 | 1,572 | CONTRIBUTOR | null | No masking is done in the original evaluation code, so the resulting perplexity is always something like 1.0. In this PR a simple fix is proposed, using just the same masked scheme as in a training code. | {
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https://api.github.com/repos/huggingface/transformers/issues/1632 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1632/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1632/comments | https://api.github.com/repos/huggingface/transformers/issues/1632/events | https://github.com/huggingface/transformers/issues/1632 | 512,426,848 | MDU6SXNzdWU1MTI0MjY4NDg= | 1,632 | Loading from ckpt is not possible for bert, neither tf to pytorch conversion works in 2.1.1 | {
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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"
] | 1,571 | 1,577 | 1,577 | NONE | null | ## 🐛 Bug
<!-- Important information -->
- I am trying to load a BERT model (for simplicity assume the original uncased-base from google's repo) using instructions in: https://github.com/huggingface/transformers/blob/ae1d03fc51bb22ed59517ee6f92c560417fdb049/transformers/modeling_tf_utils.py#L195
and more specifica... | {
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https://api.github.com/repos/huggingface/transformers/issues/1631 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1631/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1631/comments | https://api.github.com/repos/huggingface/transformers/issues/1631/events | https://github.com/huggingface/transformers/issues/1631 | 512,395,669 | MDU6SXNzdWU1MTIzOTU2Njk= | 1,631 | cannot import name 'RobertaForTokenClassification' | {
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"+ other bug\r\n - with '--evaluate_during_training'\r\n```\r\nFile \"/path-to/run_ner.py\", line 167, in train\r\n results, _ = evaluate(args, model, tokenizer, labels, pad_token_label_id)\r\nTypeError: evaluate() missing 1 required positional argument: 'mode'\r\n```",
"- update\r\n - using `pip3 install gi... | 1,571 | 1,643 | 1,578 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): BERT
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [x] the official example scripts: (give details) examples/run_ner.py
* [ ] my own modified scripts: (give details)
The tasks... | {
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https://api.github.com/repos/huggingface/transformers/issues/1630 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1630/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1630/comments | https://api.github.com/repos/huggingface/transformers/issues/1630/events | https://github.com/huggingface/transformers/pull/1630 | 512,346,876 | MDExOlB1bGxSZXF1ZXN0MzMyMzc0OTQ1 | 1,630 | rename _has_sklearn to _sklearn_available | {
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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"
] | 1,571 | 1,577 | 1,577 | NONE | null | Rename `_has_sklearn` to `_sklearn_available`, because variables that act like `_has_sklearn` in `transformers/file_utils.py` are named like `_{module}_available` | {
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https://api.github.com/repos/huggingface/transformers/issues/1629 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1629/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1629/comments | https://api.github.com/repos/huggingface/transformers/issues/1629/events | https://github.com/huggingface/transformers/issues/1629 | 512,342,672 | MDU6SXNzdWU1MTIzNDI2NzI= | 1,629 | Perm Mask in XLNet | {
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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"
] | 1,571 | 1,577 | 1,577 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
"Mask to indicate the attention pattern for each input token with values selected in [0, 1]: **If perm_mask[k, i, j] = 0, i attend to j in batch k; if perm_mask[k, i, j] = 1**, i does not attend to j in batch k. If None, each token atte... | {
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https://api.github.com/repos/huggingface/transformers/issues/1628 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1628/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1628/comments | https://api.github.com/repos/huggingface/transformers/issues/1628/events | https://github.com/huggingface/transformers/pull/1628 | 512,196,872 | MDExOlB1bGxSZXF1ZXN0MzMyMjU1Mjk1 | 1,628 | run_tf_glue works with all tasks | {
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Updated the script so that all tasks are now available, with regression tasks (STS-B) as well as all classification tasks.
Should update the import into PyTorch that currently tests if tw... | {
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https://api.github.com/repos/huggingface/transformers/issues/1627 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1627/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1627/comments | https://api.github.com/repos/huggingface/transformers/issues/1627/events | https://github.com/huggingface/transformers/issues/1627 | 512,187,827 | MDU6SXNzdWU1MTIxODc4Mjc= | 1,627 | Loading pretrained RobertaForSequenceClassification fails, size missmatch error | {
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"Hi! You're initializing RoBERTa with a blank configuration, which results in a very BERT-like configuration. BERT has different attributes than RoBERTa (different vocabulary size, positional embeddings size etc) so this indeed results in an error.\r\n\r\nTo instantiate RoBERTa you can simply do:\r\n\r\n```py\r\nmo... | 1,571 | 1,580 | 1,571 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using `RobertaForSequenceClassification` and when I tried to load `'roberta-base'` model using this code on Google Colab:
```from transformers import RobertaForSequenceClassification, RobertaConfig
config = RobertaConfig()
model = RobertaForSequenceClassifi... | {
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https://api.github.com/repos/huggingface/transformers/issues/1626 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1626/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1626/comments | https://api.github.com/repos/huggingface/transformers/issues/1626/events | https://github.com/huggingface/transformers/issues/1626 | 512,089,028 | MDU6SXNzdWU1MTIwODkwMjg= | 1,626 | What is currently the best way to add a custom dictionary to a neural machine translator that uses the transformer architecture? | {
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"This question is too general for this repo. It's not specific to anything this repository offers. Perhaps it's better to ask this on one of the Stack Exchange sites. ",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Than... | 1,571 | 1,578 | 1,578 | NONE | null | ## ❓ Questions & Help
It's common to add a custom dictionary to a machine translator to ensure that terminology from a specific domain is correctly translated. For example, the term server should be translated differently when the document is about data centers, vs when the document is about restaurants.
With a t... | {
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https://api.github.com/repos/huggingface/transformers/issues/1625 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1625/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1625/comments | https://api.github.com/repos/huggingface/transformers/issues/1625/events | https://github.com/huggingface/transformers/pull/1625 | 512,084,518 | MDExOlB1bGxSZXF1ZXN0MzMyMTYyOTE4 | 1,625 | Update run_ner.py example with RoBERTa | {
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"Only issue I saw when running the prediction for RoBERTa, I noticed some `Maximum sequence length exceeded` warnings.",
"That's awesome! We can merge as soon as tests pass, unless you plan on pushing something else before.\r\n\r\nFor reference, do you think you could add Eval results for `bert-base-cased` too?",... | 1,571 | 1,571 | 1,571 | CONTRIBUTOR | null | PR for #1534
The `run_ner.py` script in the examples directory only used BERT based models. The main objective was to utilize the new DistilRoBERTa model for NER as it is cased by default, potentially leading to better results (at least for the English language). This PR is based on #1613, I will rebase after it is ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1624 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1624/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1624/comments | https://api.github.com/repos/huggingface/transformers/issues/1624/events | https://github.com/huggingface/transformers/pull/1624 | 512,018,137 | MDExOlB1bGxSZXF1ZXN0MzMyMTA4Nzk1 | 1,624 | Add support for resumable downloads for HTTP protocol. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1624?src=pr&el=h1) Report\n> Merging [#1624](https://codecov.io/gh/huggingface/transformers/pull/1624?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/10bd1ddb39235b2f58594e48867595e7d38cd619?src=pr&el=desc) will **i... | 1,571 | 1,574 | 1,574 | CONTRIBUTOR | null | Hi. This PR adds support for resumable downloads for HTTP protocol (`resume_download` flag, disabled by default). It solved my problems with unreliable network connection and may also prevent issues like
* https://github.com/huggingface/transformers/issues/985
* https://github.com/huggingface/transformers/issues/1... | {
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https://api.github.com/repos/huggingface/transformers/issues/1623 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1623/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1623/comments | https://api.github.com/repos/huggingface/transformers/issues/1623/events | https://github.com/huggingface/transformers/issues/1623 | 511,978,600 | MDU6SXNzdWU1MTE5Nzg2MDA= | 1,623 | --cache_dir argument in run_lm_finetuning.py not used at all | {
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<!-- Important information -->
Model I am using (Bert, XLNet....): GPT-2
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [ ] the official example scripts: run_lm_finetuning.py
The tasks I am working on is:
* [ ] my own task or dataset: Language... | {
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https://api.github.com/repos/huggingface/transformers/issues/1622 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1622/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1622/comments | https://api.github.com/repos/huggingface/transformers/issues/1622/events | https://github.com/huggingface/transformers/issues/1622 | 511,950,866 | MDU6SXNzdWU1MTE5NTA4NjY= | 1,622 | Fine-tuning BERT using Next sentence prediction loss | {
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"We do not have any scripts that display how to do next sentence prediction as it was shown with RoBERTa to be of little importance during training.\r\n\r\nWe had some scripts until version 1.1.0 that allowed this, you can find them [here](https://github.com/huggingface/transformers/tree/1.1.0/examples/lm_finetunin... | 1,571 | 1,571 | 1,571 | NONE | null | In `pytorch_pretrained_bert`, there is an example for fine-tuning BERT using next sentence prediction loss. In the new version, how shall we fine-tune BERT on the next sentence prediction task?
Thank you. | {
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https://api.github.com/repos/huggingface/transformers/issues/1621 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1621/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1621/comments | https://api.github.com/repos/huggingface/transformers/issues/1621/events | https://github.com/huggingface/transformers/issues/1621 | 511,914,482 | MDU6SXNzdWU1MTE5MTQ0ODI= | 1,621 | tokenization slow | {
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"Hi, with the current implementation of the `run_lm_finetuning.py` file there is no way to speed up the tokenization. It is an example to showcase how to use the library and is therefore not completely optimized especially concerning the data pre-processing.\r\n\r\nYou could modify the script a bit to setup multipr... | 1,571 | 1,603 | 1,578 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Hi,
I want to fine-tune the gpt2 model with a very large corpus (~9GB text data)
However, the tokenization of run_lm_finetuning.py takes forever (what is not surprising with a 9GB text file)
My question is: is there any way to speed ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1620 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1620/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1620/comments | https://api.github.com/repos/huggingface/transformers/issues/1620/events | https://github.com/huggingface/transformers/issues/1620 | 511,903,449 | MDU6SXNzdWU1MTE5MDM0NDk= | 1,620 | 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte | {
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"Hi, could you provide more information: **e.g. respect the template**? Please tell us which model, which bin file, with which command?",
"> Hi, could you provide more information: **e.g. respect the template**? Please tell us which model, which bin file, with which command?\r\n\r\ntokenizer = BertTokenizer.from_... | 1,571 | 1,598 | 1,571 | NONE | null | When I load the pretrained model from the local bin file, there is a decoding problem. | {
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https://api.github.com/repos/huggingface/transformers/issues/1619 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1619/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1619/comments | https://api.github.com/repos/huggingface/transformers/issues/1619/events | https://github.com/huggingface/transformers/issues/1619 | 511,825,182 | MDU6SXNzdWU1MTE4MjUxODI= | 1,619 | AttributeError: 'BertForPreTraining' object has no attribute 'classifier' | {
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"Hi! Are your fine-tuned models in the format of the original BERT, or were they fine-tuned using our library?",
"@LysandreJik It is fine tuned in the format of the original BERT.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activi... | 1,571 | 1,585 | 1,577 | NONE | null | I was trying to convert my fine tuned model to pytorch using the following command.
`
tf_checkpoint_path='models/model.ckpt-21'
bert_config_file='PRETRAINED_MODELS/uncased_L-12_H-768_A-12/bert_config.json'
pytorch_dump_path='pytorch_models/pytorch_model.bin'
python convert_bert_original_tf_checkpoint_to_pytorc... | {
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https://api.github.com/repos/huggingface/transformers/issues/1618 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1618/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1618/comments | https://api.github.com/repos/huggingface/transformers/issues/1618/events | https://github.com/huggingface/transformers/issues/1618 | 511,820,415 | MDU6SXNzdWU1MTE4MjA0MTU= | 1,618 | Format problem when training DistilBert | {
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"Hi, I believe that `torch.bool` was introduced in PyTorch 1.2.0. Do you think you could try to upgrade it to 1.2.0 to try out the distillation scripts?",
"Problem fixed, the problem was the PyTorch version as you said, thank you so much! :)"
] | 1,571 | 1,572 | 1,572 | NONE | null | ## Format problem when training DistilBert
Hello,
I'm trying to train DistilBert from scratch on French language with the official "trainin with distillation task" script.
## To Reproduce
Steps to reproduce the behavior:
The problem arise when I invoke the script :
https://github.com/huggingface/transfor... | {
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https://api.github.com/repos/huggingface/transformers/issues/1617 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1617/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1617/comments | https://api.github.com/repos/huggingface/transformers/issues/1617/events | https://github.com/huggingface/transformers/issues/1617 | 511,820,362 | MDU6SXNzdWU1MTE4MjAzNjI= | 1,617 | Add T5 model | {
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"+1, it is a very impressive work",
"https://github.com/google-research/text-to-text-transfer-transformer\r\n\r\nHowever i would prefer seeing Albert implemented before T5.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occur... | 1,571 | 1,581 | 1,578 | CONTRIBUTOR | null | # 🌟New model addition
## Model description
Google released paper + code + dataset + pre-trained model about their new **T5**, beating state-of-the-art in 17/24 tasks.
[Paper link](https://arxiv.org/pdf/1910.10683.pdf)
## Open Source status
* [x] the model implementation and weights are available: [Offic... | {
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https://api.github.com/repos/huggingface/transformers/issues/1616 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1616/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1616/comments | https://api.github.com/repos/huggingface/transformers/issues/1616/events | https://github.com/huggingface/transformers/issues/1616 | 511,815,033 | MDU6SXNzdWU1MTE4MTUwMzM= | 1,616 | run_generation.py example for a batch | {
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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"
] | 1,571 | 1,577 | 1,577 | NONE | null | Hi
I want to use example/run_generation.py to enter a batch of sentences and get a batch of generated outputs. could you please assist me and provide me with the commands how I can do it, is this possible with this code, if not I really appreciate adding this feature. thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/1615 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1615/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1615/comments | https://api.github.com/repos/huggingface/transformers/issues/1615/events | https://github.com/huggingface/transformers/issues/1615 | 511,812,872 | MDU6SXNzdWU1MTE4MTI4NzI= | 1,615 | CUDA error: device-side assert triggered(pretrained_model.cuda()) | {
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"Hello! Is your checkpoint the original one from the XLNet repository or one of our TensorFlow checkpoints hosted on S3?",
"> Hello! Is your checkpoint the original one from the XLNet repository or one of our TensorFlow checkpoints hosted on S3?\r\n\r\nThe checkpoint is from the XLNet repository.",
"Could you t... | 1,571 | 1,578 | 1,571 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (XLNet....):
Language I am using the model on (English):
The problem arise when using:
config = XLNetConfig.from_json_file('/data2/liping/xlnet/xlnet_cased_L-12_H-768_A-12/xlnet_config.json')
encoder_model = XLNetModel.from_pretrained("/data2/l... | {
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https://api.github.com/repos/huggingface/transformers/issues/1614 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1614/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1614/comments | https://api.github.com/repos/huggingface/transformers/issues/1614/events | https://github.com/huggingface/transformers/issues/1614 | 511,745,465 | MDU6SXNzdWU1MTE3NDU0NjU= | 1,614 | Slight different output between transformers and pytorch-transformers | {
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"Maybe you didn't put the model in evaluation mode in one of the tests and the DropOut modules were not deactivated as such.",
"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"
] | 1,571 | 1,578 | 1,578 | NONE | null | I am now working on a Chinese NER tagging task. I applied BertForTokenClassification. The original library I used is pytorch-transformers 1.2.0. Then I migrated to Tranformers 2.1.1. But I found the output is slightly different between two versions. See the pics below
![Screen Shot 2019-10-24 at 14 46 00](https://us... | {
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https://api.github.com/repos/huggingface/transformers/issues/1613 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1613/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1613/comments | https://api.github.com/repos/huggingface/transformers/issues/1613/events | https://github.com/huggingface/transformers/pull/1613 | 511,710,395 | MDExOlB1bGxSZXF1ZXN0MzMxODU4MDAy | 1,613 | Roberta token classification | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/1613?src=pr&el=h1) Report\n> Merging [#1613](https://codecov.io/gh/huggingface/transformers/pull/1613?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5b6cafb11b39e78724dc13b57b81bd73c9a66b49?src=pr&el=desc) will **d... | 1,571 | 1,571 | 1,571 | CONTRIBUTOR | null | Roberta is missing the token classification that is already available in the BERT models. Per discussion in #1166 they mention it should be more or less a copy paste of the current `BertForTokenClassification` and `TFBertForTokenClassification `. I noticed this is also missing as I hope to update the `run_ner.py` file ... | {
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https://api.github.com/repos/huggingface/transformers/issues/1612 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/1612/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/1612/comments | https://api.github.com/repos/huggingface/transformers/issues/1612/events | https://github.com/huggingface/transformers/pull/1612 | 511,676,044 | MDExOlB1bGxSZXF1ZXN0MzMxODI5NzU1 | 1,612 | add model & config address in appendix, and add link to appendix.md i… | {
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"I don't think we want to commit to maintaining an exhaustive, centralized list of models in the future.\r\n\r\nWill close this unless further comments"
] | 1,571 | 1,572 | 1,572 | NONE | null | Support certain model & config download address in appendix. | {
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I want to get the probability of a word which fits the masked place.
```
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertForMaskedLM.from_pretrained('bert-base-uncased')
model.eval()
text = '[CLS] I want to [MASK] the car because it is cheap . [SEP]'
tokenized... | {
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