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https://api.github.com/repos/huggingface/transformers/issues/2312 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2312/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2312/comments | https://api.github.com/repos/huggingface/transformers/issues/2312/events | https://github.com/huggingface/transformers/pull/2312 | 542,364,419 | MDExOlB1bGxSZXF1ZXN0MzU2ODIyMDEw | 2,312 | Correct tokenization for special and added tokens | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2312?src=pr&el=h1) Report\n> Merging [#2312](https://codecov.io/gh/huggingface/transformers/pull/2312?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cea04a244351a7c5bce44e1cfc01abde0ceb60fd?src=pr&el=desc) will **i... | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | When a tokenizer is being loaded with `PreTrainedTokenizer._from_pretrained`, it should set `added_tokens` and `all_special_tokens` to `unique_added_tokens_encoder`.
If we don't do it, it will corrupt the tokenization.
Example:
```
import transformers
tokenizer = transformers.BertTokenizer.from_pretrained("ber... | {
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https://api.github.com/repos/huggingface/transformers/issues/2311 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2311/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2311/comments | https://api.github.com/repos/huggingface/transformers/issues/2311/events | https://github.com/huggingface/transformers/issues/2311 | 542,342,605 | MDU6SXNzdWU1NDIzNDI2MDU= | 2,311 | Can I use BERT / gpt-2 for text generation | {
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"You could do something like this when using gpt2\r\n\r\n```\r\nfrom transformers import GPT2LMHeadModel, GPT2Tokenizer\r\nfrom torch.nn import functional as F\r\nimport torch\r\n\r\nmodel = GPT2LMHeadModel.from_pretrained('gpt2-medium')\r\ntokenizer = GPT2Tokenizer.from_pretrained('gpt2-medium')\r\n\r\n# encode in... | 1,577 | 1,589 | 1,583 | NONE | null | ## ❓ Questions & Help
I want to get a list of possible completions and their probabilities.
For example,
For the sentence "I put the glass of the _"
I want to get a vector with word and probabilities from a pre-trained model, such as :
desk = 0.1
table = 0.2
car = 0.05
shirt = 0.001
Is that possible? | {
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https://api.github.com/repos/huggingface/transformers/issues/2310 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2310/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2310/comments | https://api.github.com/repos/huggingface/transformers/issues/2310/events | https://github.com/huggingface/transformers/pull/2310 | 542,268,571 | MDExOlB1bGxSZXF1ZXN0MzU2NzQ1MTIz | 2,310 | revert erroneous fix #2276 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2310?src=pr&el=h1) Report\n> Merging [#2310](https://codecov.io/gh/huggingface/transformers/pull/2310?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/81db12c3ba0c2067f43c4a63edf5e45f54161042?src=pr&el=desc) will **n... | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | I based #2276 on having an error pop up on an older pytorch version, and also on the erroneous (current!) documentation for pytorch.Tensor.scatter():
> `scatter(dim, index, source)` → Tensor
>
> Out-of-place version of torch.Tensor.scatter_()
>
> `scatter_(dim, index, src)` → Tensor
> ...
The argument ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2309 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2309/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2309/comments | https://api.github.com/repos/huggingface/transformers/issues/2309/events | https://github.com/huggingface/transformers/issues/2309 | 542,253,499 | MDU6SXNzdWU1NDIyNTM0OTk= | 2,309 | Bug: Tokenization of Special Tokens | {
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The commit https://github.com/huggingface/transformers/commit/deceb001616995199a6a5dca866ffec95c3ebe74 introduces a bug in the tokenization of special tokens when using `from_pretrained` to initialize the tokenizer.
```
from transformers import AutoTokenizer
bert_tokenizer = AutoTokenizer.from_pretr... | {
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https://api.github.com/repos/huggingface/transformers/issues/2308 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2308/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2308/comments | https://api.github.com/repos/huggingface/transformers/issues/2308/events | https://github.com/huggingface/transformers/issues/2308 | 542,242,412 | MDU6SXNzdWU1NDIyNDI0MTI= | 2,308 | pytorch_pretrained_bert giving different scores for BertForNextSentencePrediction | {
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from pytorch_transformers.modeling_bert import BertForNextSentencePrediction
from pytorch_transformers import BertTokenizer, BertConfig
import torch
#Load pretrained model from local
config = BertConfig.from_json_file('resources/bert_config.json')
token = BertTokenizer('resources/vocab.txt... | {
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https://api.github.com/repos/huggingface/transformers/issues/2307 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2307/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2307/comments | https://api.github.com/repos/huggingface/transformers/issues/2307/events | https://github.com/huggingface/transformers/issues/2307 | 542,228,368 | MDU6SXNzdWU1NDIyMjgzNjg= | 2,307 | What's the exact name of BERT large in results ( GermEval 2014)? | {
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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"
] | 1,577 | 1,583 | 1,583 | NONE | null | ## ❓ Questions & Help
I use BERT large cased model downloaded by run_ner.py script. But I can't get the result in the table below.
<!-- A clear and concise description of the question. -->
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https://api.github.com/repos/huggingface/transformers/issues/2306 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2306/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2306/comments | https://api.github.com/repos/huggingface/transformers/issues/2306/events | https://github.com/huggingface/transformers/issues/2306 | 542,226,506 | MDU6SXNzdWU1NDIyMjY1MDY= | 2,306 | Non-Deterministic Behavior in BertTokenizer | {
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"As an update I've been able to reproduce this problem using a python script",
"I cannot reproduce this on Windows, PT1.4, latest transformers master.",
"I think I was using an old version of transformers :( \r\n\r\nThis seems to have been fixed in v2.2.2 - After upgrading to latest I haven't observed this anym... | 1,577 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): BertTokenizer only
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [ ] the official example scripts: (give details)
* [X] my own modified scripts: Jupyter Notebook
The tasks I am worki... | {
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https://api.github.com/repos/huggingface/transformers/issues/2305 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2305/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2305/comments | https://api.github.com/repos/huggingface/transformers/issues/2305/events | https://github.com/huggingface/transformers/issues/2305 | 542,225,339 | MDU6SXNzdWU1NDIyMjUzMzk= | 2,305 | [CLS] token / is used as the aggregate sequence representation for classification tasks | {
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"[CLS], [SEP] are \"special token\" of bert. Its included in the vocabulary of size 30522. Its starts with like 101, 103 something.",
"of course these two tokens are special tokens. \r\n\r\n **is used as the aggregate sequence representation for classification tasks.**\r\n\r\nin which way does happen this agg... | 1,577 | 1,583 | 1,583 | NONE | null | [CLS] is fed into an output layer for classification. How will be built this token. Is there something special done for it during training? in which way does happen this aggregations of sequences?
Thanks for response | {
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https://api.github.com/repos/huggingface/transformers/issues/2304 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2304/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2304/comments | https://api.github.com/repos/huggingface/transformers/issues/2304/events | https://github.com/huggingface/transformers/issues/2304 | 542,216,248 | MDU6SXNzdWU1NDIyMTYyNDg= | 2,304 | Why are you getting just the last encoder states in the summarization code? | {
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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"
] | 1,577 | 1,583 | 1,583 | CONTRIBUTOR | null | The line is here:
https://github.com/huggingface/transformers/blob/v2.3.0/examples/summarization/modeling_bertabs.py#L142
By changing the line to `encoder_hidden_states = encoder_output` I was able to fine-tune the model successfully, as well as, run the inference code from the `run_summarization.py` script.
S... | {
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https://api.github.com/repos/huggingface/transformers/issues/2303 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2303/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2303/comments | https://api.github.com/repos/huggingface/transformers/issues/2303/events | https://github.com/huggingface/transformers/pull/2303 | 542,169,501 | MDExOlB1bGxSZXF1ZXN0MzU2NjY4ODUw | 2,303 | fix repetition penalty error in modeling_utils.py | {
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https://api.github.com/repos/huggingface/transformers/issues/2302 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2302/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2302/comments | https://api.github.com/repos/huggingface/transformers/issues/2302/events | https://github.com/huggingface/transformers/issues/2302 | 542,169,302 | MDU6SXNzdWU1NDIxNjkzMDI= | 2,302 | Repetition penalty work falsely in case the logit of the token is negativ | {
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"Propsed fix in PR #2303 "
] | 1,577 | 1,577 | 1,577 | MEMBER | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (LMHeadModels; distilgpt2 in this example but holds true for all LMHeadModels):
Language I am using the model on 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/2301 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2301/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2301/comments | https://api.github.com/repos/huggingface/transformers/issues/2301/events | https://github.com/huggingface/transformers/issues/2301 | 542,129,271 | MDU6SXNzdWU1NDIxMjkyNzE= | 2,301 | Can I use run_lm_finetuning.py for training models in an uncovered language? | {
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"You can now leave `--model_name_or_path` to None in `run_language_modeling.py` to train a model from scratch.\r\n\r\nSee also https://huggingface.co/blog/how-to-train"
] | 1,577 | 1,581 | 1,581 | NONE | null | Is it possibile to use run_lm_finetuning.py script to train one of the models from scratch in a language not covered by the available pretrained models? (like spanish, italian, german).
My idea is to replicate something like camemBERT for a language different from french, given that I have the corpora needed for the... | {
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https://api.github.com/repos/huggingface/transformers/issues/2300 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2300/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2300/comments | https://api.github.com/repos/huggingface/transformers/issues/2300/events | https://github.com/huggingface/transformers/issues/2300 | 542,114,005 | MDU6SXNzdWU1NDIxMTQwMDU= | 2,300 | run_ner.py RobertaForTokenClassification.from_pretrained "size mismatch for classifier.bias" | {
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I have a trouble on run_ner.py([https://github.com/huggingface/transformers/blob/master/examples/run_ner.py](url)) evaluation using **Roberta**. My error is in this snippet:
```python
# Load pretrained model and tokenizer
if args.local_rank not in [-1, 0]:
torch.distributed.... | {
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https://api.github.com/repos/huggingface/transformers/issues/2299 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2299/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2299/comments | https://api.github.com/repos/huggingface/transformers/issues/2299/events | https://github.com/huggingface/transformers/issues/2299 | 542,052,247 | MDU6SXNzdWU1NDIwNTIyNDc= | 2,299 | Model2Model inference | {
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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"
] | 1,577 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
I am trying to implement a simple Model2Model question-answer task, where the input is question and the answer needs to be generated. At inference time I feed in the "[CLS]" token to let it generate but it only generates a single token instead of the entire sentence. The ppl at which I do the inf... | {
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https://api.github.com/repos/huggingface/transformers/issues/2298 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2298/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2298/comments | https://api.github.com/repos/huggingface/transformers/issues/2298/events | https://github.com/huggingface/transformers/issues/2298 | 542,043,285 | MDU6SXNzdWU1NDIwNDMyODU= | 2,298 | Why cosine similarity of BERT, ALBERT, Robert is so big, almost near 1.0? | {
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"BERT was not designed to produce useful word / sentence embeddings that can be used with cosine similarities. Cosine-similarity treats all dimensions equally which puts high requirements for the created embeddings.\r\n\r\nBERT as not intended for this. See this post by Jacob Devlin:\r\nhttps://github.com/UKPLab/se... | 1,577 | 1,583 | 1,583 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I tried to use bert models to do similarity comparison of words/sentences, but I found that the cosine similarities are all very high, even for very different words/sentences in meaning. Why?
Does all the vector are located in a smal... | {
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https://api.github.com/repos/huggingface/transformers/issues/2297 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2297/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2297/comments | https://api.github.com/repos/huggingface/transformers/issues/2297/events | https://github.com/huggingface/transformers/issues/2297 | 542,033,367 | MDU6SXNzdWU1NDIwMzMzNjc= | 2,297 | RunTimeError in "run_summarization": expected device cuda:0 and dtype byte but got device cuda: 0 and dtype Bool | {
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"Someone suggested to use Pytorch v1.1.0 instead of 1.2.0. But not sure if it is ok. ",
"it's a version inconsistent issue. \r\nin ver 1.1.0, torch.gt outputs:\r\ntorch.gt(torch.tensor([[1, 2], [3, 4]]), torch.tensor([[1, 1], [4, 4]]))\r\ntensor([[ 0, 1],\r\n [ 0, 0]], dtype=torch.uint8)\r\nwhile in ver ... | 1,577 | 1,577 | 1,577 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
bertabs-finetuned-cnndm-extractive-abstractive-summarization-pytorch_model
Language I am using the model on (, Chinese....):
English
The problem arise when using:
* [ ] the official example scripts: (give details) run_summariza... | {
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https://api.github.com/repos/huggingface/transformers/issues/2296 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2296/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2296/comments | https://api.github.com/repos/huggingface/transformers/issues/2296/events | https://github.com/huggingface/transformers/issues/2296 | 541,974,120 | MDU6SXNzdWU1NDE5NzQxMjA= | 2,296 | A question about BERT position embedding. | {
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"The sentence \"Today is a nice day\" will already be padded to 512 because of the tokenization process, so the input will remain 512 in the embedding layer",
"> The sentence \"Today is a nice day\" will already be padded to 512 because of the tokenization process, so the input will remain 512 in the embedding la... | 1,577 | 1,577 | 1,577 | NONE | null | ## ❓ Questions & Help
I noticed that in Transformers, it turn position_ids into position_embedding through `nn.Embedding(config.max_position_embeddings, config.hidden_size)`
Here `config.max_position_embeddings` is 512 ,and `config.hidden_size` is 768.
So, when I input a sentence shorter than 512 ,such as "Tod... | {
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https://api.github.com/repos/huggingface/transformers/issues/2295 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2295/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2295/comments | https://api.github.com/repos/huggingface/transformers/issues/2295/events | https://github.com/huggingface/transformers/issues/2295 | 541,958,983 | MDU6SXNzdWU1NDE5NTg5ODM= | 2,295 | How do you handle large documents? | {
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"apparently the answer may be to feed smaller sequences of tokens and use the past input keyword itn pytorch models or hidden states in tensorflow. models both this past input and the stateful nature of models aren't documented. it would be interesting to have methods to manage big inputs",
"Recent models like... | 1,577 | 1,645 | 1,584 | NONE | null | ## ❓ Questions & Help
I have been a huge fan of this library for a while now. I've used it to accomplish things like sentence classification, a chat bot, and even stock market price prediction, this is truly a fantastic library. But I have not yet learned how to tackle large documents (e.g. documents 10x the size of... | {
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https://api.github.com/repos/huggingface/transformers/issues/2294 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2294/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2294/comments | https://api.github.com/repos/huggingface/transformers/issues/2294/events | https://github.com/huggingface/transformers/issues/2294 | 541,956,928 | MDU6SXNzdWU1NDE5NTY5Mjg= | 2,294 | Is there any efficient way to convert BERT outputs to fit token-level tasks? | {
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"i am also curious about it. ;;\r\nhttps://github.com/dsindex/etagger/blob/master/feed.py\r\nthis is not efficient way. just pooling.",
"> i am also curious about it. ;;\r\n> https://github.com/dsindex/etagger/blob/master/feed.py\r\n> this is not efficient way. just pooling.\r\n\r\nHi, I think I get the solution.... | 1,577 | 1,577 | 1,577 | NONE | null | Say I have a sentence consisting of two words: S = [“Definitely”, “not”], and what I want is to transfer S into an embedding matrix T with a size of (2, 100), where each row represents a word.
I want to adopt BERT embeddings. But in BERT, each word is represented as a sub-word unit. This means that S will be represe... | {
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https://api.github.com/repos/huggingface/transformers/issues/2293 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2293/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2293/comments | https://api.github.com/repos/huggingface/transformers/issues/2293/events | https://github.com/huggingface/transformers/issues/2293 | 541,935,686 | MDU6SXNzdWU1NDE5MzU2ODY= | 2,293 | Train custom NER model with new Pipeline | {
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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"
] | 1,577 | 1,584 | 1,584 | NONE | null | ## 🚀 Feature
New `Pipelines` feature is great! I am wondering whether it will be possible to implement a pre-training on domain specific data (similar to ULMFiT approach, unsupervised encoder-decoder) and then train a custom NER model with annotated data (similar to spaCy)? | {
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https://api.github.com/repos/huggingface/transformers/issues/2292 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2292/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2292/comments | https://api.github.com/repos/huggingface/transformers/issues/2292/events | https://github.com/huggingface/transformers/pull/2292 | 541,918,709 | MDExOlB1bGxSZXF1ZXN0MzU2NDY0NTc4 | 2,292 | Add cached past for language generation | {
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"That a great idea, @patrickvonplaten \r\n\r\nI'll let you finish this PR when you have time and ping me for review or questions.",
"True, I will implement this tomorrow!",
"tested for transfo_xl, gpt2, openai-gpt and xlnet in combination with PR #2289 ",
"This looks great!\r\nTo pass the code quality test, y... | 1,577 | 1,577 | 1,577 | MEMBER | null | add past input for gpt2 and ctrl for faster decoding for language generation.
1. add `prepare_inputs_for_generation` fn for gpt2 and ctrl
2. add private `_do_output_past` fn for PretrainModel class to check whether model outputs past key-value states
- fn only covers cases for gpt2 and ctrl for the moment ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2291 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2291/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2291/comments | https://api.github.com/repos/huggingface/transformers/issues/2291/events | https://github.com/huggingface/transformers/pull/2291 | 541,912,412 | MDExOlB1bGxSZXF1ZXN0MzU2NDU5NDgz | 2,291 | Fix F841 flake8 warning | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2291?src=pr&el=h1) Report\n> Merging [#2291](https://codecov.io/gh/huggingface/transformers/pull/2291?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/072750f4dc4f586cb53f0face4b4a448bb0cdcac?src=pr&el=desc) will **d... | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | This PR completes the "fix all flake8 warnings" effort of the last few days.
There's a lot of judgment in the fixes here: when the result of an expression is assigned to a variable that isn't used:
- if the expression has no side effect, then it can safely be removed
- if the expression has side effects, then it... | {
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https://api.github.com/repos/huggingface/transformers/issues/2290 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2290/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2290/comments | https://api.github.com/repos/huggingface/transformers/issues/2290/events | https://github.com/huggingface/transformers/pull/2290 | 541,899,530 | MDExOlB1bGxSZXF1ZXN0MzU2NDQ4ODg3 | 2,290 | duplicated line for repeating_words_penalty_for_language_generation | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2290?src=pr&el=h1) Report\n> Merging [#2290](https://codecov.io/gh/huggingface/transformers/pull/2290?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/aeef4823ab6099249679756182700e6800024c36?src=pr&el=desc) will **d... | 1,577 | 1,577 | 1,577 | MEMBER | null | length_penalty has a duplicated wrong documentation for language generation -> delete two lines | {
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https://api.github.com/repos/huggingface/transformers/issues/2289 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2289/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2289/comments | https://api.github.com/repos/huggingface/transformers/issues/2289/events | https://github.com/huggingface/transformers/pull/2289 | 541,898,397 | MDExOlB1bGxSZXF1ZXN0MzU2NDQ4MDAy | 2,289 | fix bug in prepare inputs for language generation for xlm for effective batch_size > 1 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2289?src=pr&el=h1) Report\n> Merging [#2289](https://codecov.io/gh/huggingface/transformers/pull/2289?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/81db12c3ba0c2067f43c4a63edf5e45f54161042?src=pr&el=desc) will **d... | 1,577 | 1,577 | 1,577 | MEMBER | null | if multiple sentence are to be generated the masked tokens to be appended have to equal the effective batch size | {
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https://api.github.com/repos/huggingface/transformers/issues/2288 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2288/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2288/comments | https://api.github.com/repos/huggingface/transformers/issues/2288/events | https://github.com/huggingface/transformers/pull/2288 | 541,894,003 | MDExOlB1bGxSZXF1ZXN0MzU2NDQ0Mjg0 | 2,288 | Improve handling of optional imports | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2288?src=pr&el=h1) Report\n> Merging [#2288](https://codecov.io/gh/huggingface/transformers/pull/2288?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/23dad8447c8db53682abc3c53d1b90f85d222e4b?src=pr&el=desc) will **i... | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2287 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2287/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2287/comments | https://api.github.com/repos/huggingface/transformers/issues/2287/events | https://github.com/huggingface/transformers/issues/2287 | 541,863,648 | MDU6SXNzdWU1NDE4NjM2NDg= | 2,287 | Do Hugging Face GPT-2 Transformer Models Automatically Does the Absolute Position Embedding for Users? | {
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"Indeed, as you can see from the source code [here](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_gpt2.py#L414-L417), when no position ids are passed, they are created as absolute position embeddings.\r\n\r\nYou could have trained a model with a GPT-2 architecture that was using ... | 1,577 | 1,578 | 1,578 | NONE | null | Hello,
According to Hugging Face ```GPT2DoubleHeadsModel``` documentation (https://huggingface.co/transformers/model_doc/gpt2.html#gpt2doubleheadsmodel)
```
"Indices of input sequence tokens in the vocabulary.
GPT-2 is a model with absolute position embeddings"
```
So does this mean that, when we implement... | {
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https://api.github.com/repos/huggingface/transformers/issues/2286 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2286/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2286/comments | https://api.github.com/repos/huggingface/transformers/issues/2286/events | https://github.com/huggingface/transformers/pull/2286 | 541,837,667 | MDExOlB1bGxSZXF1ZXN0MzU2Mzk3Nzg2 | 2,286 | Typo in tokenization_utils.py | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2286?src=pr&el=h1) Report\n> Merging [#2286](https://codecov.io/gh/huggingface/transformers/pull/2286?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/23dad8447c8db53682abc3c53d1b90f85d222e4b?src=pr&el=desc) will **i... | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | avoir -> avoid | {
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https://api.github.com/repos/huggingface/transformers/issues/2285 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2285/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2285/comments | https://api.github.com/repos/huggingface/transformers/issues/2285/events | https://github.com/huggingface/transformers/issues/2285 | 541,794,129 | MDU6SXNzdWU1NDE3OTQxMjk= | 2,285 | BertTokenizer custom UNK unexpected behavior | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I actually have the same problem with GPT-2 tokenizer. Is this the expected behavior?"
] | 1,577 | 1,596 | 1,582 | 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:
* [ ] the official example scripts: (give details)
* [X] my own modified scripts: (give details)
Importing transformers to my ow... | {
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https://api.github.com/repos/huggingface/transformers/issues/2284 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2284/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2284/comments | https://api.github.com/repos/huggingface/transformers/issues/2284/events | https://github.com/huggingface/transformers/issues/2284 | 541,785,206 | MDU6SXNzdWU1NDE3ODUyMDY= | 2,284 | [ALBERT]: Albert base model itself consuming 32 GB GPU memory.. | {
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"i have similar situation.\r\n\r\nhttps://github.com/dsindex/iclassifier#emb_classalbert\r\n\r\nin the paper( https://arxiv.org/pdf/1909.11942.pdf ), ALBERT xlarge has just 60M parameters which is much less than BERT large(334M)'s. \r\nbut, we are unable to load albert-xlarge-v2 on 32G GPU memory.\r\n(no problem on... | 1,577 | 1,683 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using TFALBERT:
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [ ] the official example scripts:
`from transformers import TFAlbertForSequenceClassification`
`model = TFAlbertForSequenceClassification... | {
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https://api.github.com/repos/huggingface/transformers/issues/2283 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2283/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2283/comments | https://api.github.com/repos/huggingface/transformers/issues/2283/events | https://github.com/huggingface/transformers/issues/2283 | 541,775,253 | MDU6SXNzdWU1NDE3NzUyNTM= | 2,283 | Loading sciBERT failed | {
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"Try to use the following commands:\r\n\r\n```bash\r\n$ wget \"https://s3-us-west-2.amazonaws.com/ai2-s2-research/scibert/huggingface_pytorch/scibert_scivocab_uncased.tar\"\r\n$ tar -xf scibert_scivocab_uncased.tar\r\n\r\nThe sciBERT model is now extracted and located under: `./scibert_scivocab_uncased`.\r\n\r\nTo ... | 1,577 | 1,577 | 1,577 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I am trying to compare the effect of different pre-trained models on RE, the code to load bert is:
`self.bert = BertModel.from_pretrained(pretrain_path)`
When the "pretrain_path" is "pretrain/bert-base-uncased" , everything is fine,... | {
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https://api.github.com/repos/huggingface/transformers/issues/2282 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2282/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2282/comments | https://api.github.com/repos/huggingface/transformers/issues/2282/events | https://github.com/huggingface/transformers/issues/2282 | 541,747,239 | MDU6SXNzdWU1NDE3NDcyMzk= | 2,282 | Maybe some parameters are error in document for distributed training ? | {
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> Here is an example using distributed training on 8 V100 GPUs and Bert Whole Word Masking uncased model to reach a F1 > 93 on SQuAD... | {
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https://api.github.com/repos/huggingface/transformers/issues/2281 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2281/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2281/comments | https://api.github.com/repos/huggingface/transformers/issues/2281/events | https://github.com/huggingface/transformers/pull/2281 | 541,738,119 | MDExOlB1bGxSZXF1ZXN0MzU2MzE0NzIw | 2,281 | Add Dutch pre-trained BERT model | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2281?src=pr&el=h1) Report\n> Merging [#2281](https://codecov.io/gh/huggingface/transformers/pull/2281?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ba2378ced560c12f8ee97ca7998fd28b93fcfb47?src=pr&el=desc) will **n... | 1,577 | 1,580 | 1,580 | CONTRIBUTOR | null | We trained a Dutch cased BERT model at the University of Groningen.
Details are on [Github](https://github.com/wietsedv/bertje/) and [Arxiv](https://arxiv.org/abs/1912.09582). | {
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https://api.github.com/repos/huggingface/transformers/issues/2280 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2280/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2280/comments | https://api.github.com/repos/huggingface/transformers/issues/2280/events | https://github.com/huggingface/transformers/issues/2280 | 541,699,278 | MDU6SXNzdWU1NDE2OTkyNzg= | 2,280 | Do anyone have solution for this | {
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<!-- A clear and concise description of the question. -->
| {
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https://api.github.com/repos/huggingface/transformers/issues/2279 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2279/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2279/comments | https://api.github.com/repos/huggingface/transformers/issues/2279/events | https://github.com/huggingface/transformers/issues/2279 | 541,692,724 | MDU6SXNzdWU1NDE2OTI3MjQ= | 2,279 | Help with finetune BERT pretraining | {
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"I suggest you follow the [run_lm_finetuning.py](https://github.com/huggingface/transformers/blob/master/examples/run_lm_finetuning.py) script. Instead of downloading a pretrained model, simply start with a fresh one. Here's an example:\r\n\r\n```\r\nfrom transformers import BertModel, BertConfig, BertTokenizer\r\n... | 1,577 | 1,581 | 1,581 | NONE | null | Hi
could you please assist me how I can pretrain the BERT model, so not like SNLI/MNLI when we finetune a pretrained model, but doing pretraining objective.
thanks a lot
and Merry Christmas and happy new year in advance to the team | {
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https://api.github.com/repos/huggingface/transformers/issues/2278 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2278/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2278/comments | https://api.github.com/repos/huggingface/transformers/issues/2278/events | https://github.com/huggingface/transformers/issues/2278 | 541,658,379 | MDU6SXNzdWU1NDE2NTgzNzk= | 2,278 | where is the script of a second step of knwoledge distillation on SQuAD 1.0? | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"Check here: https://github.com/huggingface/transformers/blob/master/examples/distillation/run_squad_w_distillation.py"
] | 1,577 | 1,588 | 1,582 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
In Distil part, there is a paragraph description which is "distilbert-base-uncased-distilled-squad: A finetuned version of distilbert-base-uncased finetuned using (a second step of) knwoledge distillation on SQuAD 1.0. This model reache... | {
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https://api.github.com/repos/huggingface/transformers/issues/2277 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2277/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2277/comments | https://api.github.com/repos/huggingface/transformers/issues/2277/events | https://github.com/huggingface/transformers/issues/2277 | 541,642,599 | MDU6SXNzdWU1NDE2NDI1OTk= | 2,277 | Does the calling order need to be changed? | {
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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"
] | 1,577 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
pytorch: 1.3.0
torch/optim/lr_scheduler.py:100: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`. Failure to do this will result in PyTorch ski... | {
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https://api.github.com/repos/huggingface/transformers/issues/2276 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2276/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2276/comments | https://api.github.com/repos/huggingface/transformers/issues/2276/events | https://github.com/huggingface/transformers/pull/2276 | 541,615,777 | MDExOlB1bGxSZXF1ZXN0MzU2MjEyMTgz | 2,276 | fix error due to wrong argument name to Tensor.scatter() | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2276?src=pr&el=h1) Report\n> Merging [#2276](https://codecov.io/gh/huggingface/transformers/pull/2276?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ce50305e5b8c8748b81b0c8f5539a337b6a995b9?src=pr&el=desc) will **n... | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | The named argument is called "source", not "src" in the out of place version for some reason, despite it being called "src" in the in-place version of the same Pytorch function. This causes an error. | {
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https://api.github.com/repos/huggingface/transformers/issues/2275 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2275/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2275/comments | https://api.github.com/repos/huggingface/transformers/issues/2275/events | https://github.com/huggingface/transformers/issues/2275 | 541,581,647 | MDU6SXNzdWU1NDE1ODE2NDc= | 2,275 | Gpt2/xl Broken on "Write With Transformer" site | {
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"Same problem. And it seems not fixed yet.",
"It should be fixed now. Thank you for raising this issue."
] | 1,577 | 1,579 | 1,579 | NONE | null | If you navigate to the [GPT-2 section of the Write With Transformer site](https://transformer.huggingface.co/doc/gpt2-large), select gpt2/xl, and try to generate text, the process will not generate anything. | {
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https://api.github.com/repos/huggingface/transformers/issues/2274 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2274/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2274/comments | https://api.github.com/repos/huggingface/transformers/issues/2274/events | https://github.com/huggingface/transformers/issues/2274 | 541,549,362 | MDU6SXNzdWU1NDE1NDkzNjI= | 2,274 | AttributeError: 'GPT2LMHeadModel' object has no attribute 'generate' | {
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"Same problem",
"I have found the reason.\r\n\r\nSo it turns out that the `generate()` method of the `PreTrainedModel` class is newly added, even newer than the latest release (2.3.0). Quite understandable since this library is iterating very fast.\r\n\r\nSo to make `run_generation.py` work, you can install this ... | 1,577 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
The example script `run_generation.py` is broken with the error message `AttributeError: 'GPT2LMHeadModel' object has no attribute 'generate'`
## To Reproduce
Steps to reproduce the behavior:
1. In a terminal, cd to `transformers/examples` and then `python run_g... | {
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https://api.github.com/repos/huggingface/transformers/issues/2273 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2273/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2273/comments | https://api.github.com/repos/huggingface/transformers/issues/2273/events | https://github.com/huggingface/transformers/issues/2273 | 541,514,550 | MDU6SXNzdWU1NDE1MTQ1NTA= | 2,273 | adding special tokens after truncating in run_lm_finetuning.py | {
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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"
] | 1,577 | 1,583 | 1,583 | 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)
In `run_lm_finetuning.py`, we have the following
```
for i in range(0, len... | {
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https://api.github.com/repos/huggingface/transformers/issues/2272 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2272/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2272/comments | https://api.github.com/repos/huggingface/transformers/issues/2272/events | https://github.com/huggingface/transformers/issues/2272 | 541,513,624 | MDU6SXNzdWU1NDE1MTM2MjQ= | 2,272 | Run_tf_ner.py error on TPU | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I have the same issue on Colab TPU with tf-nightly 2.2.0. @dlauc did you solve the problem?",
"Hi @BOUALILILila, I've switched to the... | 1,577 | 1,584 | 1,582 | NONE | null | ## 🐛 Bug
run_tf_ner.py does not work with TPU. The first error is:
`File system scheme '[local]' not implemented `
When the script is changed and .tfrecord file is moved to gs:// address (and also hardcoded "/tmp/mylogs" is replaced with gs:/// dir) there is an error with optimiser:
`AttributeError: 'device_map' ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2271 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2271/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2271/comments | https://api.github.com/repos/huggingface/transformers/issues/2271/events | https://github.com/huggingface/transformers/pull/2271 | 541,493,262 | MDExOlB1bGxSZXF1ZXN0MzU2MTE1MTQ2 | 2,271 | Improve setup and requirements | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2271?src=pr&el=h1) Report\n> Merging [#2271](https://codecov.io/gh/huggingface/transformers/pull/2271?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/23dad8447c8db53682abc3c53d1b90f85d222e4b?src=pr&el=desc) will **d... | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | - Clean up several requirements files generated with pip freeze, with no clear update process
- Rely on extra_requires for managing optional requirements
- Update contribution instructions | {
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https://api.github.com/repos/huggingface/transformers/issues/2270 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2270/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2270/comments | https://api.github.com/repos/huggingface/transformers/issues/2270/events | https://github.com/huggingface/transformers/pull/2270 | 541,479,400 | MDExOlB1bGxSZXF1ZXN0MzU2MTA2MTk1 | 2,270 | Remove support for Python 2 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2270?src=pr&el=h1) Report\n> Merging [#2270](https://codecov.io/gh/huggingface/transformers/pull/2270?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b6ea0f43aeb7ff1dcb03658e38bacae1130abd91?src=pr&el=desc) will **i... | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2269 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2269/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2269/comments | https://api.github.com/repos/huggingface/transformers/issues/2269/events | https://github.com/huggingface/transformers/issues/2269 | 541,450,275 | MDU6SXNzdWU1NDE0NTAyNzU= | 2,269 | Bad F1 Score for run_squad.py on SQuAD2.0 | {
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<!-- A clear and concise description of the question. -->
When I run the run_squad.py for SQuAD2.0 like this
python3 run_squad.py \
--model_type bert \
--model_name_or_path bert-base-cased \
--do_train \
--do_eval \
--train_file /share/nas165/Wendy/transformers/examples/tests... | {
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https://api.github.com/repos/huggingface/transformers/issues/2268 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2268/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2268/comments | https://api.github.com/repos/huggingface/transformers/issues/2268/events | https://github.com/huggingface/transformers/pull/2268 | 541,447,952 | MDExOlB1bGxSZXF1ZXN0MzU2MDg0MTA3 | 2,268 | Improve repository structure | {
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"Last test run failed only because of a flaky test — this is #2240."
] | 1,577 | 1,577 | 1,577 | CONTRIBUTOR | null | This PR builds on top of #2255 (which should be merged first).
Since it changes the location of the source code, once it's merged, contributors must update their local development environment with:
$ pip uninstall transformers
$ pip install -e .
I'll clarify this when I update the contributor ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2267 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2267/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2267/comments | https://api.github.com/repos/huggingface/transformers/issues/2267/events | https://github.com/huggingface/transformers/issues/2267 | 541,433,305 | MDU6SXNzdWU1NDE0MzMzMDU= | 2,267 | Does Pre-Trained Weights Work Internally in pytorch? | {
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"`BertPredictionHeadTransform` is never used in itself AFAIK, and is only part of the full scale models (e.g. `BertModel`). As such, the weights for the prediction head are loaded when you run BertModel.from_pretrained(), since the `BertPredictionHeadTransform` is only a module in the whole model.",
"> `BertPredi... | 1,577 | 1,582 | 1,582 | NONE | null | I am using bert’s pretrained model in from_pretrained and coming across it’s fine tuning code we can save the new model weights and other hyper params in save_pretrained.
My doubt is in there modeling_bert code there is no explicit code that takes the pre-trained weights in acount and then trains as it generally takes... | {
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https://api.github.com/repos/huggingface/transformers/issues/2266 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2266/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2266/comments | https://api.github.com/repos/huggingface/transformers/issues/2266/events | https://github.com/huggingface/transformers/issues/2266 | 541,433,070 | MDU6SXNzdWU1NDE0MzMwNzA= | 2,266 | Imports likely broken in examples | {
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"@aaugustin it seems like that i met the same problem when i use convert_bertabs_original_pytorch_checkpoint.py ,have you ever fixed it or find any way to make it work.\r\nAppriciate it if you can tell me!",
"I didn't attempt to fix this issue. I merely noticed it while I was working on the overall quality of t... | 1,577 | 1,584 | 1,584 | CONTRIBUTOR | null | ## 🐛 Bug
While cleaning up imports with isort, I classified them all. I failed to identify the following four imports:
1. model_bertabs
2. utils_squad
3. utils_squad_evaluate
4. models.model_builder
These modules aren't available on PyPI or in the transformers code repository.
I think they will result i... | {
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https://api.github.com/repos/huggingface/transformers/issues/2265 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2265/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2265/comments | https://api.github.com/repos/huggingface/transformers/issues/2265/events | https://github.com/huggingface/transformers/issues/2265 | 541,427,548 | MDU6SXNzdWU1NDE0Mjc1NDg= | 2,265 | Only the Bert model is currently supported | {
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"You need to give more information. What are you trying to do, what is the code that you use for it, what does not work the way you intended to?",
"> You need to give more information. What are you trying to do, what is the code that you use for it, what does not work the way you intended to?\r\n\r\nI am learning... | 1,577 | 1,578 | 1,578 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using Model2Model and BertTokenizer:
Language I am using the model on English:
The problem arise when using:
* the official example scripts: (give details)
<!-- If you have a code sample, error messages, stack traces, please provide it here as well. -... | {
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https://api.github.com/repos/huggingface/transformers/issues/2264 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2264/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2264/comments | https://api.github.com/repos/huggingface/transformers/issues/2264/events | https://github.com/huggingface/transformers/pull/2264 | 541,417,303 | MDExOlB1bGxSZXF1ZXN0MzU2MDYyMjQ1 | 2,264 | Fix doc link in README | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2264?src=pr&el=h1) Report\n> Merging [#2264](https://codecov.io/gh/huggingface/transformers/pull/2264?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/645713e2cb8307e41febb2b7c9f6036f6645efce?src=pr&el=desc) will **n... | 1,576 | 1,577 | 1,577 | CONTRIBUTOR | null | close https://github.com/huggingface/transformers/issues/2252
- [x] Update `.circleci/deploy.sh`
- [x] Update `deploy_multi_version_doc.sh`
Set commit hash before "Release: v2.3.0".
| {
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https://api.github.com/repos/huggingface/transformers/issues/2263 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2263/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2263/comments | https://api.github.com/repos/huggingface/transformers/issues/2263/events | https://github.com/huggingface/transformers/issues/2263 | 541,416,531 | MDU6SXNzdWU1NDE0MTY1MzE= | 2,263 | BertModel sometimes produces the same output during evaluation | {
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"Did you set a fixed seed? If you want deterministic results, you should set a fixed seed. ",
"> Did you set a fixed seed? If you want deterministic results, you should set a fixed seed.\r\n\r\nNo, I didn't. My problem seems that the model finetuned is totally wrong sometimes. Is it a problem related to random se... | 1,576 | 1,585 | 1,585 | NONE | null | ## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
I finetune BertModel as a part of my model to produce word embeddings. I found sometimes the performance was very bad, then i run the code again without any change, the performance was normal. It is very strange. I check my code to try ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2262 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2262/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2262/comments | https://api.github.com/repos/huggingface/transformers/issues/2262/events | https://github.com/huggingface/transformers/issues/2262 | 541,399,468 | MDU6SXNzdWU1NDEzOTk0Njg= | 2,262 | How to do_predict on run_glue? | {
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"#2198 Same here. A predict script can be really helpful to researchers.",
"same here",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,576 | 1,587 | 1,587 | NONE | null | ## ❓ Questions & Help
I have fine-tuned BERT for sequence classification task by running run_glue script. Now I have trained and evaluated model. My question is how do I make prediction with it on new instances (test set)? Thanks! | {
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https://api.github.com/repos/huggingface/transformers/issues/2261 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2261/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2261/comments | https://api.github.com/repos/huggingface/transformers/issues/2261/events | https://github.com/huggingface/transformers/issues/2261 | 541,391,565 | MDU6SXNzdWU1NDEzOTE1NjU= | 2,261 | AlbertTokenizer behavior doesn't match docs | {
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"The encoder itself would automatically add the [CLS] and [SEP] tokens so if you've done that during preprocessing, you would need to change the `add_special_tokens` parameter to `False`. So your code should probably be like this:\r\n\r\n```\r\ninput_ids = tokenizer.encode(input_text, add_special_tokens=False)\r\n`... | 1,576 | 1,583 | 1,583 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): AlbertForQuestionAnswering
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [x] the official example scripts: (give details)
* [ ] my own modified scripts: (give details)
The tas... | {
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https://api.github.com/repos/huggingface/transformers/issues/2260 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2260/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2260/comments | https://api.github.com/repos/huggingface/transformers/issues/2260/events | https://github.com/huggingface/transformers/pull/2260 | 541,372,520 | MDExOlB1bGxSZXF1ZXN0MzU2MDMwODE3 | 2,260 | Fixing incorrect link in model docstring | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2260?src=pr&el=h1) Report\n> Merging [#2260](https://codecov.io/gh/huggingface/transformers/pull/2260?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/645713e2cb8307e41febb2b7c9f6036f6645efce?src=pr&el=desc) will **n... | 1,576 | 1,579 | 1,579 | CONTRIBUTOR | null | The docstring contains a link to Salesforce/CTRL repo, while the model itself is Facebookresearch/mmbt. It may be the wrong copy\paste. | {
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https://api.github.com/repos/huggingface/transformers/issues/2259 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2259/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2259/comments | https://api.github.com/repos/huggingface/transformers/issues/2259/events | https://github.com/huggingface/transformers/issues/2259 | 541,367,085 | MDU6SXNzdWU1NDEzNjcwODU= | 2,259 | problem in the doc, in the "Quick Start" GPT2 example | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,576 | 1,582 | 1,582 | NONE | null | I am going through the GPT2 example in the doc. Is there a mistake in the "Using the past" code. The main loop to generate text is:
```python
for i in range(100):
print(i)
output, past = model(context, past=past)
token = torch.argmax(output[0, :])
generated += [token.tolist()]
context = tok... | {
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https://api.github.com/repos/huggingface/transformers/issues/2258 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2258/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2258/comments | https://api.github.com/repos/huggingface/transformers/issues/2258/events | https://github.com/huggingface/transformers/issues/2258 | 541,361,605 | MDU6SXNzdWU1NDEzNjE2MDU= | 2,258 | run_ner.py load checkpoint issue | {
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"Can confirm this issue -> a temporary workaround would be to change the line to:\r\n\r\n```python\r\nif os.path.exists(args.model_name_or_path) and \"checkpoint\" in args.model_name_or_path:\r\n```",
"See also related (recent) fix on master: https://github.com/huggingface/transformers/commit/4d36472b96d144887cbe... | 1,576 | 1,587 | 1,587 | NONE | null | Hi,
I just launched the **transformers/examples/run_ner.py** script with my custom model:
`python3 transformers/examples/run_ner.py --data_dir $INPUT_DATA_DIR \
--tokenizer_name $TOKENIZER_FILE_PATH --output_dir $OUTPUT_DIR --model_type camembert --labels $LABELS_DIR --model_name_or_path $BERT_MODEL --max_seq_leng... | {
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https://api.github.com/repos/huggingface/transformers/issues/2257 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2257/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2257/comments | https://api.github.com/repos/huggingface/transformers/issues/2257/events | https://github.com/huggingface/transformers/issues/2257 | 541,360,019 | MDU6SXNzdWU1NDEzNjAwMTk= | 2,257 | HuggingFace transformers documentation webpage is blank? | {
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"Having the same issue.",
"May be related to this:\r\nhttps://twitter.com/Thom_Wolf/status/1208365367493636096\r\n",
"Are you still having an issue or is it fixed (if it is, please close the issue)?",
"Hello,\r\nI am still having the same issue.\r\n",
"Ok, we are in the process of fixing it. Thanks for the ... | 1,576 | 1,577 | 1,577 | NONE | null | Hello,
Is HuggingFace updating their transformers documentation site (https://huggingface.co/transformers/)?
I looked there to get some information about the HugginFace GPT-2, but for some reason all the contents of the website are gone.
Thank you,
| {
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https://api.github.com/repos/huggingface/transformers/issues/2256 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2256/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2256/comments | https://api.github.com/repos/huggingface/transformers/issues/2256/events | https://github.com/huggingface/transformers/issues/2256 | 541,358,601 | MDU6SXNzdWU1NDEzNTg2MDE= | 2,256 | Untrainable dense layer in TFBert. "WARNING:tensorflow:Gradients do not exist for variables ['tf_bert_model/bert/pooler/dense/kernel:0', 'tf_bert_model/bert/pooler/dense/bias:0'] when minimizing the loss." | {
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"After looking at \r\n\r\nhttps://github.com/huggingface/transformers/issues/1727\r\n\r\nI figured out we're getting the warning because we're not using the pooler, therefore it gets no updates. ",
"@Santosh-Gupta can you please update your colab notebook with correct version. i am unbale to get this resolved",
... | 1,576 | 1,634 | 1,576 | CONTRIBUTOR | null | ## 🐛 Bug
<!-- Important information -->
I am getting
> WARNING:tensorflow:Gradients do not exist for variables ['tf_bert_model/bert/pooler/dense/kernel:0', 'tf_bert_model/bert/pooler/dense/bias:0'] when minimizing the loss.
> WARNING:tensorflow:Gradients do not exist for variables ['tf_bert_model/bert/poole... | {
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https://api.github.com/repos/huggingface/transformers/issues/2255 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2255/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2255/comments | https://api.github.com/repos/huggingface/transformers/issues/2255/events | https://github.com/huggingface/transformers/pull/2255 | 541,334,908 | MDExOlB1bGxSZXF1ZXN0MzU2MDA2NDU1 | 2,255 | Implement some Python best practices | {
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"This is in reasonably good shape. There are two tasks left:\r\n\r\n1. Figure out why isort doesn't behave the same locally and on Circle CI. Most likely this has to do with how it classifies first-party / third-party / unknown libraries. Then enable it on Circle CI. **EDIT - fixed** - this was a matter of installi... | 1,576 | 1,577 | 1,577 | CONTRIBUTOR | null | Improve source code quality with black, isort & flake8. | {
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https://api.github.com/repos/huggingface/transformers/issues/2254 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2254/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2254/comments | https://api.github.com/repos/huggingface/transformers/issues/2254/events | https://github.com/huggingface/transformers/pull/2254 | 541,332,443 | MDExOlB1bGxSZXF1ZXN0MzU2MDA0NzE5 | 2,254 | adding positional embeds masking to TFRoBERTa | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2254?src=pr&el=h1) Report\n> Merging [#2254](https://codecov.io/gh/huggingface/transformers/pull/2254?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/73f6e9817c744caae0b73fa343ceaf95ba76f9f8?src=pr&el=desc) will **i... | 1,576 | 1,651 | 1,576 | MEMBER | null | Adding positional embeds masking to TFRoBERTa following its addition to the PT model in #1764 to fix PT <=> TF equivalence test | {
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https://api.github.com/repos/huggingface/transformers/issues/2253 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2253/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2253/comments | https://api.github.com/repos/huggingface/transformers/issues/2253/events | https://github.com/huggingface/transformers/issues/2253 | 541,314,350 | MDU6SXNzdWU1NDEzMTQzNTA= | 2,253 | bias weights not used in T5Model | {
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"Yes, all the layer norms in T5 have no bias (so we keep the default value of 0)"
] | 1,576 | 1,578 | 1,578 | COLLABORATOR | null | ## 🐛 Bug
Running the T5Model on v2.3.0 can show the info message that all bias weights are not used:
> Weights from pretrained model not used in T5Model: ['encoder.block.0.layer.0.layer_norm.bias', 'encoder.block.0.layer.1.layer_norm.bias', 'encoder.block.1.layer.0.layer_norm.bias', 'encoder.block.1.layer.1.layer_... | {
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https://api.github.com/repos/huggingface/transformers/issues/2252 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2252/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2252/comments | https://api.github.com/repos/huggingface/transformers/issues/2252/events | https://github.com/huggingface/transformers/issues/2252 | 541,312,616 | MDU6SXNzdWU1NDEzMTI2MTY= | 2,252 | Documentation link broken | {
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"@abb4s A workaround would be downgrading `transformers` to `2.2.0`. It worked for me that way.",
"Indeed, this was an error introduced by #1548. It was patched by 1efc208. Thank you for raising this issue! ",
"This issue has been automatically marked as stale because it has not had recent activity. It will be ... | 1,576 | 1,584 | 1,584 | NONE | null | ## 🐛 Bug
<!-- Important information -->
hey I just wanted to test BERT for sst2. I have just changed official example script to this:
```
import tensorflow as tf
import tensorflow_datasets
from transformers import *
# Load dataset, tokenizer, model from pretrained model/vocabulary
tokenizer = BertToke... | {
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https://api.github.com/repos/huggingface/transformers/issues/2250 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2250/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2250/comments | https://api.github.com/repos/huggingface/transformers/issues/2250/events | https://github.com/huggingface/transformers/issues/2250 | 541,297,134 | MDU6SXNzdWU1NDEyOTcxMzQ= | 2,250 | Four tests fail when running the full test suite | {
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"The first two are easy fixes. I put fixes in the test parallelization PR.\r\n\r\nThe last two are likely the same bug, but I'm out of my depth there.",
"I guess this has been fixed by now"
] | 1,576 | 1,578 | 1,578 | CONTRIBUTOR | null | ## 🐛 Bug
```
RUN_SLOW=1 python -m unittest discover -s transformers/tests -p '*_test.py' -t . -v
```
```
======================================================================
ERROR: test_model_from_pretrained (transformers.tests.modeling_tf_albert_test.TFAlbertModelTest)
-----------------------------------... | {
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https://api.github.com/repos/huggingface/transformers/issues/2249 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2249/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2249/comments | https://api.github.com/repos/huggingface/transformers/issues/2249/events | https://github.com/huggingface/transformers/pull/2249 | 541,290,042 | MDExOlB1bGxSZXF1ZXN0MzU1OTc1MDk0 | 2,249 | bert（+lstm）+crf | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2249?src=pr&el=h1) Report\n> Merging [#2249](https://codecov.io/gh/huggingface/transformers/pull/2249?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac1b449cc938bb34bc9021feff599cfd3b2376ae?src=pr&el=desc) will **n... | 1,576 | 1,638 | 1,597 | NONE | null | add crf layer for better performance in NER tasks | {
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">My question is how to get feature embedding aligned to each token from a pretrained BertForQuestionAnswering\r\n\r\nCould you elaborate on what this means? I am currently working with BertForQuestionAnswering but haven't encountered this area before. "
] | 1,576 | 1,576 | 1,576 | NONE | null | ## ❓ Questions & Help
I have a finetuned Bert model on a custom Question Answering task (follow original Tensorflow source), I've successful converted this model and loaded it with `BertForQuestionAnswering`
<!-- A clear and concise description of the question. -->
My question is how to get feature embedding aligned... | {
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https://api.github.com/repos/huggingface/transformers/issues/2247 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2247/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2247/comments | https://api.github.com/repos/huggingface/transformers/issues/2247/events | https://github.com/huggingface/transformers/issues/2247 | 541,272,420 | MDU6SXNzdWU1NDEyNzI0MjA= | 2,247 | NER pipeline missing start/end | {
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"That would be a great feature, +1.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,576 | 1,584 | 1,584 | NONE | null | ## 🚀 Feature
2.3 is a great release! Really excited for pipelines.
The feature to add is the start/end positions of the entities.
Additionally, the option to show the recognized entity rather than in subword form would be more user-friendly as an API.
## Motivation
[The release mentions including posit... | {
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https://api.github.com/repos/huggingface/transformers/issues/2246 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2246/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2246/comments | https://api.github.com/repos/huggingface/transformers/issues/2246/events | https://github.com/huggingface/transformers/issues/2246 | 541,185,071 | MDU6SXNzdWU1NDExODUwNzE= | 2,246 | Recently added pipelines tests should be marked as slow | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,576 | 1,582 | 1,582 | CONTRIBUTOR | null | ## 🐛 Bug
Starting today, when running tests, some very large files are downloaded even though I don't enable RUN_SLOW=true.
Some tests in pipelines_test.py should be marked with `@slow` so they don't run unless RUN_SLOW=True. | {
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https://api.github.com/repos/huggingface/transformers/issues/2245 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2245/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2245/comments | https://api.github.com/repos/huggingface/transformers/issues/2245/events | https://github.com/huggingface/transformers/issues/2245 | 541,177,340 | MDU6SXNzdWU1NDExNzczNDA= | 2,245 | Training dataset is not 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",
"paging @LysandreJik ",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed i... | 1,576 | 1,587 | 1,587 | NONE | null | ## ❓ Questions & Help
As stated [here](https://github.com/huggingface/transformers/blob/1ab8dc44b3d84ed1894f5b6a6fab58fb39298fc7/examples/distillation/README.md), the model was trained using Toronto Book Corpus and English Wikipedia. Neither this repository or BERT repository provides links to obtain this data. Upon... | {
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https://api.github.com/repos/huggingface/transformers/issues/2244 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2244/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2244/comments | https://api.github.com/repos/huggingface/transformers/issues/2244/events | https://github.com/huggingface/transformers/pull/2244 | 541,169,098 | MDExOlB1bGxSZXF1ZXN0MzU1ODc3MDU2 | 2,244 | Fix Camembert and XLM-R `decode` method- Fix NER pipeline alignement | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2244?src=pr&el=h1) Report\n> Merging [#2244](https://codecov.io/gh/huggingface/transformers/pull/2244?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ceae85ad60da38cacb14eca49f752669a4fe31dc?src=pr&el=desc) will **d... | 1,576 | 1,651 | 1,576 | MEMBER | null | Fix `decode` method for Camembert and XLM-R
Simplify alignement method for NER pipeline | {
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https://api.github.com/repos/huggingface/transformers/issues/2243 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2243/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2243/comments | https://api.github.com/repos/huggingface/transformers/issues/2243/events | https://github.com/huggingface/transformers/pull/2243 | 541,125,734 | MDExOlB1bGxSZXF1ZXN0MzU1ODQwMTQw | 2,243 | fixing xlm-roberta tokenizer max_length and automodels | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2243?src=pr&el=h1) Report\n> Merging [#2243](https://codecov.io/gh/huggingface/transformers/pull/2243?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/65c75fc58796b278d58b0ce2c8d2031594ef0f64?src=pr&el=desc) will **d... | 1,576 | 1,576 | 1,576 | MEMBER | null | Fix missing max token num in XLM-Roberta | {
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https://api.github.com/repos/huggingface/transformers/issues/2242 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2242/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2242/comments | https://api.github.com/repos/huggingface/transformers/issues/2242/events | https://github.com/huggingface/transformers/issues/2242 | 541,046,723 | MDU6SXNzdWU1NDEwNDY3MjM= | 2,242 | BertTokenizer / CamemBERTokenizer `decode` behaviour ? | {
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"> tokenizer.decode(ids)\r\n\r\nI've made some tests, and this problem occurs also with `BertTokenizer`.\r\n",
"Should be fixed by #2244, can you check that you get the expected behaviour on master?\r\n\r\nThanks!",
"I confirm with the version with the merge commit and new version 2.3.0, it works.\r\nThank you ... | 1,576 | 1,577 | 1,577 | NONE | null | ## 🐛 Bug
Thank you for CamemBERT, it's a great work 😃
Model I am using (Bert, XLNet....): CamemBERT
Language I am using the model on (English, Chinese....): French
The problem arise when using:
* [ ] the official example scripts:
* [x] my own modified scripts: followed by the official documentation at ht... | {
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https://api.github.com/repos/huggingface/transformers/issues/2241 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2241/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2241/comments | https://api.github.com/repos/huggingface/transformers/issues/2241/events | https://github.com/huggingface/transformers/issues/2241 | 541,025,116 | MDU6SXNzdWU1NDEwMjUxMTY= | 2,241 | How to load the finetuned model for retraining from checkpoints in run_squad.py? | {
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"Ah, turns out to run from a pretrained model we have to specify the output_dir as the previous checkpoint. I feel like its quite unintuitive. ",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contribut... | 1,576 | 1,582 | 1,582 | NONE | null | Because of bad internet connection and computational issues its hard for us to train a large number of epochs. We're trying to use the run_squad.py script for bangla QA system training. We have trained the model before and have the checkpoints.
```
!python run_squad.py \
--model_type distilbert \
--model_nam... | {
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https://api.github.com/repos/huggingface/transformers/issues/2240 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2240/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2240/comments | https://api.github.com/repos/huggingface/transformers/issues/2240/events | https://github.com/huggingface/transformers/issues/2240 | 541,021,382 | MDU6SXNzdWU1NDEwMjEzODI= | 2,240 | TFDistilBertModelTest.test_pt_tf_model_equivalence thrown while merging after PR | {
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"I've seen the same error when running the test suite locally.",
"I know how to reproduce/debug this particular failure so I'll take a look on monday (unless someone beats me to it)",
"aaarg, I can't reproduce it locally anymore.",
"This issue has been automatically marked as stale because it has not had rece... | 1,576 | 1,586 | 1,586 | NONE | null | ## 🐛 Bug
I've seen that some PRs failed because of the same error, such as #2239 (today) and #2237 (today). If I'm not remember wrong, there is also another PR in the last days involved @rlouf that he had the same error. Even if the changes made not affect `DistilBertModel` such as #2237, this error occurs!
Questi... | {
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https://api.github.com/repos/huggingface/transformers/issues/2239 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2239/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2239/comments | https://api.github.com/repos/huggingface/transformers/issues/2239/events | https://github.com/huggingface/transformers/pull/2239 | 540,999,192 | MDExOlB1bGxSZXF1ZXN0MzU1NzMzOTMz | 2,239 | HANS evaluation | {
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"Thanks a lot for that Nafise!\r\n\r\nI've started to update the readme.\r\n\r\nDo you think you would have an example of a command to run the script together with associated results?",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2239?src=pr&el=h1) Report\n> Merging [#2239](https://codecov.io... | 1,576 | 1,579 | 1,579 | NONE | null | Adding the evaluation on the HANS dataset in examples | {
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https://api.github.com/repos/huggingface/transformers/issues/2238 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2238/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2238/comments | https://api.github.com/repos/huggingface/transformers/issues/2238/events | https://github.com/huggingface/transformers/issues/2238 | 540,944,537 | MDU6SXNzdWU1NDA5NDQ1Mzc= | 2,238 | Readme installation/test order can lead to confusion when running example unit tests | {
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"related to what @aaugustin is working on",
"Yes I'm planning to rework the contributor documentation. Currently it's a bit haphazard, sorry.",
"This is now clarified. The general README points to the README for examples which is unambiguous."
] | 1,576 | 1,577 | 1,577 | NONE | null | ## ❓ Questions & Help
When following the main readme installation/testing instructions in order, it is not mentioned that in order to let the examples tests pass, the separate examples/requirements.txt must be installed.
Thus, `pip install -r ./examples/requirements.txt` should come before `python -m pytest -sv ./t... | {
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https://api.github.com/repos/huggingface/transformers/issues/2236 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2236/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2236/comments | https://api.github.com/repos/huggingface/transformers/issues/2236/events | https://github.com/huggingface/transformers/issues/2236 | 540,933,848 | MDU6SXNzdWU1NDA5MzM4NDg= | 2,236 | Removing redundant model weights | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,576 | 1,582 | 1,582 | NONE | null | ## 🐛 This is not a bug, more like implemetation detail
I am using BertForTokenClassification model for my binary token classification problem. If my understanding is right, BertForTokenClassification has one layer on top with num_classes output neurons (one for each class) with softmax activation function + CrossEn... | {
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https://api.github.com/repos/huggingface/transformers/issues/2235 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2235/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2235/comments | https://api.github.com/repos/huggingface/transformers/issues/2235/events | https://github.com/huggingface/transformers/pull/2235 | 540,912,867 | MDExOlB1bGxSZXF1ZXN0MzU1NjYwODUz | 2,235 | add example for Model2Model in quickstart | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2235?src=pr&el=h1) Report\n> Merging [#2235](https://codecov.io/gh/huggingface/transformers/pull/2235?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ff36e6d8d713901af807719fa604518c451ff2e5?src=pr&el=desc) will **d... | 1,576 | 1,651 | 1,576 | CONTRIBUTOR | null | As per discussed @LysandreJik | {
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https://api.github.com/repos/huggingface/transformers/issues/2234 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2234/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2234/comments | https://api.github.com/repos/huggingface/transformers/issues/2234/events | https://github.com/huggingface/transformers/issues/2234 | 540,829,506 | MDU6SXNzdWU1NDA4Mjk1MDY= | 2,234 | Supoort loading model weights from a single file. | {
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"As my best knowledge, you **can't** load a model _directly_ from a file. As said in #2094 by @LysandreJik, if you saved using the `save_pretrained` method, then the directory already should have a `config.json` file specifying the shape of the model, so you can simply load it using:\r\n```\r\n>>> import transforme... | 1,576 | 1,582 | 1,582 | NONE | null | So far, transformers package supports loading a model from a directory, such as
```python
model = BertModel.from_pretrained('./test/saved_model/') # E.g. model was saved using save_pretrained('./test/saved_model/')
```
Actually, it loads model weight from $directory/pytorch_model.bin.
Is it possible to load mod... | {
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https://api.github.com/repos/huggingface/transformers/issues/2233 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2233/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2233/comments | https://api.github.com/repos/huggingface/transformers/issues/2233/events | https://github.com/huggingface/transformers/issues/2233 | 540,809,715 | MDU6SXNzdWU1NDA4MDk3MTU= | 2,233 | The code used to be clean... | {
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"Updating code by hand seems a very messy way of working. Can't you just make a copy of the (old version of the) examples directory, and make your changes there - regardless of the current installation of `transformers` itself?"
] | 1,576 | 1,576 | 1,576 | NONE | null | Hi, thanks to all contributors!
From my point of view, recent changes in examples codes, especially run_squad script, are kinda confusing.
May I know what is the reason that we delete old utils_squad.py and store all data processing and evaluating scripts under the transformer/data folder? This makes code look quit... | {
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https://api.github.com/repos/huggingface/transformers/issues/2232 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2232/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2232/comments | https://api.github.com/repos/huggingface/transformers/issues/2232/events | https://github.com/huggingface/transformers/pull/2232 | 540,676,584 | MDExOlB1bGxSZXF1ZXN0MzU1NDU1MzY4 | 2,232 | Keep even the first of the special tokens intact while lowercasing | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2232?src=pr&el=h1) Report\n> Merging [#2232](https://codecov.io/gh/huggingface/transformers/pull/2232?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a5a06a851e1da79138e53978aa079a093f243dde?src=pr&el=desc) will **n... | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | This fixes #2220. The order of `all_special_tokens` is random, and the first one of these will get broken by the lowercasing. There are 5 special tokens, so you have a 1 in 5 chance of hitting the problem. | {
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https://api.github.com/repos/huggingface/transformers/issues/2231 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2231/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2231/comments | https://api.github.com/repos/huggingface/transformers/issues/2231/events | https://github.com/huggingface/transformers/pull/2231 | 540,639,657 | MDExOlB1bGxSZXF1ZXN0MzU1NDIyNTY2 | 2,231 | [http] customizable requests user-agent | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2231?src=pr&el=h1) Report\n> Merging [#2231](https://codecov.io/gh/huggingface/transformers/pull/2231?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a5a06a851e1da79138e53978aa079a093f243dde?src=pr&el=desc) will **d... | 1,576 | 1,577 | 1,576 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2230 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2230/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2230/comments | https://api.github.com/repos/huggingface/transformers/issues/2230/events | https://github.com/huggingface/transformers/issues/2230 | 540,520,796 | MDU6SXNzdWU1NDA1MjA3OTY= | 2,230 | what is the most efficient way to store all hidden layers' weights? | {
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"PyTorch has its [own saving utility](https://pytorch.org/tutorials/beginner/saving_loading_models.html): `torch.save`, which sounds good for your use case as you can easily save/load the tensors. It's based on pickle.",
"This issue has been automatically marked as stale because it has not had recent activity. It... | 1,576 | 1,582 | 1,582 | NONE | null | Hi,
I am following this [post](https://mccormickml.com/2019/05/14/BERT-word-embeddings-tutorial/) for getting all 12 hidden layers' weights for every token in a sentence.
Consider I have a short text with 2 sentences: `He stole money today. He is fishing on the Mississippi riverbank.`
I want to store 5 + 8 = 1... | {
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https://api.github.com/repos/huggingface/transformers/issues/2229 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2229/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2229/comments | https://api.github.com/repos/huggingface/transformers/issues/2229/events | https://github.com/huggingface/transformers/pull/2229 | 540,456,604 | MDExOlB1bGxSZXF1ZXN0MzU1MjYyNzkw | 2,229 | Minor/basic text fixes | {
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https://api.github.com/repos/huggingface/transformers/issues/2228 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2228/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2228/comments | https://api.github.com/repos/huggingface/transformers/issues/2228/events | https://github.com/huggingface/transformers/issues/2228 | 540,431,341 | MDU6SXNzdWU1NDA0MzEzNDE= | 2,228 | Trouble loading Albert model | {
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"Indeed, that's an error from the docs! I just fixed it with 33adab2. The doc should be updated now, thanks for raising this issue.",
"Wow, that was fast. Thank you!"
] | 1,576 | 1,576 | 1,576 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....): Albert
Language I am using the model on (English, Chinese....): English
The problem arise when using:
* [x] the official example scripts: (give details):
* [ ] my own modified scripts: (give details)
The tasks I am working on ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2227 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2227/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2227/comments | https://api.github.com/repos/huggingface/transformers/issues/2227/events | https://github.com/huggingface/transformers/pull/2227 | 540,373,915 | MDExOlB1bGxSZXF1ZXN0MzU1MTk1MzEw | 2,227 | Add "Train on Valohai" buttons to README | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2227?src=pr&el=h1) Report\n> Merging [#2227](https://codecov.io/gh/huggingface/transformers/pull/2227?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/62c1fc3c1ecdfab787ee3c34d1ec1eba65c18877?src=pr&el=desc) will **n... | 1,576 | 1,583 | 1,583 | NONE | null | This pull request adds two "Train on Valohai" buttons to README:
and...
![Screenshot from 2019-12-19 17-00-07](https://user-images.githubusercontent.com/2681608/71184213-1... | {
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https://api.github.com/repos/huggingface/transformers/issues/2226 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2226/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2226/comments | https://api.github.com/repos/huggingface/transformers/issues/2226/events | https://github.com/huggingface/transformers/pull/2226 | 540,345,360 | MDExOlB1bGxSZXF1ZXN0MzU1MTcxMzk0 | 2,226 | [REVIEW] Updated a out-of-date comment in run_lm_finetuning.py | {
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https://api.github.com/repos/huggingface/transformers/issues/2225 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2225/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2225/comments | https://api.github.com/repos/huggingface/transformers/issues/2225/events | https://github.com/huggingface/transformers/pull/2225 | 540,332,806 | MDExOlB1bGxSZXF1ZXN0MzU1MTYwODEx | 2,225 | [REVIEW] Updated comments in run_lm_finetuning.py | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2225?src=pr&el=h1) Report\n> Merging [#2225](https://codecov.io/gh/huggingface/transformers/pull/2225?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8efc6dd544bf1a30d99d4b5abfc5e214699eab2b?src=pr&el=desc) will **n... | 1,576 | 1,576 | 1,576 | NONE | null | I've added DistilBERT and CamemBERT models in the description of the models that can be used for fine-tuning a LM model on a custom dataset. | {
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https://api.github.com/repos/huggingface/transformers/issues/2224 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2224/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2224/comments | https://api.github.com/repos/huggingface/transformers/issues/2224/events | https://github.com/huggingface/transformers/pull/2224 | 540,325,818 | MDExOlB1bGxSZXF1ZXN0MzU1MTU0OTA2 | 2,224 | [REVIEW] Removed duplicate XLMConfig, XLMForQuestionAnswering and XLMTokenizer in run_squad.py | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2224?src=pr&el=h1) Report\n> Merging [#2224](https://codecov.io/gh/huggingface/transformers/pull/2224?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8efc6dd544bf1a30d99d4b5abfc5e214699eab2b?src=pr&el=desc) will **n... | 1,576 | 1,576 | 1,576 | NONE | null | Before this PR, in run_squad.py at lines 58-65 were the following:
```
MODEL_CLASSES = {
'bert': (BertConfig, BertForQuestionAnswering, BertTokenizer),
'xlnet': (XLNetConfig, XLNetForQuestionAnswering, XLNetTokenizer),
'xlm': (XLMConfig, XLMForQuestionAnswering, XLMTokenizer),
'distilbert': (Disti... | {
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https://api.github.com/repos/huggingface/transformers/issues/2223 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2223/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2223/comments | https://api.github.com/repos/huggingface/transformers/issues/2223/events | https://github.com/huggingface/transformers/issues/2223 | 540,280,594 | MDU6SXNzdWU1NDAyODA1OTQ= | 2,223 | Need pretrained XLNET on Squad which can be loaded from_pre_trained | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,576 | 1,582 | 1,582 | NONE | null | ## ❓ Questions & Help
It will be great ,if someone could share their username/model for XLNET pretrained on squad
<!-- A clear and concise description of the question. -->
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https://api.github.com/repos/huggingface/transformers/issues/2222 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2222/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2222/comments | https://api.github.com/repos/huggingface/transformers/issues/2222/events | https://github.com/huggingface/transformers/issues/2222 | 540,160,475 | MDU6SXNzdWU1NDAxNjA0NzU= | 2,222 | Can we remove force_download=True from tests? | {
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"After further research, I'm seeing two possible issues.\r\n\r\n**transformers gets files from S3 with https:// URLs, not s3:// URLs.**\r\n\r\nI think we want to preserve the capability to use the library offline; we don't want to require an Internet connection to check the ETag in all cases. So we have two possibi... | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | ## 🚀 Feature
I would like to remove `force_download=True` from tests and rely on the cache to keep cached files up to date.
## Motivation
Currently, several tests use `force_download=True` on large model files, e.g.:
https://github.com/huggingface/transformers/blob/9c58b236ef5fbbe5d0cbde4932eb342a73eaa0dc/... | {
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https://api.github.com/repos/huggingface/transformers/issues/2221 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2221/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2221/comments | https://api.github.com/repos/huggingface/transformers/issues/2221/events | https://github.com/huggingface/transformers/pull/2221 | 540,150,776 | MDExOlB1bGxSZXF1ZXN0MzU1MDA3MzAz | 2,221 | Updated typo on the link | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2221?src=pr&el=h1) Report\n> Merging [#2221](https://codecov.io/gh/huggingface/transformers/pull/2221?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8efc6dd544bf1a30d99d4b5abfc5e214699eab2b?src=pr&el=desc) will **n... | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | Updated documentation due to typo | {
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https://api.github.com/repos/huggingface/transformers/issues/2220 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2220/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2220/comments | https://api.github.com/repos/huggingface/transformers/issues/2220/events | https://github.com/huggingface/transformers/issues/2220 | 540,022,572 | MDU6SXNzdWU1NDAwMjI1NzI= | 2,220 | tokenizer of bert-base-uncased gives an incorrect split | {
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"As you can see, I'm not able to reproduce your bug, therefore **in my environment it works as expected without bugs**. Here the source code I've used (the same as you):\r\n```\r\nPython 3.6.9 |Anaconda, Inc.| (default, Jul 30 2019, 19:07:31) \r\n[GCC 7.3.0] on linux\r\nType \"help\", \"copyright\", \"credits\" or ... | 1,576 | 1,576 | 1,576 | NONE | null | I found the following code gives an incorrect split
`tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')`
`text = "[CLS] Who was Jim Henson ? [SEP] Jim Henson was a puppeteer [SEP]"`
`tokenized_text = tokenizer.tokenize(text)`
`print(' '.join(tokenized_text))`
> [ cl ##s ] who was jim henson ? [ sep... | {
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https://api.github.com/repos/huggingface/transformers/issues/2219 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2219/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2219/comments | https://api.github.com/repos/huggingface/transformers/issues/2219/events | https://github.com/huggingface/transformers/issues/2219 | 540,013,521 | MDU6SXNzdWU1NDAwMTM1MjE= | 2,219 | When i run the script run_tf_ner.py, i got ValueError: Expected floating point type, got <dtype: 'int32'>. | {
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"> I have tried tf 2.0.0a0, 2.0.0b0, 2.0.0b1, but the same error was reported.\r\n> \r\n> ## Questions & Help\r\n> Traceback (most recent call last):\r\n> File \"run_tf_ner.py\", line 615, in \r\n> app.run(main)\r\n> File \"/home/zpchen/anaconda7/lib/python3.6/site-packages/absl/app.py\", line 299, in run\r\n> _ru... | 1,576 | 1,598 | 1,582 | NONE | null | I have tried tf 2.0.0a0, 2.0.0b0, 2.0.0b1, but the same error was reported.
## ❓ Questions & Help
<!-- A clear and concise description of the question. -->
Traceback (most recent call last):
File "run_tf_ner.py", line 615, in <module>
app.run(main)
File "/home/zpchen/anaconda7/lib/python3.6/site-packa... | {
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https://api.github.com/repos/huggingface/transformers/issues/2218 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2218/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2218/comments | https://api.github.com/repos/huggingface/transformers/issues/2218/events | https://github.com/huggingface/transformers/pull/2218 | 540,002,809 | MDExOlB1bGxSZXF1ZXN0MzU0ODg0NDcz | 2,218 | corrected typo in example for t5 model input argument | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2218?src=pr&el=h1) Report\n> Merging [#2218](https://codecov.io/gh/huggingface/transformers/pull/2218?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8efc6dd544bf1a30d99d4b5abfc5e214699eab2b?src=pr&el=desc) will **n... | 1,576 | 1,576 | 1,576 | MEMBER | null | For the T5Model the argument name of the input has to be specified explicitly since the forward function is defined as
`def forward(self, **kwargs):`
and can therefore only handle keyworded arguments such as `input_ids=inputs_ids`. | {
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https://api.github.com/repos/huggingface/transformers/issues/2217 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2217/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2217/comments | https://api.github.com/repos/huggingface/transformers/issues/2217/events | https://github.com/huggingface/transformers/pull/2217 | 539,946,892 | MDExOlB1bGxSZXF1ZXN0MzU0ODM2OTEw | 2,217 | Support running tests in parallel | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2217?src=pr&el=h1) Report\n> Merging [#2217](https://codecov.io/gh/huggingface/transformers/pull/2217?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ac1b449cc938bb34bc9021feff599cfd3b2376ae?src=pr&el=desc) will **i... | 1,576 | 1,576 | 1,576 | CONTRIBUTOR | null | At this point, after `pip install pytest-xdist`, I'm getting a **2.5x speedup** running tests locally on my 2016 MBP (2,9 GHz Quad-Core Intel Core i7):
- `python -m pytest -n auto -s -v ./transformers/tests/` runs in slightly less than 2 minutes
- `python -m pytest -s -v ./transformers/tests/` takes slightly more t... | {
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https://api.github.com/repos/huggingface/transformers/issues/2216 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2216/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2216/comments | https://api.github.com/repos/huggingface/transformers/issues/2216/events | https://github.com/huggingface/transformers/issues/2216 | 539,855,885 | MDU6SXNzdWU1Mzk4NTU4ODU= | 2,216 | Error while loading Pretrained Enocder and Decoder transformers | {
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"How we can solve this problem you've highlighted? Do you want to open a separate PR? If you want, we can work together on this problem!",
"Sure. Drop me a mail at anandhperumal02@gmail.com",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no furth... | 1,576 | 1,582 | 1,582 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model I am using (Bert, XLNet....):
Language I am using the model on (English, Chinese....):
The problem arise when using:
* [ ] the official example scripts: (give details)
* [X ] my own modified scripts: (give details)
The tasks I am working on is:
* [ ] an o... | {
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https://api.github.com/repos/huggingface/transformers/issues/2215 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2215/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2215/comments | https://api.github.com/repos/huggingface/transformers/issues/2215/events | https://github.com/huggingface/transformers/issues/2215 | 539,802,157 | MDU6SXNzdWU1Mzk4MDIxNTc= | 2,215 | Return overflowing tokens if max_length is not given | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,576 | 1,582 | 1,582 | COLLABORATOR | null | ## 🚀 Feature
The tokenizer can return overflowing tokens in the `encode_plus` method if 1. `return_overflowing_tokens=True`; and 2. if `max_length` is given. I imagine that it could also be useful to allow to return the overflowing tokens when a max_length is not given but when the input is longer than the model's... | {
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https://api.github.com/repos/huggingface/transformers/issues/2214 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2214/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2214/comments | https://api.github.com/repos/huggingface/transformers/issues/2214/events | https://github.com/huggingface/transformers/issues/2214 | 539,739,617 | MDU6SXNzdWU1Mzk3Mzk2MTc= | 2,214 | XLM run_squad errors with size mismatch | {
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"I've tried different `XLM*` models with and I've obtained the same error you've. I suspect it's broken something into the implementation of `XLM*` models or the .bin file uploaded to AWS S3.\r\nN.B: I've tried to load `xlm-mlm-17-1280` with the usual procedure (i.e. by using `from_pretrained` method) which works a... | 1,576 | 1,576 | 1,576 | NONE | null | ## 🐛 Bug
<!-- Important information -->
Model: XLM_mlm_ende_1024
Language: English
Using: the official example scripts: ``run_squad.py``
## To Reproduce
Steps to reproduce the behavior:
1. install dependecies and download squad v1.1 data; pull, install transformers from github master.
2. run ``r... | {
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https://api.github.com/repos/huggingface/transformers/issues/2213 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2213/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2213/comments | https://api.github.com/repos/huggingface/transformers/issues/2213/events | https://github.com/huggingface/transformers/issues/2213 | 539,670,826 | MDU6SXNzdWU1Mzk2NzA4MjY= | 2,213 | T5 - Finetuning of an EncoderDecoder Model | {
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"As I know, there is **no** Python scripts for fine-tuning T5 model, **at the moment**.\r\nBesides the source code you can see in this library, you can see the PR #1739 which implements T5 model.\r\n\r\n> Hello,\r\n> \r\n> I know that the T5 implementation is quite new, but is there already code to finetune and lat... | 1,576 | 1,582 | 1,582 | NONE | null | Hello,
I know that the T5 implementation is quite new, but is there already code to finetune and lateron decode from the T5 model?
As I understand most of your models are no EncoderDecoder models, so I guess that the default pipeline / code is not working for T5, is that right?
Could you point me to a script ... | {
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