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https://api.github.com/repos/huggingface/transformers/issues/303 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/303/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/303/comments | https://api.github.com/repos/huggingface/transformers/issues/303/events | https://github.com/huggingface/transformers/issues/303 | 412,468,953 | MDU6SXNzdWU0MTI0Njg5NTM= | 303 | Example Code in README fails. | {
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The text that is input to the model
`"[CLS] Who was Jim Henson ? [SEP] Jim Henson was a puppeteer [SEP]"`
is expected to be tokenized and masked like so
`['[CLS]', 'who', 'was', 'jim', 'henson', '?', '[SEP]', 'jim', '[MASK]', 'was', 'a', 'pupp... | {
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"This could be related to #266 - are you using the latest version of `pytorch-pretrained-BERT`?",
"No, I was on 0.4, I upgraded to 0.6.1 and it worked."
] |
https://api.github.com/repos/huggingface/transformers/issues/284 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/284/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/284/comments | https://api.github.com/repos/huggingface/transformers/issues/284/events | https://github.com/huggingface/transformers/issues/284 | 410,782,598 | MDU6SXNzdWU0MTA3ODI1OTg= | 284 | Error in Apex's FusedLayerNorm | {
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"followers_url": "https://api.github.... | [] | closed | false | [] | null | 1 | 2019-02-15T14:01:48Z | 2019-02-20T15:47:28Z | 2019-02-20T15:46:50Z | null | NONE | [] | null | null | null | null | After installing `apex` with the cuda extensions and running BERT, I get the following error in `FusedLayerNormAffineFunction`, [apex/normalization/fused_layer_norm.py](https://github.com/NVIDIA/apex/blob/master/apex/normalization/fused_layer_norm.py#L16) (line 21).
```
RuntimeError: a Tensor with 2482176 elements ... | {
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"This was an error in `apex`, due to mismatched compiled libraries. Fix can be found [here](https://github.com/NVIDIA/apex/issues/156#issuecomment-465301976).\r\n\r\n> Try a full `pip uninstall apex`, then `cd apex_repo_dir; rm-rf build; python setup.py install --cuda_ext --cpp_ext` and see if the segfault persists... |
https://api.github.com/repos/huggingface/transformers/issues/305 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/305/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/305/comments | https://api.github.com/repos/huggingface/transformers/issues/305/events | https://github.com/huggingface/transformers/pull/305 | 412,578,975 | MDExOlB1bGxSZXF1ZXN0MjU0NzU1NTQw | 305 | Update run_openai_gpt.py | {
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"merged_at": "2019... | Adding invocation to the top of `run_openai_gpt.py` so that's it's easy to find. Previously, the header said that running the script w/ default values works, but actually you need to set some paths. | {
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https://api.github.com/repos/huggingface/transformers/issues/99 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/99/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/99/comments | https://api.github.com/repos/huggingface/transformers/issues/99/events | https://github.com/huggingface/transformers/issues/99 | 388,660,542 | MDU6SXNzdWUzODg2NjA1NDI= | 99 | run_squad.py stuck on batch size greater than 1 | {
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"followers_url": "https://api.github.com/users/wcgan/follow... | [] | closed | false | [] | null | 7 | 2018-12-07T13:44:09Z | 2019-02-21T03:01:25Z | 2018-12-14T14:43:02Z | null | NONE | [] | null | null | null | null | Thanks a lot for the code! I need help figuring out why the script is not working so long the batch_size is set to be above 1. Specifically, it seems to be stuck at Line 908: loss = model(input_ids, segment_ids, input_mask, start_positions, end_positions). I am using 4 k80. Thanks! | {
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"Please copy paste the command you are using to run this example.",
"Here you go\r\n\r\n```\r\npython ./run_squad.py \r\n --bert_model bert-base-uncased \\\r\n --do_train \\\r\n --do_predict \\\r\n --train_file $SQUAD_DIR/train-v1.1.json \\\r\n --predict_file $SQUAD_DIR/dev-v1.1.json \\\r\n --learning_rate ... |
https://api.github.com/repos/huggingface/transformers/issues/307 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/307/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/307/comments | https://api.github.com/repos/huggingface/transformers/issues/307/events | https://github.com/huggingface/transformers/pull/307 | 412,731,345 | MDExOlB1bGxSZXF1ZXN0MjU0ODczOTY0 | 307 | Update README.md | {
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https://api.github.com/repos/huggingface/transformers/issues/304 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/304/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/304/comments | https://api.github.com/repos/huggingface/transformers/issues/304/events | https://github.com/huggingface/transformers/issues/304 | 412,565,139 | MDU6SXNzdWU0MTI1NjUxMzk= | 304 | Can I do a code reference in implementing my code? | {
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I am trying simply implementing gpt-2 on Pytorch
I have trouble in trasfering tensorflow checkpoint to pytorch :(
https://github.com/graykode/gpt-2-Pytorch
Could I do this code reference in implementing my code? I'll write reference in my code!!
Thanks for awesome sharing! | {
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"Hi @graykode,\r\nWhat do you mean by \"code reference\"?",
"@thomwolf \r\nHello thomwolf!\r\nIt mean that I apply your code about `GPT-2 model and transferring tensorflow checkpoint to pytorch` in my project!\r\n I show the origin of the information in my project code comment when I refer to your code.\r\nThanks... |
https://api.github.com/repos/huggingface/transformers/issues/310 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/310/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/310/comments | https://api.github.com/repos/huggingface/transformers/issues/310/events | https://github.com/huggingface/transformers/pull/310 | 412,821,213 | MDExOlB1bGxSZXF1ZXN0MjU0OTQyMDc3 | 310 | Few small nits in GPT-2's README code examples | {
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"They were just basic typos :) Thanks Stanislas"
] |
https://api.github.com/repos/huggingface/transformers/issues/314 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/314/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/314/comments | https://api.github.com/repos/huggingface/transformers/issues/314/events | https://github.com/huggingface/transformers/issues/314 | 413,272,916 | MDU6SXNzdWU0MTMyNzI5MTY= | 314 | Issue with apex import on MAC | {
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MacOS High Sierra 10.13.6
```
Traceback (most recent call last):
File "examples/classifier.py", line 1, in <module>
from pytorch_pretrained_bert.tokenization import BertTokenizer, WordpieceTokenizer
File "/Users/Bhoomit/work/robin/nlp/pytorch-pretrained-BERT/env/lib/python3.7/site-packages/py... | {
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"Unfortunately, apex (and fp16 in general) only work on GPU. So you can't use it on MacOS :/"
] |
https://api.github.com/repos/huggingface/transformers/issues/213 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/213/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/213/comments | https://api.github.com/repos/huggingface/transformers/issues/213/events | https://github.com/huggingface/transformers/issues/213 | 401,219,022 | MDU6SXNzdWU0MDEyMTkwMjI= | 213 | will examples update the parameters of bert model? | {
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"Could you please show the part of the paper where you have seen mentioned, I haven't found it.\r\n\r\nAre you talking about this paragraph?\r\n\r\n>In this section we evaluate how well BERT performs in the feature-based approach by generating ELMo-like pre-trained contextual representations on the CoNLL-2003 NER t... |
https://api.github.com/repos/huggingface/transformers/issues/317 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/317/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/317/comments | https://api.github.com/repos/huggingface/transformers/issues/317/events | https://github.com/huggingface/transformers/issues/317 | 413,719,230 | MDU6SXNzdWU0MTM3MTkyMzA= | 317 | anyone notice large difference of using fp16 ? | {
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I'm trying to see the reason and noticed examples from apex:
https://github.com/NVIDIA/apex/tree/master/examples
actually... | {
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https://api.github.com/repos/huggingface/transformers/issues/316 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/316/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/316/comments | https://api.github.com/repos/huggingface/transformers/issues/316/events | https://github.com/huggingface/transformers/pull/316 | 413,621,140 | MDExOlB1bGxSZXF1ZXN0MjU1NTY2MTU5 | 316 | update documentation for gpt-2 | {
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"merged_at": "2019... | fixes a few incorrect details in the gpt-2 documentation.
one remaining thing, all of the models return an extra `presents` variable that I'm not quite sure what it is, so there's a ... in the doc. if you tell me what to put there I can put it there, or you can do it yourself. | {
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"Hi @joelgrus, you are right, the docstring were lagging a lot.\r\nAll the information is in the `README.py`, more specifically [these sections detailing the API of the GPT2 models](https://github.com/huggingface/pytorch-pretrained-BERT#14-gpt2model) but I forgot to update the docstrings. Do you want to have a look... |
https://api.github.com/repos/huggingface/transformers/issues/308 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/308/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/308/comments | https://api.github.com/repos/huggingface/transformers/issues/308/events | https://github.com/huggingface/transformers/issues/308 | 412,742,435 | MDU6SXNzdWU0MTI3NDI0MzU= | 308 | It seems the eval speed of transformer-xl is not faster than bert-base-uncased. | {
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The log:
```
Better speed can be achieved with apex installed from https://www.github.com/nvidia/apex.
02/21/2019 12:11:44 - INFO - __main__ - device: cpu n_gpu: 1, distributed training: False, 16-bits training: False
0... | {
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https://api.github.com/repos/huggingface/transformers/issues/280 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/280/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/280/comments | https://api.github.com/repos/huggingface/transformers/issues/280/events | https://github.com/huggingface/transformers/issues/280 | 410,591,310 | MDU6SXNzdWU0MTA1OTEzMTA= | 280 | Have you eval the inference speed of transformer-xl? | {
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https://api.github.com/repos/huggingface/transformers/issues/331 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/331/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/331/comments | https://api.github.com/repos/huggingface/transformers/issues/331/events | https://github.com/huggingface/transformers/issues/331 | 415,505,133 | MDU6SXNzdWU0MTU1MDUxMzM= | 331 | Can BERT do the next-word-predict task? As it is bidirectional. | {
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Thank you very much! | {
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https://api.github.com/repos/huggingface/transformers/issues/320 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/320/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/320/comments | https://api.github.com/repos/huggingface/transformers/issues/320/events | https://github.com/huggingface/transformers/issues/320 | 414,497,924 | MDU6SXNzdWU0MTQ0OTc5MjQ= | 320 | what is the batch size we can use for SQUAD task? | {
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I have a Tesla M60 GPU which has about 8GB of memory. For bert-large-uncased model, I can only take batch size as 2, even after I used --fp16. Is it normal?
| {
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"solved"
] |
https://api.github.com/repos/huggingface/transformers/issues/26 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/26/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/26/comments | https://api.github.com/repos/huggingface/transformers/issues/26/events | https://github.com/huggingface/transformers/issues/26 | 381,718,424 | MDU6SXNzdWUzODE3MTg0MjQ= | 26 | Checkpoints not saved | {
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"In the `run_squad.py`script, I added the following lines after the training loop:\r\n\r\n```\r\nlogger.info(***** Saving fine-tuned model *****)\r\noutput_model_file = os.path.join(args.output_dir, \"pytorch_model.bin\")\r\nif n_gpu > 1:\r\n torch.save(model.module.bert.state_dict(), output_model_file)\r\nelse:... |
https://api.github.com/repos/huggingface/transformers/issues/342 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/342/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/342/comments | https://api.github.com/repos/huggingface/transformers/issues/342/events | https://github.com/huggingface/transformers/issues/342 | 417,050,205 | MDU6SXNzdWU0MTcwNTAyMDU= | 342 | Usage example needs [CLS] and [SEP] added post-tokenization | {
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```
['[',
'cl',
'##s',
']',
'who',
'was',
'jim',
'henson',
'[MASK]',
'[',
'sep',
']',
'jim',
'henson',
'was',
'a',
'puppet',
'##eer',
'[',
'sep',
... | {
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"Argh, I just realized that due to dependency conflicts, pip had installed an old version `0.3.0`.\r\n\r\nWas fixed here:\r\nhttps://github.com/huggingface/pytorch-pretrained-BERT/issues/303\r\n"
] |
https://api.github.com/repos/huggingface/transformers/issues/346 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/346/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/346/comments | https://api.github.com/repos/huggingface/transformers/issues/346/events | https://github.com/huggingface/transformers/issues/346 | 417,441,346 | MDU6SXNzdWU0MTc0NDEzNDY= | 346 | MRPC Score Lower than Expected | {
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I am running with the provided command and fp16, using a GCE instance with a Tesla T4.
> time py... | {
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"Argh, just realized I was on `0.3.0` which is what pip installed due to some dependencies. Upgrading to `0.6.1` and now I'm getting expected scores:\r\n```\r\neval_accuracy = 0.8529411764705882\r\neval_loss = 0.39120761538837473\r\nglobal_step = 345\r\nloss = 0.17308216924252717\r\n\r\neval_accuracy = 0.843137254... |
https://api.github.com/repos/huggingface/transformers/issues/327 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/327/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/327/comments | https://api.github.com/repos/huggingface/transformers/issues/327/events | https://github.com/huggingface/transformers/pull/327 | 415,258,178 | MDExOlB1bGxSZXF1ZXN0MjU2Nzg1NjI3 | 327 | Issue#324: warmup linear fixes | {
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- Using the same schedule functions in BertAdam and OpenAIAdam, fixing `warmup_linear` of OpenAIAdam
- fix for negative learning rate after t_total for `warmup_linear`
- some more docstrings
- warning when t_total is exceede... | {
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"Great, thanks @lukovnikov!"
] |
https://api.github.com/repos/huggingface/transformers/issues/341 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/341/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/341/comments | https://api.github.com/repos/huggingface/transformers/issues/341/events | https://github.com/huggingface/transformers/pull/341 | 417,023,120 | MDExOlB1bGxSZXF1ZXN0MjU4MTEzNTQ3 | 341 | catch exception if pathlib not install | {
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"Thanks!"
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https://api.github.com/repos/huggingface/transformers/issues/347 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/347/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/347/comments | https://api.github.com/repos/huggingface/transformers/issues/347/events | https://github.com/huggingface/transformers/pull/347 | 417,468,974 | MDExOlB1bGxSZXF1ZXN0MjU4NDU5NjA3 | 347 | Processor for SST-2 task | {
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"Thanks @jplehmann!"
] |
https://api.github.com/repos/huggingface/transformers/issues/348 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/348/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/348/comments | https://api.github.com/repos/huggingface/transformers/issues/348/events | https://github.com/huggingface/transformers/pull/348 | 417,472,951 | MDExOlB1bGxSZXF1ZXN0MjU4NDYyNzI3 | 348 | output data | {
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"Wrong upstream I guess. Closing."
] | |
https://api.github.com/repos/huggingface/transformers/issues/239 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/239/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/239/comments | https://api.github.com/repos/huggingface/transformers/issues/239/events | https://github.com/huggingface/transformers/issues/239 | 404,850,329 | MDU6SXNzdWU0MDQ4NTAzMjk= | 239 | cannot load BERTAdam when restoring from BioBert | {
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The conversion script loads the checkpoint, but appears to balk at BERTAdam when building the Pytorch model.
```
...
Building PyTorch model from configuration: {
"attention_probs_dropout_prob": 0.1,
... | {
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"I see. This is because they didn't use the same names for the adam optimizer variables than the Google team. I'll see if I can find a simple way around this for future cases.\r\n\r\nIn the mean time, you can install `pytorch-pretrained-bert` from the master (`git clone ...` and `pip install -e .`) and add the name... |
https://api.github.com/repos/huggingface/transformers/issues/256 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/256/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/256/comments | https://api.github.com/repos/huggingface/transformers/issues/256/events | https://github.com/huggingface/transformers/issues/256 | 407,051,972 | MDU6SXNzdWU0MDcwNTE5NzI= | 256 | does run_lm_finetuning.py actually use --eval_batch_size? | {
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"No, there's no evaluation step in the example script yet. What I can recommend is using your downstream task for evaluation of the pretrained BERT. Alternatively, you could of course also add some evaluation of the LM / nextSentence loss on a validation set.",
"Perhaps for clarity then, that parameter should be ... |
https://api.github.com/repos/huggingface/transformers/issues/257 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/257/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/257/comments | https://api.github.com/repos/huggingface/transformers/issues/257/events | https://github.com/huggingface/transformers/issues/257 | 407,218,110 | MDU6SXNzdWU0MDcyMTgxMTA= | 257 | Minor redundancy in model defintion? | {
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https://github.com/huggingface/pytorch-pretrained-BERT/blob/822915142b2f201c0b01acd7cffe1b05994d2d82/pytorch_pretrained_bert/modeling.py#L206-L212
L212 can simply be replaced by `self.all_head_size = config.hidden_size` as you already error out if the... | {
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"Yes, feel free to submit a PR. Otherwise, I'll fix it in the next release."
] |
https://api.github.com/repos/huggingface/transformers/issues/264 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/264/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/264/comments | https://api.github.com/repos/huggingface/transformers/issues/264/events | https://github.com/huggingface/transformers/issues/264 | 408,729,916 | MDU6SXNzdWU0MDg3Mjk5MTY= | 264 | RuntimeError: cuda runtime error while running run_classifier.py with 'bert-large-uncased' bert model | {
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"reduce batch size?",
"It is 32 as of now . What do you think I should reduce it to ?",
"Start very low and increase while looking at `nvidia-smi` or a similar GPU memory visualization tool.",
"Closing this for now, feel free to re-open if you have other issues."
] | |
https://api.github.com/repos/huggingface/transformers/issues/272 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/272/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/272/comments | https://api.github.com/repos/huggingface/transformers/issues/272/events | https://github.com/huggingface/transformers/issues/272 | 409,598,865 | MDU6SXNzdWU0MDk1OTg4NjU= | 272 | Facing issue in Run Fine tune LM | {
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So in BERTDataSet len is giving negative
I tried changing it to self.num_docs - 1
def __len__(self):
print(self.corpus_lines ,self.num_docs)
return self.corpus_lines - self.num_docs - 1
I am also getting errors at multiple steps, Is the... | {
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"Yes, you need documents with multiple lines because only sentences from the same doc are used as positive examples for the nextSentence prediction. ",
"Seems like the expected behavior. Feel free to open a PR to extend the example if you want @tuhinjubcse."
] |
https://api.github.com/repos/huggingface/transformers/issues/274 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/274/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/274/comments | https://api.github.com/repos/huggingface/transformers/issues/274/events | https://github.com/huggingface/transformers/issues/274 | 409,715,950 | MDU6SXNzdWU0MDk3MTU5NTA= | 274 | Help: how to get index/symbol from last_hidden, on text8? | {
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how to get index/symbol from last_hidden, on text8?
Thanks | {
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"Hi,\r\nThere is no pretrained character-level model for text8 right now.\r\nOnly a word-level model trained on wikitext 103."
] |
https://api.github.com/repos/huggingface/transformers/issues/279 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/279/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/279/comments | https://api.github.com/repos/huggingface/transformers/issues/279/events | https://github.com/huggingface/transformers/issues/279 | 410,143,066 | MDU6SXNzdWU0MTAxNDMwNjY= | 279 | DataParallel imbalanced memory usage | {
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"followers_url": "https://api.github.com/use... | [] | closed | false | [] | null | 2 | 2019-02-14T06:06:38Z | 2019-03-06T09:01:28Z | 2019-03-06T09:01:27Z | null | NONE | [] | null | null | null | null | Simialr to this issue: https://discuss.pytorch.org/t/dataparallel-imbalanced-memory-usage/22551/12, when I run run_lm_finetuning.py using 4 GPUs on Microsoft Azure, the first GPU will have 4000MB Memory usage while the other 3 are at 700MB. The Volatile Util for the first GPU also is at 100% while the rest are at 0%. ... | {
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"Managed to get volatile GPU to work properly but memory allocation is sitll imbalanced\r\n\r\n+-----------------------------------------------------------------------------+\r\n| NVIDIA-SMI 410.78 Driver Version: 410.78 CUDA Version: 10.0 |\r\n|-------------------------------+----------------------... |
https://api.github.com/repos/huggingface/transformers/issues/289 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/289/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/289/comments | https://api.github.com/repos/huggingface/transformers/issues/289/events | https://github.com/huggingface/transformers/issues/289 | 411,430,245 | MDU6SXNzdWU0MTE0MzAyNDU= | 289 | HugginFace or HuggingFace? | {
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https://github.com/huggingface/pytorch-pretrained-BERT/search?q=hugginface&unscoped_q=hugginface | {
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"Thanks, I'll fix that in a future release."
] |
https://api.github.com/repos/huggingface/transformers/issues/291 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/291/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/291/comments | https://api.github.com/repos/huggingface/transformers/issues/291/events | https://github.com/huggingface/transformers/issues/291 | 411,558,891 | MDU6SXNzdWU0MTE1NTg4OTE= | 291 | Too much info @ stdout | {
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For example: it prints directly to `stdout` "Better speed can be achieved with apex installed from https://www.github.com/nvidia/apex.... | {
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"Oh that's right, this one should be a logging.info event like the other ones.",
"Fixed"
] |
https://api.github.com/repos/huggingface/transformers/issues/299 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/299/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/299/comments | https://api.github.com/repos/huggingface/transformers/issues/299/events | https://github.com/huggingface/transformers/issues/299 | 412,197,859 | MDU6SXNzdWU0MTIxOTc4NTk= | 299 | Tests failure | {
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"followers_url": "https://api.github.com/users/g-... | [] | closed | false | [] | null | 5 | 2019-02-20T01:11:52Z | 2019-03-06T09:11:51Z | 2019-03-06T09:11:51Z | null | NONE | [] | null | null | null | null | Steps to reproduce:
1. Clone the repo.
2. Set up a plain virtual environment `venv` for the repo with Python 3.6.
3. Run `pip install .` (using the `[--editable]` didn't work and there was some error, so I just removed it)
4. Run `pip install spacy ftfy==4.4.3` and `python -m spacy download en` -- SUCCESSFUL.
5.... | {
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"Update:\r\n\r\nI manually uninstalled PyTorch (`torch | 1.0.1.post2 | 1.0.1.post2` in the list above) from my venv and installed PyTorch 0.4.0 (I couldn't find the whl file for 0.4.1 for Mac OS, which is my platform) by running\r\n\r\n`pip install https://download.pytorch.org/whl/torch-0.4.0-cp36-cp36m-macosx_10_7... |
https://api.github.com/repos/huggingface/transformers/issues/315 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/315/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/315/comments | https://api.github.com/repos/huggingface/transformers/issues/315/events | https://github.com/huggingface/transformers/issues/315 | 413,590,083 | MDU6SXNzdWU0MTM1OTAwODM= | 315 | run_classifier.py : TypeError: join() argument must be str or bytes, not 'PosixPath' | {
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python3.5 run_classifier.py \
--task_name MRPC \
--do_train \
--do_eval \
--do_lower_case \
--data_dir $GLUE_DIR/MRPC/ \
--bert_model bert-base-uncased \
--max_seq_length 128 \
--train_batch_size 32 \
--learning_rate 2e-5 \
--num_train_epochs 3.0 \
--o... | {
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"https://github.com/huggingface/pytorch-pretrained-BERT/blob/master/pytorch_pretrained_bert/file_utils.py#L30\r\n`PYTORCH_PRETRAINED_BERT_CACHE = Path(os.getenv('PYTORCH_PRETRAINED_BERT_CACHE',\r\n Path.home() / '.pytorch_pretrained_bert'))` --> \r\n`PYTORCH_PRETRAI... |
https://api.github.com/repos/huggingface/transformers/issues/318 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/318/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/318/comments | https://api.github.com/repos/huggingface/transformers/issues/318/events | https://github.com/huggingface/transformers/issues/318 | 413,789,252 | MDU6SXNzdWU0MTM3ODkyNTI= | 318 | TransfoXLLMHeadModel output interpretation | {
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"followers_url": "https://api.github.com/users/bergen/follow... | [] | closed | false | [] | null | 1 | 2019-02-24T06:52:50Z | 2019-03-06T09:25:23Z | 2019-03-06T09:25:23Z | null | NONE | [] | null | null | null | null | TransfoXLLMHeadModel gives an output of log probabilities of shape [batch_size, sequence_length, n_tokens]. What do these probabilities represent? For example, what distribution is output at the first sequence position? Is it the conditional distribution given the first word? If so, how can the probability of a complet... | {
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"Hi,\r\n1/ it's the usual language modeling probabilities: each token probability given the previous tokens\r\n2/ thanks, fixed."
] |
https://api.github.com/repos/huggingface/transformers/issues/321 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/321/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/321/comments | https://api.github.com/repos/huggingface/transformers/issues/321/events | https://github.com/huggingface/transformers/issues/321 | 414,583,129 | MDU6SXNzdWU0MTQ1ODMxMjk= | 321 | how to load classification model and predict? | {
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"Should work. Without more information I can't really help you."
] |
https://api.github.com/repos/huggingface/transformers/issues/322 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/322/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/322/comments | https://api.github.com/repos/huggingface/transformers/issues/322/events | https://github.com/huggingface/transformers/issues/322 | 414,596,654 | MDU6SXNzdWU0MTQ1OTY2NTQ= | 322 | Single sentence corpus in run_lm_finetuning? | {
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I am trying to pre-train using `BertForPreTraning` in `run_lm_finetuning.py`. My target corpus is based on very many tweets and I am unsure how the model will tackle that since they are mostly only one sentence. Will it affect the IsNextSentence task?
Should my .txt input file consist of one tweet on each li... | {
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"https://github.com/huggingface/pytorch-pretrained-BERT/issues/272\r\n\r\nI had the same issue and but apparently this cant be done in BERT",
"Yes, can't be done currently. Feel free to submit a PR to extend the `run_lm_finetuning` example @vebits!"
] |
https://api.github.com/repos/huggingface/transformers/issues/326 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/326/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/326/comments | https://api.github.com/repos/huggingface/transformers/issues/326/events | https://github.com/huggingface/transformers/issues/326 | 414,938,885 | MDU6SXNzdWU0MTQ5Mzg4ODU= | 326 | run_classifier with evaluation job only | {
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However, I have encountered some problem.
After training the model, I just want to do eval on another dataset with the trained model. Therefore I only open do_eval.
However, it gives me this error:
Traceback (most recent call last):
File "run_classifier_torch.py", line 6... | {
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" evalonly works last ver, need to mv some code out of train...",
"> evalonly works last ver, need to mv some code out of train...\r\n\r\nyup I agree. I shall do the eval loss and do it\r\n",
"Seems fixed in master, right? Feel free to re-open the issue if it's not the case."
] |
https://api.github.com/repos/huggingface/transformers/issues/330 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/330/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/330/comments | https://api.github.com/repos/huggingface/transformers/issues/330/events | https://github.com/huggingface/transformers/issues/330 | 415,471,564 | MDU6SXNzdWU0MTU0NzE1NjQ= | 330 | Can we fine tune our model on Chinese corpus | {
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Thanks. | {
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"You should probably use the `bert-base-chinese` model to start from.\r\nPlease refer to the original bert tensorflow implementation from Google.\r\nThere are a lot of discussion about chinese models in the issues of this repo."
] |
https://api.github.com/repos/huggingface/transformers/issues/333 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/333/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/333/comments | https://api.github.com/repos/huggingface/transformers/issues/333/events | https://github.com/huggingface/transformers/issues/333 | 415,994,820 | MDU6SXNzdWU0MTU5OTQ4MjA= | 333 | Add lm and next sentence accuracy for run_lm_finetuning example | {
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"Yes, feel free to submit a PR for that."
] | |
https://api.github.com/repos/huggingface/transformers/issues/340 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/340/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/340/comments | https://api.github.com/repos/huggingface/transformers/issues/340/events | https://github.com/huggingface/transformers/issues/340 | 416,582,484 | MDU6SXNzdWU0MTY1ODI0ODQ= | 340 | optimizer.zero_grad() in run_openai_gpt.py? | {
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https://github.com/huggingface/pytorch-pretrained-BERT/blob/2152bfeae82439600dc5b5deab057a3c4331c62d/examples/run_openai_gpt.py#L212 | {
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"Oh that's a mistake indeed, thanks for pointing out.\r\nFixed on master."
] |
https://api.github.com/repos/huggingface/transformers/issues/234 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/234/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/234/comments | https://api.github.com/repos/huggingface/transformers/issues/234/events | https://github.com/huggingface/transformers/issues/234 | 404,294,481 | MDU6SXNzdWU0MDQyOTQ0ODE= | 234 | Fine tuning for evaluation | {
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1) Help me please figure out, what would be optimal batch size for evaluating nextSentencePrediction model? For performance. Is it same as used during pre-training (128)?
2) If i building high performance evaluating backend on CUDA, would it be a good idea to use several threads with bert model in each, or its ... | {
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"1. For evaluation I would advise the maximum batch size that your GPU allows. You will be able to use more efficiently this way.\r\n\r\n2. I think you will be better off by using a single thread.",
"Thanks! How can i figure out optimal batch size? I want to try tesla k80",
"You increase it gradually and when t... |
https://api.github.com/repos/huggingface/transformers/issues/309 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/309/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/309/comments | https://api.github.com/repos/huggingface/transformers/issues/309/events | https://github.com/huggingface/transformers/issues/309 | 412,807,997 | MDU6SXNzdWU0MTI4MDc5OTc= | 309 | Tests error: Issue with python3 compatibility, on zope interface implementation | {
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________________________________________________________________________________ ERROR collecting tests/modeling_test.py __________________________________________________________________________________
modeling_test.py:25:... | {
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"any solution here?",
"This looks like an incompatibility between apex and zope.\r\nHave you tried without installing apex?",
"> This looks like an incompatibility between apex and zope.\r\n> Have you tried without installing apex?\r\n\r\nI uninstalled apex, it works now!\r\nThank you so much!!!! "
] |
https://api.github.com/repos/huggingface/transformers/issues/356 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/356/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/356/comments | https://api.github.com/repos/huggingface/transformers/issues/356/events | https://github.com/huggingface/transformers/issues/356 | 418,022,337 | MDU6SXNzdWU0MTgwMjIzMzc= | 356 | How to add input mask to GPT? | {
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"GPT is a causal model so each tokens only attend to the left context and masking is not really needed.\r\nJust mask the output according to your lengths (and be such that each input sample start at the very first left token)."
] |
https://api.github.com/repos/huggingface/transformers/issues/336 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/336/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/336/comments | https://api.github.com/repos/huggingface/transformers/issues/336/events | https://github.com/huggingface/transformers/issues/336 | 416,450,176 | MDU6SXNzdWU0MTY0NTAxNzY= | 336 | F1 and EM scores output for run_squad.py | {
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I was doing prediction after fine-tuning the bert-base model and I was wondering whether the f1 and em scores will show automatically since I only saw the following two log outputs
03/02/2019 22:20:05 - INFO - __main__ - Writing predictions to: /tmp/debug_squad/predictions.json
03/02/2019 22:20:05 - INFO - ... | {
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"Use the Squad python scripts available on their website",
"Is that run_squad.py? I used that one but didn’t see output scores, having\nthe output predictions files though. Thanks!\n\nabeljim <notifications@github.com>于2019年3月3日 周日上午3:03写道：\n\n> Use the Squad python scripts available on their website\n>\n> —\n> Y... |
https://api.github.com/repos/huggingface/transformers/issues/345 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/345/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/345/comments | https://api.github.com/repos/huggingface/transformers/issues/345/events | https://github.com/huggingface/transformers/issues/345 | 417,196,931 | MDU6SXNzdWU0MTcxOTY5MzE= | 345 | Not able to import RandomSampler, Getting error "ImportError: cannot import name 'RandomSampler'"? | {
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"how do you fix this issue?",
"> how do you fix this issue?\r\n\r\ntry to update your torch version，i found it didn't work in torch 4.0.0, try \"torch >=4.0.1\""
] |
https://api.github.com/repos/huggingface/transformers/issues/281 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/281/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/281/comments | https://api.github.com/repos/huggingface/transformers/issues/281/events | https://github.com/huggingface/transformers/issues/281 | 410,646,108 | MDU6SXNzdWU0MTA2NDYxMDg= | 281 | Conversion of gpt-2 small model | {
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"I'd like to help out on this. I will have a look and try to understand the earlier bridges in this repo. Let me know if you see anywhere a newcomer can be helpful with.",
"Sure, would be happy to welcome a PR.\r\nYou can start from `modeling_openai.py` and `tokenization_openai.py`'s codes.\r\nIt's pretty much th... |
https://api.github.com/repos/huggingface/transformers/issues/357 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/357/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/357/comments | https://api.github.com/repos/huggingface/transformers/issues/357/events | https://github.com/huggingface/transformers/pull/357 | 418,202,612 | MDExOlB1bGxSZXF1ZXN0MjU5MDI5Mjg5 | 357 | Use Dropout Layer in OpenAIGPTMultipleChoiceHead | {
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"merged_at": "2019... | closes #354 | {
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"Seems good to me, thanks for that.\r\nLet me just check why we don't have Circle-CI tests on the PR anymore and I'll merge it."
] |
https://api.github.com/repos/huggingface/transformers/issues/354 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/354/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/354/comments | https://api.github.com/repos/huggingface/transformers/issues/354/events | https://github.com/huggingface/transformers/issues/354 | 417,878,794 | MDU6SXNzdWU0MTc4Nzg3OTQ= | 354 | Dropout Layer in OpenAIGPTMultipleChoiceHead not used | {
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"Thanks @cdjhz "
] | |
https://api.github.com/repos/huggingface/transformers/issues/344 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/344/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/344/comments | https://api.github.com/repos/huggingface/transformers/issues/344/events | https://github.com/huggingface/transformers/issues/344 | 417,137,321 | MDU6SXNzdWU0MTcxMzczMjE= | 344 | BertEmbedding not initialized with `padding_idx=0` | {
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The bert-embeddings are not initialized with `padding_idx=0`, which may potentially result in none zero embeddings for zeros paddings in some early version of pytorch. | {
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"Could be, do you want to submit a PR to update this?",
"Closed by #358, thanks @cdjhz!"
] |
https://api.github.com/repos/huggingface/transformers/issues/362 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/362/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/362/comments | https://api.github.com/repos/huggingface/transformers/issues/362/events | https://github.com/huggingface/transformers/pull/362 | 419,078,044 | MDExOlB1bGxSZXF1ZXN0MjU5NjkyOTc3 | 362 | Make the hyperlink of NVIDIA Apex clickable | {
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"Thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/374 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/374/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/374/comments | https://api.github.com/repos/huggingface/transformers/issues/374/events | https://github.com/huggingface/transformers/pull/374 | 420,484,831 | MDExOlB1bGxSZXF1ZXN0MjYwNzU0MzU4 | 374 | handle ImportError exception when used from projects outside | {
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... | The relative path that starts with . does not work when a file is used from an outside project. I added a safe code to handle the ImportError exception in this case, so I can use the source file without having to make local changes to it. | {
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"Just doing `from pytorch_pretrained_bert import BertTokenizer, BertModel` in your project doesn't work?\r\n\r\nThat's what they do in [AllenNLP](https://github.com/allenai/allennlp/blob/3f0953d19de3676ea82e642659fc96d90690e34d/allennlp/modules/token_embedders/bert_token_embedder.py#L14) or [flair](https://github.c... |
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"Thanks @tseretelitornike!"
] | |
https://api.github.com/repos/huggingface/transformers/issues/383 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/383/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/383/comments | https://api.github.com/repos/huggingface/transformers/issues/383/events | https://github.com/huggingface/transformers/pull/383 | 421,762,773 | MDExOlB1bGxSZXF1ZXN0MjYxNzQzODU2 | 383 | pull from original | {
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https://api.github.com/repos/huggingface/transformers/issues/371 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/371/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/371/comments | https://api.github.com/repos/huggingface/transformers/issues/371/events | https://github.com/huggingface/transformers/pull/371 | 420,279,516 | MDExOlB1bGxSZXF1ZXN0MjYwNTk1MzQx | 371 | Simplify code, delete redundancy line | {
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"wouldn't this cause some kind of indentation error? (I don't have time to test the change sorry)"
] |
https://api.github.com/repos/huggingface/transformers/issues/350 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/350/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/350/comments | https://api.github.com/repos/huggingface/transformers/issues/350/events | https://github.com/huggingface/transformers/issues/350 | 417,703,868 | MDU6SXNzdWU0MTc3MDM4Njg= | 350 | Bert Uncased Large giving very low results with SQUAD v1.1 dataset | {
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- do_lower_case=True
- max_answer_length=30
- max_answer_length=30
- n_best_size=20
- verbose_logging=False
- bert_model="bert-large-uncased"
- max_seq_length=384
- doc_stride=128
- max_query_length=192
- local_rank=-1
- train_batch_size=12
- predict_batch_size=12
- num_train_epochs=2.0
... | {
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https://api.github.com/repos/huggingface/transformers/issues/361 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/361/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/361/comments | https://api.github.com/repos/huggingface/transformers/issues/361/events | https://github.com/huggingface/transformers/pull/361 | 419,008,830 | MDExOlB1bGxSZXF1ZXN0MjU5NjQ3NjM0 | 361 | Correct line number in README for classes | {
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"Thanks @junjieqian!"
] |
https://api.github.com/repos/huggingface/transformers/issues/312 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/312/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/312/comments | https://api.github.com/repos/huggingface/transformers/issues/312/events | https://github.com/huggingface/transformers/issues/312 | 413,204,487 | MDU6SXNzdWU0MTMyMDQ0ODc= | 312 | Problems converting TF BioBERT model to PyTorch | {
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I have (seemingly) successfully transfered the checkpoint using the `./pytorch_pretrained_bert/convert_... | {
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"I have solved my issue. All my code was correctly written. The error was an corrupted/improperly saved model.bin file.",
"I'm trying to convert BioBert to Pytorch also, so just wondering if you could share a bit more details on how you are doing the conversion. Thanks!",
"First, I downloaded the BioBERT TF che... |
https://api.github.com/repos/huggingface/transformers/issues/399 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/399/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/399/comments | https://api.github.com/repos/huggingface/transformers/issues/399/events | https://github.com/huggingface/transformers/issues/399 | 424,392,950 | MDU6SXNzdWU0MjQzOTI5NTA= | 399 | Is the GPT-2 pretrained model language agnostic? | {
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Thank You. | {
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"Hi Aly, GPT-2 is pretrained on an English only corpus.",
"Hi @thomwolf , thank you for the clarification."
] |
https://api.github.com/repos/huggingface/transformers/issues/413 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/413/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/413/comments | https://api.github.com/repos/huggingface/transformers/issues/413/events | https://github.com/huggingface/transformers/issues/413 | 425,665,342 | MDU6SXNzdWU0MjU2NjUzNDI= | 413 | Bert Pretrained model has no modules nor parameters | {
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bert_model = BertPreTrainedModel.from_pretrained(pretrained_model_name_or_path='bert-base-uncased')
bert_model.to(device)"
returns:
2019-03-26 21:38:07,404 pytorch_pretrained_bert.modeling INFO loading archive file https://s3.amazonaws.com/mode... | {
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https://api.github.com/repos/huggingface/transformers/issues/406 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/406/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/406/comments | https://api.github.com/repos/huggingface/transformers/issues/406/events | https://github.com/huggingface/transformers/issues/406 | 425,045,668 | MDU6SXNzdWU0MjUwNDU2Njg= | 406 | error when trying to get embeddings after fine tuning | {
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Now I want to use the fine tuned model to get better embeddings.
>>> import torch
>>> config = modeling.BertConfig(attention_probs_dropout_prob=0.1, hidden_dropout_prob=0.1, hidden_size=768, initializer_range=0.02, intermediate_size=3072, max_po... | {
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"I realised that the way I was loading model was wrong.\r\n\r\nI used this code\r\n\r\n ```\r\n# Save a trained model \r\n model_to_save = model.module if hasattr(model, 'module') else model # Only save the model it-self \r\n output_model_file = os.path.join(args.output_dir, \"pytorch_model.bin\") \r\n torch.save(... |
https://api.github.com/repos/huggingface/transformers/issues/392 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/392/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/392/comments | https://api.github.com/repos/huggingface/transformers/issues/392/events | https://github.com/huggingface/transformers/pull/392 | 423,390,699 | MDExOlB1bGxSZXF1ZXN0MjYyOTcyNjkw | 392 | Add full language model fine-tuning | {
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"Also, build_py2 has failed because I deliberately did not include Py2 compatibility - it's only a few months from end-of-life now. If you really want me to, I can go back and include it, but we should be trying to let it go by now!",
"This is really great @Rocketknight1!\r\nThanks for taking the time to make a v... |
https://api.github.com/repos/huggingface/transformers/issues/394 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/394/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/394/comments | https://api.github.com/repos/huggingface/transformers/issues/394/events | https://github.com/huggingface/transformers/pull/394 | 423,573,705 | MDExOlB1bGxSZXF1ZXN0MjYzMTE3Mzk4 | 394 | Minor change in README | {
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"Thanks!"
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https://api.github.com/repos/huggingface/transformers/issues/396 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/396/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/396/comments | https://api.github.com/repos/huggingface/transformers/issues/396/events | https://github.com/huggingface/transformers/pull/396 | 423,718,783 | MDExOlB1bGxSZXF1ZXN0MjYzMjI2Nzk2 | 396 | add tqdm to the process of eval in examples/run_swag.py | {
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"tests/tokenization_openai_test.py::OpenAIGPTTokenizationTest::test_full_tokenizer FAILED",
"Ok, thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/409 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/409/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/409/comments | https://api.github.com/repos/huggingface/transformers/issues/409/events | https://github.com/huggingface/transformers/pull/409 | 425,405,711 | MDExOlB1bGxSZXF1ZXN0MjY0NTA5NzI5 | 409 | Remove padding_idx from position_embeddings and token_type_embeddings | {
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"merged_at": "2019... | Because embedding vectors at 0th position of `position_embeddings` and `token_type_embeddings` have roles in the model (i.e., representing the first token and the token in the first sentence), these vectors should not be treated as padding vectors. | {
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"Indeed, thanks @ikuyamada!"
] |
https://api.github.com/repos/huggingface/transformers/issues/411 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/411/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/411/comments | https://api.github.com/repos/huggingface/transformers/issues/411/events | https://github.com/huggingface/transformers/issues/411 | 425,415,282 | MDU6SXNzdWU0MjU0MTUyODI= | 411 | Why average the loss when training on multi-GPUs | {
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https://github.com/huggingface/pytorch-pretrained-BERT/blob/master/examples/run_classifier.py#L573-L574 | {
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"Multi-GPU loss returns a tuple of losses with one loss for each GPU.\r\nWe average them to get the full loss. See [this blog post](https://medium.com/huggingface/training-larger-batches-practical-tips-on-1-gpu-multi-gpu-distributed-setups-ec88c3e51255) for more details."
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https://api.github.com/repos/huggingface/transformers/issues/376 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/376/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/376/comments | https://api.github.com/repos/huggingface/transformers/issues/376/events | https://github.com/huggingface/transformers/issues/376 | 420,585,426 | MDU6SXNzdWU0MjA1ODU0MjY= | 376 | run_lm_finetuning generates short training cases | {
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"Sorry, I just realized this was mentioned in the [original PR](https://github.com/huggingface/pytorch-pretrained-BERT/pull/124).",
"Indeed. Happy to welcome a PR if you want to improve this example!",
"Working on it now! One question, though: It seems likely that I'll have to make significant changes. The reas... |
https://api.github.com/repos/huggingface/transformers/issues/325 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/325/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/325/comments | https://api.github.com/repos/huggingface/transformers/issues/325/events | https://github.com/huggingface/transformers/pull/325 | 414,937,998 | MDExOlB1bGxSZXF1ZXN0MjU2NTM0ODg4 | 325 | add BertTokenizer flag to skip basic tokenization | {
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"merged_at": "2019... | When tokenization is done before text hits this package (e.g., when tokenization is specified as part of the dataset) there exists a use case for skipping the `BasicTokenizer` step, going right to `WordpieceTokenizer`.
When one still wants to use the `BertTokenizer.from_pretrained` helper function, they have been ab... | {
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"Thanks for the PR (and documenting this), I added a note",
"Ok this is great, thanks @john-hewitt, thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/398 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/398/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/398/comments | https://api.github.com/repos/huggingface/transformers/issues/398/events | https://github.com/huggingface/transformers/pull/398 | 424,000,240 | MDExOlB1bGxSZXF1ZXN0MjYzNDUwODM5 | 398 | Multi GPU | {
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... | This is an incomplete proof-of-concept of how to run BERT across multiple GPUs. It will take advantage of multiple GPUs' memory, but not of their compute cores.
Do not merge | {
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"Hi @dirkgr, thanks for this PR.\r\n\r\nI think we will keep all the GPU/multi-GPU logic outside of the main library for now. It makes it easier to integrate the module in downstream libraries and integrating such modifications at the current stage would cause too many breaking changes for the users unfortunately.\... |
https://api.github.com/repos/huggingface/transformers/issues/388 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/388/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/388/comments | https://api.github.com/repos/huggingface/transformers/issues/388/events | https://github.com/huggingface/transformers/pull/388 | 421,917,407 | MDExOlB1bGxSZXF1ZXN0MjYxODM5NTEw | 388 | Added remaining GLUE tasks to 'run_classifier.py' | {
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"Hi @ananyahjha93,\r\nThanks for this PR.\r\nDo you have some results from fine-tuning BERT on the other tasks?\r\nAlso, I think we should add some details on the available tasks in the readme as well.",
"@thomwolf I have added results on GLUE dev set in the README and details on how to run any GLUE task. But, I ... |
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i.e. shouldn't this be `encoded_layers[0]` below?
https://github.com/huggingface/pytorch-pretrained-BERT/blob/f7c9dc8c998395d2ad9edbf0fd6fa072f03cc66... | {
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"Never mind, I think I got confused. Is it that the pooler already takes care of that and encoded_layers represents the pooler output for each attention layer?",
"Hi Catalin, the content of the outputs (`encoded_layers` and `pooled_output`) is detailed in the readme [here](https://github.com/huggingface/pytorch-p... |
https://api.github.com/repos/huggingface/transformers/issues/425 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/425/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/425/comments | https://api.github.com/repos/huggingface/transformers/issues/425/events | https://github.com/huggingface/transformers/pull/425 | 426,865,891 | MDExOlB1bGxSZXF1ZXN0MjY1NjIxMjQ5 | 425 | fix lm_finetuning's link | {
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"Thanks!"
] | |
https://api.github.com/repos/huggingface/transformers/issues/418 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/418/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/418/comments | https://api.github.com/repos/huggingface/transformers/issues/418/events | https://github.com/huggingface/transformers/issues/418 | 426,349,075 | MDU6SXNzdWU0MjYzNDkwNzU= | 418 | can I fine-tuning pretrained gpt2 model on my corpus? | {
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https://api.github.com/repos/huggingface/transformers/issues/430 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/430/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/430/comments | https://api.github.com/repos/huggingface/transformers/issues/430/events | https://github.com/huggingface/transformers/pull/430 | 427,305,693 | MDExOlB1bGxSZXF1ZXN0MjY1OTU0MTYy | 430 | Fix typo in example code | {
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https://api.github.com/repos/huggingface/transformers/issues/437 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/437/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/437/comments | https://api.github.com/repos/huggingface/transformers/issues/437/events | https://github.com/huggingface/transformers/pull/437 | 428,115,435 | MDExOlB1bGxSZXF1ZXN0MjY2NTU3Nzc5 | 437 | Fix links in README | {
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https://api.github.com/repos/huggingface/transformers/issues/435 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/435/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/435/comments | https://api.github.com/repos/huggingface/transformers/issues/435/events | https://github.com/huggingface/transformers/pull/435 | 427,870,022 | MDExOlB1bGxSZXF1ZXN0MjY2MzY5NDAy | 435 | Fixes to the TensorFlow conversion tool | {
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"merged_at": "2019... | This PR contains a small fix to the script which converts TensorFlow weights to PyTorch weights. The related issues are #50, #306, etc.
Thanks for all of the open source code you've been putting out in this domain, it has been incredibly helpful to me and my team. | {
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"Yes! Thanks @marpaia!"
] |
https://api.github.com/repos/huggingface/transformers/issues/373 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/373/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/373/comments | https://api.github.com/repos/huggingface/transformers/issues/373/events | https://github.com/huggingface/transformers/issues/373 | 420,367,615 | MDU6SXNzdWU0MjAzNjc2MTU= | 373 | performance degraded when using paddings between queries and contexts. | {
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I am doing modifications on the run_squad.py example.
So for the original training feature, the input ids are [cls]qqqqq[sep]cccccc000000. The attention mask is just something like 111111100000 where first k inputs were mask... | {
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"Similar problem. My token ids is something like \"[cls]qqqq[sep]0000cccccccc[sep]00000\". Have you solve it? or is there anyone met the similar problem?",
"> Similar problem. My token ids is something like \"[cls]qqqq[sep]0000cccccccc[sep]00000\". Have you solve it? or is there anyone met the similar problem?\r\... |
https://api.github.com/repos/huggingface/transformers/issues/419 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/419/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/419/comments | https://api.github.com/repos/huggingface/transformers/issues/419/events | https://github.com/huggingface/transformers/issues/419 | 426,376,347 | MDU6SXNzdWU0MjYzNzYzNDc= | 419 | bug in examples/run_squad.py line 88 & 90 | {
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if self.start_position:
s += ", end_position: %d" % (self.end_position)
if self.start_position:
s += ", is_impossible: %r" % (self.is_impossible)
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"Indeed, thanks"
] |
https://api.github.com/repos/huggingface/transformers/issues/422 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/422/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/422/comments | https://api.github.com/repos/huggingface/transformers/issues/422/events | https://github.com/huggingface/transformers/issues/422 | 426,611,523 | MDU6SXNzdWU0MjY2MTE1MjM= | 422 | BertForTokenClassification for NER, mask labels | {
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Say I have 10 words with 10 labels, after WordPiece tokenization I get 15 tokens and I assign them labels, "X" for pieces of words like (##ing).
In the original paper https://arxiv.org/pdf/1810.04805.pdf in 4.3 section is said that we don't ma... | {
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"Sequence tagging is explained here: https://github.com/huggingface/pytorch-pretrained-BERT/issues/64#issuecomment-443703063",
"Yes, this is the relevant issue on this topic. I'll close this issue in favor of #64."
] |
https://api.github.com/repos/huggingface/transformers/issues/433 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/433/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/433/comments | https://api.github.com/repos/huggingface/transformers/issues/433/events | https://github.com/huggingface/transformers/issues/433 | 427,720,799 | MDU6SXNzdWU0Mjc3MjA3OTk= | 433 | how to do the pre training the model form scratch? | {
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"```\r\npython3 examples/lm_finetuning/simple_lm_finetuning.py \r\n--train_corpus sample_text.txt \r\n--bert_model bert-base-uncased \r\n--do_lower_case \r\n--output_dir finetuned_lm/\r\n```\r\nIn addition, you can refer to #385 ",
"Yes let's keep a single issue on this. Closing in favor of #385."
] |
https://api.github.com/repos/huggingface/transformers/issues/426 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/426/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/426/comments | https://api.github.com/repos/huggingface/transformers/issues/426/events | https://github.com/huggingface/transformers/pull/426 | 426,985,414 | MDExOlB1bGxSZXF1ZXN0MjY1NzE0ODgz | 426 | instantiate loss_fct once | {
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"Thanks for the PR but I think it's fine like it is now (slightly easier to read and debug)."
] | |
https://api.github.com/repos/huggingface/transformers/issues/389 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/389/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/389/comments | https://api.github.com/repos/huggingface/transformers/issues/389/events | https://github.com/huggingface/transformers/pull/389 | 422,242,965 | MDExOlB1bGxSZXF1ZXN0MjYyMDc1MDc5 | 389 | Fix cosine schedule | {
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"merged_at": "2019... | Fixing similar problem to #327 and #324 in cosine schedule.
Btw, do you think it would make sense to have [something like this](https://github.com/lukovnikov/pytorch-pretrained-BERT/blob/optim/pytorch_pretrained_bert/optimization.py) for both of your `optimization.py`'s? | {
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"Hi @lukovnikov, yes I think the various schedules you have added to your fork are very nice!\r\nDo you want to add them in this PR as well?\r\nOtherwise, I'll merge it.",
"Merging it for now. Thanks @lukovnikov ",
"Hi, sorry, lost track of this, will make a new PR soon."
] |
https://api.github.com/repos/huggingface/transformers/issues/50 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/50/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/50/comments | https://api.github.com/repos/huggingface/transformers/issues/50/events | https://github.com/huggingface/transformers/issues/50 | 383,055,235 | MDU6SXNzdWUzODMwNTUyMzU= | 50 | pytorch_pretrained_bert/convert_tf_checkpoint_to_pytorch.py error | {
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"Maybe some additional information could help me help you?",
"Initialize PyTorch weight ['cls', 'seq_relationship', 'output_weights']\r\nSkipping cls/seq_relationship/output_weights/adam_m\r\nSkipping cls/seq_relationship/output_weights/adam_v\r\nTraceback (most recent call last):\r\n File \"/home/tiandan.cxj/py... |
https://api.github.com/repos/huggingface/transformers/issues/428 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/428/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/428/comments | https://api.github.com/repos/huggingface/transformers/issues/428/events | https://github.com/huggingface/transformers/issues/428 | 427,271,826 | MDU6SXNzdWU0MjcyNzE4MjY= | 428 | Cannot find Synthetic self-training in this repository. | {
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There is a PDF explaining it: https://nlp.stanford.edu/seminar/details/jdevlin.pdf?fbclid=IwAR2TBFCJOeZ9cGhxB-z5cJJ17vHN4W25oWsjI8NqJoTEmlYIYEKG7oh4tlY but I have found no such model within t... | {
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"Hi, indeed there is no Synthetic self-training in this repository, and the SQuAD leaderboard website actually refers to the Tensorflow repository so I'll close this issue.",
"Will you be adding synthetic self training though?"
] |
https://api.github.com/repos/huggingface/transformers/issues/207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/207/comments | https://api.github.com/repos/huggingface/transformers/issues/207/events | https://github.com/huggingface/transformers/issues/207 | 400,885,697 | MDU6SXNzdWU0MDA4ODU2OTc= | 207 | AttributeError: 'NoneType' object has no attribute 'start_logit' | {
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```
Evaluating: 100%|███████████████████████████| 1529/1529 [05:12<00:00, 4.88it/s]
01/18/2019 21:42:28 - INFO - __main__ - Writing predictions to: ./models/squad2/predictions.json
01/18/2019 21:4... | {
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"Can you post a self-contained example to reproduce your error ? Which version of python, pytorch and pytorch-pretrained-bert are you using?",
"Closing since there is no recent activity. Feel free to re-open if needed.",
"I ran into the same issue. Any pointers on how I could triage this further?",
"@thomwolf... |
https://api.github.com/repos/huggingface/transformers/issues/459 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/459/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/459/comments | https://api.github.com/repos/huggingface/transformers/issues/459/events | https://github.com/huggingface/transformers/issues/459 | 430,525,932 | MDU6SXNzdWU0MzA1MjU5MzI= | 459 | Question about BertForQuestionAnswering model | {
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"followers_url": "https://api.github.com/users/... | [] | closed | false | [] | null | 0 | 2019-04-08T15:47:53Z | 2019-04-09T02:48:50Z | 2019-04-09T02:48:50Z | null | NONE | [] | null | null | null | null | Hi, I want to train `BertForQuestionAnswering` with my own dataset. I have already taken care of the format of the dataset, however, I encounter some problem when I want to do the inference job. If I am right, the forward output of the model is `start_logits` and `end_logits`. When I use `batchsize=1`, the output shape... | {
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https://api.github.com/repos/huggingface/transformers/issues/471 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/471/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/471/comments | https://api.github.com/repos/huggingface/transformers/issues/471/events | https://github.com/huggingface/transformers/issues/471 | 431,881,640 | MDU6SXNzdWU0MzE4ODE2NDA= | 471 | modeling_openai.py bug report | {
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``` # Copy word and positional embeddings from the previous weights
self.tokens_embed.weight.data[: self.config.vocab_size, :] = old_embed.weight.data[: self.config.vocab_size, :]
self.tokens_embed.weight.data[-self.config.n_positions :, :] = old_embed.weight.dat... | {
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"Good catch, I'll fix this."
] |
https://api.github.com/repos/huggingface/transformers/issues/472 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/472/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/472/comments | https://api.github.com/repos/huggingface/transformers/issues/472/events | https://github.com/huggingface/transformers/issues/472 | 431,935,327 | MDU6SXNzdWU0MzE5MzUzMjc= | 472 | Compilation terminated | {
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I cannot pip install the package. I have
> regex_3/_regex.c:48:10: fatal error: Python.h: No such file or directory
#include "Python.h"
^~~~~~~~~~
compilation terminated.
error: command 'x86_64-linux-gnu-gcc' failed with exit status 1
Might have something to do with CI failure for ... | {
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"managed to install it by running \r\n\r\n> sudo apt-get install python3 python-dev"
] |
https://api.github.com/repos/huggingface/transformers/issues/446 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/446/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/446/comments | https://api.github.com/repos/huggingface/transformers/issues/446/events | https://github.com/huggingface/transformers/issues/446 | 428,971,570 | MDU6SXNzdWU0Mjg5NzE1NzA= | 446 | How to select a certain layer as token's representation? | {
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model = BertForTokenClassification.from_pretrained("bert-base-uncased", num_labels=len(tag2idx))
list... | {
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"Hi @yexing99,\r\nWhat you need is the `hidden_state`, not the `weights`of the model.\r\nDon't use `model.named_parameters()` but just use the output of the model.\r\nHere is an example: https://github.com/huggingface/pytorch-pretrained-BERT#bert\r\nAnd more details here: https://github.com/huggingface/pytorch-pret... |
https://api.github.com/repos/huggingface/transformers/issues/447 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/447/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/447/comments | https://api.github.com/repos/huggingface/transformers/issues/447/events | https://github.com/huggingface/transformers/issues/447 | 429,012,525 | MDU6SXNzdWU0MjkwMTI1MjU= | 447 | Dynamic max_seq_length implementation? | {
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"Hi @zijwang , the package doesn't implement any specific batching logic, only tokenizers and models.\r\nYou are supposed to take care of this yourself in your scripts."
] |
https://api.github.com/repos/huggingface/transformers/issues/453 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/453/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/453/comments | https://api.github.com/repos/huggingface/transformers/issues/453/events | https://github.com/huggingface/transformers/issues/453 | 429,654,860 | MDU6SXNzdWU0Mjk2NTQ4NjA= | 453 | What‘s op-for-op meaning? | {
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"Hi, it means that the computation graphs of the Tensorflow and PyTorch versions are identical."
] | |
https://api.github.com/repos/huggingface/transformers/issues/454 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/454/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/454/comments | https://api.github.com/repos/huggingface/transformers/issues/454/events | https://github.com/huggingface/transformers/issues/454 | 429,755,590 | MDU6SXNzdWU0Mjk3NTU1OTA= | 454 | getting sequence embeddings for pair of sentences | {
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If i get sequence embeddings, will word1 of sentence 1 will have context of word1 of sentence2? | {
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"Hi, yes."
] |
https://api.github.com/repos/huggingface/transformers/issues/464 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/464/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/464/comments | https://api.github.com/repos/huggingface/transformers/issues/464/events | https://github.com/huggingface/transformers/issues/464 | 430,879,647 | MDU6SXNzdWU0MzA4Nzk2NDc= | 464 | How to get vocab.txt and bert_config.json as output of fine tuning? | {
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I am fine tuning bert on custom data.
As output I am getting only pytorch_model.bin but how to get updated vocab.txt and bert_config.json .
Please suggest.
Thanks
Mahesh | {
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"You can get `pytorch_model.bin` and `config.json` just as indicated in the examples: https://github.com/huggingface/pytorch-pretrained-BERT/blob/master/examples/run_classifier.py#L861-L866\r\n\r\nThe vocabulary stays the same, just load the tokenizer as you did for the training (`BertTokenizer.from_pretrained(...)... |
https://api.github.com/repos/huggingface/transformers/issues/467 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/467/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/467/comments | https://api.github.com/repos/huggingface/transformers/issues/467/events | https://github.com/huggingface/transformers/pull/467 | 431,210,818 | MDExOlB1bGxSZXF1ZXN0MjY4OTM2NDAw | 467 | Update README.md | {
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"merged_at": "2019... | Fix for
```> > > > 04/09/2019 21:39:38 - INFO - __main__ - device: cuda n_gpu: 1, distributed training: False, 16-bits training: False
Traceback (most recent call last):
File "/home/ubuntu/pytorch-pretrained-BERT/examples/lm_finetuning/simple_lm_finetuning.py", line 642, in <module>
main()
File "/home/... | {
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"Thanks Yaroslav!"
] |
https://api.github.com/repos/huggingface/transformers/issues/462 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/462/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/462/comments | https://api.github.com/repos/huggingface/transformers/issues/462/events | https://github.com/huggingface/transformers/pull/462 | 430,713,066 | MDExOlB1bGxSZXF1ZXN0MjY4NTQyMTcx | 462 | fix run_gpt2.py | {
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"Fixes #412 ",
"Ok, looks good to me, thanks!"
] |
https://api.github.com/repos/huggingface/transformers/issues/427 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/427/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/427/comments | https://api.github.com/repos/huggingface/transformers/issues/427/events | https://github.com/huggingface/transformers/pull/427 | 427,247,452 | MDExOlB1bGxSZXF1ZXN0MjY1OTE3NzM2 | 427 | fix sample_doc | {
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example:
cumsum_max = {int64} 30
doc_cumsum = {ndarray} [ 5 7 11 19 30]
doc_lengths = {list} <class 'list'>: [5, 2, 4, 8, 11]
if current_idx = 1,
rand_start = ... | {
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"Good catch, thanks!",
"Gah. I meant to use `randrange()`, but this fix is equivalent!"
] |
https://api.github.com/repos/huggingface/transformers/issues/478 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/478/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/478/comments | https://api.github.com/repos/huggingface/transformers/issues/478/events | https://github.com/huggingface/transformers/pull/478 | 432,587,116 | MDExOlB1bGxSZXF1ZXN0MjcwMDI4NDcx | 478 | Added a helpful error for users with single-document corpuses | {
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"Looks good to me, thanks @Rocketknight1 "
] |
https://api.github.com/repos/huggingface/transformers/issues/474 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/474/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/474/comments | https://api.github.com/repos/huggingface/transformers/issues/474/events | https://github.com/huggingface/transformers/pull/474 | 432,218,030 | MDExOlB1bGxSZXF1ZXN0MjY5NzMyMTY1 | 474 | Fix tsv read error in Windows | {
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It is solved by adding `encoding='utf-8'` when reading the `.tsv` ... | {
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} | https://api.github.com/repos/huggingface/transformers/issues/474/timeline | null | null | null | null | null | null | true | [
"Ok, thanks @jiesutd!"
] |
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